The Use of Multiple Regression and Trend Analysis to Understand Enrollment Fluctuations. AIR Forum 1979 Paper.

ERIC Educational Resources Information Center

Campbell, S. Duke; Greenberg, Barry

The development of a predictive equation capable of explaining a significant percentage of enrollment variability at Florida International University is described. A model utilizing trend analysis and a multiple regression approach to enrollment forecasting was adapted to investigate enrollment dynamics at the university. Four independent…

What Happens to Students Placed into Developmental Education? A Meta-Analysis of Regression Discontinuity Studies

ERIC Educational Resources Information Center

Valentine, Jeffrey C.; Konstantopoulos, Spyros; Goldrick-Rab, Sara

2017-01-01

This article reports a systematic review and meta-analysis of studies that use regression discontinuity to examine the effects of placement into developmental education. Results suggest that placement into developmental education is associated with effects that are negative, statistically significant, and substantively large for three outcomes:…

The microbiological profile and presence of bloodstream infection influence mortality rates in necrotizing fasciitis

PubMed Central

2011-01-01

Introduction Necrotizing fasciitis (NF) is a life threatening infectious disease with a high mortality rate. We carried out a microbiological characterization of the causative pathogens. We investigated the correlation of mortality in NF with bloodstream infection and with the presence of co-morbidities. Methods In this retrospective study, we analyzed 323 patients who presented with necrotizing fasciitis at two different institutions. Bloodstream infection (BSI) was defined as a positive blood culture result. The patients were categorized as survivors and non-survivors. Eleven clinically important variables which were statistically significant by univariate analysis were selected for multivariate regression analysis and a stepwise logistic regression model was developed to determine the association between BSI and mortality. Results Univariate logistic regression analysis showed that patients with hypotension, heart disease, liver disease, presence of Vibrio spp. in wound cultures, presence of fungus in wound cultures, and presence of Streptococcus group A, Aeromonas spp. or Vibrio spp. in blood cultures, had a significantly higher risk of in-hospital mortality. Our multivariate logistic regression analysis showed a higher risk of mortality in patients with pre-existing conditions like hypotension, heart disease, and liver disease. Multivariate logistic regression analysis also showed that presence of Vibrio spp in wound cultures, and presence of Streptococcus Group A in blood cultures were associated with a high risk of mortality while debridement > = 3 was associated with improved survival. Conclusions Mortality in patients with necrotizing fasciitis was significantly associated with the presence of Vibrio in wound cultures and Streptococcus group A in blood cultures. PMID:21693053

Factor analysis and multiple regression between topography and precipitation on Jeju Island, Korea

NASA Astrophysics Data System (ADS)

Um, Myoung-Jin; Yun, Hyeseon; Jeong, Chang-Sam; Heo, Jun-Haeng

2011-11-01

SummaryIn this study, new factors that influence precipitation were extracted from geographic variables using factor analysis, which allow for an accurate estimation of orographic precipitation. Correlation analysis was also used to examine the relationship between nine topographic variables from digital elevation models (DEMs) and the precipitation in Jeju Island. In addition, a spatial analysis was performed in order to verify the validity of the regression model. From the results of the correlation analysis, it was found that all of the topographic variables had a positive correlation with the precipitation. The relations between the variables also changed in accordance with a change in the precipitation duration. However, upon examining the correlation matrix, no significant relationship between the latitude and the aspect was found. According to the factor analysis, eight topographic variables (latitude being the exception) were found to have a direct influence on the precipitation. Three factors were then extracted from the eight topographic variables. By directly comparing the multiple regression model with the factors (model 1) to the multiple regression model with the topographic variables (model 3), it was found that model 1 did not violate the limits of statistical significance and multicollinearity. As such, model 1 was considered to be appropriate for estimating the precipitation when taking into account the topography. In the study of model 1, the multiple regression model using factor analysis was found to be the best method for estimating the orographic precipitation on Jeju Island.

Use of principal-component, correlation, and stepwise multiple-regression analyses to investigate selected physical and hydraulic properties of carbonate-rock aquifers

USGS Publications Warehouse

Brown, C. Erwin

1993-01-01

Correlation analysis in conjunction with principal-component and multiple-regression analyses were applied to laboratory chemical and petrographic data to assess the usefulness of these techniques in evaluating selected physical and hydraulic properties of carbonate-rock aquifers in central Pennsylvania. Correlation and principal-component analyses were used to establish relations and associations among variables, to determine dimensions of property variation of samples, and to filter the variables containing similar information. Principal-component and correlation analyses showed that porosity is related to other measured variables and that permeability is most related to porosity and grain size. Four principal components are found to be significant in explaining the variance of data. Stepwise multiple-regression analysis was used to see how well the measured variables could predict porosity and (or) permeability for this suite of rocks. The variation in permeability and porosity is not totally predicted by the other variables, but the regression is significant at the 5% significance level. ?? 1993.

Evaluation of Regression Models of Balance Calibration Data Using an Empirical Criterion

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert; Volden, Thomas R.

2012-01-01

An empirical criterion for assessing the significance of individual terms of regression models of wind tunnel strain gage balance outputs is evaluated. The criterion is based on the percent contribution of a regression model term. It considers a term to be significant if its percent contribution exceeds the empirical threshold of 0.05%. The criterion has the advantage that it can easily be computed using the regression coefficients of the gage outputs and the load capacities of the balance. First, a definition of the empirical criterion is provided. Then, it is compared with an alternate statistical criterion that is widely used in regression analysis. Finally, calibration data sets from a variety of balances are used to illustrate the connection between the empirical and the statistical criterion. A review of these results indicated that the empirical criterion seems to be suitable for a crude assessment of the significance of a regression model term as the boundary between a significant and an insignificant term cannot be defined very well. Therefore, regression model term reduction should only be performed by using the more universally applicable statistical criterion.

Population heterogeneity in the salience of multiple risk factors for adolescent delinquency.

PubMed

Lanza, Stephanie T; Cooper, Brittany R; Bray, Bethany C

2014-03-01

To present mixture regression analysis as an alternative to more standard regression analysis for predicting adolescent delinquency. We demonstrate how mixture regression analysis allows for the identification of population subgroups defined by the salience of multiple risk factors. We identified population subgroups (i.e., latent classes) of individuals based on their coefficients in a regression model predicting adolescent delinquency from eight previously established risk indices drawn from the community, school, family, peer, and individual levels. The study included N = 37,763 10th-grade adolescents who participated in the Communities That Care Youth Survey. Standard, zero-inflated, and mixture Poisson and negative binomial regression models were considered. Standard and mixture negative binomial regression models were selected as optimal. The five-class regression model was interpreted based on the class-specific regression coefficients, indicating that risk factors had varying salience across classes of adolescents. Standard regression showed that all risk factors were significantly associated with delinquency. Mixture regression provided more nuanced information, suggesting a unique set of risk factors that were salient for different subgroups of adolescents. Implications for the design of subgroup-specific interventions are discussed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

PubMed

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

Neck-focused panic attacks among Cambodian refugees; a logistic and linear regression analysis.

PubMed

Hinton, Devon E; Chhean, Dara; Pich, Vuth; Um, Khin; Fama, Jeanne M; Pollack, Mark H

2006-01-01

Consecutive Cambodian refugees attending a psychiatric clinic were assessed for the presence and severity of current--i.e., at least one episode in the last month--neck-focused panic. Among the whole sample (N=130), in a logistic regression analysis, the Anxiety Sensitivity Index (ASI; odds ratio=3.70) and the Clinician-Administered PTSD Scale (CAPS; odds ratio=2.61) significantly predicted the presence of current neck panic (NP). Among the neck panic patients (N=60), in the linear regression analysis, NP severity was significantly predicted by NP-associated flashbacks (beta=.42), NP-associated catastrophic cognitions (beta=.22), and CAPS score (beta=.28). Further analysis revealed the effect of the CAPS score to be significantly mediated (Sobel test [Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182]) by both NP-associated flashbacks and catastrophic cognitions. In the care of traumatized Cambodian refugees, NP severity, as well as NP-associated flashbacks and catastrophic cognitions, should be specifically assessed and treated.

Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis

ERIC Educational Resources Information Center

Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.

2006-01-01

Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…

Using destination image to predict visitors' intention to revisit three Hudson River Valley, New York, communities

Treesearch

Rudy M. Schuster; Laura Sullivan; Duarte Morais; Diane Kuehn

2009-01-01

This analysis explores the differences in Affective and Cognitive Destination Image among three Hudson River Valley (New York) tourism communities. Multiple regressions were used with six dimensions of visitors' images to predict future intention to revisit. Two of the three regression models were significant. The only significantly contributing independent...

Evaluating the utility of companion animal tick surveillance practices for monitoring spread and occurrence of human Lyme disease in West Virginia, 2014-2016.

PubMed

Hendricks, Brian; Mark-Carew, Miguella; Conley, Jamison

2017-11-13

Domestic dogs and cats are potentially effective sentinel populations for monitoring occurrence and spread of Lyme disease. Few studies have evaluated the public health utility of sentinel programmes using geo-analytic approaches. Confirmed Lyme disease cases diagnosed by physicians and ticks submitted by veterinarians to the West Virginia State Health Department were obtained for 2014-2016. Ticks were identified to species, and only Ixodes scapularis were incorporated in the analysis. Separate ordinary least squares (OLS) and spatial lag regression models were conducted to estimate the association between average numbers of Ix. scapularis collected on pets and human Lyme disease incidence. Regression residuals were visualised using Local Moran's I as a diagnostic tool to identify spatial dependence. Statistically significant associations were identified between average numbers of Ix. scapularis collected from dogs and human Lyme disease in the OLS (β=20.7, P<0.001) and spatial lag (β=12.0, P=0.002) regression. No significant associations were identified for cats in either regression model. Statistically significant (P≤0.05) spatial dependence was identified in all regression models. Local Moran's I maps produced for spatial lag regression residuals indicated a decrease in model over- and under-estimation, but identified a higher number of statistically significant outliers than OLS regression. Results support previous conclusions that dogs are effective sentinel populations for monitoring risk of human exposure to Lyme disease. Findings reinforce the utility of spatial analysis of surveillance data, and highlight West Virginia's unique position within the eastern United States in regards to Lyme disease occurrence.

Effect of Ankle Range of Motion (ROM) and Lower-Extremity Muscle Strength on Static Balance Control Ability in Young Adults: A Regression Analysis

PubMed Central

Kim, Seong-Gil

2018-01-01

Background The purpose of this study was to investigate the effect of ankle ROM and lower-extremity muscle strength on static balance control ability in young adults. Material/Methods This study was conducted with 65 young adults, but 10 young adults dropped out during the measurement, so 55 young adults (male: 19, female: 36) completed the study. Postural sway (length and velocity) was measured with eyes open and closed, and ankle ROM (AROM and PROM of dorsiflexion and plantarflexion) and lower-extremity muscle strength (flexor and extensor of hip, knee, and ankle joint) were measured. Pearson correlation coefficient was used to examine the correlation between variables and static balance ability. Simple linear regression analysis and multiple linear regression analysis were used to examine the effect of variables on static balance ability. Results In correlation analysis, plantarflexion ROM (AROM and PROM) and lower-extremity muscle strength (except hip extensor) were significantly correlated with postural sway (p<0.05). In simple correlation analysis, all variables that passed the correlation analysis procedure had significant influence (p<0.05). In multiple linear regression analysis, plantar flexion PROM with eyes open significantly influenced sway length (B=0.681) and sway velocity (B=0.011). Conclusions Lower-extremity muscle strength and ankle plantarflexion ROM influenced static balance control ability, with ankle plantarflexion PROM showing the greatest influence. Therefore, both contractile structures and non-contractile structures should be of interest when considering static balance control ability improvement. PMID:29760375

Effect of Ankle Range of Motion (ROM) and Lower-Extremity Muscle Strength on Static Balance Control Ability in Young Adults: A Regression Analysis.

PubMed

Kim, Seong-Gil; Kim, Wan-Soo

2018-05-15

BACKGROUND The purpose of this study was to investigate the effect of ankle ROM and lower-extremity muscle strength on static balance control ability in young adults. MATERIAL AND METHODS This study was conducted with 65 young adults, but 10 young adults dropped out during the measurement, so 55 young adults (male: 19, female: 36) completed the study. Postural sway (length and velocity) was measured with eyes open and closed, and ankle ROM (AROM and PROM of dorsiflexion and plantarflexion) and lower-extremity muscle strength (flexor and extensor of hip, knee, and ankle joint) were measured. Pearson correlation coefficient was used to examine the correlation between variables and static balance ability. Simple linear regression analysis and multiple linear regression analysis were used to examine the effect of variables on static balance ability. RESULTS In correlation analysis, plantarflexion ROM (AROM and PROM) and lower-extremity muscle strength (except hip extensor) were significantly correlated with postural sway (p<0.05). In simple correlation analysis, all variables that passed the correlation analysis procedure had significant influence (p<0.05). In multiple linear regression analysis, plantar flexion PROM with eyes open significantly influenced sway length (B=0.681) and sway velocity (B=0.011). CONCLUSIONS Lower-extremity muscle strength and ankle plantarflexion ROM influenced static balance control ability, with ankle plantarflexion PROM showing the greatest influence. Therefore, both contractile structures and non-contractile structures should be of interest when considering static balance control ability improvement.

Functional capacity following univentricular repair--midterm outcome.

PubMed

Sen, Supratim; Bandyopadhyay, Biswajit; Eriksson, Peter; Chattopadhyay, Amitabha

2012-01-01

Previous studies have seldom compared functional capacity in children following Fontan procedure alongside those with Glenn operation as destination therapy. We hypothesized that Fontan circulation enables better midterm submaximal exercise capacity as compared to Glenn physiology and evaluated this using the 6-minute walk test. Fifty-seven children aged 5-18 years with Glenn (44) or Fontan (13) operations were evaluated with standard 6-minute walk protocols. Baseline SpO(2) was significantly lower in Glenn patients younger than 10 years compared to Fontan counterparts and similar in the two groups in older children. Postexercise SpO(2) fell significantly in Glenn patients compared to the Fontan group. There was no statistically significant difference in baseline, postexercise, or postrecovery heart rates (HRs), or 6-minute walk distances in the two groups. Multiple regression analysis revealed lower resting HR, higher resting SpO(2) , and younger age at latest operation to be significant determinants of longer 6-minute walk distance. Multiple regression analysis also established that younger age at operation, higher resting SpO(2) , Fontan operation, lower resting HR, and lower postexercise HR were significant determinants of higher postexercise SpO(2) . Younger age at operation and exercise, lower resting HR and postexercise HR, higher resting SpO(2) and postexercise SpO(2) , and dominant ventricular morphology being left ventricular or indeterminate/mixed had significant association with better 6-minute work on multiple regression analysis. Lower resting HR had linear association with longer 6-minute walk distances in the Glenn patients. Compared to Glenn physiology, Fontan operation did not have better submaximal exercise capacity assessed by walk distance or work on multiple regression analysis. Lower resting HR, higher resting SpO(2) , and younger age at operation were factors uniformly associated with better submaximal exercise capacity. © 2012 Wiley Periodicals, Inc.

Visual grading characteristics and ordinal regression analysis during optimisation of CT head examinations.

PubMed

Zarb, Francis; McEntee, Mark F; Rainford, Louise

2015-06-01

To evaluate visual grading characteristics (VGC) and ordinal regression analysis during head CT optimisation as a potential alternative to visual grading assessment (VGA), traditionally employed to score anatomical visualisation. Patient images (n = 66) were obtained using current and optimised imaging protocols from two CT suites: a 16-slice scanner at the national Maltese centre for trauma and a 64-slice scanner in a private centre. Local resident radiologists (n = 6) performed VGA followed by VGC and ordinal regression analysis. VGC alone indicated that optimised protocols had similar image quality as current protocols. Ordinal logistic regression analysis provided an in-depth evaluation, criterion by criterion allowing the selective implementation of the protocols. The local radiology review panel supported the implementation of optimised protocols for brain CT examinations (including trauma) in one centre, achieving radiation dose reductions ranging from 24 % to 36 %. In the second centre a 29 % reduction in radiation dose was achieved for follow-up cases. The combined use of VGC and ordinal logistic regression analysis led to clinical decisions being taken on the implementation of the optimised protocols. This improved method of image quality analysis provided the evidence to support imaging protocol optimisation, resulting in significant radiation dose savings. • There is need for scientifically based image quality evaluation during CT optimisation. • VGC and ordinal regression analysis in combination led to better informed clinical decisions. • VGC and ordinal regression analysis led to dose reductions without compromising diagnostic efficacy.

Construction of mathematical model for measuring material concentration by colorimetric method

NASA Astrophysics Data System (ADS)

Liu, Bing; Gao, Lingceng; Yu, Kairong; Tan, Xianghua

2018-06-01

This paper use the method of multiple linear regression to discuss the data of C problem of mathematical modeling in 2017. First, we have established a regression model for the concentration of 5 substances. But only the regression model of the substance concentration of urea in milk can pass through the significance test. The regression model established by the second sets of data can pass the significance test. But this model exists serious multicollinearity. We have improved the model by principal component analysis. The improved model is used to control the system so that it is possible to measure the concentration of material by direct colorimetric method.

A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

PubMed

Anderson, Carl A; McRae, Allan F; Visscher, Peter M

2006-07-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

Length bias correction in gene ontology enrichment analysis using logistic regression.

PubMed

Mi, Gu; Di, Yanming; Emerson, Sarah; Cumbie, Jason S; Chang, Jeff H

2012-01-01

When assessing differential gene expression from RNA sequencing data, commonly used statistical tests tend to have greater power to detect differential expression of genes encoding longer transcripts. This phenomenon, called "length bias", will influence subsequent analyses such as Gene Ontology enrichment analysis. In the presence of length bias, Gene Ontology categories that include longer genes are more likely to be identified as enriched. These categories, however, are not necessarily biologically more relevant. We show that one can effectively adjust for length bias in Gene Ontology analysis by including transcript length as a covariate in a logistic regression model. The logistic regression model makes the statistical issue underlying length bias more transparent: transcript length becomes a confounding factor when it correlates with both the Gene Ontology membership and the significance of the differential expression test. The inclusion of the transcript length as a covariate allows one to investigate the direct correlation between the Gene Ontology membership and the significance of testing differential expression, conditional on the transcript length. We present both real and simulated data examples to show that the logistic regression approach is simple, effective, and flexible.

Moderation analysis using a two-level regression model.

PubMed

Yuan, Ke-Hai; Cheng, Ying; Maxwell, Scott

2014-10-01

Moderation analysis is widely used in social and behavioral research. The most commonly used model for moderation analysis is moderated multiple regression (MMR) in which the explanatory variables of the regression model include product terms, and the model is typically estimated by least squares (LS). This paper argues for a two-level regression model in which the regression coefficients of a criterion variable on predictors are further regressed on moderator variables. An algorithm for estimating the parameters of the two-level model by normal-distribution-based maximum likelihood (NML) is developed. Formulas for the standard errors (SEs) of the parameter estimates are provided and studied. Results indicate that, when heteroscedasticity exists, NML with the two-level model gives more efficient and more accurate parameter estimates than the LS analysis of the MMR model. When error variances are homoscedastic, NML with the two-level model leads to essentially the same results as LS with the MMR model. Most importantly, the two-level regression model permits estimating the percentage of variance of each regression coefficient that is due to moderator variables. When applied to data from General Social Surveys 1991, NML with the two-level model identified a significant moderation effect of race on the regression of job prestige on years of education while LS with the MMR model did not. An R package is also developed and documented to facilitate the application of the two-level model.

Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Sheyenne River, North Dakota, 1980-2006

USGS Publications Warehouse

Ryberg, Karen R.

2007-01-01

This report presents the results of a study by the U.S. Geological Survey, done in cooperation with the North Dakota State Water Commission, to estimate water-quality constituent concentrations at seven sites on the Sheyenne River, N. Dak. Regression analysis of water-quality data collected in 1980-2006 was used to estimate concentrations for hardness, dissolved solids, calcium, magnesium, sodium, and sulfate. The explanatory variables examined for the regression relations were continuously monitored streamflow, specific conductance, and water temperature. For the conditions observed in 1980-2006, streamflow was a significant explanatory variable for some constituents. Specific conductance was a significant explanatory variable for all of the constituents, and water temperature was not a statistically significant explanatory variable for any of the constituents in this study. The regression relations were evaluated using common measures of variability, including R2, the proportion of variability in the estimated constituent concentration explained by the explanatory variables and regression equation. R2 values ranged from 0.784 for calcium to 0.997 for dissolved solids. The regression relations also were evaluated by calculating the median relative percentage difference (RPD) between measured constituent concentration and the constituent concentration estimated by the regression equations. Median RPDs ranged from 1.7 for dissolved solids to 11.5 for sulfate. The regression relations also may be used to estimate daily constituent loads. The relations should be monitored for change over time, especially at sites 2 and 3 which have a short period of record. In addition, caution should be used when the Sheyenne River is affected by ice or when upstream sites are affected by isolated storm runoff. Almost all of the outliers and highly influential samples removed from the analysis were made during periods when the Sheyenne River might be affected by ice.

Analysis of geographical disparities in temporal trends of health outcomes using space-time joinpoint regression

NASA Astrophysics Data System (ADS)

Goovaerts, Pierre

2013-06-01

Analyzing temporal trends in health outcomes can provide a more comprehensive picture of the burden of a disease like cancer and generate new insights about the impact of various interventions. In the United States such an analysis is increasingly conducted using joinpoint regression outside a spatial framework, which overlooks the existence of significant variation among U.S. counties and states with regard to the incidence of cancer. This paper presents several innovative ways to account for space in joinpoint regression: (1) prior filtering of noise in the data by binomial kriging and use of the kriging variance as measure of reliability in weighted least-square regression, (2) detection of significant boundaries between adjacent counties based on tests of parallelism of time trends and confidence intervals of annual percent change of rates, and (3) creation of spatially compact groups of counties with similar temporal trends through the application of hierarchical cluster analysis to the results of boundary analysis. The approach is illustrated using time series of proportions of prostate cancer late-stage cases diagnosed yearly in every county of Florida since 1980s. The annual percent change (APC) in late-stage diagnosis and the onset years for significant declines vary greatly across Florida. Most counties with non-significant average APC are located in the north-western part of Florida, known as the Panhandle, which is more rural than other parts of Florida. The number of significant boundaries peaked in the early 1990s when prostate-specific antigen (PSA) test became widely available, a temporal trend that suggests the existence of geographical disparities in the implementation and/or impact of the new screening procedure, in particular as it began available.

Is adult gait less susceptible than paediatric gait to hip joint centre regression equation error?

PubMed

Kiernan, D; Hosking, J; O'Brien, T

2016-03-01

Hip joint centre (HJC) regression equation error during paediatric gait has recently been shown to have clinical significance. In relation to adult gait, it has been inferred that comparable errors with children in absolute HJC position may in fact result in less significant kinematic and kinetic error. This study investigated the clinical agreement of three commonly used regression equation sets (Bell et al., Davis et al. and Orthotrak) for adult subjects against the equations of Harrington et al. The relationship between HJC position error and subject size was also investigated for the Davis et al. set. Full 3-dimensional gait analysis was performed on 12 healthy adult subjects with data for each set compared to Harrington et al. The Gait Profile Score, Gait Variable Score and GDI-kinetic were used to assess clinical significance while differences in HJC position between the Davis and Harrington sets were compared to leg length and subject height using regression analysis. A number of statistically significant differences were present in absolute HJC position. However, all sets fell below the clinically significant thresholds (GPS <1.6°, GDI-Kinetic <3.6 points). Linear regression revealed a statistically significant relationship for both increasing leg length and increasing subject height with decreasing error in anterior/posterior and superior/inferior directions. Results confirm a negligible clinical error for adult subjects suggesting that any of the examined sets could be used interchangeably. Decreasing error with both increasing leg length and increasing subject height suggests that the Davis set should be used cautiously on smaller subjects. Copyright © 2016 Elsevier B.V. All rights reserved.

Statistical methods for astronomical data with upper limits. II - Correlation and regression

NASA Technical Reports Server (NTRS)

Isobe, T.; Feigelson, E. D.; Nelson, P. I.

1986-01-01

Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.

Patterns of medicinal plant use: an examination of the Ecuadorian Shuar medicinal flora using contingency table and binomial analyses.

PubMed

Bennett, Bradley C; Husby, Chad E

2008-03-28

Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111-119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Modified regression models (which accommodated assumptions of linear regression) reduced R(2) to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.

INNOVATIVE INSTRUMENTATION AND ANALYSIS OF THE TEMPERATURE MEASUREMENT FOR HIGH TEMPERATURE GASIFICATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seong W. Lee

2004-10-01

The systematic tests of the gasifier simulator on the clean thermocouple were completed in this reporting period. Within the systematic tests on the clean thermocouple, five (5) factors were considered as the experimental parameters including air flow rate, water flow rate, fine dust particle amount, ammonia addition and high/low frequency device (electric motor). The fractional factorial design method was used in the experiment design with sixteen (16) data sets of readings. Analysis of Variances (ANOVA) was applied to the results from systematic tests. The ANOVA results show that the un-balanced motor vibration frequency did not have the significant impact onmore » the temperature changes in the gasifier simulator. For the fine dust particles testing, the amount of fine dust particles has significant impact to the temperature measurements in the gasifier simulator. The effects of the air and water on the temperature measurements show the same results as reported in the previous report. The ammonia concentration was included as an experimental parameter for the reducing environment in this reporting period. The ammonia concentration does not seem to be a significant factor on the temperature changes. The linear regression analysis was applied to the temperature reading with five (5) factors. The accuracy of the linear regression is relatively low, which is less than 10% accuracy. Nonlinear regression was also conducted to the temperature reading with the same factors. Since the experiments were designed in two (2) levels, the nonlinear regression is not very effective with the dataset (16 readings). An extra central point test was conducted. With the data of the center point testing, the accuracy of the nonlinear regression is much better than the linear regression.« less

Is math anxiety in the secondary classroom limiting physics mastery? A study of math anxiety and physics performance

NASA Astrophysics Data System (ADS)

Mercer, Gary J.

This quantitative study examined the relationship between secondary students with math anxiety and physics performance in an inquiry-based constructivist classroom. The Revised Math Anxiety Rating Scale was used to evaluate math anxiety levels. The results were then compared to the performance on a physics standardized final examination. A simple correlation was performed, followed by a multivariate regression analysis to examine effects based on gender and prior math background. The correlation showed statistical significance between math anxiety and physics performance. The regression analysis showed statistical significance for math anxiety, physics performance, and prior math background, but did not show statistical significance for math anxiety, physics performance, and gender.

Effect of duration of denervation on outcomes of ansa-recurrent laryngeal nerve reinnervation.

PubMed

Li, Meng; Chen, Shicai; Wang, Wei; Chen, Donghui; Zhu, Minhui; Liu, Fei; Zhang, Caiyun; Li, Yan; Zheng, Hongliang

2014-08-01

To investigate the efficacy of laryngeal reinnervation with ansa cervicalis among unilateral vocal fold paralysis (UVFP) patients with different denervation durations. We retrospectively reviewed 349 consecutive UVFP cases of delayed ansa cervicalis to the recurrent laryngeal nerve (RLN) anastomosis. Potential influencing factors were analyzed in multivariable logistic regression analysis. Stratification analysis performed was aimed at one of the identified significant variables: denervation duration. Videostroboscopy, perceptual evaluation, acoustic analysis, maximum phonation time (MPT), and laryngeal electromyography (EMG) were performed preoperatively and postoperatively. Gender, age, preoperative EMG status and denervation duration were analyzed in multivariable logistic regression analysis. Stratification analysis was performed on denervation duration, which was divided into three groups according to the interval between RLN injury and reinnervation: group A, 6 to 12 months; group B, 12 to 24 months; and group C, > 24 months. Age, preoperative EMG, and denervation duration were identified as significant variables in multivariable logistic regression analysis. Stratification analysis on denervation duration showed significant differences between group A and C and between group B and C (P < 0.05)-but showed no significant difference between group A and B (P > 0.05) with regard to parameters overall grade, jitter, shimmer, noise-to-harmonics ratio, MPT, and postoperative EMG. In addition, videostroboscopic and laryngeal EMG data, perceptual and acoustic parameters, and MPT values were significantly improved postoperatively in each denervation duration group (P < 0.01). Although delayed laryngeal reinnervation is proved valid for UVFP, surgical outcome is better if the procedure is performed within 2 years after nerve injury than that over 2 years. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Regression analysis for solving diagnosis problem of children's health

NASA Astrophysics Data System (ADS)

Cherkashina, Yu A.; Gerget, O. M.

2016-04-01

The paper includes results of scientific researches. These researches are devoted to the application of statistical techniques, namely, regression analysis, to assess the health status of children in the neonatal period based on medical data (hemostatic parameters, parameters of blood tests, the gestational age, vascular-endothelial growth factor) measured at 3-5 days of children's life. In this paper a detailed description of the studied medical data is given. A binary logistic regression procedure is discussed in the paper. Basic results of the research are presented. A classification table of predicted values and factual observed values is shown, the overall percentage of correct recognition is determined. Regression equation coefficients are calculated, the general regression equation is written based on them. Based on the results of logistic regression, ROC analysis was performed, sensitivity and specificity of the model are calculated and ROC curves are constructed. These mathematical techniques allow carrying out diagnostics of health of children providing a high quality of recognition. The results make a significant contribution to the development of evidence-based medicine and have a high practical importance in the professional activity of the author.

Differences in Risk Factors for Rotator Cuff Tears between Elderly Patients and Young Patients.

PubMed

Watanabe, Akihisa; Ono, Qana; Nishigami, Tomohiko; Hirooka, Takahiko; Machida, Hirohisa

2018-02-01

It has been unclear whether the risk factors for rotator cuff tears are the same at all ages or differ between young and older populations. In this study, we examined the risk factors for rotator cuff tears using classification and regression tree analysis as methods of nonlinear regression analysis. There were 65 patients in the rotator cuff tears group and 45 patients in the intact rotator cuff group. Classification and regression tree analysis was performed to predict rotator cuff tears. The target factor was rotator cuff tears; explanatory variables were age, sex, trauma, and critical shoulder angle≥35°. In the results of classification and regression tree analysis, the tree was divided at age 64. For patients aged≥64, the tree was divided at trauma. For patients aged<64, the tree was divided at critical shoulder angle≥35°. The odds ratio for critical shoulder angle≥35° was significant for all ages (5.89), and for patients aged<64 (10.3) while trauma was only a significant factor for patients aged≥64 (5.13). Age, trauma, and critical shoulder angle≥35° were related to rotator cuff tears in this study. However, these risk factors showed different trends according to age group, not a linear relationship.

[Local Regression Algorithm Based on Net Analyte Signal and Its Application in Near Infrared Spectral Analysis].

PubMed

Zhang, Hong-guang; Lu, Jian-gang

2016-02-01

Abstract To overcome the problems of significant difference among samples and nonlinearity between the property and spectra of samples in spectral quantitative analysis, a local regression algorithm is proposed in this paper. In this algorithm, net signal analysis method(NAS) was firstly used to obtain the net analyte signal of the calibration samples and unknown samples, then the Euclidean distance between net analyte signal of the sample and net analyte signal of calibration samples was calculated and utilized as similarity index. According to the defined similarity index, the local calibration sets were individually selected for each unknown sample. Finally, a local PLS regression model was built on each local calibration sets for each unknown sample. The proposed method was applied to a set of near infrared spectra of meat samples. The results demonstrate that the prediction precision and model complexity of the proposed method are superior to global PLS regression method and conventional local regression algorithm based on spectral Euclidean distance.

Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

PubMed

Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

2017-05-01

This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Undergraduate Student Motivation in Modularized Developmental Mathematics Courses

ERIC Educational Resources Information Center

Pachlhofer, Keith A.

2017-01-01

This study used the Motivated Strategies for Learning Questionnaire in modularized courses at three institutions across the nation (N = 189), and multiple regression was completed to investigate five categories of student motivation that predicted academic success and course completion. The overall multiple regression analysis was significant and…

Categorical Variables in Multiple Regression: Some Cautions.

ERIC Educational Resources Information Center

O'Grady, Kevin E.; Medoff, Deborah R.

1988-01-01

Limitations of dummy coding and nonsense coding as methods of coding categorical variables for use as predictors in multiple regression analysis are discussed. The combination of these approaches often yields estimates and tests of significance that are not intended by researchers for inclusion in their models. (SLD)

Kernel machine SNP set analysis provides new insight into the association between obesity and polymorphisms located on the chromosomal 16q.12.2 region: Tehran Lipid and Glucose Study.

PubMed

Javanrouh, Niloufar; Daneshpour, Maryam S; Soltanian, Ali Reza; Tapak, Leili

2018-06-05

Obesity is a serious health problem that leads to low quality of life and early mortality. To the purpose of prevention and gene therapy for such a worldwide disease, genome wide association study is a powerful tool for finding SNPs associated with increased risk of obesity. To conduct an association analysis, kernel machine regression is a generalized regression method, has an advantage of considering the epistasis effects as well as the correlation between individuals due to unknown factors. In this study, information of the people who participated in Tehran cardio-metabolic genetic study was used. They were genotyped for the chromosomal region, evaluation 986 variations located at 16q12.2; build 38hg. Kernel machine regression and single SNP analysis were used to assess the association between obesity and SNPs genotyped data. We found that associated SNP sets with obesity, were almost in the FTO (P = 0.01), AIKTIP (P = 0.02) and MMP2 (P = 0.02) genes. Moreover, two SNPs, i.e., rs10521296 and rs11647470, showed significant association with obesity using kernel regression (P = 0.02). In conclusion, significant sets were randomly distributed throughout the region with more density around the FTO, AIKTIP and MMP2 genes. Furthermore, two intergenic SNPs showed significant association after using kernel machine regression. Therefore, more studies have to be conducted to assess their functionality or precise mechanism. Copyright © 2018 Elsevier B.V. All rights reserved.

Determining the Statistical Significance of Relative Weights

ERIC Educational Resources Information Center

Tonidandel, Scott; LeBreton, James M.; Johnson, Jeff W.

2009-01-01

Relative weight analysis is a procedure for estimating the relative importance of correlated predictors in a regression equation. Because the sampling distribution of relative weights is unknown, researchers using relative weight analysis are unable to make judgments regarding the statistical significance of the relative weights. J. W. Johnson…

Meta-Analysis of the Reasoned Action Approach (RAA) to Understanding Health Behaviors.

PubMed

McEachan, Rosemary; Taylor, Natalie; Harrison, Reema; Lawton, Rebecca; Gardner, Peter; Conner, Mark

2016-08-01

Reasoned action approach (RAA) includes subcomponents of attitude (experiential/instrumental), perceived norm (injunctive/descriptive), and perceived behavioral control (capacity/autonomy) to predict intention and behavior. To provide a meta-analysis of the RAA for health behaviors focusing on comparing the pairs of RAA subcomponents and differences between health protection and health-risk behaviors. The present research reports a meta-analysis of correlational tests of RAA subcomponents, examination of moderators, and combined effects of subcomponents on intention and behavior. Regressions were used to predict intention and behavior based on data from studies measuring all variables. Capacity and experiential attitude had large, and other constructs had small-medium-sized correlations with intention; all constructs except autonomy were significant independent predictors of intention in regressions. Intention, capacity, and experiential attitude had medium-large, and other constructs had small-medium-sized correlations with behavior; intention, capacity, experiential attitude, and descriptive norm were significant independent predictors of behavior in regressions. The RAA subcomponents have utility in predicting and understanding health behaviors.

Tensile properties of cooked meat sausages and their correlation with texture profile analysis (TPA) parameters and physico-chemical characteristics.

PubMed

Herrero, A M; de la Hoz, L; Ordóñez, J A; Herranz, B; Romero de Ávila, M D; Cambero, M I

2008-11-01

The possibilities of using breaking strength (BS) and energy to fracture (EF) for monitoring textural properties of some cooked meat sausages (chopped, mortadella and galantines) were studied. Texture profile analysis (TPA), folding test and physico-chemical measurements were also performed. Principal component analysis enabled these meat products to be grouped into three textural profiles which showed significant (p<0.05) differences mainly for BS, hardness, adhesiveness and cohesiveness. Multivariate analysis indicated that BS, EF and TPA parameters were correlated (p<0.05) for every individual meat product (chopped, mortadella and galantines) and all products together. On the basis of these results, TPA parameters could be used for constructing regression models to predict BS. The resulting regression model for all cooked meat products was BS=-0.160+6.600∗cohesiveness-1.255∗adhesiveness+0.048∗hardness-506.31∗springiness (R(2)=0.745, p<0.00005). Simple linear regression analysis showed significant coefficients of determination between BS (R(2)=0.586, p<0.0001) versus folding test grade (FG) and EF versus FG (R(2)=0.564, p<0.0001).

A Systematic Review and Meta-Regression Analysis of Lung Cancer Risk and Inorganic Arsenic in Drinking Water.

PubMed

Lamm, Steven H; Ferdosi, Hamid; Dissen, Elisabeth K; Li, Ji; Ahn, Jaeil

2015-12-07

High levels (> 200 µg/L) of inorganic arsenic in drinking water are known to be a cause of human lung cancer, but the evidence at lower levels is uncertain. We have sought the epidemiological studies that have examined the dose-response relationship between arsenic levels in drinking water and the risk of lung cancer over a range that includes both high and low levels of arsenic. Regression analysis, based on six studies identified from an electronic search, examined the relationship between the log of the relative risk and the log of the arsenic exposure over a range of 1-1000 µg/L. The best-fitting continuous meta-regression model was sought and found to be a no-constant linear-quadratic analysis where both the risk and the exposure had been logarithmically transformed. This yielded both a statistically significant positive coefficient for the quadratic term and a statistically significant negative coefficient for the linear term. Sub-analyses by study design yielded results that were similar for both ecological studies and non-ecological studies. Statistically significant X-intercepts consistently found no increased level of risk at approximately 100-150 µg/L arsenic.

A Systematic Review and Meta-Regression Analysis of Lung Cancer Risk and Inorganic Arsenic in Drinking Water

PubMed Central

Lamm, Steven H.; Ferdosi, Hamid; Dissen, Elisabeth K.; Li, Ji; Ahn, Jaeil

2015-01-01

High levels (> 200 µg/L) of inorganic arsenic in drinking water are known to be a cause of human lung cancer, but the evidence at lower levels is uncertain. We have sought the epidemiological studies that have examined the dose-response relationship between arsenic levels in drinking water and the risk of lung cancer over a range that includes both high and low levels of arsenic. Regression analysis, based on six studies identified from an electronic search, examined the relationship between the log of the relative risk and the log of the arsenic exposure over a range of 1–1000 µg/L. The best-fitting continuous meta-regression model was sought and found to be a no-constant linear-quadratic analysis where both the risk and the exposure had been logarithmically transformed. This yielded both a statistically significant positive coefficient for the quadratic term and a statistically significant negative coefficient for the linear term. Sub-analyses by study design yielded results that were similar for both ecological studies and non-ecological studies. Statistically significant X-intercepts consistently found no increased level of risk at approximately 100–150 µg/L arsenic. PMID:26690190

Serum dehydroepiandrosterone sulphate, psychosocial factors and musculoskeletal pain in workers.

PubMed

Marinelli, A; Prodi, A; Pesel, G; Ronchese, F; Bovenzi, M; Negro, C; Larese Filon, F

2017-12-30

The serum level of dehydroepiandrosterone sulphate (DHEA-S) has been suggested as a biological marker of stress. To assess the association between serum DHEA-S, psychosocial factors and musculoskeletal (MS) pain in university workers. The study population included voluntary workers at the scientific departments of the University of Trieste (Italy) who underwent periodical health surveillance from January 2011 to June 2012. DHEA-S level was analysed in serum. The assessment tools included the General Health Questionnaire (GHQ) and a modified Nordic musculoskeletal symptoms questionnaire. The relation between DHEA-S, individual characteristics, pain perception and psychological factors was assessed by means of multivariable linear regression analysis. There were 189 study participants. The study population was characterized by high reward and low effort. Pain perception in the neck, shoulder, upper limbs, upper back and lower back was reported by 42, 32, 19, 29 and 43% of people, respectively. In multivariable regression analysis, gender, age and pain perception in the shoulder and upper limbs were significantly related to serum DHEA-S. Effort and overcommitment were related to shoulder and neck pain but not to DHEA-S. The GHQ score was associated with pain perception in different body sites and inversely to DHEA-S but significance was lost in multivariable regression analysis. DHEA-S was associated with age, gender and perception of MS pain, while effort-reward imbalance dimensions and GHQ score failed to reach the statistical significance in multivariable regression analysis. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Meta-analysis of haplotype-association studies: comparison of methods and empirical evaluation of the literature

PubMed Central

2011-01-01

Background Meta-analysis is a popular methodology in several fields of medical research, including genetic association studies. However, the methods used for meta-analysis of association studies that report haplotypes have not been studied in detail. In this work, methods for performing meta-analysis of haplotype association studies are summarized, compared and presented in a unified framework along with an empirical evaluation of the literature. Results We present multivariate methods that use summary-based data as well as methods that use binary and count data in a generalized linear mixed model framework (logistic regression, multinomial regression and Poisson regression). The methods presented here avoid the inflation of the type I error rate that could be the result of the traditional approach of comparing a haplotype against the remaining ones, whereas, they can be fitted using standard software. Moreover, formal global tests are presented for assessing the statistical significance of the overall association. Although the methods presented here assume that the haplotypes are directly observed, they can be easily extended to allow for such an uncertainty by weighting the haplotypes by their probability. Conclusions An empirical evaluation of the published literature and a comparison against the meta-analyses that use single nucleotide polymorphisms, suggests that the studies reporting meta-analysis of haplotypes contain approximately half of the included studies and produce significant results twice more often. We show that this excess of statistically significant results, stems from the sub-optimal method of analysis used and, in approximately half of the cases, the statistical significance is refuted if the data are properly re-analyzed. Illustrative examples of code are given in Stata and it is anticipated that the methods developed in this work will be widely applied in the meta-analysis of haplotype association studies. PMID:21247440

Application of least median of squared orthogonal distance (LMD) and LMD-based reweighted least squares (RLS) methods on the stock-recruitment relationship

NASA Astrophysics Data System (ADS)

Wang, Yan-Jun; Liu, Qun

1999-03-01

Analysis of stock-recruitment (SR) data is most often done by fitting various SR relationship curves to the data. Fish population dynamics data often have stochastic variations and measurement errors, which usually result in a biased regression analysis. This paper presents a robust regression method, least median of squared orthogonal distance (LMD), which is insensitive to abnormal values in the dependent and independent variables in a regression analysis. Outliers that have significantly different variance from the rest of the data can be identified in a residual analysis. Then, the least squares (LS) method is applied to the SR data with defined outliers being down weighted. The application of LMD and LMD-based Reweighted Least Squares (RLS) method to simulated and real fisheries SR data is explored.

Cervical Vertebral Body's Volume as a New Parameter for Predicting the Skeletal Maturation Stages.

PubMed

Choi, Youn-Kyung; Kim, Jinmi; Yamaguchi, Tetsutaro; Maki, Koutaro; Ko, Ching-Chang; Kim, Yong-Il

2016-01-01

This study aimed to determine the correlation between the volumetric parameters derived from the images of the second, third, and fourth cervical vertebrae by using cone beam computed tomography with skeletal maturation stages and to propose a new formula for predicting skeletal maturation by using regression analysis. We obtained the estimation of skeletal maturation levels from hand-wrist radiographs and volume parameters derived from the second, third, and fourth cervical vertebrae bodies from 102 Japanese patients (54 women and 48 men, 5-18 years of age). We performed Pearson's correlation coefficient analysis and simple regression analysis. All volume parameters derived from the second, third, and fourth cervical vertebrae exhibited statistically significant correlations (P < 0.05). The simple regression model with the greatest R-square indicated the fourth-cervical-vertebra volume as an independent variable with a variance inflation factor less than ten. The explanation power was 81.76%. Volumetric parameters of cervical vertebrae using cone beam computed tomography are useful in regression models. The derived regression model has the potential for clinical application as it enables a simple and quantitative analysis to evaluate skeletal maturation level.

Cervical Vertebral Body's Volume as a New Parameter for Predicting the Skeletal Maturation Stages

PubMed Central

Choi, Youn-Kyung; Kim, Jinmi; Maki, Koutaro; Ko, Ching-Chang

2016-01-01

This study aimed to determine the correlation between the volumetric parameters derived from the images of the second, third, and fourth cervical vertebrae by using cone beam computed tomography with skeletal maturation stages and to propose a new formula for predicting skeletal maturation by using regression analysis. We obtained the estimation of skeletal maturation levels from hand-wrist radiographs and volume parameters derived from the second, third, and fourth cervical vertebrae bodies from 102 Japanese patients (54 women and 48 men, 5–18 years of age). We performed Pearson's correlation coefficient analysis and simple regression analysis. All volume parameters derived from the second, third, and fourth cervical vertebrae exhibited statistically significant correlations (P < 0.05). The simple regression model with the greatest R-square indicated the fourth-cervical-vertebra volume as an independent variable with a variance inflation factor less than ten. The explanation power was 81.76%. Volumetric parameters of cervical vertebrae using cone beam computed tomography are useful in regression models. The derived regression model has the potential for clinical application as it enables a simple and quantitative analysis to evaluate skeletal maturation level. PMID:27340668

Radiomorphometric analysis of frontal sinus for sex determination.

PubMed

Verma, Saumya; Mahima, V G; Patil, Karthikeya

2014-09-01

Sex determination of unknown individuals carries crucial significance in forensic research, in cases where fragments of skull persist with no likelihood of identification based on dental arch. In these instances sex determination becomes important to rule out certain number of possibilities instantly and helps in establishing a biological profile of human remains. The aim of the study is to evaluate a mathematical method based on logistic regression analysis capable of ascertaining the sex of individuals in the South Indian population. The study was conducted in the department of Oral Medicine and Radiology. The right and left areas, maximum height, width of frontal sinus were determined in 100 Caldwell views of 50 women and 50 men aged 20 years and above, with the help of Vernier callipers and a square grid with 1 square measuring 1mm(2) in area. Student's t-test, logistic regression analysis. The mean values of variables were greater in men, based on Student's t-test at 5% level of significance. The mathematical model based on logistic regression analysis gave percentage agreement of total area to correctly predict the female gender as 55.2%, of right area as 60.9% and of left area as 55.2%. The areas of the frontal sinus and the logistic regression proved to be unreliable in sex determination. (Logit = 0.924 - 0.00217 × right area).

Performance of an Axisymmetric Rocket Based Combined Cycle Engine During Rocket Only Operation Using Linear Regression Analysis

NASA Technical Reports Server (NTRS)

Smith, Timothy D.; Steffen, Christopher J., Jr.; Yungster, Shaye; Keller, Dennis J.

1998-01-01

The all rocket mode of operation is shown to be a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. An axisymmetric RBCC engine was used to determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and multiple linear regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inlet diameter ratio. A perfect gas computational fluid dynamics analysis, using both the Spalart-Allmaras and k-omega turbulence models, was performed with the NPARC code to obtain values of vacuum specific impulse. Results from the multiple linear regression analysis showed that for both the full flow and gas generator configurations increasing mixer-ejector area ratio and rocket area ratio increase performance, while increasing mixer-ejector inlet area ratio and mixer-ejector length-to-diameter ratio decrease performance. Increasing injected secondary flow increased performance for the gas generator analysis, but was not statistically significant for the full flow analysis. Chamber pressure was found to be not statistically significant.

Regression Model Term Selection for the Analysis of Strain-Gage Balance Calibration Data

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred; Volden, Thomas R.

2010-01-01

The paper discusses the selection of regression model terms for the analysis of wind tunnel strain-gage balance calibration data. Different function class combinations are presented that may be used to analyze calibration data using either a non-iterative or an iterative method. The role of the intercept term in a regression model of calibration data is reviewed. In addition, useful algorithms and metrics originating from linear algebra and statistics are recommended that will help an analyst (i) to identify and avoid both linear and near-linear dependencies between regression model terms and (ii) to make sure that the selected regression model of the calibration data uses only statistically significant terms. Three different tests are suggested that may be used to objectively assess the predictive capability of the final regression model of the calibration data. These tests use both the original data points and regression model independent confirmation points. Finally, data from a simplified manual calibration of the Ames MK40 balance is used to illustrate the application of some of the metrics and tests to a realistic calibration data set.

Assessing risk factors for periodontitis using regression

NASA Astrophysics Data System (ADS)

Lobo Pereira, J. A.; Ferreira, Maria Cristina; Oliveira, Teresa

2013-10-01

Multivariate statistical analysis is indispensable to assess the associations and interactions between different factors and the risk of periodontitis. Among others, regression analysis is a statistical technique widely used in healthcare to investigate and model the relationship between variables. In our work we study the impact of socio-demographic, medical and behavioral factors on periodontal health. Using regression, linear and logistic models, we can assess the relevance, as risk factors for periodontitis disease, of the following independent variables (IVs): Age, Gender, Diabetic Status, Education, Smoking status and Plaque Index. The multiple linear regression analysis model was built to evaluate the influence of IVs on mean Attachment Loss (AL). Thus, the regression coefficients along with respective p-values will be obtained as well as the respective p-values from the significance tests. The classification of a case (individual) adopted in the logistic model was the extent of the destruction of periodontal tissues defined by an Attachment Loss greater than or equal to 4 mm in 25% (AL≥4mm/≥25%) of sites surveyed. The association measures include the Odds Ratios together with the correspondent 95% confidence intervals.

Neither fixed nor random: weighted least squares meta-regression.

PubMed

Stanley, T D; Doucouliagos, Hristos

2017-03-01

Our study revisits and challenges two core conventional meta-regression estimators: the prevalent use of 'mixed-effects' or random-effects meta-regression analysis and the correction of standard errors that defines fixed-effects meta-regression analysis (FE-MRA). We show how and explain why an unrestricted weighted least squares MRA (WLS-MRA) estimator is superior to conventional random-effects (or mixed-effects) meta-regression when there is publication (or small-sample) bias that is as good as FE-MRA in all cases and better than fixed effects in most practical applications. Simulations and statistical theory show that WLS-MRA provides satisfactory estimates of meta-regression coefficients that are practically equivalent to mixed effects or random effects when there is no publication bias. When there is publication selection bias, WLS-MRA always has smaller bias than mixed effects or random effects. In practical applications, an unrestricted WLS meta-regression is likely to give practically equivalent or superior estimates to fixed-effects, random-effects, and mixed-effects meta-regression approaches. However, random-effects meta-regression remains viable and perhaps somewhat preferable if selection for statistical significance (publication bias) can be ruled out and when random, additive normal heterogeneity is known to directly affect the 'true' regression coefficient. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Functional Data Analysis Applied to Modeling of Severe Acute Mucositis and Dysphagia Resulting From Head and Neck Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dean, Jamie A., E-mail: jamie.dean@icr.ac.uk; Wong, Kee H.; Gay, Hiram

Purpose: Current normal tissue complication probability modeling using logistic regression suffers from bias and high uncertainty in the presence of highly correlated radiation therapy (RT) dose data. This hinders robust estimates of dose-response associations and, hence, optimal normal tissue–sparing strategies from being elucidated. Using functional data analysis (FDA) to reduce the dimensionality of the dose data could overcome this limitation. Methods and Materials: FDA was applied to modeling of severe acute mucositis and dysphagia resulting from head and neck RT. Functional partial least squares regression (FPLS) and functional principal component analysis were used for dimensionality reduction of the dose-volume histogrammore » data. The reduced dose data were input into functional logistic regression models (functional partial least squares–logistic regression [FPLS-LR] and functional principal component–logistic regression [FPC-LR]) along with clinical data. This approach was compared with penalized logistic regression (PLR) in terms of predictive performance and the significance of treatment covariate–response associations, assessed using bootstrapping. Results: The area under the receiver operating characteristic curve for the PLR, FPC-LR, and FPLS-LR models was 0.65, 0.69, and 0.67, respectively, for mucositis (internal validation) and 0.81, 0.83, and 0.83, respectively, for dysphagia (external validation). The calibration slopes/intercepts for the PLR, FPC-LR, and FPLS-LR models were 1.6/−0.67, 0.45/0.47, and 0.40/0.49, respectively, for mucositis (internal validation) and 2.5/−0.96, 0.79/−0.04, and 0.79/0.00, respectively, for dysphagia (external validation). The bootstrapped odds ratios indicated significant associations between RT dose and severe toxicity in the mucositis and dysphagia FDA models. Cisplatin was significantly associated with severe dysphagia in the FDA models. None of the covariates was significantly associated with severe toxicity in the PLR models. Dose levels greater than approximately 1.0 Gy/fraction were most strongly associated with severe acute mucositis and dysphagia in the FDA models. Conclusions: FPLS and functional principal component analysis marginally improved predictive performance compared with PLR and provided robust dose-response associations. FDA is recommended for use in normal tissue complication probability modeling.« less

Functional Data Analysis Applied to Modeling of Severe Acute Mucositis and Dysphagia Resulting From Head and Neck Radiation Therapy.

PubMed

Dean, Jamie A; Wong, Kee H; Gay, Hiram; Welsh, Liam C; Jones, Ann-Britt; Schick, Ulrike; Oh, Jung Hun; Apte, Aditya; Newbold, Kate L; Bhide, Shreerang A; Harrington, Kevin J; Deasy, Joseph O; Nutting, Christopher M; Gulliford, Sarah L

2016-11-15

Current normal tissue complication probability modeling using logistic regression suffers from bias and high uncertainty in the presence of highly correlated radiation therapy (RT) dose data. This hinders robust estimates of dose-response associations and, hence, optimal normal tissue-sparing strategies from being elucidated. Using functional data analysis (FDA) to reduce the dimensionality of the dose data could overcome this limitation. FDA was applied to modeling of severe acute mucositis and dysphagia resulting from head and neck RT. Functional partial least squares regression (FPLS) and functional principal component analysis were used for dimensionality reduction of the dose-volume histogram data. The reduced dose data were input into functional logistic regression models (functional partial least squares-logistic regression [FPLS-LR] and functional principal component-logistic regression [FPC-LR]) along with clinical data. This approach was compared with penalized logistic regression (PLR) in terms of predictive performance and the significance of treatment covariate-response associations, assessed using bootstrapping. The area under the receiver operating characteristic curve for the PLR, FPC-LR, and FPLS-LR models was 0.65, 0.69, and 0.67, respectively, for mucositis (internal validation) and 0.81, 0.83, and 0.83, respectively, for dysphagia (external validation). The calibration slopes/intercepts for the PLR, FPC-LR, and FPLS-LR models were 1.6/-0.67, 0.45/0.47, and 0.40/0.49, respectively, for mucositis (internal validation) and 2.5/-0.96, 0.79/-0.04, and 0.79/0.00, respectively, for dysphagia (external validation). The bootstrapped odds ratios indicated significant associations between RT dose and severe toxicity in the mucositis and dysphagia FDA models. Cisplatin was significantly associated with severe dysphagia in the FDA models. None of the covariates was significantly associated with severe toxicity in the PLR models. Dose levels greater than approximately 1.0 Gy/fraction were most strongly associated with severe acute mucositis and dysphagia in the FDA models. FPLS and functional principal component analysis marginally improved predictive performance compared with PLR and provided robust dose-response associations. FDA is recommended for use in normal tissue complication probability modeling. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

A comparison of three methods of assessing differential item functioning (DIF) in the Hospital Anxiety Depression Scale: ordinal logistic regression, Rasch analysis and the Mantel chi-square procedure.

PubMed

Cameron, Isobel M; Scott, Neil W; Adler, Mats; Reid, Ian C

2014-12-01

It is important for clinical practice and research that measurement scales of well-being and quality of life exhibit only minimal differential item functioning (DIF). DIF occurs where different groups of people endorse items in a scale to different extents after being matched by the intended scale attribute. We investigate the equivalence or otherwise of common methods of assessing DIF. Three methods of measuring age- and sex-related DIF (ordinal logistic regression, Rasch analysis and Mantel χ(2) procedure) were applied to Hospital Anxiety Depression Scale (HADS) data pertaining to a sample of 1,068 patients consulting primary care practitioners. Three items were flagged by all three approaches as having either age- or sex-related DIF with a consistent direction of effect; a further three items identified did not meet stricter criteria for important DIF using at least one method. When applying strict criteria for significant DIF, ordinal logistic regression was slightly less sensitive. Ordinal logistic regression, Rasch analysis and contingency table methods yielded consistent results when identifying DIF in the HADS depression and HADS anxiety scales. Regardless of methods applied, investigators should use a combination of statistical significance, magnitude of the DIF effect and investigator judgement when interpreting the results.

Matched cohort comparison of endovascular abdominal aortic aneurysm repair with and without EndoAnchors.

PubMed

Muhs, Bart E; Jordan, William; Ouriel, Kenneth; Rajaee, Sareh; de Vries, Jean-Paul

2018-06-01

The objective of this study was to examine whether prophylactic use of EndoAnchors (Medtronic, Santa Rosa, Calif) contributes to improved outcomes after endovascular aneurysm repair (EVAR) of abdominal aortic aneurysms through 2 years. The Aneurysm Treatment Using the Heli-FX Aortic Securement System Global Registry (ANCHOR) subjects who received prophylactic EndoAnchors during EVAR were considered for this analysis. Imaging data of retrospective subjects who underwent EVAR at ANCHOR enrolling institutions were obtained to create a control sample. Nineteen baseline anatomic measurements were used to perform propensity score matching, yielding 99 matched pairs. Follow-up imaging of the ANCHOR and control cohorts was then compared to examine outcomes through 2 years, using Kaplan-Meier survival analysis. Freedom from type Ia endoleak was 97.0% ± 2.1% in the ANCHOR cohort and 94.1% ± 2.5% in the control cohort through 2 years (P = .34). The 2-year freedom from neck dilation in the ANCHOR and control cohorts was 90.4% ± 5.6% and 87.3% ± 4.3%, respectively (P = .46); 2-year freedom from sac enlargement was 97.0% ± 2.1% and 94.0% ± 3.0%, respectively (P = .67). No device migration was observed. Aneurysm sac regression was observed in 81.1% ± 9.5% of ANCHOR subjects through 2 years compared with 48.7% ± 5.9% of control subjects (P = .01). Cox regression analysis found an inverse correlation between number of hostile neck criteria met and later sac regression (P = .05). Preoperative neck thrombus circumference and infrarenal diameter were also variables associated with later sac regression, although not to a significant degree (P = .10 and P = .06, respectively). Control subjects with thrombus were significantly less likely to experience later sac regression than those without thrombus (6% and 43%, respectively; P = .001). In ANCHOR subjects, rate of regression was not significantly different in subjects with or without thrombus (33% and 36%, respectively; P = .82). Control subjects with wide aortic necks (>28 mm) were observed to experience sac regression at a lower rate than subjects with smaller diameter necks (10% and 44%, respectively; P = .004). Wide neck and normal neck subjects implanted with EndoAnchors experienced later sac regression at roughly equivalent rates (44% and 33%, respectively; P = .50). In propensity-matched cohorts of subjects undergoing EVAR, the rate of sac regression in subjects treated with EndoAnchors was significantly higher. EndoAnchors may mitigate the adverse effect of wide infrarenal necks and neck thrombus on sac regression, although further studies are needed to evaluate the long-term effect of EndoAnchors. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Does buccal cancer have worse prognosis than other oral cavity cancers?

PubMed

Camilon, P Ryan; Stokes, William A; Fuller, Colin W; Nguyen, Shaun A; Lentsch, Eric J

2014-06-01

To determine whether buccal squamous cell carcinoma has worse overall survival (OS) and disease-specific survival (DSS) than cancers in the rest of the oral cavity. Retrospective analysis of a large population database. We began with a Kaplan-Meier analysis of OS and DSS for buccal versus nonbuccal tumors with unmatched data, followed by an analysis of cases matched for race, age at diagnosis, stage at diagnosis, and treatment modality. This was supported by a univariate Cox regression comparing buccal cancer to nonbuccal cancer, followed by a multivariate Cox regression that included all significant variables studied. With unmatched data, buccal cancer had significantly lesser OS and DSS values than cancers in the rest of the oral cavity (P < .001). After case matching, the differences between OS and DSS for buccal cancer versus nonbuccal oral cancer were no longer significant. Univariate Cox regression models with respect to OS and DSS showed a significant difference between buccal cancer and nonbuccal cancer. However, with multivariate analysis, buccal hazard ratios for OS and DSS were not significant. With the largest series of buccal carcinoma to date, our study concludes that the OS and DSS of buccal cancer are similar to those of cancers in other oral cavity sites once age at diagnosis, tumor stage, treatment, and race are taken into consideration. The previously perceived poor prognosis of buccal carcinoma may be due to variations in tumor presentation, such as later stage and older patient age. 2b. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Modelling fourier regression for time series data- a case study: modelling inflation in foods sector in Indonesia

NASA Astrophysics Data System (ADS)

Prahutama, Alan; Suparti; Wahyu Utami, Tiani

2018-03-01

Regression analysis is an analysis to model the relationship between response variables and predictor variables. The parametric approach to the regression model is very strict with the assumption, but nonparametric regression model isn’t need assumption of model. Time series data is the data of a variable that is observed based on a certain time, so if the time series data wanted to be modeled by regression, then we should determined the response and predictor variables first. Determination of the response variable in time series is variable in t-th (yt), while the predictor variable is a significant lag. In nonparametric regression modeling, one developing approach is to use the Fourier series approach. One of the advantages of nonparametric regression approach using Fourier series is able to overcome data having trigonometric distribution. In modeling using Fourier series needs parameter of K. To determine the number of K can be used Generalized Cross Validation method. In inflation modeling for the transportation sector, communication and financial services using Fourier series yields an optimal K of 120 parameters with R-square 99%. Whereas if it was modeled by multiple linear regression yield R-square 90%.

Support vector methods for survival analysis: a comparison between ranking and regression approaches.

PubMed

Van Belle, Vanya; Pelckmans, Kristiaan; Van Huffel, Sabine; Suykens, Johan A K

2011-10-01

To compare and evaluate ranking, regression and combined machine learning approaches for the analysis of survival data. The literature describes two approaches based on support vector machines to deal with censored observations. In the first approach the key idea is to rephrase the task as a ranking problem via the concordance index, a problem which can be solved efficiently in a context of structural risk minimization and convex optimization techniques. In a second approach, one uses a regression approach, dealing with censoring by means of inequality constraints. The goal of this paper is then twofold: (i) introducing a new model combining the ranking and regression strategy, which retains the link with existing survival models such as the proportional hazards model via transformation models; and (ii) comparison of the three techniques on 6 clinical and 3 high-dimensional datasets and discussing the relevance of these techniques over classical approaches fur survival data. We compare svm-based survival models based on ranking constraints, based on regression constraints and models based on both ranking and regression constraints. The performance of the models is compared by means of three different measures: (i) the concordance index, measuring the model's discriminating ability; (ii) the logrank test statistic, indicating whether patients with a prognostic index lower than the median prognostic index have a significant different survival than patients with a prognostic index higher than the median; and (iii) the hazard ratio after normalization to restrict the prognostic index between 0 and 1. Our results indicate a significantly better performance for models including regression constraints above models only based on ranking constraints. This work gives empirical evidence that svm-based models using regression constraints perform significantly better than svm-based models based on ranking constraints. Our experiments show a comparable performance for methods including only regression or both regression and ranking constraints on clinical data. On high dimensional data, the former model performs better. However, this approach does not have a theoretical link with standard statistical models for survival data. This link can be made by means of transformation models when ranking constraints are included. Copyright © 2011 Elsevier B.V. All rights reserved.

Binary logistic regression-Instrument for assessing museum indoor air impact on exhibits.

PubMed

Bucur, Elena; Danet, Andrei Florin; Lehr, Carol Blaziu; Lehr, Elena; Nita-Lazar, Mihai

2017-04-01

This paper presents a new way to assess the environmental impact on historical artifacts using binary logistic regression. The prediction of the impact on the exhibits during certain pollution scenarios (environmental impact) was calculated by a mathematical model based on the binary logistic regression; it allows the identification of those environmental parameters from a multitude of possible parameters with a significant impact on exhibitions and ranks them according to their severity effect. Air quality (NO 2 , SO 2 , O 3 and PM 2.5 ) and microclimate parameters (temperature, humidity) monitoring data from a case study conducted within exhibition and storage spaces of the Romanian National Aviation Museum Bucharest have been used for developing and validating the binary logistic regression method and the mathematical model. The logistic regression analysis was used on 794 data combinations (715 to develop of the model and 79 to validate it) by a Statistical Package for Social Sciences (SPSS 20.0). The results from the binary logistic regression analysis demonstrated that from six parameters taken into consideration, four of them present a significant effect upon exhibits in the following order: O 3 >PM 2.5 >NO 2 >humidity followed at a significant distance by the effects of SO 2 and temperature. The mathematical model, developed in this study, correctly predicted 95.1 % of the cumulated effect of the environmental parameters upon the exhibits. Moreover, this model could also be used in the decisional process regarding the preventive preservation measures that should be implemented within the exhibition space. The paper presents a new way to assess the environmental impact on historical artifacts using binary logistic regression. The mathematical model developed on the environmental parameters analyzed by the binary logistic regression method could be useful in a decision-making process establishing the best measures for pollution reduction and preventive preservation of exhibits.

Clinical management provided by board-certificated physiatrists in early rehabilitation is a significant determinant of functional improvement in acute stroke patients: a retrospective analysis of Japan rehabilitation database.

PubMed

Kinoshita, Shoji; Kakuda, Wataru; Momosaki, Ryo; Yamada, Naoki; Sugawara, Hidekazu; Watanabe, Shu; Abo, Masahiro

2015-05-01

Early rehabilitation for acute stroke patients is widely recommended. We tested the hypothesis that clinical outcome of stroke patients who receive early rehabilitation managed by board-certificated physiatrists (BCP) is generally better than that provided by other medical specialties. Data of stroke patients who underwent early rehabilitation in 19 acute hospitals between January 2005 and December 2013 were collected from the Japan Rehabilitation Database and analyzed retrospectively. Multivariate linear regression analysis using generalized estimating equations method was performed to assess the association between Functional Independence Measure (FIM) effectiveness and management provided by BCP in early rehabilitation. In addition, multivariate logistic regression analysis was also performed to assess the impact of management provided by BCP in acute phase on discharge destination. After setting the inclusion criteria, data of 3838 stroke patients were eligible for analysis. BCP provided early rehabilitation in 814 patients (21.2%). Both the duration of daily exercise time and the frequency of regular conferencing were significantly higher for patients managed by BCP than by other specialties. Although the mortality rate was not different, multivariate regression analysis showed that FIM effectiveness correlated significantly and positively with the management provided by BCP (coefficient, .35; 95% confidence interval [CI], .012-.059; P < .005). In addition, multivariate logistic analysis identified clinical management by BCP as a significant determinant of home discharge (odds ratio, 1.24; 95% CI, 1.08-1.44; P < .005). Our retrospective cohort study demonstrated that clinical management provided by BCP in early rehabilitation can lead to functional recovery of acute stroke. Copyright © 2015 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Constitution of traditional chinese medicine and related factors in women of childbearing age.

PubMed

Jiang, Qiao-Yu; Li, Jue; Zheng, Liang; Wang, Guang-Hua; Wang, Jing

2018-04-01

This study investigates the constitution of traditional Chinese medicine (TCM) among women who want to be pregnant in one year and explores factors related to TCM constitution. This study was conducted on women who participated in free preconception check-ups provided by the Zhabei District Maternity and Child Care Center in Shanghai, China. The information regarding the female demographic characteristics, physical condition, history of pregnancy and childbearing, diet and behavior, and social psychological factors was collected, and TCM constitution assessment was performed. The Chi-square test, t-test, logistic regression analysis, and multinomial logistic regression analysis were used to explore the related factors of TCM constitution. The participants in this study were aged 28.3 ± 3.0 years. Approximately fifty-five women in this study had Unbalanced Constitution. Logistic regression analysis showed that Shanghai residence, dysmenorrhea, gum bleeding, aversion to vegetables, preference for raw meat, job stress, and economic stress were significantly and negatively associated with Balanced Constitution. Multinomial logistic analysis showed that Shanghai residence was significantly associated with Yang-deficiency, Yin-deficiency, and Stagnant Qi Constitutions; gum bleeding was significantly associated with Yin-deficiency, Stagnant Blood, Stagnant Qi, and Inherited Special Constitutions; aversion to vegetables was significantly associated with Damp-heat Constitution; job stress was significantly associated with Yang-deficiency, Phlegm-dampness, Damp-heat, Stagnant Blood, and Stagnant Qi Constitutions; and economic stress was significantly associated with Yang-deficiency, and Stagnant Qi Constitutions. The application of TCM constitution to preconception care would be beneficial for early identification of potential TCM constitution risks and be beneficial for early intervention (e.g., health education, and dietary education), especially during the women who do not have a medical condition and those who have related factors found in this study. Copyright © 2018. Published by Elsevier Taiwan LLC.

[Spatial interpolation of soil organic matter using regression Kriging and geographically weighted regression Kriging].

PubMed

Yang, Shun-hua; Zhang, Hai-tao; Guo, Long; Ren, Yan

2015-06-01

Relative elevation and stream power index were selected as auxiliary variables based on correlation analysis for mapping soil organic matter. Geographically weighted regression Kriging (GWRK) and regression Kriging (RK) were used for spatial interpolation of soil organic matter and compared with ordinary Kriging (OK), which acts as a control. The results indicated that soil or- ganic matter was significantly positively correlated with relative elevation whilst it had a significantly negative correlation with stream power index. Semivariance analysis showed that both soil organic matter content and its residuals (including ordinary least square regression residual and GWR resi- dual) had strong spatial autocorrelation. Interpolation accuracies by different methods were esti- mated based on a data set of 98 validation samples. Results showed that the mean error (ME), mean absolute error (MAE) and root mean square error (RMSE) of RK were respectively 39.2%, 17.7% and 20.6% lower than the corresponding values of OK, with a relative-improvement (RI) of 20.63. GWRK showed a similar tendency, having its ME, MAE and RMSE to be respectively 60.6%, 23.7% and 27.6% lower than those of OK, with a RI of 59.79. Therefore, both RK and GWRK significantly improved the accuracy of OK interpolation of soil organic matter due to their in- corporation of auxiliary variables. In addition, GWRK performed obviously better than RK did in this study, and its improved performance should be attributed to the consideration of sample spatial locations.

A comparison of methods for the analysis of binomial clustered outcomes in behavioral research.

PubMed

Ferrari, Alberto; Comelli, Mario

2016-12-01

In behavioral research, data consisting of a per-subject proportion of "successes" and "failures" over a finite number of trials often arise. This clustered binary data are usually non-normally distributed, which can distort inference if the usual general linear model is applied and sample size is small. A number of more advanced methods is available, but they are often technically challenging and a comparative assessment of their performances in behavioral setups has not been performed. We studied the performances of some methods applicable to the analysis of proportions; namely linear regression, Poisson regression, beta-binomial regression and Generalized Linear Mixed Models (GLMMs). We report on a simulation study evaluating power and Type I error rate of these models in hypothetical scenarios met by behavioral researchers; plus, we describe results from the application of these methods on data from real experiments. Our results show that, while GLMMs are powerful instruments for the analysis of clustered binary outcomes, beta-binomial regression can outperform them in a range of scenarios. Linear regression gave results consistent with the nominal level of significance, but was overall less powerful. Poisson regression, instead, mostly led to anticonservative inference. GLMMs and beta-binomial regression are generally more powerful than linear regression; yet linear regression is robust to model misspecification in some conditions, whereas Poisson regression suffers heavily from violations of the assumptions when used to model proportion data. We conclude providing directions to behavioral scientists dealing with clustered binary data and small sample sizes. Copyright © 2016 Elsevier B.V. All rights reserved.

Specific factors for prenatal lead exposure in the border area of China.

PubMed

Kawata, Kimiko; Li, Yan; Liu, Hao; Zhang, Xiao Qin; Ushijima, Hiroshi

2006-07-01

The objectives of this study are to examine the prevalence of increased blood lead concentrations in mothers and their umbilical cords, and to identify risk factors for prenatal lead exposure in Kunming city, Yunnan province, China. The study was conducted at two obstetrics departments, and 100 peripartum women were enrolled. The mean blood lead concentrations of the mothers and the umbilical cords were 67.3microg/l and 53.1microg/l, respectively. In multiple linear regression analysis, maternal occupational exposure, maternal consumption of homemade dehydrated vegetables and maternal habitation period in Kunming city were significantly associated with an increase of umbilical cord blood lead concentration. In addition, logistic regression analysis was used to assess the association of umbilical cord blood lead concentrations that possibly have adverse effects on brain development of newborns with each potential risk factor. Maternal frequent use of tableware with color patterns inside was significantly associated with higher cord blood lead concentration in addition to the three items in the multiple linear regression analysis. These points should be considered as specific recommendations for maternal and fetal lead exposure in this city.

A Regression Framework for Effect Size Assessments in Longitudinal Modeling of Group Differences

PubMed Central

Feingold, Alan

2013-01-01

The use of growth modeling analysis (GMA)--particularly multilevel analysis and latent growth modeling--to test the significance of intervention effects has increased exponentially in prevention science, clinical psychology, and psychiatry over the past 15 years. Model-based effect sizes for differences in means between two independent groups in GMA can be expressed in the same metric (Cohen’s d) commonly used in classical analysis and meta-analysis. This article first reviews conceptual issues regarding calculation of d for findings from GMA and then introduces an integrative framework for effect size assessments that subsumes GMA. The new approach uses the structure of the linear regression model, from which effect sizes for findings from diverse cross-sectional and longitudinal analyses can be calculated with familiar statistics, such as the regression coefficient, the standard deviation of the dependent measure, and study duration. PMID:23956615

Feminist identity as a predictor of eating disorder diagnostic status.

PubMed

Green, Melinda A; Scott, Norman A; Riopel, Cori M; Skaggs, Anna K

2008-06-01

Passive Acceptance (PA) and Active Commitment (AC) subscales of the Feminist Identity Development Scale (FIDS) were examined as predictors of eating disorder diagnostic status as assessed by the Questionnaire for Eating Disorder Diagnoses (Q-EDD). Results of a hierarchical regression analysis revealed PA and AC scores were not statistically significant predictors of ED diagnostic status after controlling for diagnostic subtype. Results of a multiple regression analysis revealed FIDS as a statistically significant predictor of ED diagnostic status when failing to control for ED diagnostic subtype. Discrepancies suggest ED diagnostic subtype may serve as a moderator variable in the relationship between ED diagnostic status and FIDS. (c) 2008 Wiley Periodicals, Inc.

Diabetic Prevalence in Bangladesh: The Role of Some Associated Demographic and Socioeconomic Characteristics

NASA Astrophysics Data System (ADS)

Imam, Tasneem

2012-12-01

The study attempts at examining the association of a few selected socio-economic and demographic characteristics on diabetic prevalence. Nationally representative data from BIRDEM 2000 have been used to meet the objectives of the study. Cross tabulation, Chi-square and logistic regression analysis have been used to portray the necessary associations. Chi- square reveals significant relationship between diabetic prevalence and all the selected demographic and socio-economic variables except ìeducationî while logistic regression analysis shows no significant contribution of ìageî and ìeducationî in diabetic prevalence. It has to be noted that, this paper dealt with all the three types of diabetes- Type 1, Type 2 and Gestational.

Detrended fluctuation analysis as a regression framework: Estimating dependence at different scales

NASA Astrophysics Data System (ADS)

Kristoufek, Ladislav

2015-02-01

We propose a framework combining detrended fluctuation analysis with standard regression methodology. The method is built on detrended variances and covariances and it is designed to estimate regression parameters at different scales and under potential nonstationarity and power-law correlations. The former feature allows for distinguishing between effects for a pair of variables from different temporal perspectives. The latter ones make the method a significant improvement over the standard least squares estimation. Theoretical claims are supported by Monte Carlo simulations. The method is then applied on selected examples from physics, finance, environmental science, and epidemiology. For most of the studied cases, the relationship between variables of interest varies strongly across scales.

Regression equations for disinfection by-products for the Mississippi, Ohio and Missouri rivers

USGS Publications Warehouse

Rathbun, R.E.

1996-01-01

Trihalomethane and nonpurgeable total organic-halide formation potentials were determined for the chlorination of water samples from the Mississippi, Ohio and Missouri Rivers. Samples were collected during the summer and fall of 1991 and the spring of 1992 at twelve locations on the Mississippi from New Orleans to Minneapolis, and on the Ohio and Missouri 1.6 km upstream from their confluences with the Mississippi. Formation potentials were determined as a function of pH, initial free-chlorine concentration, and reaction time. Multiple linear regression analysis of the data indicated that pH, reaction time, and the dissolved organic carbon concentration and/or the ultraviolet absorbance of the water were the most significant variables. The initial free-chlorine concentration had less significance and bromide concentration had little or no significance. Analysis of combinations of the dissolved organic carbon concentration and the ultraviolet absorbance indicated that use of the ultraviolet absorbance alone provided the best prediction of the experimental data. Regression coefficients for the variables were generally comparable to coefficients previously presented in the literature for waters from other parts of the United States.

Identifying predictive features in drug response using machine learning: opportunities and challenges.

PubMed

Vidyasagar, Mathukumalli

2015-01-01

This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

Effects of Social Class and School Conditions on Educational Enrollment and Achievement of Boys and Girls in Rural Viet Nam

ERIC Educational Resources Information Center

Nguyen, Phuong L.

2006-01-01

This study examines the effects of parental SES, school quality, and community factors on children's enrollment and achievement in rural areas in Viet Nam, using logistic regression and ordered logistic regression. Multivariate analysis reveals significant differences in educational enrollment and outcomes by level of household expenditures and…

Using Regression Analysis in Departmental Budget Allocations. IR Applications, Volume 24, November 1, 2009

ERIC Educational Resources Information Center

Luna, Andrew L.; Brennan, Kelly A.

2009-01-01

This study uses a regression model to determine if a significant difference exists between the actual budget allocation that an academic department received and the model's predicted budget allocation for that same department. Budget data from a Southeastern Master's/Comprehensive state university were used as the dependent variable, and the…

Multiple linear regression analysis

NASA Technical Reports Server (NTRS)

Edwards, T. R.

1980-01-01

Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

Blastocoele expansion degree predicts live birth after single blastocyst transfer for fresh and vitrified/warmed single blastocyst transfer cycles.

PubMed

Du, Qing-Yun; Wang, En-Yin; Huang, Yan; Guo, Xiao-Yi; Xiong, Yu-Jing; Yu, Yi-Ping; Yao, Gui-Dong; Shi, Sen-Lin; Sun, Ying-Pu

2016-04-01

To evaluate the independent effects of the degree of blastocoele expansion and re-expansion and the inner cell mass (ICM) and trophectoderm (TE) grades on predicting live birth after fresh and vitrified/warmed single blastocyst transfer. Retrospective study. Reproductive medical center. Women undergoing 844 fresh and 370 vitrified/warmed single blastocyst transfer cycles. None. Live-birth rate correlated with blastocyst morphology parameters by logistic regression analysis and Spearman correlations analysis. The degree of blastocoele expansion and re-expansion was the only blastocyst morphology parameter that exhibited a significant ability to predict live birth in both fresh and vitrified/warmed single blastocyst transfer cycles respectively by multivariate logistic regression and Spearman correlations analysis. Although the ICM grade was significantly related to live birth in fresh cycles according to the univariate model, its effect was not maintained in the multivariate logistic analysis. In vitrified/warmed cycles, neither ICM nor TE grade was correlated with live birth by logistic regression analysis. This study is the first to confirm that the degree of blastocoele expansion and re-expansion is a better predictor of live birth after both fresh and vitrified/warmed single blastocyst transfer cycles than ICM or TE grade. Copyright © 2016. Published by Elsevier Inc.

The more total cognitive load is reduced by cues, the better retention and transfer of multimedia learning: A meta-analysis and two meta-regression analyses.

PubMed

Xie, Heping; Wang, Fuxing; Hao, Yanbin; Chen, Jiaxue; An, Jing; Wang, Yuxin; Liu, Huashan

2017-01-01

Cueing facilitates retention and transfer of multimedia learning. From the perspective of cognitive load theory (CLT), cueing has a positive effect on learning outcomes because of the reduction in total cognitive load and avoidance of cognitive overload. However, this has not been systematically evaluated. Moreover, what remains ambiguous is the direct relationship between the cue-related cognitive load and learning outcomes. A meta-analysis and two subsequent meta-regression analyses were conducted to explore these issues. Subjective total cognitive load (SCL) and scores on a retention test and transfer test were selected as dependent variables. Through a systematic literature search, 32 eligible articles encompassing 3,597 participants were included in the SCL-related meta-analysis. Among them, 25 articles containing 2,910 participants were included in the retention-related meta-analysis and the following retention-related meta-regression, while there were 29 articles containing 3,204 participants included in the transfer-related meta-analysis and the transfer-related meta-regression. The meta-analysis revealed a statistically significant cueing effect on subjective ratings of cognitive load (d = -0.11, 95% CI = [-0.19, -0.02], p < 0.05), retention performance (d = 0.27, 95% CI = [0.08, 0.46], p < 0.01), and transfer performance (d = 0.34, 95% CI = [0.12, 0.56], p < 0.01). The subsequent meta-regression analyses showed that dSCL for cueing significantly predicted dretention for cueing (β = -0.70, 95% CI = [-1.02, -0.38], p < 0.001), as well as dtransfer for cueing (β = -0.60, 95% CI = [-0.92, -0.28], p < 0.001). Thus in line with CLT, adding cues in multimedia materials can indeed reduce SCL and promote learning outcomes, and the more SCL is reduced by cues, the better retention and transfer of multimedia learning.

The more total cognitive load is reduced by cues, the better retention and transfer of multimedia learning: A meta-analysis and two meta-regression analyses

PubMed Central

Hao, Yanbin; Chen, Jiaxue; An, Jing; Wang, Yuxin; Liu, Huashan

2017-01-01

Cueing facilitates retention and transfer of multimedia learning. From the perspective of cognitive load theory (CLT), cueing has a positive effect on learning outcomes because of the reduction in total cognitive load and avoidance of cognitive overload. However, this has not been systematically evaluated. Moreover, what remains ambiguous is the direct relationship between the cue-related cognitive load and learning outcomes. A meta-analysis and two subsequent meta-regression analyses were conducted to explore these issues. Subjective total cognitive load (SCL) and scores on a retention test and transfer test were selected as dependent variables. Through a systematic literature search, 32 eligible articles encompassing 3,597 participants were included in the SCL-related meta-analysis. Among them, 25 articles containing 2,910 participants were included in the retention-related meta-analysis and the following retention-related meta-regression, while there were 29 articles containing 3,204 participants included in the transfer-related meta-analysis and the transfer-related meta-regression. The meta-analysis revealed a statistically significant cueing effect on subjective ratings of cognitive load (d = −0.11, 95% CI = [−0.19, −0.02], p < 0.05), retention performance (d = 0.27, 95% CI = [0.08, 0.46], p < 0.01), and transfer performance (d = 0.34, 95% CI = [0.12, 0.56], p < 0.01). The subsequent meta-regression analyses showed that dSCL for cueing significantly predicted dretention for cueing (β = −0.70, 95% CI = [−1.02, −0.38], p < 0.001), as well as dtransfer for cueing (β = −0.60, 95% CI = [−0.92, −0.28], p < 0.001). Thus in line with CLT, adding cues in multimedia materials can indeed reduce SCL and promote learning outcomes, and the more SCL is reduced by cues, the better retention and transfer of multimedia learning. PMID:28854205

Forecasting Air Force Logistics Command Second Destination Transportation: An Application of Multiple Regression Analysis and Neural Networks

DTIC Science & Technology

1990-09-01

without the help from the DSXR staff. William Lyons, Charles Ramsey , and Martin Meeks went above and beyond to help complete this research. Special...develop a valid forecasting model that is significantly more accurate than the one presently used by DSXR and suggested the development and testing of a...method, Strom tested DSXR’s iterative linear regression forecasting technique by examining P1 in the simple regression equation to determine whether

Chronic atrophic gastritis in association with hair mercury level.

PubMed

Xue, Zeyun; Xue, Huiping; Jiang, Jianlan; Lin, Bing; Zeng, Si; Huang, Xiaoyun; An, Jianfu

2014-11-01

The objective of this study was to explore hair mercury level in association with chronic atrophic gastritis, a precancerous stage of gastric cancer (GC), and thus provide a brand new angle of view on the timely intervention of precancerous stage of GC. We recruited 149 healthy volunteers as controls and 152 patients suffering from chronic gastritis as cases. The controls denied upper gastrointestinal discomforts, and the cases were diagnosed as chronic superficial gastritis (n=68) or chronic atrophic gastritis (n=84). We utilized Mercury Automated Analyzer (NIC MA-3000) to detect hair mercury level of both healthy controls and cases of chronic gastritis. The statistic of measurement data was expressed as mean ± standard deviation, which was analyzed using Levene variance equality test and t test. Pearson correlation analysis was employed to determine associated factors affecting hair mercury levels, and multiple stepwise regression analysis was performed to deduce regression equations. Statistical significance is considered if p value is less than 0.05. The overall hair mercury level was 0.908949 ± 0.8844490 ng/g [mean ± standard deviation (SD)] in gastritis cases and 0.460198 ± 0.2712187 ng/g (mean±SD) in healthy controls; the former level was significantly higher than the latter one (p=0.000<0.01). The hair mercury level in chronic atrophic gastritis subgroup was 1.155220 ± 0.9470246 ng/g (mean ± SD) and that in chronic superficial gastritis subgroup was 0.604732 ± 0.6942509 ng/g (mean ± SD); the former level was significantly higher than the latter level (p<0.01). The hair mercury level in chronic superficial gastritis cases was significantly higher than that in healthy controls (p<0.05). The hair mercury level in chronic atrophic gastritis cases was significantly higher than that in healthy controls (p<0.01). Stratified analysis indicated that the hair mercury level in healthy controls with eating seafood was significantly higher than that in healthy controls without eating seafood (p<0.01) and that the hair mercury level in chronic atrophic gastritis cases was significantly higher than that in chronic superficial gastritis cases (p<0.01). Pearson correlation analysis indicated that eating seafood was most correlated with hair mercury level and positively correlated in the healthy controls and that the severity of gastritis was most correlated with hair mercury level and positively correlated in the gastritis cases. Multiple stepwise regression analysis indicated that the regression equation of hair mercury level in controls could be expressed as 0.262 multiplied the value of eating seafood plus 0.434, the model that was statistically significant (p<0.01). Multiple stepwise regression analysis also indicated that the regression equation of hair mercury level in gastritis cases could be expressed as 0.305 multiplied the severity of gastritis, the model that was also statistically significant (p<0.01). The graphs of regression standardized residual for both controls and cases conformed to normal distribution. The main positively correlated factor affecting the hair mercury level is eating seafood in healthy people whereas the predominant positively correlated factor affecting the hair mercury level is the severity of gastritis in chronic gastritis patients. That is to say, the severity of chronic gastritis is positively correlated with the level of hair mercury. The incessantly increased level of hair mercury possibly reflects the development of gastritis from normal stomach to superficial gastritis and to atrophic gastritis. The detection of hair mercury is potentially a means to predict the severity of chronic gastritis and possibly to insinuate the environmental mercury threat to human health in terms of gastritis or even carcinogenesis.

[Visual field progression in glaucoma: cluster analysis].

PubMed

Bresson-Dumont, H; Hatton, J; Foucher, J; Fonteneau, M

2012-11-01

Visual field progression analysis is one of the key points in glaucoma monitoring, but distinction between true progression and random fluctuation is sometimes difficult. There are several different algorithms but no real consensus for detecting visual field progression. The trend analysis of global indices (MD, sLV) may miss localized deficits or be affected by media opacities. Conversely, point-by-point analysis makes progression difficult to differentiate from physiological variability, particularly when the sensitivity of a point is already low. The goal of our study was to analyse visual field progression with the EyeSuite™ Octopus Perimetry Clusters algorithm in patients with no significant changes in global indices or worsening of the analysis of pointwise linear regression. We analyzed the visual fields of 162 eyes (100 patients - 58 women, 42 men, average age 66.8 ± 10.91) with ocular hypertension or glaucoma. For inclusion, at least six reliable visual fields per eye were required, and the trend analysis (EyeSuite™ Perimetry) of visual field global indices (MD and SLV), could show no significant progression. The analysis of changes in cluster mode was then performed. In a second step, eyes with statistically significant worsening of at least one of their clusters were analyzed point-by-point with the Octopus Field Analysis (OFA). Fifty four eyes (33.33%) had a significant worsening in some clusters, while their global indices remained stable over time. In this group of patients, more advanced glaucoma was present than in stable group (MD 6.41 dB vs. 2.87); 64.82% (35/54) of those eyes in which the clusters progressed, however, had no statistically significant change in the trend analysis by pointwise linear regression. Most software algorithms for analyzing visual field progression are essentially trend analyses of global indices, or point-by-point linear regression. This study shows the potential role of analysis by clusters trend. However, for best results, it is preferable to compare the analyses of several tests in combination with morphologic exam. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Investigation of marital satisfaction and its relationship with job stress and general health of nurses in Qazvin, Iran.

PubMed

Azimian, Jalil; Piran, Pegah; Jahanihashemi, Hassan; Dehghankar, Leila

2017-04-01

Pressures in nursing can affect family life and marital problems, disrupt common social problems, increase work-family conflicts and endanger people's general health. To determine marital satisfaction and its relationship with job stress and general health of nurses. This descriptive and cross-sectional study was done in 2015 in medical educational centers of Qazvin by using an ENRICH marital satisfaction scale and General Health and Job Stress questionnaires completed by 123 nurses. Analysis was done by SPSS version 19 using descriptive and analytical statistics (Pearson correlation, t-test, ANOVA, Chi-square, regression line, multiple regression analysis). The findings showed that 64.4% of nurses had marital satisfaction. There was significant relationship between age (p=0.03), job experience (p=0.01), age of spouse (p=0.01) and marital satisfaction. The results showed that there was a significant relationship between marital satisfaction and general health (p<0.0001). Multiple regression analysis showed that there was a significant relationship between depression (p=0.012) and anxiety (p=0.001) with marital satisfaction. Due to high levels of job stress and disorder in general health of nurses and low marital satisfaction by running health promotion programs and paying attention to its dimensions can help work and family health of nurses.

Fish consumption in a sample of people in Bandar Abbas, Iran: application of the theory of planned behavior.

PubMed

Aghamolaei, Teamur; Sadat Tavafian, Sedigheh; Madani, Abdoulhossain

2012-09-01

This study aimed to apply the conceptual framework of the theory of planned behavior (TPB) to explain fish consumption in a sample of people who lived in Bandar Abbass, Iran. We investigated the role of three traditional constructs of TPB that included attitude, social norms, and perceived behavioral control in an effort to characterize the intention to consume fish as well as the behavioral trends that characterize fish consumption. Data were derived from a cross-sectional sample of 321 subjects. Alpha coefficient correlation and linear regression analysis were applied to test the relationships between constructs. The predictors of fish consumption frequency were also evaluated. Multiple regression analysis revealed that attitude, subjective norms, and perceived behavioral control significantly predicted intention to eat fish (R2 = 0.54, F = 128.4, P < 0.001). Multiple regression analysis for the intention to eat fish and perceived behavioral control revealed that both factors significantly predicted fish consumption frequency (R2 = 0.58, F = 223.1, P < 0.001). The results indicated that the models fit well with the data. Attitude, subjective norms, and perceived behavioral control all had significant positive impacts on behavioral intention. Moreover, both intention and perceived behavioral control could be used to predict the frequency of fish consumption.

Prediction of hearing outcomes by multiple regression analysis in patients with idiopathic sudden sensorineural hearing loss.

PubMed

Suzuki, Hideaki; Tabata, Takahisa; Koizumi, Hiroki; Hohchi, Nobusuke; Takeuchi, Shoko; Kitamura, Takuro; Fujino, Yoshihisa; Ohbuchi, Toyoaki

2014-12-01

This study aimed to create a multiple regression model for predicting hearing outcomes of idiopathic sudden sensorineural hearing loss (ISSNHL). The participants were 205 consecutive patients (205 ears) with ISSNHL (hearing level ≥ 40 dB, interval between onset and treatment ≤ 30 days). They received systemic steroid administration combined with intratympanic steroid injection. Data were examined by simple and multiple regression analyses. Three hearing indices (percentage hearing improvement, hearing gain, and posttreatment hearing level [HLpost]) and 7 prognostic factors (age, days from onset to treatment, initial hearing level, initial hearing level at low frequencies, initial hearing level at high frequencies, presence of vertigo, and contralateral hearing level) were included in the multiple regression analysis as dependent and explanatory variables, respectively. In the simple regression analysis, the percentage hearing improvement, hearing gain, and HLpost showed significant correlation with 2, 5, and 6 of the 7 prognostic factors, respectively. The multiple correlation coefficients were 0.396, 0.503, and 0.714 for the percentage hearing improvement, hearing gain, and HLpost, respectively. Predicted values of HLpost calculated by the multiple regression equation were reliable with 70% probability with a 40-dB-width prediction interval. Prediction of HLpost by the multiple regression model may be useful to estimate the hearing prognosis of ISSNHL. © The Author(s) 2014.

A framework for longitudinal data analysis via shape regression

NASA Astrophysics Data System (ADS)

Fishbaugh, James; Durrleman, Stanley; Piven, Joseph; Gerig, Guido

2012-02-01

Traditional longitudinal analysis begins by extracting desired clinical measurements, such as volume or head circumference, from discrete imaging data. Typically, the continuous evolution of a scalar measurement is estimated by choosing a 1D regression model, such as kernel regression or fitting a polynomial of fixed degree. This type of analysis not only leads to separate models for each measurement, but there is no clear anatomical or biological interpretation to aid in the selection of the appropriate paradigm. In this paper, we propose a consistent framework for the analysis of longitudinal data by estimating the continuous evolution of shape over time as twice differentiable flows of deformations. In contrast to 1D regression models, one model is chosen to realistically capture the growth of anatomical structures. From the continuous evolution of shape, we can simply extract any clinical measurements of interest. We demonstrate on real anatomical surfaces that volume extracted from a continuous shape evolution is consistent with a 1D regression performed on the discrete measurements. We further show how the visualization of shape progression can aid in the search for significant measurements. Finally, we present an example on a shape complex of the brain (left hemisphere, right hemisphere, cerebellum) that demonstrates a potential clinical application for our framework.

Blood Glucose Reduction by Diabetic Drugs with Minimal Hypoglycemia Risk for Cardiovascular Outcomes: Evidence from Meta-regression Analysis of Randomized Controlled Trials.

PubMed

Huang, Chi-Jung; Wang, Wei-Ting; Sung, Shih-Hsien; Chen, Chen-Huan; Lip, Gregory Yh; Cheng, Hao-Min; Chiang, Chern-En

2018-05-02

To investigate the effects of blood glucose control with antihyperglycemic agents with minimal hypoglycemia risk on cardiovascular outcomes in patients with type 2 diabetes (T2D). Randomized controlled trials (RCTs) comparing the relative efficacy and safety of antidiabetic drugs with less hypoglycemia risk were comprehensively searched in MEDLINE, Embase, and the Cochrane Library up to January 27, 2018. Mixed-effects meta-regression analysis was conducted to explore the relationship between haemoglobin A1c (HbA1c) reduction and the risk of major adverse cardiovascular events (MACE), myocardial infarction, stroke, cardiovascular death, all-cause death, and hospitalization for heart failure. Ten RCTs comprising 92400 participants with T2D were included and provided information on 9773 MACE during a median follow-up of 2.6 years. The mean HbA1c concentration was 0.42% lower (median, 0.27-0.86%) for participants given antihyperglycemic agents than those given placebo. The meta-regression analysis demonstrated that HbA1c reduction was significantly associated with a decreased risk of MACE (β value, -0.39 to -0.55; P<0.02) even after adjusting for each of the following possible confounding factors including age, sex, baseline HbA1c, duration of follow-up, difference in achieved systolic blood pressure, difference in achieved body weight, or risk difference in hypoglycemia. Lowering HbA1c by 1% conferred a significant risk reduction of 30% (95% CI, 17-40%) for MACE. By contrast, the meta-regression analysis for trials using conventional agents failed to demonstrate a significant relationship between achieved HbA1c difference and MACE risk (P>0.74). Compared with placebo, newer T2D agents with less hypoglycemic hazard significantly reduced the risk of MACE. The MACE reduction seems to be associated with HbA1c reduction in a linear relationship. This article is protected by copyright. All rights reserved.

Emission and distribution of phosphine in paddy fields and its relationship with greenhouse gases.

PubMed

Chen, Weiyi; Niu, Xiaojun; An, Shaorong; Sheng, Hong; Tang, Zhenghua; Yang, Zhiquan; Gu, Xiaohong

2017-12-01

Phosphine (PH 3 ), as a gaseous phosphide, plays an important role in the phosphorus cycle in ecosystems. In this study, the emission and distribution of phosphine, carbon dioxide (CO 2 ) and methane (CH 4 ) in paddy fields were investigated to speculate the future potential impacts of enhanced greenhouse effect on phosphorus cycle involved in phosphine by the method of Pearson correlation analysis and multiple linear regression analysis. During the whole period of rice growth, there was a significant positive correlation between CO 2 emission flux and PH 3 emission flux (r=0.592, p=0.026, n=14). Similarly, a significant positive correlation of emission flux was also observed between CH 4 and PH 3 (r=0.563, p=0.036, n=14). The linear regression relationship was determined as [PH 3 ] flux =0.007[CO 2 ] flux +0.063[CH 4 ] flux -4.638. No significant differences were observed for all values of matrix-bound phosphine (MBP), soil carbon dioxide (SCO 2 ), and soil methane (SCH 4 ) in paddy soils. However, there was a significant positive correlation between MBP and SCO 2 at heading, flowering and ripening stage. The correlation coefficients were 0.909, 0.890 and 0.827, respectively. In vertical distribution, MBP had the analogical variation trend with SCO 2 and SCH 4 . Through Pearson correlation analysis and multiple stepwise linear regression analysis, pH, redox potential (Eh), total phosphorus (TP) and acid phosphatase (ACP) were identified as the principal factors affecting MBP levels, with correlative rankings of Eh>pH>TP>ACP. The multiple stepwise regression model ([MBP]=0.456∗[ACP]+0.235∗[TP]-1.458∗[Eh]-36.547∗[pH]+352.298) was obtained. The findings in this study hold great reference values to the global biogeochemical cycling of phosphorus in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Multivariate logistic regression analysis of postoperative complications and risk model establishment of gastrectomy for gastric cancer: A single-center cohort report.

PubMed

Zhou, Jinzhe; Zhou, Yanbing; Cao, Shougen; Li, Shikuan; Wang, Hao; Niu, Zhaojian; Chen, Dong; Wang, Dongsheng; Lv, Liang; Zhang, Jian; Li, Yu; Jiao, Xuelong; Tan, Xiaojie; Zhang, Jianli; Wang, Haibo; Zhang, Bingyuan; Lu, Yun; Sun, Zhenqing

2016-01-01

Reporting of surgical complications is common, but few provide information about the severity and estimate risk factors of complications. If have, but lack of specificity. We retrospectively analyzed data on 2795 gastric cancer patients underwent surgical procedure at the Affiliated Hospital of Qingdao University between June 2007 and June 2012, established multivariate logistic regression model to predictive risk factors related to the postoperative complications according to the Clavien-Dindo classification system. Twenty-four out of 86 variables were identified statistically significant in univariate logistic regression analysis, 11 significant variables entered multivariate analysis were employed to produce the risk model. Liver cirrhosis, diabetes mellitus, Child classification, invasion of neighboring organs, combined resection, introperative transfusion, Billroth II anastomosis of reconstruction, malnutrition, surgical volume of surgeons, operating time and age were independent risk factors for postoperative complications after gastrectomy. Based on logistic regression equation, p=Exp∑BiXi / (1+Exp∑BiXi), multivariate logistic regression predictive model that calculated the risk of postoperative morbidity was developed, p = 1/(1 + e((4.810-1.287X1-0.504X2-0.500X3-0.474X4-0.405X5-0.318X6-0.316X7-0.305X8-0.278X9-0.255X10-0.138X11))). The accuracy, sensitivity and specificity of the model to predict the postoperative complications were 86.7%, 76.2% and 88.6%, respectively. This risk model based on Clavien-Dindo grading severity of complications system and logistic regression analysis can predict severe morbidity specific to an individual patient's risk factors, estimate patients' risks and benefits of gastric surgery as an accurate decision-making tool and may serve as a template for the development of risk models for other surgical groups.

Spirometry results (FEV1 and FVC) in young Bantu men from Tanzania vs environmental and family characteristics.

PubMed

Rębacz-Maron, Ewa; Parafiniuk, Mirosław

2014-01-01

The aim of this paper was to examine the extent to which socioeconomic factors, anthropological data and somatic indices influenced the results of spirometric measurements (FEV1 and FVC) in Tanzanian youth. The population studied were young black Bantu men aged 12.8-24.0 years. Analysis was performed for the whole data set (n = 255), as well as separately for two age groups: under 17.5 years (n = 168) and 17.5 + (n = 87). A backward stepwise multiple regression analysis was performed for FEV1 and FVC as dependent variables on socioeconomic and anthropometric data. Multiple regression analysis for the whole group revealed that the socioeconomic and anthropometric data under analysis accounted for 38% of the variation in FEV1. In addition the analysis demonstrated that 34% of the variation in FVC could be accounted for by the variables used in the regression. A significant impact in explaining the variability of FVC was exhibited by the thorax mobility, financial situation of the participants and Pignet-Verwaecka Index. Analysis of the data indicates the significant role of selected socio-economic factors on the development of the biological specimens investigated. There were no perceptible pathologies, and the results can be treated as a credible interpretation of the influence exerted by the environment in which the teenagers under study grew up.

The time frame of Epstein-Barr virus latent membrane protein-1 gene to disappear in nasopharyngeal swabs after initiation of primary radiotherapy is an independently significant prognostic factor predicting local control for patients with nasopharyngeal carcinoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, S.-Y.; Chang, K.-P.; Graduate Institute of Clinical Medical Sciences, Chang Gung University, Linkou, Taiwan

Purpose: The presence of Epstein-Barr virus latent membrane protein-1 (LMP-1) gene in nasopharyngeal swabs indicates the presence of nasopharyngeal carcinoma (NPC) mucosal tumor cells. This study was undertaken to investigate whether the time taken for LMP-1 to disappear after initiation of primary radiotherapy (RT) was inversely associated with NPC local control. Methods and Materials: During July 1999 and October 2002, there were 127 nondisseminated NPC patients receiving serial examinations of nasopharyngeal swabbing with detection of LMP-1 during the RT course. The time for LMP-1 regression was defined as the number of days after initiation of RT for LMP-1 results tomore » turn negative. The primary outcome was local control, which was represented by freedom from local recurrence. Results: The time for LMP-1 regression showed a statistically significant influence on NPC local control both univariately (p < 0.0001) and multivariately (p = 0.004). In multivariate analysis, the administration of chemotherapy conferred a significantly more favorable local control (p = 0.03). Advanced T status ({>=} T2b), overall treatment time of external photon radiotherapy longer than 55 days, and older age showed trends toward being poor prognosticators. The time for LMP-1 regression was very heterogeneous. According to the quartiles of the time for LMP-1 regression, we defined the pattern of LMP-1 regression as late regression if it required 40 days or more. Kaplan-Meier plots indicated that the patients with late regression had a significantly worse local control than those with intermediate or early regression (p 0.0129). Conclusion: Among the potential prognostic factors examined in this study, the time for LMP-1 regression was the most independently significant factor that was inversely associated with NPC local control.« less

Effective psychological and psychosocial approaches to reduce repetition of self-harm: a systematic review, meta-analysis and meta-regression

PubMed Central

Robinson, Jo; Spittal, Matthew J; Carter, Greg

2016-01-01

Objective To examine the efficacy of psychological and psychosocial interventions for reductions in repeated self-harm. Design We conducted a systematic review, meta-analysis and meta-regression to examine the efficacy of psychological and psychosocial interventions to reduce repeat self-harm in adults. We included a sensitivity analysis of studies with a low risk of bias for the meta-analysis. For the meta-regression, we examined whether the type, intensity (primary analyses) and other components of intervention or methodology (secondary analyses) modified the overall intervention effect. Data sources A comprehensive search of MEDLINE, PsycInfo and EMBASE (from 1999 to June 2016) was performed. Eligibility criteria for selecting studies Randomised controlled trials of psychological and psychosocial interventions for adult self-harm patients. Results Forty-five trials were included with data available from 36 (7354 participants) for the primary analysis. Meta-analysis showed a significant benefit of all psychological and psychosocial interventions combined (risk ratio 0.84; 95% CI 0.74 to 0.96; number needed to treat=33); however, sensitivity analyses showed that this benefit was non-significant when restricted to a limited number of high-quality studies. Meta-regression showed that the type of intervention did not modify the treatment effects. Conclusions Consideration of a psychological or psychosocial intervention over and above treatment as usual is worthwhile; with the public health benefits of ensuring that this practice is widely adopted potentially worth the investment. However, the specific type and nature of the intervention that should be delivered is not yet clear. Cognitive–behavioural therapy or interventions with an interpersonal focus and targeted on the precipitants to self-harm may be the best candidates on the current evidence. Further research is required. PMID:27660314

The Impact of Aortic Occlusion Balloon on Mortality After Endovascular Repair of Ruptured Abdominal Aortic Aneurysms: A Meta-analysis and Meta-regression Analysis.

PubMed

Karkos, Christos D; Papadimitriou, Christina T; Chatzivasileiadis, Theodoros N; Kapsali, Nikoletta S; Kalogirou, Thomas E; Giagtzidis, Ioakeim T; Papazoglou, Konstantinos O

2015-12-01

We aimed to investigate whether the use of aortic occlusion balloon (AOB) has an impact on mortality of patients undergoing endovascular repair of ruptured abdominal aortic aneurysms (RAAAs). A meta-analysis of the English-language literature was undertaken through February 2013. Articles reporting data on outcome after endovascular repair of RAAAs were identified and information regarding the use of AOB was sought. Included in this meta-analysis were 39 eligible studies reporting 1277 patients. The pooled perioperative mortality was 21.6% (95% CI 18.1-25.1%). There was significant within-study heterogeneity (I(2) 50.2%, P < 0.001). A total of 200 patients required AOB with an estimated pooled proportion of 14.1% (8.9-19.3%). Individual random-effects meta-regression investigating the effect of AOB and other risk factors on mortality revealed a significant linear association of hemodynamic instability, bifurcated endograft approach, and primary conversion to open repair with mortality and a nonlinear (second degree polynomial) association of AOB with mortality. On multivariable meta-regression models, both hemodynamic instability and AOB were found to be statistically significant, independent predictors of mortality. In particular, there was a statistically significant negative correlation between AOB and mortality and a positive effect of hemodynamic instability on mortality. In practical terms, mortality was significantly higher in studies with a higher proportion of hemodynamically unstable patients and lower in studies with a higher rate of AOB use. This study provides meta-analytical evidence that the use of an AOB in unstable RAAA patients undergoing endovascular repair may improve the results.

Multiple Regression Analysis of mRNA-miRNA Associations in Colorectal Cancer Pathway

PubMed Central

Wang, Fengfeng; Wong, S. C. Cesar; Chan, Lawrence W. C.; Cho, William C. S.; Yip, S. P.; Yung, Benjamin Y. M.

2014-01-01

Background. MicroRNA (miRNA) is a short and endogenous RNA molecule that regulates posttranscriptional gene expression. It is an important factor for tumorigenesis of colorectal cancer (CRC), and a potential biomarker for diagnosis, prognosis, and therapy of CRC. Our objective is to identify the related miRNAs and their associations with genes frequently involved in CRC microsatellite instability (MSI) and chromosomal instability (CIN) signaling pathways. Results. A regression model was adopted to identify the significantly associated miRNAs targeting a set of candidate genes frequently involved in colorectal cancer MSI and CIN pathways. Multiple linear regression analysis was used to construct the model and find the significant mRNA-miRNA associations. We identified three significantly associated mRNA-miRNA pairs: BCL2 was positively associated with miR-16 and SMAD4 was positively associated with miR-567 in the CRC tissue, while MSH6 was positively associated with miR-142-5p in the normal tissue. As for the whole model, BCL2 and SMAD4 models were not significant, and MSH6 model was significant. The significant associations were different in the normal and the CRC tissues. Conclusion. Our results have laid down a solid foundation in exploration of novel CRC mechanisms, and identification of miRNA roles as oncomirs or tumor suppressor mirs in CRC. PMID:24895601

Methods for estimating the magnitude and frequency of peak streamflows for unregulated streams in Oklahoma

USGS Publications Warehouse

Lewis, Jason M.

2010-01-01

Peak-streamflow regression equations were determined for estimating flows with exceedance probabilities from 50 to 0.2 percent for the state of Oklahoma. These regression equations incorporate basin characteristics to estimate peak-streamflow magnitude and frequency throughout the state by use of a generalized least squares regression analysis. The most statistically significant independent variables required to estimate peak-streamflow magnitude and frequency for unregulated streams in Oklahoma are contributing drainage area, mean-annual precipitation, and main-channel slope. The regression equations are applicable for watershed basins with drainage areas less than 2,510 square miles that are not affected by regulation. The resulting regression equations had a standard model error ranging from 31 to 46 percent. Annual-maximum peak flows observed at 231 streamflow-gaging stations through water year 2008 were used for the regression analysis. Gage peak-streamflow estimates were used from previous work unless 2008 gaging-station data were available, in which new peak-streamflow estimates were calculated. The U.S. Geological Survey StreamStats web application was used to obtain the independent variables required for the peak-streamflow regression equations. Limitations on the use of the regression equations and the reliability of regression estimates for natural unregulated streams are described. Log-Pearson Type III analysis information, basin and climate characteristics, and the peak-streamflow frequency estimates for the 231 gaging stations in and near Oklahoma are listed. Methodologies are presented to estimate peak streamflows at ungaged sites by using estimates from gaging stations on unregulated streams. For ungaged sites on urban streams and streams regulated by small floodwater retarding structures, an adjustment of the statewide regression equations for natural unregulated streams can be used to estimate peak-streamflow magnitude and frequency.

Quantile regression and clustering analysis of standardized precipitation index in the Tarim River Basin, Xinjiang, China

NASA Astrophysics Data System (ADS)

Yang, Peng; Xia, Jun; Zhang, Yongyong; Han, Jian; Wu, Xia

2017-11-01

Because drought is a very common and widespread natural disaster, it has attracted a great deal of academic interest. Based on 12-month time scale standardized precipitation indices (SPI12) calculated from precipitation data recorded between 1960 and 2015 at 22 weather stations in the Tarim River Basin (TRB), this study aims to identify the trends of SPI and drought duration, severity, and frequency at various quantiles and to perform cluster analysis of drought events in the TRB. The results indicated that (1) both precipitation and temperature at most stations in the TRB exhibited significant positive trends during 1960-2015; (2) multiple scales of SPIs changed significantly around 1986; (3) based on quantile regression analysis of temporal drought changes, the positive SPI slopes indicated less severe and less frequent droughts at lower quantiles, but clear variation was detected in the drought frequency; and (4) significantly different trends were found in drought frequency probably between severe droughts and drought frequency.

Growth and inactivation of Salmonella at low refrigerated storage temperatures and thermal inactivation on raw chicken meat and laboratory media: mixed effect meta-analysis.

PubMed

Smadi, Hanan; Sargeant, Jan M; Shannon, Harry S; Raina, Parminder

2012-12-01

Growth and inactivation regression equations were developed to describe the effects of temperature on Salmonella concentration on chicken meat for refrigerated temperatures (⩽10°C) and for thermal treatment temperatures (55-70°C). The main objectives were: (i) to compare Salmonella growth/inactivation in chicken meat versus laboratory media; (ii) to create regression equations to estimate Salmonella growth in chicken meat that can be used in quantitative risk assessment (QRA) modeling; and (iii) to create regression equations to estimate D-values needed to inactivate Salmonella in chicken meat. A systematic approach was used to identify the articles, critically appraise them, and pool outcomes across studies. Growth represented in density (Log10CFU/g) and D-values (min) as a function of temperature were modeled using hierarchical mixed effects regression models. The current meta-analysis analysis found a significant difference (P⩽0.05) between the two matrices - chicken meat and laboratory media - for both growth at refrigerated temperatures and inactivation by thermal treatment. Growth and inactivation were significantly influenced by temperature after controlling for other variables; however, no consistent pattern in growth was found. Validation of growth and inactivation equations against data not used in their development is needed. Copyright © 2012 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd. All rights reserved.

Stress Regression Analysis of Asphalt Concrete Deck Pavement Based on Orthogonal Experimental Design and Interlayer Contact

NASA Astrophysics Data System (ADS)

Wang, Xuntao; Feng, Jianhu; Wang, Hu; Hong, Shidi; Zheng, Supei

2018-03-01

A three-dimensional finite element box girder bridge and its asphalt concrete deck pavement were established by ANSYS software, and the interlayer bonding condition of asphalt concrete deck pavement was assumed to be contact bonding condition. Orthogonal experimental design is used to arrange the testing plans of material parameters, and an evaluation of the effect of different material parameters in the mechanical response of asphalt concrete surface layer was conducted by multiple linear regression model and using the results from the finite element analysis. Results indicated that stress regression equations can well predict the stress of the asphalt concrete surface layer, and elastic modulus of waterproof layer has a significant influence on stress values of asphalt concrete surface layer.

Customized Fetal Growth Charts for Parents' Characteristics, Race, and Parity by Quantile Regression Analysis: A Cross-sectional Multicenter Italian Study.

PubMed

Ghi, Tullio; Cariello, Luisa; Rizzo, Ludovica; Ferrazzi, Enrico; Periti, Enrico; Prefumo, Federico; Stampalija, Tamara; Viora, Elsa; Verrotti, Carla; Rizzo, Giuseppe

2016-01-01

The purpose of this study was to construct fetal biometric charts between 16 and 40 weeks' gestation that were customized for parental characteristics, race, and parity, using quantile regression analysis. In a multicenter cross-sectional study, 8070 sonographic examinations from low-risk pregnancies between 16 and 40 weeks' gestation were analyzed. The fetal measurements obtained were biparietal diameter, head circumference, abdominal circumference, and femur diaphysis length. Quantile regression was used to examine the impact of parental height and weight, parity, and race across biometric percentiles for the fetal measurements considered. Paternal and maternal height were significant covariates for all of the measurements considered (P < .05). Maternal weight significantly influenced head circumference, abdominal circumference, and femur diaphysis length. Parity was significantly associated with biparietal diameter and head circumference. Central African race was associated with head circumference and femur diaphysis length, whereas North African race was only associated with femur diaphysis length. In this study we constructed customized biometric growth charts using quantile regression in a large cohort of low-risk pregnancies. These charts offer the advantage of defining individualized normal ranges of fetal biometric parameters at each specific percentile corrected for parental height and weight, parity, and race. This study supports the importance of including these variables in routine sonographic screening for fetal growth abnormalities.

Challenges Associated with Estimating Utility in Wet Age-Related Macular Degeneration: A Novel Regression Analysis to Capture the Bilateral Nature of the Disease.

PubMed

Hodgson, Robert; Reason, Timothy; Trueman, David; Wickstead, Rose; Kusel, Jeanette; Jasilek, Adam; Claxton, Lindsay; Taylor, Matthew; Pulikottil-Jacob, Ruth

2017-10-01

The estimation of utility values for the economic evaluation of therapies for wet age-related macular degeneration (AMD) is a particular challenge. Previous economic models in wet AMD have been criticized for failing to capture the bilateral nature of wet AMD by modelling visual acuity (VA) and utility values associated with the better-seeing eye only. Here we present a de novo regression analysis using generalized estimating equations (GEE) applied to a previous dataset of time trade-off (TTO)-derived utility values from a sample of the UK population that wore contact lenses to simulate visual deterioration in wet AMD. This analysis allows utility values to be estimated as a function of VA in both the better-seeing eye (BSE) and worse-seeing eye (WSE). VAs in both the BSE and WSE were found to be statistically significant (p < 0.05) when regressed separately. When included without an interaction term, only the coefficient for VA in the BSE was significant (p = 0.04), but when an interaction term between VA in the BSE and WSE was included, only the constant term (mean TTO utility value) was significant, potentially a result of the collinearity between the VA of the two eyes. The lack of both formal model fit statistics from the GEE approach and theoretical knowledge to support the superiority of one model over another make it difficult to select the best model. Limitations of this analysis arise from the potential influence of collinearity between the VA of both eyes, and the use of contact lenses to reflect VA states to obtain the original dataset. Whilst further research is required to elicit more accurate utility values for wet AMD, this novel regression analysis provides a possible source of utility values to allow future economic models to capture the quality of life impact of changes in VA in both eyes. Novartis Pharmaceuticals UK Limited.

Advanced glycation end products and antioxidant status in type 2 diabetic patients with and without peripheral artery disease.

PubMed

Lapolla, Annunziata; Piarulli, Francesco; Sartore, Giovanni; Ceriello, Antonio; Ragazzi, Eugenio; Reitano, Rachele; Baccarin, Lorenzo; Laverda, Barbara; Fedele, Domenico

2007-03-01

Advanced glycation end products (AGEs), pentosidine and malondialdehyde (MDA), are elevated in type 2 diabetic subjects with coronary and carotid angiopathy. We investigated the relationship of AGEs, MDA, total reactive antioxidant potentials (TRAPs), and vitamin E in type 2 diabetic patients with and without peripheral artery disease (PAD). AGEs, pentosidine, MDA, TRAP, vitamin E, and ankle-brachial index (ABI) were measured in 99 consecutive type 2 diabetic subjects and 20 control subjects. AGEs, pentosidine, and MDA were higher and vitamin E and TRAP were lower in patients with PAD (ABI <0.9) than in patients without PAD (ABI >0.9) (P < 0.001). After multiple regression analysis, a correlation between AGEs and pentosidine, as independent variables, and ABI, as the dependent variable, was found in both patients with and without PAD (r = 0.9198, P < 0.001 and r = 0.5764, P < 0.001, respectively) but not in control subjects. When individual regression coefficients were evaluated, only that due to pentosidine was confirmed as significant. For patients with PAD, considering TRAP, vitamin E, and MDA as independent variables and ABI as the dependent variable produced an overall significant regression (r = 0.6913, P < 0.001). The regression coefficients for TRAP and vitamin E were not significant, indicating that the model is best explained by a single linear regression between MDA and ABI. These findings were also confirmed by principal component analysis. Results show that pentosidine and MDA are strongly associated with PAD in type 2 diabetic patients.

Parental education predicts change in intelligence quotient after childhood epilepsy surgery.

PubMed

Meekes, Joost; van Schooneveld, Monique M J; Braams, Olga B; Jennekens-Schinkel, Aag; van Rijen, Peter C; Hendriks, Marc P H; Braun, Kees P J; van Nieuwenhuizen, Onno

2015-04-01

To know whether change in the intelligence quotient (IQ) of children who undergo epilepsy surgery is associated with the educational level of their parents. Retrospective analysis of data obtained from a cohort of children who underwent epilepsy surgery between January 1996 and September 2010. We performed simple and multiple regression analyses to identify predictors associated with IQ change after surgery. In addition to parental education, six variables previously demonstrated to be associated with IQ change after surgery were included as predictors: age at surgery, duration of epilepsy, etiology, presurgical IQ, reduction of antiepileptic drugs, and seizure freedom. We used delta IQ (IQ 2 years after surgery minus IQ shortly before surgery) as the primary outcome variable, but also performed analyses with pre- and postsurgical IQ as outcome variables to support our findings. To validate the results we performed simple regression analysis with parental education as the predictor in specific subgroups. The sample for regression analysis included 118 children (60 male; median age at surgery 9.73 years). Parental education was significantly associated with delta IQ in simple regression analysis (p = 0.004), and also contributed significantly to postsurgical IQ in multiple regression analysis (p = 0.008). Additional analyses demonstrated that parental education made a unique contribution to prediction of delta IQ, that is, it could not be replaced by the illness-related variables. Subgroup analyses confirmed the association of parental education with IQ change after surgery for most groups. Children whose parents had higher education demonstrate on average a greater increase in IQ after surgery and a higher postsurgical--but not presurgical--IQ than children whose parents completed at most lower secondary education. Parental education--and perhaps other environmental variables--should be considered in the prognosis of cognitive function after childhood epilepsy surgery. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

The role of empathy and emotional intelligence in nurses' communication attitudes using regression models and fuzzy-set qualitative comparative analysis models.

PubMed

Giménez-Espert, María Del Carmen; Prado-Gascó, Vicente Javier

2018-03-01

To analyse link between empathy and emotional intelligence as a predictor of nurses' attitudes towards communication while comparing the contribution of emotional aspects and attitudinal elements on potential behaviour. Nurses' attitudes towards communication, empathy and emotional intelligence are key skills for nurses involved in patient care. There are currently no studies analysing this link, and its investigation is needed because attitudes may influence communication behaviours. Correlational study. To attain this goal, self-reported instruments (attitudes towards communication of nurses, trait emotional intelligence (Trait Emotional Meta-Mood Scale) and Jefferson Scale of Nursing Empathy (Jefferson Scale Nursing Empathy) were collected from 460 nurses between September 2015-February 2016. Two different analytical methodologies were used: traditional regression models and fuzzy-set qualitative comparative analysis models. The results of the regression model suggest that cognitive dimensions of attitude are a significant and positive predictor of the behavioural dimension. The perspective-taking dimension of empathy and the emotional-clarity dimension of emotional intelligence were significant positive predictors of the dimensions of attitudes towards communication, except for the affective dimension (for which the association was negative). The results of the fuzzy-set qualitative comparative analysis models confirm that the combination of high levels of cognitive dimension of attitudes, perspective-taking and emotional clarity explained high levels of the behavioural dimension of attitude. Empathy and emotional intelligence are predictors of nurses' attitudes towards communication, and the cognitive dimension of attitude is a good predictor of the behavioural dimension of attitudes towards communication of nurses in both regression models and fuzzy-set qualitative comparative analysis. In general, the fuzzy-set qualitative comparative analysis models appear to be better predictors than the regression models are. To evaluate current practices, establish intervention strategies and evaluate their effectiveness. The evaluation of these variables and their relationships are important in creating a satisfied and sustainable workforce and improving quality of care and patient health. © 2018 John Wiley & Sons Ltd.

A systematic review and meta-analysis of the effects of antibiotic consumption on antibiotic resistance

PubMed Central

2014-01-01

Background Greater use of antibiotics during the past 50 years has exerted selective pressure on susceptible bacteria and may have favoured the survival of resistant strains. Existing information on antibiotic resistance patterns from pathogens circulating among community-based patients is substantially less than from hospitalized patients on whom guidelines are often based. We therefore chose to assess the relationship between the antibiotic resistance pattern of bacteria circulating in the community and the consumption of antibiotics in the community. Methods Both gray literature and published scientific literature in English and other European languages was examined. Multiple regression analysis was used to analyse whether studies found a positive relationship between antibiotic consumption and resistance. A subsequent meta-analysis and meta-regression was conducted for studies for which a common effect size measure (odds ratio) could be calculated. Results Electronic searches identified 974 studies but only 243 studies were considered eligible for inclusion by the two independent reviewers who extracted the data. A binomial test revealed a positive relationship between antibiotic consumption and resistance (p < .001) but multiple regression modelling did not produce any significant predictors of study outcome. The meta-analysis generated a significant pooled odds ratio of 2.3 (95% confidence interval 2.2 to 2.5) with a meta-regression producing several significant predictors (F(10,77) = 5.82, p < .01). Countries in southern Europe produced a stronger link between consumption and resistance than other regions. Conclusions Using a large set of studies we found that antibiotic consumption is associated with the development of antibiotic resistance. A subsequent meta-analysis, with a subsample of the studies, generated several significant predictors. Countries in southern Europe produced a stronger link between consumption and resistance than other regions so efforts at reducing antibiotic consumption may need to be strengthened in this area. Increased consumption of antibiotics may not only produce greater resistance at the individual patient level but may also produce greater resistance at the community, country, and regional levels, which can harm individual patients. PMID:24405683

A model for national outcome audit in vascular surgery.

PubMed

Prytherch, D R; Ridler, B M; Beard, J D; Earnshaw, J J

2001-06-01

The aim was to model vascular surgical outcome in a national study using POSSUM scoring. One hundred and twenty-one British and Irish surgeons completed data questionnaires on patients undergoing arterial surgery under their care (mean 12 patients, range 1-49) in May/June 1998. A total of 1480 completed data records were available for logistic regression analysis using P-POSSUM methodology. Information collected included all POSSUM data items plus other factors thought to have a significant bearing on patient outcome: "extra items". The main outcome measures were death and major postoperative complications. The data were checked and inconsistent records were excluded. The remaining 1313 were divided into two sets for analysis. The first "training" set was used to obtain logistic regression models that were applied prospectively to the second "test" dataset. using POSSUM data items alone, it was possible to predict both mortality and morbidity after vascular reconstruction using P-POSSUM analysis. The addition of the "extra items" found significant in regression analysis did not significantly improve the accuracy of prediction. It was possible to predict both mortality and morbidity derived from the preoperative physiology components of the POSSUM data items alone. this study has shown that P-POSSUM methodology can be used to predict outcome after arterial surgery across a range of surgeons in different hospitals and could form the basis of a national outcome audit. It was also possible to obtain accurate models for both mortality and major morbidity from the POSSUM physiology scores alone. Copyright 2001 Harcourt Publishers Limited.

Contributions of sociodemographic factors to criminal behavior

PubMed Central

Mundia, Lawrence; Matzin, Rohani; Mahalle, Salwa; Hamid, Malai Hayati; Osman, Ratna Suriani

2016-01-01

We explored the extent to which prisoner sociodemographic variables (age, education, marital status, employment, and whether their parents were married or not) influenced offending in 64 randomly selected Brunei inmates, comprising both sexes. A quantitative field survey design ideal for the type of participants used in a prison context was employed to investigate the problem. Hierarchical multiple regression analysis with backward elimination identified prisoner marital status and age groups as significantly related to offending. Furthermore, hierarchical multinomial logistic regression analysis with backward elimination indicated that prisoners’ age, primary level education, marital status, employment status, and parental marital status as significantly related to stealing offenses with high odds ratios. All 29 nonrecidivists were false negatives and predicted to reoffend upon release. Similarly, all 33 recidivists were projected to reoffend after release. Hierarchical binary logistic regression analysis revealed age groups (24–29 years and 30–35 years), employed prisoner, and primary level education as variables with high likelihood trends for reoffending. The results suggested that prisoner interventions (educational, counseling, and psychotherapy) in Brunei should treat not only antisocial personality, psychopathy, and mental health problems but also sociodemographic factors. The study generated offending patterns, trends, and norms that may inform subsequent investigations on Brunei prisoners. PMID:27382342

Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Red River of the North, Fargo, North Dakota, 2003-05

USGS Publications Warehouse

Ryberg, Karen R.

2006-01-01

This report presents the results of a study by the U.S. Geological Survey, done in cooperation with the Bureau of Reclamation, U.S. Department of the Interior, to estimate water-quality constituent concentrations in the Red River of the North at Fargo, North Dakota. Regression analysis of water-quality data collected in 2003-05 was used to estimate concentrations and loads for alkalinity, dissolved solids, sulfate, chloride, total nitrite plus nitrate, total nitrogen, total phosphorus, and suspended sediment. The explanatory variables examined for regression relation were continuously monitored physical properties of water-streamflow, specific conductance, pH, water temperature, turbidity, and dissolved oxygen. For the conditions observed in 2003-05, streamflow was a significant explanatory variable for all estimated constituents except dissolved solids. pH, water temperature, and dissolved oxygen were not statistically significant explanatory variables for any of the constituents in this study. Specific conductance was a significant explanatory variable for alkalinity, dissolved solids, sulfate, and chloride. Turbidity was a significant explanatory variable for total phosphorus and suspended sediment. For the nutrients, total nitrite plus nitrate, total nitrogen, and total phosphorus, cosine and sine functions of time also were used to explain the seasonality in constituent concentrations. The regression equations were evaluated using common measures of variability, including R2, or the proportion of variability in the estimated constituent explained by the regression equation. R2 values ranged from 0.703 for total nitrogen concentration to 0.990 for dissolved-solids concentration. The regression equations also were evaluated by calculating the median relative percentage difference (RPD) between measured constituent concentration and the constituent concentration estimated by the regression equations. Median RPDs ranged from 1.1 for dissolved solids to 35.2 for total nitrite plus nitrate. Regression equations also were used to estimate daily constituent loads. Load estimates can be used by water-quality managers for comparison of current water-quality conditions to water-quality standards expressed as total maximum daily loads (TMDLs). TMDLs are a measure of the maximum amount of chemical constituents that a water body can receive and still meet established water-quality standards. The peak loads generally occurred in June and July when streamflow also peaked.

Association of the FGA and SLC6A4 genes with autistic spectrum disorder in a Korean population.

PubMed

Ro, Myungja; Won, Seongsik; Kang, Hyunjun; Kim, Su-Yeon; Lee, Seung Ku; Nam, Min; Bang, Hee Jung; Yang, Jae Won; Choi, Kyung-Sik; Kim, Su Kang; Chung, Joo-Ho; Kwack, Kyubum

2013-01-01

Autism spectrum disorder (ASD) is a neurobiological disorder characterized by distinctive impairments in cognitive function, language, and behavior. Linkage and population studies suggest a genetic association between solute carrier family 6 member 4 (SLC6A4) variants and ASD. Logistic regression was used to identify associations between single-nucleotide polymorphisms (SNPs) and ASD with 3 alternative models (additive, dominant, and recessive). Linear regression analysis was performed to determine the influence of SNPs on Childhood Autism Rating Scale (CARS) scores as a quantitative phenotype. In the present study, we examined the associations of SNPs in the SLC6A4 gene and the fibrinogen alpha chain (FGA) gene. Logistic regression analysis showed a significant association between the risk of ASD and rs2070025 and rs2070011 in the FGA gene. The gene-gene interaction between SLC6A4 and FGA was not significantly associated with ASD susceptibility. However, polymorphisms in both SLC6A4 and the FGA gene significantly affected the symptoms of ASD. Our findings indicate that FGA and SLC6A4 gene interactions may contribute to the phenotypes of ASD rather than the incidence of ASD. © 2013 S. Karger AG, Basel.

Test anxiety and academic performance in chiropractic students.

PubMed

Zhang, Niu; Henderson, Charles N R

2014-01-01

Objective : We assessed the level of students' test anxiety, and the relationship between test anxiety and academic performance. Methods : We recruited 166 third-quarter students. The Test Anxiety Inventory (TAI) was administered to all participants. Total scores from written examinations and objective structured clinical examinations (OSCEs) were used as response variables. Results : Multiple regression analysis shows that there was a modest, but statistically significant negative correlation between TAI scores and written exam scores, but not OSCE scores. Worry and emotionality were the best predictive models for written exam scores. Mean total anxiety and emotionality scores for females were significantly higher than those for males, but not worry scores. Conclusion : Moderate-to-high test anxiety was observed in 85% of the chiropractic students examined. However, total test anxiety, as measured by the TAI score, was a very weak predictive model for written exam performance. Multiple regression analysis demonstrated that replacing total anxiety (TAI) with worry and emotionality (TAI subscales) produces a much more effective predictive model of written exam performance. Sex, age, highest current academic degree, and ethnicity contributed little additional predictive power in either regression model. Moreover, TAI scores were not found to be statistically significant predictors of physical exam skill performance, as measured by OSCEs.

Cross reactions elicited by serum 17-OH progesterone and 11-desoxycortisol in cortisol assays.

PubMed

Brossaud, Julie; Barat, Pascal; Gualde, Dominique; Corcuff, Jean-Benoît

2009-09-01

Different pathophysiological situations such as congenital adrenal hyperplasia, adrenocortical carcinoma, metyrapone treatment, etc. elicit specificity problems with serum cortisol assay. We assayed cortisol using 2 kits and performed cross reaction studies as well as multiple regression analysis using 2 other steroids: 11-desoxycortisol and 17-OH progesterone. Analysis showed the existence of an analytical bias. Importantly, significantly different biases were demonstrated in newborns or patients taking metyrapone. Multiple regression analysis and cross reaction studies showed that 11-desoxycortisol level significantly influenced cortisol determination. Moreover, despite using the normal ranges provided by manufacturers discrepant results occurred such as 17% discordance in the diagnosis of hypocorticism in infants. We wish to raise awareness about the consequences of the (lack of) specificity of cortisol assays with regard to the evaluation of hypocorticism in infants or when "unusual" steroids may be increased.

Reflectance measurements for the detection and mapping of soil limitations

NASA Technical Reports Server (NTRS)

Benson, L. A.; Frazee, C. J.

1973-01-01

During 1971 and 1972 research was conducted on two fallow fields in the proposed Oahe Irrigation Project to investigate the relationship between the tonal variations observed on aerial photographs and the principal soil limitations of the area. A grid sampling procedure was used to collected detailed field data during the 1972 growing season. The field data was compared to imagery collected on May 14, 1971 at 3050 meters altitude. The imagery and field data were initially evaluated by a visual analysis. Correlation and regression analysis revealed a highly significant correlation and regression analysis revealed a highly significant correlation between the digitized color infrared film data and soil properties such as organic matter content, color, depth to carbonates, bulk density and reflectivity. Computer classification of the multiemulsion film data resulted in maps delineating the areas containing claypan and erosion limitations. Reflectance data from the red spectral band provided the best results.

Does Group-Level Commitment Predict Employee Well-Being?: A Prospective Analysis.

PubMed

Clausen, Thomas; Christensen, Karl Bang; Nielsen, Karina

2015-11-01

To investigate the links between group-level affective organizational commitment (AOC) and individual-level psychological well-being, self-reported sickness absence, and sleep disturbances. A total of 5085 care workers from 301 workgroups in the Danish eldercare services participated in both waves of the study (T1 [2005] and T2 [2006]). The three outcomes were analyzed using linear multilevel regression analysis, multilevel Poisson regression analysis, and multilevel logistic regression analysis, respectively. Group-level AOC (T1) significantly predicted individual-level psychological well-being, self-reported sickness absence, and sleep disturbances (T2). The association between group-level AOC (T1) and psychological well-being (T2) was fully mediated by individual-level AOC (T1), and the associations between group-level AOC (T1) and self-reported sickness absence and sleep disturbances (T2) were partially mediated by individual-level AOC (T1). Group-level AOC is an important predictor of employee well-being in contemporary health care organizations.

Comparative study of contrast-enhanced ultrasound qualitative and quantitative analysis for identifying benign and malignant breast tumor lumps.

PubMed

Liu, Jian; Gao, Yun-Hua; Li, Ding-Dong; Gao, Yan-Chun; Hou, Ling-Mi; Xie, Ting

2014-01-01

To compare the value of contrast-enhanced ultrasound (CEUS) qualitative and quantitative analysis in the identification of breast tumor lumps. Qualitative and quantitative indicators of CEUS for 73 cases of breast tumor lumps were retrospectively analyzed by univariate and multivariate approaches. Logistic regression was applied and ROC curves were drawn for evaluation and comparison. The CEUS qualitative indicator-generated regression equation contained three indicators, namely enhanced homogeneity, diameter line expansion and peak intensity grading, which demonstrated prediction accuracy for benign and malignant breast tumor lumps of 91.8%; the quantitative indicator-generated regression equation only contained one indicator, namely the relative peak intensity, and its prediction accuracy was 61.5%. The corresponding areas under the ROC curve for qualitative and quantitative analyses were 91.3% and 75.7%, respectively, which exhibited a statistically significant difference by the Z test (P<0.05). The ability of CEUS qualitative analysis to identify breast tumor lumps is better than with quantitative analysis.

Methods for estimating the magnitude and frequency of peak streamflows at ungaged sites in and near the Oklahoma Panhandle

USGS Publications Warehouse

Smith, S. Jerrod; Lewis, Jason M.; Graves, Grant M.

2015-09-28

Generalized-least-squares multiple-linear regression analysis was used to formulate regression relations between peak-streamflow frequency statistics and basin characteristics. Contributing drainage area was the only basin characteristic determined to be statistically significant for all percentage of annual exceedance probabilities and was the only basin characteristic used in regional regression equations for estimating peak-streamflow frequency statistics on unregulated streams in and near the Oklahoma Panhandle. The regression model pseudo-coefficient of determination, converted to percent, for the Oklahoma Panhandle regional regression equations ranged from about 38 to 63 percent. The standard errors of prediction and the standard model errors for the Oklahoma Panhandle regional regression equations ranged from about 84 to 148 percent and from about 76 to 138 percent, respectively. These errors were comparable to those reported for regional peak-streamflow frequency regression equations for the High Plains areas of Texas and Colorado. The root mean square errors for the Oklahoma Panhandle regional regression equations (ranging from 3,170 to 92,000 cubic feet per second) were less than the root mean square errors for the Oklahoma statewide regression equations (ranging from 18,900 to 412,000 cubic feet per second); therefore, the Oklahoma Panhandle regional regression equations produce more accurate peak-streamflow statistic estimates for the irrigated period of record in the Oklahoma Panhandle than do the Oklahoma statewide regression equations. The regression equations developed in this report are applicable to streams that are not substantially affected by regulation, impoundment, or surface-water withdrawals. These regression equations are intended for use for stream sites with contributing drainage areas less than or equal to about 2,060 square miles, the maximum value for the independent variable used in the regression analysis.

School Progress Among Children of Same-Sex Couples.

PubMed

Watkins, Caleb S

2018-06-01

This study uses logit regressions on a pooled sample of children from the 2012, 2013, and 2014 American Community Survey to perform a nationally representative analysis of school progress for a large sample of 4,430 children who reside with same-sex couples. Odds ratios from regressions that compare children between different-sex married couples and same-sex couples fail to show significant differences in normal school progress between households across a variety of sample compositions. Likewise, marginal effects from regressions that compare children with similar family dynamics between different-sex married couples and same-sex couples fail to predict significantly higher probabilities of grade retention for children of same-sex couples. Significantly lower grade retention rates are sometimes predicted for children of same-sex couples than for different-sex married couples, but these differences are sensitive to sample exclusions and do not indicate causal benefits to same-sex parenting.

Two-dimensional advective transport in ground-water flow parameter estimation

USGS Publications Warehouse

Anderman, E.R.; Hill, M.C.; Poeter, E.P.

1996-01-01

Nonlinear regression is useful in ground-water flow parameter estimation, but problems of parameter insensitivity and correlation often exist given commonly available hydraulic-head and head-dependent flow (for example, stream and lake gain or loss) observations. To address this problem, advective-transport observations are added to the ground-water flow, parameter-estimation model MODFLOWP using particle-tracking methods. The resulting model is used to investigate the importance of advective-transport observations relative to head-dependent flow observations when either or both are used in conjunction with hydraulic-head observations in a simulation of the sewage-discharge plume at Otis Air Force Base, Cape Cod, Massachusetts, USA. The analysis procedure for evaluating the probable effect of new observations on the regression results consists of two steps: (1) parameter sensitivities and correlations calculated at initial parameter values are used to assess the model parameterization and expected relative contributions of different types of observations to the regression; and (2) optimal parameter values are estimated by nonlinear regression and evaluated. In the Cape Cod parameter-estimation model, advective-transport observations did not significantly increase the overall parameter sensitivity; however: (1) inclusion of advective-transport observations decreased parameter correlation enough for more unique parameter values to be estimated by the regression; (2) realistic uncertainties in advective-transport observations had a small effect on parameter estimates relative to the precision with which the parameters were estimated; and (3) the regression results and sensitivity analysis provided insight into the dynamics of the ground-water flow system, especially the importance of accurate boundary conditions. In this work, advective-transport observations improved the calibration of the model and the estimation of ground-water flow parameters, and use of regression and related techniques produced significant insight into the physical system.

Visual Acuity Is Correlated with the Area of the Foveal Avascular Zone in Diabetic Retinopathy and Retinal Vein Occlusion.

PubMed

Balaratnasingam, Chandrakumar; Inoue, Maiko; Ahn, Seungjun; McCann, Jesse; Dhrami-Gavazi, Elona; Yannuzzi, Lawrence A; Freund, K Bailey

2016-11-01

To determine if the area of the foveal avascular zone (FAZ) is correlated with visual acuity (VA) in diabetic retinopathy (DR) and retinal vein occlusion (RVO). Cross-sectional study. Ninety-five eyes of 66 subjects with DR (65 eyes), branch retinal vein occlusion (19 eyes), and central retinal vein occlusion (11 eyes). Structural optical coherence tomography (OCT; Spectralis, Heidelberg Engineering) and OCT angiography (OCTA; Avanti, Optovue RTVue XR) data from a single visit were analyzed. FAZ area, point thickness of central fovea, central 1-mm subfield thickness, the occurrence of intraretinal cysts, ellipsoid zone disruption, and disorganization of retinal inner layers (DRIL) length were measured. VA was also recorded. Correlations between FAZ area and VA were explored using regression models. Main outcome measure was VA. Mean age was 62.9±13.2 years. There was no difference in demographic and OCT-derived anatomic measurements between branch retinal vein occlusion and central retinal vein occlusion groups (all P ≥ 0.058); therefore, data from the 2 groups were pooled together to a single RVO group for further statistical comparisons. Univariate and multiple regression analysis showed that the area of the FAZ was significantly correlated with VA in DR and RVO (all P ≤ 0.003). The relationship between FAZ area and VA varied with age (P = 0.026) such that for a constant FAZ area, an increase in patient age was associated with poorer vision (rise in logarithm of the minimum angle of resolution visual acuity). Disruption of the ellipsoid zone was significantly correlated with VA in univariate and multiple regression analysis (both P < 0.001). Occurrence of intraretinal cysts, DRIL length, and lens status were significantly correlated with VA in the univariate regression analysis (P ≤ 0.018) but not the multiple regression analysis (P ≥ 0.210). Remaining variables evaluated in this study were not predictive of VA (all P ≥ 0.225). The area of the FAZ is significantly correlated with VA in DR and RVO and this relationship is modulated by patient age. Further study about FAZ area and VA correlations during the natural course of retinal vascular diseases and following treatment is warranted. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Investigation of marital satisfaction and its relationship with job stress and general health of nurses in Qazvin, Iran

PubMed Central

Azimian, Jalil; Piran, Pegah; Jahanihashemi, Hassan; Dehghankar, Leila

2017-01-01

Background Pressures in nursing can affect family life and marital problems, disrupt common social problems, increase work-family conflicts and endanger people’s general health. Aim To determine marital satisfaction and its relationship with job stress and general health of nurses. Methods This descriptive and cross-sectional study was done in 2015 in medical educational centers of Qazvin by using an ENRICH marital satisfaction scale and General Health and Job Stress questionnaires completed by 123 nurses. Analysis was done by SPSS version 19 using descriptive and analytical statistics (Pearson correlation, t-test, ANOVA, Chi-square, regression line, multiple regression analysis). Results The findings showed that 64.4% of nurses had marital satisfaction. There was significant relationship between age (p=0.03), job experience (p=0.01), age of spouse (p=0.01) and marital satisfaction. The results showed that there was a significant relationship between marital satisfaction and general health (p<0.0001). Multiple regression analysis showed that there was a significant relationship between depression (p=0.012) and anxiety (p=0.001) with marital satisfaction. Conclusions Due to high levels of job stress and disorder in general health of nurses and low marital satisfaction by running health promotion programs and paying attention to its dimensions can help work and family health of nurses. PMID:28607660

Multiple regression analysis of anthropometric measurements influencing the cephalic index of male Japanese university students.

PubMed

Hossain, Md Golam; Saw, Aik; Alam, Rashidul; Ohtsuki, Fumio; Kamarul, Tunku

2013-09-01

Cephalic index (CI), the ratio of head breadth to head length, is widely used to categorise human populations. The aim of this study was to access the impact of anthropometric measurements on the CI of male Japanese university students. This study included 1,215 male university students from Tokyo and Kyoto, selected using convenient sampling. Multiple regression analysis was used to determine the effect of anthropometric measurements on CI. The variance inflation factor (VIF) showed no evidence of a multicollinearity problem among independent variables. The coefficients of the regression line demonstrated a significant positive relationship between CI and minimum frontal breadth (p < 0.01), bizygomatic breadth (p < 0.01) and head height (p < 0.05), and a negative relationship between CI and morphological facial height (p < 0.01) and head circumference (p < 0.01). Moreover, the coefficient and odds ratio of logistic regression analysis showed a greater likelihood for minimum frontal breadth (p < 0.01) and bizygomatic breadth (p < 0.01) to predict round-headedness, and morphological facial height (p < 0.05) and head circumference (p < 0.01) to predict long-headedness. Stepwise regression analysis revealed bizygomatic breadth, head circumference, minimum frontal breadth, head height and morphological facial height to be the best predictor craniofacial measurements with respect to CI. The results suggest that most of the variables considered in this study appear to influence the CI of adult male Japanese students.

Effects of problem-based learning by learning style in medical education.

PubMed

Chae, Su-Jin

2012-12-01

Although problem-based learning (PBL) has been popularized in many colleges, few studies have analyzed the relationship between individual differences and PBL. The purpose of this study was to analyze the relationship between learning style and the perception on the effects of PBL. Grasha-Riechmann Student Learning Style Scales was used to assess the learning styles of 38 students at Ajou University School of Medicine who were enrolled in a respiratory system course in 2011. The data were analyzed by regression analysis and Spearman correlation analysis. By regression analysis, dependent beta=0.478) and avoidant styles (beta=-0.815) influenced the learner's satisfaction with PBL. By Spearman correlation analysis, there was significant link between independent, dependent, and avoidant styles and the perception of the effect of PBL. There are few significant relationships between learning style and the perception of the effects of PBL. We must determine how to teach students with different learning styles and the factors that influence PBL.

The Effect of Sitagliptin on the Regression of Carotid Intima-Media Thickening in Patients with Type 2 Diabetes Mellitus: A Post Hoc Analysis of the Sitagliptin Preventive Study of Intima-Media Thickness Evaluation.

PubMed

Mita, Tomoya; Katakami, Naoto; Shiraiwa, Toshihiko; Yoshii, Hidenori; Gosho, Masahiko; Shimomura, Iichiro; Watada, Hirotaka

2017-01-01

Background. The effect of dipeptidyl peptidase-4 (DPP-4) inhibitors on the regression of carotid IMT remains largely unknown. The present study aimed to clarify whether sitagliptin, DPP-4 inhibitor, could regress carotid intima-media thickness (IMT) in insulin-treated patients with type 2 diabetes mellitus (T2DM). Methods . This is an exploratory analysis of a randomized trial in which we investigated the effect of sitagliptin on the progression of carotid IMT in insulin-treated patients with T2DM. Here, we compared the efficacy of sitagliptin treatment on the number of patients who showed regression of carotid IMT of ≥0.10 mm in a post hoc analysis. Results . The percentages of the number of the patients who showed regression of mean-IMT-CCA (28.9% in the sitagliptin group versus 16.4% in the conventional group, P  = 0.022) and left max-IMT-CCA (43.0% in the sitagliptin group versus 26.2% in the conventional group, P  = 0.007), but not right max-IMT-CCA, were higher in the sitagliptin treatment group compared with those in the non-DPP-4 inhibitor treatment group. In multiple logistic regression analysis, sitagliptin treatment significantly achieved higher target attainment of mean-IMT-CCA ≥0.10 mm and right and left max-IMT-CCA ≥0.10 mm compared to conventional treatment. Conclusions . Our data suggested that DPP-4 inhibitors were associated with the regression of carotid atherosclerosis in insulin-treated T2DM patients. This study has been registered with the University Hospital Medical Information Network Clinical Trials Registry (UMIN000007396).

The use of generalized estimating equations in the analysis of motor vehicle crash data.

PubMed

Hutchings, Caroline B; Knight, Stacey; Reading, James C

2003-01-01

The purpose of this study was to determine if it is necessary to use generalized estimating equations (GEEs) in the analysis of seat belt effectiveness in preventing injuries in motor vehicle crashes. The 1992 Utah crash dataset was used, excluding crash participants where seat belt use was not appropriate (n=93,633). The model used in the 1996 Report to Congress [Report to congress on benefits of safety belts and motorcycle helmets, based on data from the Crash Outcome Data Evaluation System (CODES). National Center for Statistics and Analysis, NHTSA, Washington, DC, February 1996] was analyzed for all occupants with logistic regression, one level of nesting (occupants within crashes), and two levels of nesting (occupants within vehicles within crashes) to compare the use of GEEs with logistic regression. When using one level of nesting compared to logistic regression, 13 of 16 variance estimates changed more than 10%, and eight of 16 parameter estimates changed more than 10%. In addition, three of the independent variables changed from significant to insignificant (alpha=0.05). With the use of two levels of nesting, two of 16 variance estimates and three of 16 parameter estimates changed more than 10% from the variance and parameter estimates in one level of nesting. One of the independent variables changed from insignificant to significant (alpha=0.05) in the two levels of nesting model; therefore, only two of the independent variables changed from significant to insignificant when the logistic regression model was compared to the two levels of nesting model. The odds ratio of seat belt effectiveness in preventing injuries was 12% lower when a one-level nested model was used. Based on these results, we stress the need to use a nested model and GEEs when analyzing motor vehicle crash data.

Promoting motivation through mode of instruction: The relationship between use of affective teaching techniques and motivation to learn science

NASA Astrophysics Data System (ADS)

Sanchez Rivera, Yamil

The purpose of this study is to add to what we know about the affective domain and to create a valid instrument for future studies. The Motivation to Learn Science (MLS) Inventory is based on Krathwohl's Taxonomy of Affective Behaviors (Krathwohl et al., 1964). The results of the Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) demonstrated that the MLS Inventory is a valid and reliable instrument. Therefore, the MLS Inventory is a uni-dimensional instrument composed of 9 items with convergent validity (no divergence). The instrument had a high Chronbach Alpha value of .898 during the EFA analysis and .919 with the CFA analysis. Factor loadings on the 9 items ranged from .617 to .800. Standardized regression weights ranged from .639 to .835 in the CFA analysis. Various indices (RMSEA = .033; NFI = .987; GFI = .985; CFI = 1.000) demonstrated a good fitness of the proposed model. Hierarchical linear modeling was used to statistical analyze data where students' motivation to learn science scores (level-1) were nested within teachers (level-2). The analysis was geared toward identifying if teachers' use of affective behavior (a level-2 classroom variable) was significantly related with students' MLS scores (level-1 criterion variable). Model testing proceeded in three phases: intercept-only model, means-as-outcome model, and a random-regression coefficient model. The intercept-only model revealed an intra-class correlation coefficient of .224 with an estimated reliability of .726. Therefore, data suggested that only 22.4% of the variance in MLS scores is between-classes and the remaining 77.6% is at the student-level. Due to the significant variance in MLS scores, X2(62.756, p<.0001), teachers' TAB scores were added as a level-2 predictor. The regression coefficient was non-significant (p>.05). Therefore, the teachers' self-reported use of affective behaviors was not a significant predictor of students' motivation to learn science.

Spatially resolved regression analysis of pre-treatment FDG, FLT and Cu-ATSM PET from post-treatment FDG PET: an exploratory study

PubMed Central

Bowen, Stephen R; Chappell, Richard J; Bentzen, Søren M; Deveau, Michael A; Forrest, Lisa J; Jeraj, Robert

2012-01-01

Purpose To quantify associations between pre-radiotherapy and post-radiotherapy PET parameters via spatially resolved regression. Materials and methods Ten canine sinonasal cancer patients underwent PET/CT scans of [18F]FDG (FDGpre), [18F]FLT (FLTpre), and [61Cu]Cu-ATSM (Cu-ATSMpre). Following radiotherapy regimens of 50 Gy in 10 fractions, veterinary patients underwent FDG PET/CT scans at three months (FDGpost). Regression of standardized uptake values in baseline FDGpre, FLTpre and Cu-ATSMpre tumour voxels to those in FDGpost images was performed for linear, log-linear, generalized-linear and mixed-fit linear models. Goodness-of-fit in regression coefficients was assessed by R2. Hypothesis testing of coefficients over the patient population was performed. Results Multivariate linear model fits of FDGpre to FDGpost were significantly positive over the population (FDGpost~0.17 FDGpre, p=0.03), and classified slopes of RECIST non-responders and responders to be different (0.37 vs. 0.07, p=0.01). Generalized-linear model fits related FDGpre to FDGpost by a linear power law (FDGpost~FDGpre0.93, p<0.001). Univariate mixture model fits of FDGpre improved R2 from 0.17 to 0.52. Neither baseline FLT PET nor Cu-ATSM PET uptake contributed statistically significant multivariate regression coefficients. Conclusions Spatially resolved regression analysis indicates that pre-treatment FDG PET uptake is most strongly associated with three-month post-treatment FDG PET uptake in this patient population, though associations are histopathology-dependent. PMID:22682748

Increased risk for complications following removal of hardware in patients with liver disease, pilon or pelvic fractures: A regression analysis.

PubMed

Brown, Bryan D; Steinert, Justin N; Stelzer, John W; Yoon, Richard S; Langford, Joshua R; Koval, Kenneth J

2017-12-01

Indications for removing orthopedic hardware on an elective basis varies widely. Although viewed as a relatively benign procedure, there is a lack of data regarding overall complication rates after fracture fixation. The purpose of this study is to determine the overall short-term complication rate for elective removal of orthopedic hardware after fracture fixation and to identify associated risk factors. Adult patients indicated for elective hardware removal after fracture fixation between July 2012 and July 2016 were screened for inclusion. Inclusion criteria included patients with hardware related pain and/or impaired cosmesis with complete medical and radiographic records and at least 3-month follow-up. Exclusion criteria were those patients indicated for hardware removal for a diagnosis of malunion, non-union, and/or infection. Data collected included patient age, gender, anatomic location of hardware removed, body mass index, ASA score, and comorbidities. Overall complications, as well as complications requiring revision surgery were recorded. Statistical analysis was performed with SPSS 20.0, and included univariate and multivariate regression analysis. 391 patients (418 procedures) were included for analysis. Overall complication rates were 8.4%, with a 3.6% revision surgery rate. Univariate regression analysis revealed that patients who had liver disease were at significant risk for complication (p=0.001) and revision surgery (p=0.036). Multivariate regression analysis showed that: 1) patients who had liver disease were at significant risk of overall complication (p=0.001) and revision surgery (p=0.039); 2) Removal of hardware following fixation for a pilon had significantly increased risk for complication (p=0.012), but not revision surgery (p=0.43); and 3) Removal of hardware for pelvic fixation had a significantly increased risk for revision surgery (p=0.017). Removal of hardware following fracture fixation is not a risk-free procedure. Patients with liver disease are at increased risk for complications, including increased risk for needing revision surgery following hardware removal. Patients having hardware removed following fixation for pilon fractures also are at increased risk for complication, although they may not require a return trip to the operating room. Finally, removal of pelvic hardware is associated with a higher return to the operating room. Copyright © 2017 Elsevier Ltd. All rights reserved.

[A correlational study on uncertainty, mastery and appraisal of uncertainty in hospitalized children's mothers].

PubMed

Yoo, Kyung Hee

2007-06-01

This study was conducted to investigate the correlation among uncertainty, mastery and appraisal of uncertainty in hospitalized children's mothers. Self report questionnaires were used to measure the variables. Variables were uncertainty, mastery and appraisal of uncertainty. In data analysis, the SPSSWIN 12.0 program was utilized for descriptive statistics, Pearson's correlation coefficients, and regression analysis. Reliability of the instruments was cronbach's alpha=.84~.94. Mastery negatively correlated with uncertainty(r=-.444, p=.000) and danger appraisal of uncertainty(r=-.514, p=.000). In regression of danger appraisal of uncertainty, uncertainty and mastery were significant predictors explaining 39.9%. Mastery was a significant mediating factor between uncertainty and danger appraisal of uncertainty in hospitalized children's mothers. Therefore, nursing interventions which improve mastery must be developed for hospitalized children's mothers.

Trochanteric entry femoral nails yield better femoral version and lower revision rates-A large cohort multivariate regression analysis.

PubMed

Yoon, Richard S; Gage, Mark J; Galos, David K; Donegan, Derek J; Liporace, Frank A

2017-06-01

Intramedullary nailing (IMN) has become the standard of care for the treatment of most femoral shaft fractures. Different IMN options include trochanteric and piriformis entry as well as retrograde nails, which may result in varying degrees of femoral rotation. The objective of this study was to analyze postoperative femoral version between three types of nails and to delineate any significant differences in femoral version (DFV) and revision rates. Over a 10-year period, 417 patients underwent IMN of a diaphyseal femur fracture (AO/OTA 32A-C). Of these patients, 316 met inclusion criteria and obtained postoperative computed tomography (CT) scanograms to calculate femoral version and were thus included in the study. In this study, our main outcome measure was the difference in femoral version (DFV) between the uninjured limb and the injured limb. The effect of the following variables on DFV and revision rates were determined via univariate, multivariate, and ordinal regression analyses: gender, age, BMI, ethnicity, mechanism of injury, operative side, open fracture, and table type/position. Statistical significance was set at p<0.05. A total of 316 patients were included. Piriformis entry nails made up the majority (n=141), followed by retrograde (n=108), then trochanteric entry nails (n=67). Univariate regression analysis revealed that a lower BMI was significantly associated with a lower DFV (p=0.006). Controlling for possible covariables, multivariate analysis yielded a significantly lower DFV for trochanteric entry nails than piriformis or retrograde nails (7.9±6.10 vs. 9.5±7.4 vs. 9.4±7.8°, p<0.05). Using revision as an endpoint, trochanteric entry nails also had a significantly lower revision rate, even when controlling for all other variables (p<0.05). Comparative, objective comparisons between DFV between different nails based on entry point revealed that trochanteric nails had a significantly lower DFV and a lower revision rate, even after regression analysis. However, this is not to state that the other nail types exhibited abnormal DFV. Translation to the clinical impact of a few degrees of DFV is also unknown. Future studies to more in-depth study the intricacies of femoral version may lead to improved technology in addition to potentially improved clinical outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

The association of lung function and St. George's respiratory questionnaire with exacerbations in COPD: a systematic literature review and regression analysis.

PubMed

Martin, Amber L; Marvel, Jessica; Fahrbach, Kyle; Cadarette, Sarah M; Wilcox, Teresa K; Donohue, James F

2016-04-16

This study investigated the relationship between changes in lung function (as measured by forced expiratory volume in one second [FEV1]) and the St. George's Respiratory Questionnaire (SGRQ) and economically significant outcomes of exacerbations and health resource utilization, with an aim to provide insight into whether the effects of COPD treatment on lung function and health status relate to a reduced risk for exacerbations. A systematic literature review was conducted in MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials to identify randomized controlled trials of adult COPD patients published in English since 2002 in order to relate mean change in FEV1 and SGRQ total score to exacerbations and hospitalizations. These predictor/outcome pairs were analyzed using sample-size weighted regression analyses, which estimated a regression slope relating the two treatment effects, as well as a confidence interval and a test of statistical significance. Sixty-seven trials were included in the analysis. Significant relationships were seen between: FEV1 and any exacerbation (time to first exacerbation or patients with at least one exacerbation, p = 0.001); between FEV1 and moderate-to-severe exacerbations (time to first exacerbation, patients with at least one exacerbation, or annualized rate, p = 0.045); between SGRQ score and any exacerbation (time to first exacerbation or patients with at least one exacerbation, p = 0.0002) and between SGRQ score and moderate-to-severe exacerbations (time to first exacerbation or patients with at least one exacerbation, p = 0.0279; annualized rate, p = 0.0024). Relationships between FEV1 or SGRQ score and annualized exacerbation rate for any exacerbation or hospitalized exacerbations were not significant. The regression analysis demonstrated a significant association between improvements in FEV1 and SGRQ score and lower risk for COPD exacerbations. Even in cases of non-significant relationships, results were in the expected direction with few exceptions. The results of this analysis offer health care providers and payers a broader picture of the relationship between exacerbations and mean change in FEV1 as well as SGRQ score, and will help inform clinical and formulary-making decisions while stimulating new research questions for future prospective studies.

Temporal trends in sperm count: a systematic review and meta-regression analysis.

PubMed

Levine, Hagai; Jørgensen, Niels; Martino-Andrade, Anderson; Mendiola, Jaime; Weksler-Derri, Dan; Mindlis, Irina; Pinotti, Rachel; Swan, Shanna H

2017-11-01

Reported declines in sperm counts remain controversial today and recent trends are unknown. A definitive meta-analysis is critical given the predictive value of sperm count for fertility, morbidity and mortality. To provide a systematic review and meta-regression analysis of recent trends in sperm counts as measured by sperm concentration (SC) and total sperm count (TSC), and their modification by fertility and geographic group. PubMed/MEDLINE and EMBASE were searched for English language studies of human SC published in 1981-2013. Following a predefined protocol 7518 abstracts were screened and 2510 full articles reporting primary data on SC were reviewed. A total of 244 estimates of SC and TSC from 185 studies of 42 935 men who provided semen samples in 1973-2011 were extracted for meta-regression analysis, as well as information on years of sample collection and covariates [fertility group ('Unselected by fertility' versus 'Fertile'), geographic group ('Western', including North America, Europe Australia and New Zealand versus 'Other', including South America, Asia and Africa), age, ejaculation abstinence time, semen collection method, method of measuring SC and semen volume, exclusion criteria and indicators of completeness of covariate data]. The slopes of SC and TSC were estimated as functions of sample collection year using both simple linear regression and weighted meta-regression models and the latter were adjusted for pre-determined covariates and modification by fertility and geographic group. Assumptions were examined using multiple sensitivity analyses and nonlinear models. SC declined significantly between 1973 and 2011 (slope in unadjusted simple regression models -0.70 million/ml/year; 95% CI: -0.72 to -0.69; P < 0.001; slope in adjusted meta-regression models = -0.64; -1.06 to -0.22; P = 0.003). The slopes in the meta-regression model were modified by fertility (P for interaction = 0.064) and geographic group (P for interaction = 0.027). There was a significant decline in SC between 1973 and 2011 among Unselected Western (-1.38; -2.02 to -0.74; P < 0.001) and among Fertile Western (-0.68; -1.31 to -0.05; P = 0.033), while no significant trends were seen among Unselected Other and Fertile Other. Among Unselected Western studies, the mean SC declined, on average, 1.4% per year with an overall decline of 52.4% between 1973 and 2011. Trends for TSC and SC were similar, with a steep decline among Unselected Western (-5.33 million/year, -7.56 to -3.11; P < 0.001), corresponding to an average decline in mean TSC of 1.6% per year and overall decline of 59.3%. Results changed minimally in multiple sensitivity analyses, and there was no statistical support for the use of a nonlinear model. In a model restricted to data post-1995, the slope both for SC and TSC among Unselected Western was similar to that for the entire period (-2.06 million/ml, -3.38 to -0.74; P = 0.004 and -8.12 million, -13.73 to -2.51, P = 0.006, respectively). This comprehensive meta-regression analysis reports a significant decline in sperm counts (as measured by SC and TSC) between 1973 and 2011, driven by a 50-60% decline among men unselected by fertility from North America, Europe, Australia and New Zealand. Because of the significant public health implications of these results, research on the causes of this continuing decline is urgently needed. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Effect of removing the common mode errors on linear regression analysis of noise amplitudes in position time series of a regional GPS network & a case study of GPS stations in Southern California

NASA Astrophysics Data System (ADS)

Jiang, Weiping; Ma, Jun; Li, Zhao; Zhou, Xiaohui; Zhou, Boye

2018-05-01

The analysis of the correlations between the noise in different components of GPS stations has positive significance to those trying to obtain more accurate uncertainty of velocity with respect to station motion. Previous research into noise in GPS position time series focused mainly on single component evaluation, which affects the acquisition of precise station positions, the velocity field, and its uncertainty. In this study, before and after removing the common-mode error (CME), we performed one-dimensional linear regression analysis of the noise amplitude vectors in different components of 126 GPS stations with a combination of white noise, flicker noise, and random walking noise in Southern California. The results show that, on the one hand, there are above-moderate degrees of correlation between the white noise amplitude vectors in all components of the stations before and after removal of the CME, while the correlations between flicker noise amplitude vectors in horizontal and vertical components are enhanced from un-correlated to moderately correlated by removing the CME. On the other hand, the significance tests show that, all of the obtained linear regression equations, which represent a unique function of the noise amplitude in any two components, are of practical value after removing the CME. According to the noise amplitude estimates in two components and the linear regression equations, more accurate noise amplitudes can be acquired in the two components.

Associations of body mass index with cancer incidence among populations, genders, and menopausal status: A systematic review and meta-analysis.

PubMed

Wang, Jun; Yang, Dong-Lin; Chen, Zhong-Zhu; Gou, Ben-Fu

2016-06-01

In order to further reveal the differences of association between body mass index (BMI) and cancer incidence across populations, genders, and menopausal status, we performed comprehensive meta-analysis with eligible citations. The risk ratio (RR) of incidence at 10 different cancer sites (per 5kg/m(2) increase in BMI) were quantified separately by employing generalized least-squares to estimate trends, and combined by meta-analyses. We observed significantly stronger association between increased BMI and breast cancer incidence in the Asia-Pacific group (RR 1.18:1.11-1.26) than in European-Australian (1.05:1.00-1.09) and North-American group (1.06:1.03-1.08) (meta-regression p<0.05). No association between increased BMI and pancreatic cancer incidence (0.94:0.71-1.24) was shown in the Asia-Pacific group (meta-regression p<0.05), whereas positive associations were found in other two groups. A significantly higher RR in men was found for colorectal cancer in comparison with women (meta-regression p<0.05). Compared with postmenopausal women, premenopausal women displayed significantly higher RR for ovarian cancer (pre- vs. post-=1.10 vs. 1.01, meta-regression p<0.05), but lower RR for breast cancer (pre- vs. post-=0.99 vs. 1.11, meta-regression p<0.0001). Our results indicate that overweight or obesity is a strong risk factor of cancer incidence at several cancer sites. Genders, populations, and menopausal status are important factors effecting the association between obesity and cancer incidence for certain cancer types. Copyright © 2016 Elsevier Ltd. All rights reserved.

Role of anthropometric data in the prediction of 4-stranded hamstring graft size in anterior cruciate ligament reconstruction.

PubMed

Ho, Sean Wei Loong; Tan, Teong Jin Lester; Lee, Keng Thiam

2016-03-01

To evaluate whether pre-operative anthropometric data can predict the optimal diameter and length of hamstring tendon autograft for anterior cruciate ligament (ACL) reconstruction. This was a cohort study that involved 169 patients who underwent single-bundle ACL reconstruction (single surgeon) with 4-stranded MM Gracilis and MM Semi-Tendinosus autografts. Height, weight, body mass index (BMI), gender, race, age and -smoking status were recorded pre-operatively. Intra-operatively, the diameter and functional length of the 4-stranded autograft was recorded. Multiple regression analysis was used to determine the relationship between the anthropometric measurements and the length and diameter of the implanted autografts. The strongest correlation between 4-stranded hamstring autograft diameter was height and weight. This correlation was stronger in females than males. BMI had a moderate correlation with the diameter of the graft in females. Females had a significantly smaller graft both in diameter and length when compared with males. Linear regression models did not show any significant correlation between hamstring autograft length with height and weight (p>0.05). Simple regression analysis demonstrated that height and weight can be used to predict hamstring graft diameter. The following regression equation was obtained for females: Graft diameter=0.012+0.034*Height+0.026*Weight (R2=0.358, p=0.004) The following regression equation was obtained for males: Graft diameter=5.130+0.012*Height+0.007*Weight (R2=0.086, p=0.002). Pre-operative anthropometric data has a positive correlation with the diameter of 4 stranded hamstring autografts but no significant correlation with the length. This data can be utilised to predict the autograft diameter and may be useful for pre-operative planning and patient counseling for graft selection.

The Relationship among Leisure Interests, Personality Traits, Affect, and Mood

ERIC Educational Resources Information Center

Wilkinson, Todd J.; Hansen, Jo-Ida C.

2006-01-01

The present study examined relationships between leisure interests and the Big Five personality traits, positive and negative affect, and moods. Regression analysis identified particular personality but not mood or affect variables as significant predictors of leisure factor scores. Further exploration through factor analysis revealed factor…

Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation.

PubMed

Hayes, Andrew F; Rockwood, Nicholas J

2017-11-01

There have been numerous treatments in the clinical research literature about various design, analysis, and interpretation considerations when testing hypotheses about mechanisms and contingencies of effects, popularly known as mediation and moderation analysis. In this paper we address the practice of mediation and moderation analysis using linear regression in the pages of Behaviour Research and Therapy and offer some observations and recommendations, debunk some popular myths, describe some new advances, and provide an example of mediation, moderation, and their integration as conditional process analysis using the PROCESS macro for SPSS and SAS. Our goal is to nudge clinical researchers away from historically significant but increasingly old school approaches toward modifications, revisions, and extensions that characterize more modern thinking about the analysis of the mechanisms and contingencies of effects. Copyright © 2016 Elsevier Ltd. All rights reserved.

Solutions for Determining the Significance Region Using the Johnson-Neyman Type Procedure in Generalized Linear (Mixed) Models

ERIC Educational Resources Information Center

Lazar, Ann A.; Zerbe, Gary O.

2011-01-01

Researchers often compare the relationship between an outcome and covariate for two or more groups by evaluating whether the fitted regression curves differ significantly. When they do, researchers need to determine the "significance region," or the values of the covariate where the curves significantly differ. In analysis of covariance (ANCOVA),…

The influence of sarcopenia on survival and surgical complications in ovarian cancer patients undergoing primary debulking surgery.

PubMed

Rutten, I J G; Ubachs, J; Kruitwagen, R F P M; van Dijk, D P J; Beets-Tan, R G H; Massuger, L F A G; Olde Damink, S W M; Van Gorp, T

2017-04-01

Sarcopenia, severe skeletal muscle loss, has been identified as a prognostic factor in various malignancies. This study aims to investigate whether sarcopenia is associated with overall survival (OS) and surgical complications in patients with advanced ovarian cancer undergoing primary debulking surgery (PDS). Ovarian cancer patients (n = 216) treated with PDS were enrolled retrospectively. Total skeletal muscle surface area was measured on axial computed tomography at the level of the third lumbar vertebra. Optimum stratification was used to find the optimal skeletal muscle index cut-off to define sarcopenia (≤38.73 cm 2 /m 2 ). Cox-regression and Kaplan-Meier analysis were used to analyse the relationship between sarcopenia and OS. The effect of sarcopenia on the development of major surgical complications was studied with logistic regression. Kaplan-Meier analysis showed a significant survival disadvantage for patients with sarcopenia compared to patients without sarcopenia (p = 0.010). Sarcopenia univariably predicted OS (HR 1.536 (95% CI 1.105-2.134), p = 0.011) but was not significant in multivariable Cox-regression analysis (HR 1.362 (95% CI 0.968-1.916), p = 0.076). Significant predictors for OS in multivariable Cox-regression analysis were complete PDS, treatment in a specialised centre and the development of major complications. Sarcopenia was not predictive of major complications. Sarcopenia was not predictive of OS or major complications in ovarian cancer patients undergoing primary debulking surgery. However a strong trend towards a survival disadvantage for patients with sarcopenia was seen. Future prospective studies should focus on interventions to prevent or reverse sarcopenia and possibly increase ovarian cancer survival. Complete cytoreduction remains the strongest predictor of ovarian cancer survival. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

The Relative Impact of Educational Attainment and Fatherlessness on Criminality.

ERIC Educational Resources Information Center

Koski, Douglas D.

1996-01-01

Regression analysis of 40 years of data on median income, education, divorce rate, and female-headed households was conducted to determine their influence on crime rates, especially homicide. Educational attainment had a significant bearing on criminality. Single parenting was less significant than low income. (SK)

Predictors of High Profit and High Deficit Outliers under SwissDRG of a Tertiary Care Center

PubMed Central

Mehra, Tarun; Müller, Christian Thomas Benedikt; Volbracht, Jörk; Seifert, Burkhardt; Moos, Rudolf

2015-01-01

Principles Case weights of Diagnosis Related Groups (DRGs) are determined by the average cost of cases from a previous billing period. However, a significant amount of cases are largely over- or underfunded. We therefore decided to analyze earning outliers of our hospital as to search for predictors enabling a better grouping under SwissDRG. Methods 28,893 inpatient cases without additional private insurance discharged from our hospital in 2012 were included in our analysis. Outliers were defined by the interquartile range method. Predictors for deficit and profit outliers were determined with logistic regressions. Predictors were shortlisted with the LASSO regularized logistic regression method and compared to results of Random forest analysis. 10 of these parameters were selected for quantile regression analysis as to quantify their impact on earnings. Results Psychiatric diagnosis and admission as an emergency case were significant predictors for higher deficit with negative regression coefficients for all analyzed quantiles (p<0.001). Admission from an external health care provider was a significant predictor for a higher deficit in all but the 90% quantile (p<0.001 for Q10, Q20, Q50, Q80 and p = 0.0017 for Q90). Burns predicted higher earnings for cases which were favorably remunerated (p<0.001 for the 90% quantile). Osteoporosis predicted a higher deficit in the most underfunded cases, but did not predict differences in earnings for balanced or profitable cases (Q10 and Q20: p<0.00, Q50: p = 0.10, Q80: p = 0.88 and Q90: p = 0.52). ICU stay, mechanical and patient clinical complexity level score (PCCL) predicted higher losses at the 10% quantile but also higher profits at the 90% quantile (p<0.001). Conclusion We suggest considering psychiatric diagnosis, admission as an emergencay case and admission from an external health care provider as DRG split criteria as they predict large, consistent and significant losses. PMID:26517545

Predictors of High Profit and High Deficit Outliers under SwissDRG of a Tertiary Care Center.

PubMed

Mehra, Tarun; Müller, Christian Thomas Benedikt; Volbracht, Jörk; Seifert, Burkhardt; Moos, Rudolf

2015-01-01

Case weights of Diagnosis Related Groups (DRGs) are determined by the average cost of cases from a previous billing period. However, a significant amount of cases are largely over- or underfunded. We therefore decided to analyze earning outliers of our hospital as to search for predictors enabling a better grouping under SwissDRG. 28,893 inpatient cases without additional private insurance discharged from our hospital in 2012 were included in our analysis. Outliers were defined by the interquartile range method. Predictors for deficit and profit outliers were determined with logistic regressions. Predictors were shortlisted with the LASSO regularized logistic regression method and compared to results of Random forest analysis. 10 of these parameters were selected for quantile regression analysis as to quantify their impact on earnings. Psychiatric diagnosis and admission as an emergency case were significant predictors for higher deficit with negative regression coefficients for all analyzed quantiles (p<0.001). Admission from an external health care provider was a significant predictor for a higher deficit in all but the 90% quantile (p<0.001 for Q10, Q20, Q50, Q80 and p = 0.0017 for Q90). Burns predicted higher earnings for cases which were favorably remunerated (p<0.001 for the 90% quantile). Osteoporosis predicted a higher deficit in the most underfunded cases, but did not predict differences in earnings for balanced or profitable cases (Q10 and Q20: p<0.00, Q50: p = 0.10, Q80: p = 0.88 and Q90: p = 0.52). ICU stay, mechanical and patient clinical complexity level score (PCCL) predicted higher losses at the 10% quantile but also higher profits at the 90% quantile (p<0.001). We suggest considering psychiatric diagnosis, admission as an emergency case and admission from an external health care provider as DRG split criteria as they predict large, consistent and significant losses.

The Association of Fever with Total Mechanical Ventilation Time in Critically Ill Patients.

PubMed

Park, Dong Won; Egi, Moritoki; Nishimura, Masaji; Chang, Youjin; Suh, Gee Young; Lim, Chae Man; Kim, Jae Yeol; Tada, Keiichi; Matsuo, Koichi; Takeda, Shinhiro; Tsuruta, Ryosuke; Yokoyama, Takeshi; Kim, Seon Ok; Koh, Younsuck

2016-12-01

This research aims to investigate the impact of fever on total mechanical ventilation time (TVT) in critically ill patients. Subgroup analysis was conducted using a previous prospective, multicenter observational study. We included mechanically ventilated patients for more than 24 hours from 10 Korean and 15 Japanese intensive care units (ICU), and recorded maximal body temperature under the support of mechanical ventilation (MAX(MV)). To assess the independent association of MAX(MV) with TVT, we used propensity-matched analysis in a total of 769 survived patients with medical or surgical admission, separately. Together with multiple linear regression analysis to evaluate the association between the severity of fever and TVT, the effect of MAX(MV) on ventilator-free days was also observed by quantile regression analysis in all subjects including non-survivors. After propensity score matching, a MAX(MV) ≥ 37.5°C was significantly associated with longer mean TVT by 5.4 days in medical admission, and by 1.2 days in surgical admission, compared to those with MAX(MV) of 36.5°C to 37.4°C. In multivariate linear regression analysis, patients with three categories of fever (MAX(MV) of 37.5°C to 38.4°C, 38.5°C to 39.4°C, and ≥ 39.5°C) sustained a significantly longer duration of TVT than those with normal range of MAX(MV) in both categories of ICU admission. A significant association between MAX(MV) and mechanical ventilator-free days was also observed in all enrolled subjects. Fever may be a detrimental factor to prolong TVT in mechanically ventilated patients. These findings suggest that fever in mechanically ventilated patients might be associated with worse mechanical ventilation outcome.

The impact of meteorology on the occurrence of waterborne outbreaks of vero cytotoxin-producing Escherichia coli (VTEC): a logistic regression approach.

PubMed

O'Dwyer, Jean; Morris Downes, Margaret; Adley, Catherine C

2016-02-01

This study analyses the relationship between meteorological phenomena and outbreaks of waterborne-transmitted vero cytotoxin-producing Escherichia coli (VTEC) in the Republic of Ireland over an 8-year period (2005-2012). Data pertaining to the notification of waterborne VTEC outbreaks were extracted from the Computerised Infectious Disease Reporting system, which is administered through the national Health Protection Surveillance Centre as part of the Health Service Executive. Rainfall and temperature data were obtained from the national meteorological office and categorised as cumulative rainfall, heavy rainfall events in the previous 7 days, and mean temperature. Regression analysis was performed using logistic regression (LR) analysis. The LR model was significant (p < 0.001), with all independent variables: cumulative rainfall, heavy rainfall and mean temperature making a statistically significant contribution to the model. The study has found that rainfall, particularly heavy rainfall in the preceding 7 days of an outbreak, is a strong statistical indicator of a waterborne outbreak and that temperature also impacts waterborne VTEC outbreak occurrence.

The relationship between air pollution, fossil fuel energy consumption, and water resources in the panel of selected Asia-Pacific countries.

PubMed

Rafindadi, Abdulkadir Abdulrashid; Yusof, Zarinah; Zaman, Khalid; Kyophilavong, Phouphet; Akhmat, Ghulam

2014-10-01

The objective of the study is to examine the relationship between air pollution, fossil fuel energy consumption, water resources, and natural resource rents in the panel of selected Asia-Pacific countries, over a period of 1975-2012. The study includes number of variables in the model for robust analysis. The results of cross-sectional analysis show that there is a significant relationship between air pollution, energy consumption, and water productivity in the individual countries of Asia-Pacific. However, the results of each country vary according to the time invariant shocks. For this purpose, the study employed the panel least square technique which includes the panel least square regression, panel fixed effect regression, and panel two-stage least square regression. In general, all the panel tests indicate that there is a significant and positive relationship between air pollution, energy consumption, and water resources in the region. The fossil fuel energy consumption has a major dominating impact on the changes in the air pollution in the region.

[Effect of Adolescents' Abuse Experience on Suicidal Ideation: Focused on Moderated Mediation Effect of Self-esteem on Depression and Anxiety].

PubMed

Kim, Ji Young; Lee, Kyunghee

2015-10-01

The purpose of this study was to examine the moderating mediation effect of self-esteem on the relations among adolescents' abuse experiences, depression and anxiety, and suicidal ideation. The participants were selected using secondary data from a population in the 2012 Korea Welfare Panel Survey (KOWEPS). Data were analyzed using SPSS 15.0 and SPSS Macro, and bootstrapping and hierarchical regression analysis were performed to analyze multilevel models. First, analysis of the mediating effect of the adolescents' abuse showed that there was significant mediating influence between suicidal ideation and depression and anxiety. Second, hierarchical regression analysis showed that self-esteem had significant mediation effect on depression and anxiety in adolescents' suicidal ideation. Third, SPSS Macro showed that self-esteem also significantly moderated the mediating effect of adolescents' abuse experiences on suicidal ideation through depression and anxiety. The study results suggest that in future research on adolescent's abuse experience, the risk of suicide in depression and anxiety scores should be selected through evaluation of each individual's self-esteem scale. Coping strategies with immediate early intervention should be suggested.

On statistical analysis of factors affecting anthocyanin extraction from Ixora siamensis

NASA Astrophysics Data System (ADS)

Mat Nor, N. A.; Arof, A. K.

2016-10-01

This study focused on designing an experimental model in order to evaluate the influence of operative extraction parameters employed for anthocyanin extraction from Ixora siamensis on CIE color measurements (a*, b* and color saturation). Extractions were conducted at temperatures of 30, 55 and 80°C, soaking time of 60, 120 and 180 min using acidified methanol solvent with different trifluoroacetic acid (TFA) contents of 0.5, 1.75 and 3% (v/v). The statistical evaluation was performed by running analysis of variance (ANOVA) and regression calculation to investigate the significance of the generated model. Results show that the generated regression models adequately explain the data variation and significantly represented the actual relationship between the independent variables and the responses. Analysis of variance (ANOVA) showed high coefficient determination values (R2) of 0.9687 for a*, 0.9621 for b* and 0.9758 for color saturation, thus ensuring a satisfactory fit of the developed models with the experimental data. Interaction between TFA content and extraction temperature exhibited to the highest significant influence on CIE color parameter.

Socioeconomic disparities in the utilization of mechanical thrombectomy for acute ischemic stroke in US hospitals.

PubMed

Brinjikji, W; Rabinstein, A A; McDonald, J S; Cloft, H J

2014-03-01

Previous studies have demonstrated that socioeconomic disparities in the treatment of cerebrovascular diseases exist. We studied a large administrative data base to study disparities in the utilization of mechanical thrombectomy for acute ischemic stroke. With the utilization of the Perspective data base, we studied disparities in mechanical thrombectomy utilization between patient race and insurance status in 1) all patients presenting with acute ischemic stroke and 2) patients presenting with acute ischemic stroke at centers that performed mechanical thrombectomy. We examined utilization rates of mechanical thrombectomy by race/ethnicity (white, black, and Hispanic) and insurance status (Medicare, Medicaid, self-pay, and private). Multivariate logistic regression analysis adjusting for potential confounding variables was performed to study the association between race/insurance status and mechanical thrombectomy utilization. The overall mechanical thrombectomy utilization rate was 0.15% (371/249,336); utilization rate at centers that performed mechanical thrombectomy was 1.0% (371/35,376). In the sample of all patients with acute ischemic stroke, multivariate logistic regression analysis demonstrated that uninsured patients had significantly lower odds of mechanical thrombectomy utilization compared with privately insured patients (OR = 0.52, 95% CI = 0.25-0.95, P = .03), as did Medicare patients (OR = 0.53, 95% CI = 0.41-0.70, P < .0001). Blacks had significantly lower odds of mechanical thrombectomy utilization compared with whites (OR = 0.35, 95% CI = 0.23-0.51, P < .0001). When considering only patients treated at centers performing mechanical thrombectomy, multivariate logistic regression analysis demonstrated that insurance was not associated with significant disparities in mechanical thrombectomy utilization; however, black patients had significantly lower odds of mechanical thrombectomy utilization compared with whites (OR = 0.41, 95% CI = 0.27-0.60, P < .0001). Significant socioeconomic disparities exist in the utilization of mechanical thrombectomy in the United States.

Analysis of cerebrovascular disease mortality trends in Andalusia (1980-2014).

PubMed

Cayuela, A; Cayuela, L; Rodríguez-Domínguez, S; González, A; Moniche, F

2017-03-15

In recent decades, mortality rates for cerebrovascular diseases (CVD) have decreased significantly in many countries. This study analyses recent tendencies in CVD mortality rates in Andalusia (1980-2014) to identify any changes in previously observed sex and age trends. CVD mortality and population data were obtained from Spain's National Statistics Institute database. We calculated age-specific and age-standardised mortality rates using the direct method (European standard population). Joinpoint regression analysis was used to estimate the annual percentage change in rates and identify significant changes in mortality trends. We also estimated rate ratios between Andalusia and Spain. Standardised rates for both males and females showed 3 periods in joinpoint regression analysis: an initial period of significant decline (1980-1997), a period of rate stabilisation (1997-2003), and another period of significant decline (2003-2014). Between 1997 and 2003, age-standardised rates stabilised in Andalusia but continued to decrease in Spain as a whole. This increased in the gap between CVD mortality rates in Andalusia and Spain for both sexes and most age groups. Copyright © 2017 The Author(s). Publicado por Elsevier España, S.L.U. All rights reserved.

Reference-Free Removal of EEG-fMRI Ballistocardiogram Artifacts with Harmonic Regression

PubMed Central

Krishnaswamy, Pavitra; Bonmassar, Giorgio; Poulsen, Catherine; Pierce, Eric T; Purdon, Patrick L.; Brown, Emery N.

2016-01-01

Combining electroencephalogram (EEG) recording and functional magnetic resonance imaging (fMRI) offers the potential for imaging brain activity with high spatial and temporal resolution. This potential remains limited by the significant ballistocardiogram (BCG) artifacts induced in the EEG by cardiac pulsation-related head movement within the magnetic field. We model the BCG artifact using a harmonic basis, pose the artifact removal problem as a local harmonic regression analysis, and develop an efficient maximum likelihood algorithm to estimate and remove BCG artifacts. Our analysis paradigm accounts for time-frequency overlap between the BCG artifacts and neurophysiologic EEG signals, and tracks the spatiotemporal variations in both the artifact and the signal. We evaluate performance on: simulated oscillatory and evoked responses constructed with realistic artifacts; actual anesthesia-induced oscillatory recordings; and actual visual evoked potential recordings. In each case, the local harmonic regression analysis effectively removes the BCG artifacts, and recovers the neurophysiologic EEG signals. We further show that our algorithm outperforms commonly used reference-based and component analysis techniques, particularly in low SNR conditions, the presence of significant time-frequency overlap between the artifact and the signal, and/or large spatiotemporal variations in the BCG. Because our algorithm does not require reference signals and has low computational complexity, it offers a practical tool for removing BCG artifacts from EEG data recorded in combination with fMRI. PMID:26151100

Propellant Surveillance Report LGM-30 F and G Stage 1, Phase E, Series IV, TP-H1011.

DTIC Science & Technology

1978-02-01

regression analysis. From the statistical analysis of all data tested to date (twelve and one half years for F and G), significant degradation of the propellant does not appear likely for at least two years past the oldest data point.

Modeling and Analysis of Process Parameters for Evaluating Shrinkage Problems During Plastic Injection Molding of a DVD-ROM Cover

NASA Astrophysics Data System (ADS)

Öktem, H.

2012-01-01

Plastic injection molding plays a key role in the production of high-quality plastic parts. Shrinkage is one of the most significant problems of a plastic part in terms of quality in the plastic injection molding. This article focuses on the study of the modeling and analysis of the effects of process parameters on the shrinkage by evaluating the quality of the plastic part of a DVD-ROM cover made with Acrylonitrile Butadiene Styrene (ABS) polymer material. An effective regression model was developed to determine the mathematical relationship between the process parameters (mold temperature, melt temperature, injection pressure, injection time, and cooling time) and the volumetric shrinkage by utilizing the analysis data. Finite element (FE) analyses designed by Taguchi (L27) orthogonal arrays were run in the Moldflow simulation program. Analysis of variance (ANOVA) was then performed to check the adequacy of the regression model and to determine the effect of the process parameters on the shrinkage. Experiments were conducted to control the accuracy of the regression model with the FE analyses obtained from Moldflow. The results show that the regression model agrees very well with the FE analyses and the experiments. From this, it can be concluded that this study succeeded in modeling the shrinkage problem in our application.

Stress, Self-Esteem, and Suicidal Ideation in Late Adolescents

ERIC Educational Resources Information Center

Wilburn, Victor R.; Smith, Delores E.

2005-01-01

The relationships among stress, self-esteem, and suicidal ideation in late adolescents were examined in a group of college students. Multiple regression analysis indicated that both stress and self-esteem were significantly related to suicidal ideation; low self-esteem and stressful life events significantly predicted suicidal ideation. The…

Religiosity and Authoritarianism as Predictors of Attitude toward the Disabled: A Regression Analysis.

ERIC Educational Resources Information Center

Tunick, Roy H.; And Others

1979-01-01

This study identifies predictors and correlates of attitudes toward the disabled. Authoritarianism, church attendance, religious orthodoxy, age, and education were significantly related to these attitudes of people in a Rocky Mountain Community. Significant predictors of the criterion were authoritarianism, religiosity, and age. Recommendations…

α-fetoprotein levels after interferon therapy predict regression of liver fibrosis in patients with sustained virological response.

PubMed

Tachi, Yoshihiko; Hirai, Takanori; Ishizu, Youji; Honda, Takashi; Kuzuya, Teiji; Hayashi, Kazuhiko; Ishigami, Masatoshi; Goto, Hidemi

2016-05-01

Eradicating chronic hepatitis C virus (HCV) infection improves liver fibrosis and reduces hepatocellular carcinoma (HCC) incidence in chronic HCV patients. We evaluated the relationship between fibrosis regression, as assessed by sequential biopsies, and clinical factors of patients with sustained virological response (SVR). We retrospectively enrolled 130 patients (74 men; 60.1 ± 8.1 years) with chronic HCV treated with interferon and ribavirin therapy who achieved SVR. To evaluate the change in fibrosis stage over time, all patients underwent a pre-therapy initial biopsy and a second biopsy after achieving SVR. The mean time between biopsies was 5.5 ± 1.2 years. Fibrosis stage regressed in 55 patients (42.3%), remained stable in 69 (53.1%), and progressed in 6 (4.6%). The mean fibrosis stage significantly decreased, from 2.01 ± 0.99 units to 1.61 ± 1.24 units (P < 0.001). Aspartate aminotransferase, γ-glutamyltransferase, and α-fetoprotein (AFP) levels at 24 weeks after the end of treatment (EOT) were significantly lower, and the platelet count at 24 weeks after the EOT was significantly higher in patients with fibrosis regression than in those without. Logistic regression analysis confirmed that lower AFP levels (< 5.4 ng/mL) at 24 weeks after the EOT (odds ratio [OR], 4.626; 95% confidence interval [CI], 1.557-13.153; P = 0.006) and HCV genotype 2 (OR, 2.198; 95% CI, 1.010-4.786; P = 0.047) were significant independent predictive factors for regressed fibrosis after SVR. Lower post-treatment AFP levels and HCV genotype 2 significantly correlated with liver fibrosis regression after SVR. © 2015 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Relationship between serum bilirubin concentrations and diabetic nephropathy in Shanghai Han's patients with type 1 diabetes mellitus.

PubMed

Li, Xu; Zhang, Lei; Chen, Haibing; Guo, Kaifeng; Yu, Haoyong; Zhou, Jian; Li, Ming; Li, Qing; Li, Lianxi; Yin, Jun; Liu, Fang; Bao, Yuqian; Han, Junfeng; Jia, Weiping

2017-03-31

Recent studies highlight a negative association between total bilirubin concentrations and albuminuria in patients with type 2 diabetes mellitus. Our study evaluated the relationship between bilirubin concentrations and the prevalence of diabetic nephropathy (DN) in Chinese patients with type 1 diabetes mellitus (T1DM). A total of 258 patients with T1DM were recruited and bilirubin concentrations were compared between patients with or without diabetic nephropathy. Multiple stepwise regression analysis was used to examine the relationship between bilirubin concentrations and 24 h urinary microalbumin. Binary logistic regression analysis was performed to assess independent risk factors for diabetic nephropathy. Participants were divided into four groups according to the quartile of total bilirubin concentrations (Q1, 0.20-0.60; Q2, 0.60-0.80; Q3, 0.80-1.00; Q4, 1.00-1.90 mg/dL) and the chi-square test was used to compare the prevalence of DN in patients with T1DM. The median bilirubin level was 0.56 (interquartile: 0.43-0.68 mg/dL) in the DN group, significantly lower than in the non-DN group (0.70 [interquartile: 0.58-0.89 mg/dL], P < 0.001). Spearman's correlational analysis showed bilirubin concentrations were inversely correlated with 24 h urinary microalbumin (r = -0.13, P < 0.05) and multiple stepwise regression analysis showed bilirubin concentrations were independently associated with 24 h urinary microalbumin. In logistic regression analysis, bilirubin concentrations were significantly inversely associated with nephropathy. In addition, in stratified analysis, from the first to the fourth quartile group, increased bilirubin concentrations were associated with decreased prevalence of DN from 21.90% to 2.00%. High bilirubin concentrations are independently and negatively associated with albuminuria and the prevalence of DN in patients with T1DM.

Cytopathologic differential diagnosis of low-grade urothelial carcinoma and reactive urothelial proliferation in bladder washings: a logistic regression analysis.

PubMed

Cakir, Ebru; Kucuk, Ulku; Pala, Emel Ebru; Sezer, Ozlem; Ekin, Rahmi Gokhan; Cakmak, Ozgur

2017-05-01

Conventional cytomorphologic assessment is the first step to establish an accurate diagnosis in urinary cytology. In cytologic preparations, the separation of low-grade urothelial carcinoma (LGUC) from reactive urothelial proliferation (RUP) can be exceedingly difficult. The bladder washing cytologies of 32 LGUC and 29 RUP were reviewed. The cytologic slides were examined for the presence or absence of the 28 cytologic features. The cytologic criteria showing statistical significance in LGUC were increased numbers of monotonous single (non-umbrella) cells, three-dimensional cellular papillary clusters without fibrovascular cores, irregular bordered clusters, atypical single cells, irregular nuclear overlap, cytoplasmic homogeneity, increased N/C ratio, pleomorphism, nuclear border irregularity, nuclear eccentricity, elongated nuclei, and hyperchromasia (p ˂ 0.05), and the cytologic criteria showing statistical significance in RUP were inflammatory background, mixture of small and large urothelial cells, loose monolayer aggregates, and vacuolated cytoplasm (p ˂ 0.05). When these variables were subjected to a stepwise logistic regression analysis, four features were selected to distinguish LGUC from RUP: increased numbers of monotonous single (non-umbrella) cells, increased nuclear cytoplasmic ratio, hyperchromasia, and presence of small and large urothelial cells (p = 0.0001). By this logistic model of the 32 cases with proven LGUC, the stepwise logistic regression analysis correctly predicted 31 (96.9%) patients with this diagnosis, and of the 29 patients with RUP, the logistic model correctly predicted 26 (89.7%) patients as having this disease. There are several cytologic features to separate LGUC from RUP. Stepwise logistic regression analysis is a valuable tool for determining the most useful cytologic criteria to distinguish these entities. © 2017 APMIS. Published by John Wiley & Sons Ltd.

Is Susceptibility to Prenatal Methylmercury Exposure from Fish Consumption Non-Homogeneous? Tree-Structured Analysis for the Seychelles Child Development Study

PubMed Central

Huang, Li-Shan; Myers, Gary J.; Davidson, Philip W.; Cox, Christopher; Xiao, Fenyuan; Thurston, Sally W.; Cernichiari, Elsa; Shamlaye, Conrad F.; Sloane-Reeves, Jean; Georger, Lesley; Clarkson, Thomas W.

2007-01-01

Studies of the association between prenatal methylmercury exposure from maternal fish consumption during pregnancy and neurodevelopmental test scores in the Seychelles Child Development Study have found no consistent pattern of associations through age nine years. The analyses for the most recent nine-year data examined the population effects of prenatal exposure, but did not address the possibility of non-homogeneous susceptibility. This paper presents a regression tree approach: covariate effects are treated nonlinearly and non-additively and non-homogeneous effects of prenatal methylmercury exposure are permitted among the covariate clusters identified by the regression tree. The approach allows us to address whether children in the lower or higher ends of the developmental spectrum differ in susceptibility to subtle exposure effects. Of twenty-one endpoints available at age nine years, we chose the Weschler Full Scale IQ and its associated covariates to construct the regression tree. The prenatal mercury effect in each of the nine resulting clusters was assessed linearly and non-homogeneously. In addition we reanalyzed five other nine-year endpoints that in the linear analysis has a two-tailed p-value <0.2 for the effect of prenatal exposure. In this analysis, motor proficiency and activity level improved significantly with increasing MeHg for 53% of the children who had an average home environment. Motor proficiency significantly decreased with increasing prenatal MeHg exposure in 7% of the children whose home environment was below average. The regression tree results support previous analyses of outcomes in this cohort. However, this analysis raises the intriguing possibility that an effect may be non-homogeneous among children with different backgrounds and IQ levels. PMID:17942158

Is susceptibility to prenatal methylmercury exposure from fish consumption non-homogeneous? Tree-structured analysis for the Seychelles Child Development Study.

PubMed

Huang, Li-Shan; Myers, Gary J; Davidson, Philip W; Cox, Christopher; Xiao, Fenyuan; Thurston, Sally W; Cernichiari, Elsa; Shamlaye, Conrad F; Sloane-Reeves, Jean; Georger, Lesley; Clarkson, Thomas W

2007-11-01

Studies of the association between prenatal methylmercury exposure from maternal fish consumption during pregnancy and neurodevelopmental test scores in the Seychelles Child Development Study have found no consistent pattern of associations through age 9 years. The analyses for the most recent 9-year data examined the population effects of prenatal exposure, but did not address the possibility of non-homogeneous susceptibility. This paper presents a regression tree approach: covariate effects are treated non-linearly and non-additively and non-homogeneous effects of prenatal methylmercury exposure are permitted among the covariate clusters identified by the regression tree. The approach allows us to address whether children in the lower or higher ends of the developmental spectrum differ in susceptibility to subtle exposure effects. Of 21 endpoints available at age 9 years, we chose the Weschler Full Scale IQ and its associated covariates to construct the regression tree. The prenatal mercury effect in each of the nine resulting clusters was assessed linearly and non-homogeneously. In addition we reanalyzed five other 9-year endpoints that in the linear analysis had a two-tailed p-value <0.2 for the effect of prenatal exposure. In this analysis, motor proficiency and activity level improved significantly with increasing MeHg for 53% of the children who had an average home environment. Motor proficiency significantly decreased with increasing prenatal MeHg exposure in 7% of the children whose home environment was below average. The regression tree results support previous analyses of outcomes in this cohort. However, this analysis raises the intriguing possibility that an effect may be non-homogeneous among children with different backgrounds and IQ levels.

Subjective economic status, sex role attitudes, fertility, and mother's work.

PubMed

Moon, C

1987-07-01

Data were drawn from the General Social Survey conducted by the National Opinion Research Center (NORC) in 1985 to observe the effect of subjective economic status and sex role attitude on fertility and mother's work, controlling for major influential variables such as household resources, individual characteristics, and place of residence. A multiple regression method was used to examine factors affecting the employment status of currently married mothers. The study objective was to develop the household resources model by adding the subjective economic status, i.e., economic status as perceived by a mother, and to observe how a wife's work as a coping strategy varies with the current number of children and sex role attitudes, when controlling for other explanatory variables -- including the subjective economic status. The 274 study subjects were currently married women with 1 or more children and ranging in age from 18-55 years. The effect of age on women's employment was not "so" significant, i.e., there were conflicting findings on the curvilinear effect of age. The effect of wives' education was not significant at a 95% confidence level in all regression equations. Race was negatively correlated to the probability of married women. The effect of race on women's employment was not significant at .05 level for all regressions. Region had no effect on women's entry into gainful employment. The effect of current number of children was significant at a 95% confidence level before controlling for subjective economic status and sex role attitude, but its effect on women's employment was insignificant when 2 types of additional explanatory variables were introduced independently or together. The regression analysis revealed a neutral effect of husbands' occupational prestige on employment status. The observed regression coefficient revealed that the possibility of women's employment will increase by 2% when the annual family income from other sources decreases by $1000. The analysis provides evidence in support of the household resources model and Oppenheimer's economic squeezes model. The inclusion of sex role attitude in the regression model did not affect the magnitude of impact of subjective economic status on mother's employment. Financial status had a significant influence on women's working status. The influence of sex role attitude on mother's working was not significant at a 95% confidence level, but the deletion of subjective economic status variables did increase a confidence level of significance from 0.82 to 0.89, indicating the feasible interaction between sex role attitude and economic squeezes.

Application of Regression-Discontinuity Analysis in Pharmaceutical Health Services Research

PubMed Central

Zuckerman, Ilene H; Lee, Euni; Wutoh, Anthony K; Xue, Zhenyi; Stuart, Bruce

2006-01-01

Objective To demonstrate how a relatively underused design, regression-discontinuity (RD), can provide robust estimates of intervention effects when stronger designs are impossible to implement. Data Sources/Study Setting Administrative claims from a Mid-Atlantic state Medicaid program were used to evaluate the effectiveness of an educational drug utilization review intervention. Study Design Quasi-experimental design. Data Collection/Extraction Methods A drug utilization review study was conducted to evaluate a letter intervention to physicians treating Medicaid children with potentially excessive use of short-acting β2-agonist inhalers (SAB). The outcome measure is change in seasonally-adjusted SAB use 5 months pre- and postintervention. To determine if the intervention reduced monthly SAB utilization, results from an RD analysis are compared to findings from a pretest–posttest design using repeated-measure ANOVA. Principal Findings Both analyses indicated that the intervention significantly reduced SAB use among the high users. Average monthly SAB use declined by 0.9 canisters per month (p<.001) according to the repeated-measure ANOVA and by 0.2 canisters per month (p<.001) from RD analysis. Conclusions Regression-discontinuity design is a useful quasi-experimental methodology that has significant advantages in internal validity compared to other pre–post designs when assessing interventions in which subjects' assignment is based on cutoff scores for a critical variable. PMID:16584464

Femoral anteversion and tibial torsion only explain 25% of variance in regression analysis of foot progression angle in children with diplegic cerebral palsy

PubMed Central

2013-01-01

Background The relationship between torsional bony deformities and rotational gait parameters has not been sufficiently investigated. This study was to investigate the degree of contribution of torsional bony deformities to rotational gait parameters in patients with diplegic cerebral palsy (CP). Methods Thirty three legs from 33 consecutive ambulatory patients (average age 9.5 years, SD 6.9 years; 20 males and 13 females) with diplegic CP who underwent preoperative three dimensional gait analysis, foot radiographs, and computed tomography (CT) were included. Adjusted foot progression angle (FPA) was retrieved from gait analysis by correcting pelvic rotation from conventional FPA, which represented the rotational gait deviation of the lower extremity from the tip of the femoral head to the foot. Correlations between rotational gait parameters (FPA, adjusted FPA, average pelvic rotation, average hip rotation, and average knee rotation) and radiologic measurements (acetabular version, femoral anteversion, knee torsion, tibial torsion, and anteroposteriortalo-first metatarsal angle) were analyzed. Multiple regression analysis was performed to identify significant contributing radiographic measurements to adjusted FPA. Results Adjusted FPA was significantly correlated with FPA (r=0.837, p<0.001), contralateral FPA (r=0.492, p=0.004), pelvic rotation during gait (r=−0.489, p=0.004), knee rotation during gait (r=0.376, p=0.031), and femoral anteversion (r=0.350, p=0.046). In multiple regression analysis, femoral anteversion (p=0.026) and tibial torsion (p=0.034) were found to be the significant contributing structural deformities to the adjusted FPA (R2=0.247). Conclusions Femoral anteversion and tibial torsion were found to be the significant structural deformities that could affect adjusted FPA in patients with diplegic CP. Femoral anteversion and tibial torsion could explain only 24.7% of adjusted FPA. PMID:23767833

Ranibizumab alone or in combination with photodynamic therapy vs photodynamic therapy for polypoidal choroidal vasculopathy: a systematic review and Meta-analysis.

PubMed

Tang, Kai; Si, Jun-Kang; Guo, Da-Dong; Cui, Yan; Du, Yu-Xiang; Pan, Xue-Mei; Bi, Hong-Sheng

2015-01-01

To compare the efficacy of intravitreal ranibizumab (IVR) alone or in combination with photodynamic therapy (PDT) vs PDT in patients with symptomatic polypoidal choroidal vasculopathy (PCV). A systematic search of a wide range of databases (including PubMed, EMBASE, Cochrane Library and Web of Science) was searched to identify relevant studies. Both randomized controlled trials (RCTs) and non-RCT studies were included. Methodological quality of included literatures was evaluated according to the Newcastle-Ottawa Scale. RevMan 5.2.7 software was used to do the Meta-analysis. Three RCTs and 6 retrospective studies were included. The results showed that PDT monotherapy had a significantly higher proportion in patients who achieved complete regression of polyps than IVR monotherapy at months 3, 6, and 12 (All P≤0.01), respectively. However, IVR had a tendency to be more effective in improving vision on the basis of RCTs. The proportion of patients who gained complete regression of polyps revealed that there was no significant difference between the combination treatment and PDT monotherapy. The mean change of best-corrected visual acuity (BCVA) from baseline showed that the combination treatment had significant superiority in improving vision vs PDT monotherapy at months 3, 6 and 24 (All P<0.05), respectively. In the mean time, this comparison result was also significant at month 12 (P<0.01) after removal of a heterogeneous study. IVR has non-inferiority compare with PDT either in stabilizing or in improving vision, although it can hardly promote the regression of polyps. The combination treatment of PDT and IVR can exert a synergistic effect on regressing polyps and on maintaining or improving visual acuity. Thus, it can be the first-line therapy for PCV.

Ranibizumab alone or in combination with photodynamic therapy vs photodynamic therapy for polypoidal choroidal vasculopathy: a systematic review and Meta-analysis

PubMed Central

Tang, Kai; Si, Jun-Kang; Guo, Da-Dong; Cui, Yan; Du, Yu-Xiang; Pan, Xue-Mei; Bi, Hong-Sheng

2015-01-01

AIM To compare the efficacy of intravitreal ranibizumab (IVR) alone or in combination with photodynamic therapy (PDT) vs PDT in patients with symptomatic polypoidal choroidal vasculopathy (PCV). METHODS A systematic search of a wide range of databases (including PubMed, EMBASE, Cochrane Library and Web of Science) was searched to identify relevant studies. Both randomized controlled trials (RCTs) and non-RCT studies were included. Methodological quality of included literatures was evaluated according to the Newcastle-Ottawa Scale. RevMan 5.2.7 software was used to do the Meta-analysis. RESULTS Three RCTs and 6 retrospective studies were included. The results showed that PDT monotherapy had a significantly higher proportion in patients who achieved complete regression of polyps than IVR monotherapy at months 3, 6, and 12 (All P≤0.01), respectively. However, IVR had a tendency to be more effective in improving vision on the basis of RCTs. The proportion of patients who gained complete regression of polyps revealed that there was no significant difference between the combination treatment and PDT monotherapy. The mean change of best-corrected visual acuity (BCVA) from baseline showed that the combination treatment had significant superiority in improving vision vs PDT monotherapy at months 3, 6 and 24 (All P<0.05), respectively. In the mean time, this comparison result was also significant at month 12 (P<0.01) after removal of a heterogeneous study. CONCLUSION IVR has non-inferiority compare with PDT either in stabilizing or in improving vision, although it can hardly promote the regression of polyps. The combination treatment of PDT and IVR can exert a synergistic effect on regressing polyps and on maintaining or improving visual acuity. Thus, it can be the first-line therapy for PCV. PMID:26558226

Analysis of threats to research validity introduced by audio recording clinic visits: Selection bias, Hawthorne effect, both, or neither?

PubMed Central

Henry, Stephen G.; Jerant, Anthony; Iosif, Ana-Maria; Feldman, Mitchell D.; Cipri, Camille; Kravitz, Richard L.

2015-01-01

Objective To identify factors associated with participant consent to record visits; to estimate effects of recording on patient-clinician interactions Methods Secondary analysis of data from a randomized trial studying communication about depression; participants were asked for optional consent to audio record study visits. Multiple logistic regression was used to model likelihood of patient and clinician consent. Multivariable regression and propensity score analyses were used to estimate effects of audio recording on 6 dependent variables: discussion of depressive symptoms, preventive health, and depression diagnosis; depression treatment recommendations; visit length; visit difficulty. Results Of 867 visits involving 135 primary care clinicians, 39% were recorded. For clinicians, only working in academic settings (P=0.003) and having worked longer at their current practice (P=0.02) were associated with increased likelihood of consent. For patients, white race (P=0.002) and diabetes (P=0.03) were associated with increased likelihood of consent. Neither multivariable regression nor propensity score analyses revealed any significant effects of recording on the variables examined. Conclusion Few clinician or patient characteristics were significantly associated with consent. Audio recording had no significant effect on any dependent variables. Practice Implications Benefits of recording clinic visits likely outweigh the risks of bias in this setting. PMID:25837372

Quantitative analysis of binary polymorphs mixtures of fusidic acid by diffuse reflectance FTIR spectroscopy, diffuse reflectance FT-NIR spectroscopy, Raman spectroscopy and multivariate calibration.

PubMed

Guo, Canyong; Luo, Xuefang; Zhou, Xiaohua; Shi, Beijia; Wang, Juanjuan; Zhao, Jinqi; Zhang, Xiaoxia

2017-06-05

Vibrational spectroscopic techniques such as infrared, near-infrared and Raman spectroscopy have become popular in detecting and quantifying polymorphism of pharmaceutics since they are fast and non-destructive. This study assessed the ability of three vibrational spectroscopy combined with multivariate analysis to quantify a low-content undesired polymorph within a binary polymorphic mixture. Partial least squares (PLS) regression and support vector machine (SVM) regression were employed to build quantitative models. Fusidic acid, a steroidal antibiotic, was used as the model compound. It was found that PLS regression performed slightly better than SVM regression in all the three spectroscopic techniques. Root mean square errors of prediction (RMSEP) were ranging from 0.48% to 1.17% for diffuse reflectance FTIR spectroscopy and 1.60-1.93% for diffuse reflectance FT-NIR spectroscopy and 1.62-2.31% for Raman spectroscopy. The results indicate that diffuse reflectance FTIR spectroscopy offers significant advantages in providing accurate measurement of polymorphic content in the fusidic acid binary mixtures, while Raman spectroscopy is the least accurate technique for quantitative analysis of polymorphs. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimation of water table based on geomorphologic and geologic conditions using public database of geotechnical information over Japan

NASA Astrophysics Data System (ADS)

Koshigai, Masaru; Marui, Atsunao

Water table provides important information for the evaluation of groundwater resource. Recently, the estimation of water table in wide area is required for effective evaluation of groundwater resources. However, evaluation process is met with difficulties due to technical and economic constraints. Regression analysis for the prediction of groundwater levels based on geomorphologic and geologic conditions is considered as a reliable tool for the estimation of water table of wide area. Data of groundwater levels were extracted from the public database of geotechnical information. It was observed that changes in groundwater level depend on climate conditions. It was also observed and confirmed that there exist variations of groundwater levels according to geomorphologic and geologic conditions. The objective variable of the regression analysis was groundwater level. And the explanatory variables were elevation and the dummy variable consisting of group number. The constructed regression formula was significant according to the determination coefficients and analysis of the variance. Therefore, combining the regression formula and mesh map, the statistical method to estimate the water table based on geomorphologic and geologic condition for the whole country could be established.

Diesel engine exhaust and lung cancer risks - evaluation of the meta-analysis by Vermeulen et al. 2014.

PubMed

Morfeld, Peter; Spallek, Michael

2015-01-01

Vermeulen et al. 2014 published a meta-regression analysis of three relevant epidemiological US studies (Steenland et al. 1998, Garshick et al. 2012, Silverman et al. 2012) that estimated the association between occupational diesel engine exhaust (DEE) exposure and lung cancer mortality. The DEE exposure was measured as cumulative exposure to estimated respirable elemental carbon in μg/m(3)-years. Vermeulen et al. 2014 found a statistically significant dose-response association and described elevated lung cancer risks even at very low exposures. We performed an extended re-analysis using different modelling approaches (fixed and random effects regression analyses, Greenland/Longnecker method) and explored the impact of varying input data (modified coefficients of Garshick et al. 2012, results from Crump et al. 2015 replacing Silverman et al. 2012, modified analysis of Moehner et al. 2013). We reproduced the individual and main meta-analytical results of Vermeulen et al. 2014. However, our analysis demonstrated a heterogeneity of the baseline relative risk levels between the three studies. This heterogeneity was reduced after the coefficients of Garshick et al. 2012 were modified while the dose coefficient dropped by an order of magnitude for this study and was far from being significant (P = 0.6). A (non-significant) threshold estimate for the cumulative DEE exposure was found at 150 μg/m(3)-years when extending the meta-analyses of the three studies by hockey-stick regression modelling (including the modified coefficients for Garshick et al. 2012). The data used by Vermeulen and colleagues led to the highest relative risk estimate across all sensitivity analyses performed. The lowest relative risk estimate was found after exclusion of the explorative study by Steenland et al. 1998 in a meta-regression analysis of Garshick et al. 2012 (modified), Silverman et al. 2012 (modified according to Crump et al. 2015) and Möhner et al. 2013. The meta-coefficient was estimated to be about 10-20 % of the main effect estimate in Vermeulen et al. 2014 in this analysis. The findings of Vermeulen et al. 2014 should not be used without reservations in any risk assessments. This is particularly true for the low end of the exposure scale.

Cluster Analysis of Campylobacter jejuni Genotypes Isolated from Small and Medium-Sized Mammalian Wildlife and Bovine Livestock from Ontario Farms.

PubMed

Viswanathan, M; Pearl, D L; Taboada, E N; Parmley, E J; Mutschall, S K; Jardine, C M

2017-05-01

Using data collected from a cross-sectional study of 25 farms (eight beef, eight swine and nine dairy) in 2010, we assessed clustering of molecular subtypes of C. jejuni based on a Campylobacter-specific 40 gene comparative genomic fingerprinting assay (CGF40) subtypes, using unweighted pair-group method with arithmetic mean (UPGMA) analysis, and multiple correspondence analysis. Exact logistic regression was used to determine which genes differentiate wildlife and livestock subtypes in our study population. A total of 33 bovine livestock (17 beef and 16 dairy), 26 wildlife (20 raccoon (Procyon lotor), five skunk (Mephitis mephitis) and one mouse (Peromyscus spp.) C. jejuni isolates were subtyped using CGF40. Dendrogram analysis, based on UPGMA, showed distinct branches separating bovine livestock and mammalian wildlife isolates. Furthermore, two-dimensional multiple correspondence analysis was highly concordant with dendrogram analysis showing clear differentiation between livestock and wildlife CGF40 subtypes. Based on multilevel logistic regression models with a random intercept for farm of origin, we found that isolates in general, and raccoons more specifically, were significantly more likely to be part of the wildlife branch. Exact logistic regression conducted gene by gene revealed 15 genes that were predictive of whether an isolate was of wildlife or bovine livestock isolate origin. Both multiple correspondence analysis and exact logistic regression revealed that in most cases, the presence of a particular gene (13 of 15) was associated with an isolate being of livestock rather than wildlife origin. In conclusion, the evidence gained from dendrogram analysis, multiple correspondence analysis and exact logistic regression indicates that mammalian wildlife carry CGF40 subtypes of C. jejuni distinct from those carried by bovine livestock. Future studies focused on source attribution of C. jejuni in human infections will help determine whether wildlife transmit Campylobacter jejuni directly to humans. © 2016 Blackwell Verlag GmbH.

Time Series Analysis and Forecasting of Wastewater Inflow into Bandar Tun Razak Sewage Treatment Plant in Selangor, Malaysia

NASA Astrophysics Data System (ADS)

Abunama, Taher; Othman, Faridah

2017-06-01

Analysing the fluctuations of wastewater inflow rates in sewage treatment plants (STPs) is essential to guarantee a sufficient treatment of wastewater before discharging it to the environment. The main objectives of this study are to statistically analyze and forecast the wastewater inflow rates into the Bandar Tun Razak STP in Kuala Lumpur, Malaysia. A time series analysis of three years’ weekly influent data (156weeks) has been conducted using the Auto-Regressive Integrated Moving Average (ARIMA) model. Various combinations of ARIMA orders (p, d, q) have been tried to select the most fitted model, which was utilized to forecast the wastewater inflow rates. The linear regression analysis was applied to testify the correlation between the observed and predicted influents. ARIMA (3, 1, 3) model was selected with the highest significance R-square and lowest normalized Bayesian Information Criterion (BIC) value, and accordingly the wastewater inflow rates were forecasted to additional 52weeks. The linear regression analysis between the observed and predicted values of the wastewater inflow rates showed a positive linear correlation with a coefficient of 0.831.

Principal component regression analysis with SPSS.

PubMed

Liu, R X; Kuang, J; Gong, Q; Hou, X L

2003-06-01

The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

A retrospective study: Multivariate logistic regression analysis of the outcomes after pressure sores reconstruction with fasciocutaneous, myocutaneous, and perforator flaps.

PubMed

Chiu, Yu-Jen; Liao, Wen-Chieh; Wang, Tien-Hsiang; Shih, Yu-Chung; Ma, Hsu; Lin, Chih-Hsun; Wu, Szu-Hsien; Perng, Cherng-Kang

2017-08-01

Despite significant advances in medical care and surgical techniques, pressure sore reconstruction is still prone to elevated rates of complication and recurrence. We conducted a retrospective study to investigate not only complication and recurrence rates following pressure sore reconstruction but also preoperative risk stratification. This study included 181 ulcers underwent flap operations between January 2002 and December 2013 were included in the study. We performed a multivariable logistic regression model, which offers a regression-based method accounting for the within-patient correlation of the success or failure of each flap. The overall complication and recurrence rates for all flaps were 46.4% and 16.0%, respectively, with a mean follow-up period of 55.4 ± 38.0 months. No statistically significant differences of complication and recurrence rates were observed among three different reconstruction methods. In subsequent analysis, albumin ≤3.0 g/dl and paraplegia were significantly associated with higher postoperative complication. The anatomic factor, ischial wound location, significantly trended toward the development of ulcer recurrence. In the fasciocutaneous group, paraplegia had significant correlation to higher complication and recurrence rates. In the musculocutaneous flap group, variables had no significant correlation to complication and recurrence rates. In the free-style perforator group, ischial wound location and malnourished status correlated with significantly higher complication rates; ischial wound location also correlated with significantly higher recurrence rate. Ultimately, our review of a noteworthy cohort with lengthy follow-up helped identify and confirm certain risk factors that can facilitate a more informed and thoughtful pre- and postoperative decision-making process for patients with pressure ulcers. Copyright © 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Evaluation of drainage-area ratio method used to estimate streamflow for the Red River of the North Basin, North Dakota and Minnesota

USGS Publications Warehouse

Emerson, Douglas G.; Vecchia, Aldo V.; Dahl, Ann L.

2005-01-01

The drainage-area ratio method commonly is used to estimate streamflow for sites where no streamflow data were collected. To evaluate the validity of the drainage-area ratio method and to determine if an improved method could be developed to estimate streamflow, a multiple-regression technique was used to determine if drainage area, main channel slope, and precipitation were significant variables for estimating streamflow in the Red River of the North Basin. A separate regression analysis was performed for streamflow for each of three seasons-- winter, spring, and summer. Drainage area and summer precipitation were the most significant variables. However, the regression equations generally overestimated streamflows for North Dakota stations and underestimated streamflows for Minnesota stations. To correct the bias in the residuals for the two groups of stations, indicator variables were included to allow both the intercept and the coefficient for the logarithm of drainage area to depend on the group. Drainage area was the only significant variable in the revised regression equations. The exponents for the drainage-area ratio were 0.85 for the winter season, 0.91 for the spring season, and 1.02 for the summer season.

Identification of Key Beliefs Explaining Male Circumcision Motivation Among Adolescent Boys in Zimbabwe: Targets for Behavior Change Communication.

PubMed

Kasprzyk, Danuta; Tshimanga, Mufuta; Hamilton, Deven T; Gorn, Gerald J; Montaño, Daniel E

2018-02-01

Male circumcision (MC) significantly reduces HIV acquisition among men, leading WHO/UNAIDS to recommend high HIV and low MC prevalence countries circumcise 80% of adolescents and men age 15-49. Despite significant investment to increase MC capacity only 27% of the goal has been achieved in Zimbabwe. To increase adoption, research to create evidence-based messages is greatly needed. The Integrated Behavioral Model (IBM) was used to investigate factors affecting MC motivation among adolescents. Based on qualitative elicitation study results a survey was designed and administered to a representative sample of 802 adolescent boys aged 13-17 in two urban and two rural areas in Zimbabwe. Multiple regression analysis found all six IBM constructs (2 attitude, 2 social influence, 2 personal agency) significantly explained MC intention (R 2  = 0.55). Stepwise regression analysis of beliefs underlying each IBM belief-based construct found 9 behavioral, 6 injunctive norm, 2 descriptive norm, 5 efficacy, and 8 control beliefs significantly explained MC intention. A final stepwise regression of all the significant IBM construct beliefs identified 12 key beliefs best explaining intention. Similar analyses were carried out with subgroups of adolescents by urban-rural and age. Different sets of behavioral, normative, efficacy, and control beliefs were significant for each sub-group. This study demonstrates the application of theory-driven research to identify evidence-based targets for the design of effective MC messages for interventions to increase adolescents' motivation. Incorporating these findings into communication campaigns is likely to improve demand for MC.

Strengths use as a secret of happiness: Another dimension of visually impaired individuals' psychological state.

PubMed

Matsuguma, Shinichiro; Kawashima, Motoko; Negishi, Kazuno; Sano, Fumiya; Mimura, Masaru; Tsubota, Kazuo

2018-01-01

It is well recognized that visual impairments (VI) worsen individuals' mental condition. However, little is known about the positive aspects including subjective happiness, positive emotions, and strengths. Therefore, the purpose of this study was to investigate the positive aspects of persons with VI including their subjective happiness, positive emotions, and strengths use. Positive aspects of persons with VI were measured using the Subjective Happiness Scale (SHS), the Scale of Positive and Negative Experience-Balance (SPANE-B), and the Strengths Use Scale (SUS). A cross-sectional analysis was utilized to examine personal information in a Tokyo sample (N = 44). We used a simple regression analysis and found significant relationships between the SHS or SPANE-B and SUS; on the contrary, VI-related variables were not correlated with them. A multiple regression analysis confirmed that SUS was a significant factor associated with both the SHS and SPANE-B. Strengths use might be a possible protective factor from the negative effects of VI.

Experimental investigation of fuel regression rate in a HTPB based lab-scale hybrid rocket motor

NASA Astrophysics Data System (ADS)

Li, Xintian; Tian, Hui; Yu, Nanjia; Cai, Guobiao

2014-12-01

The fuel regression rate is an important parameter in the design process of the hybrid rocket motor. Additives in the solid fuel may have influences on the fuel regression rate, which will affect the internal ballistics of the motor. A series of firing experiments have been conducted on lab-scale hybrid rocket motors with 98% hydrogen peroxide (H2O2) oxidizer and hydroxyl terminated polybutadiene (HTPB) based fuels in this paper. An innovative fuel regression rate analysis method is established to diminish the errors caused by start and tailing stages in a short time firing test. The effects of the metal Mg, Al, aromatic hydrocarbon anthracene (C14H10), and carbon black (C) on the fuel regression rate are investigated. The fuel regression rate formulas of different fuel components are fitted according to the experiment data. The results indicate that the influence of C14H10 on the fuel regression rate of HTPB is not evident. However, the metal additives in the HTPB fuel can increase the fuel regression rate significantly.

Drusen regression is associated with local changes in fundus autofluorescence in intermediate age-related macular degeneration.

PubMed

Toy, Brian C; Krishnadev, Nupura; Indaram, Maanasa; Cunningham, Denise; Cukras, Catherine A; Chew, Emily Y; Wong, Wai T

2013-09-01

To investigate the association of spontaneous drusen regression in intermediate age-related macular degeneration (AMD) with changes on fundus photography and fundus autofluorescence (FAF) imaging. Prospective observational case series. Fundus images from 58 eyes (in 58 patients) with intermediate AMD and large drusen were assessed over 2 years for areas of drusen regression that exceeded the area of circle C1 (diameter 125 μm; Age-Related Eye Disease Study grading protocol). Manual segmentation and computer-based image analysis were used to detect and delineate areas of drusen regression. Delineated regions were graded as to their appearance on fundus photographs and FAF images, and changes in FAF signal were graded manually and quantitated using automated image analysis. Drusen regression was detected in approximately half of study eyes using manual (48%) and computer-assisted (50%) techniques. At year-2, the clinical appearance of areas of drusen regression on fundus photography was mostly unremarkable, with a majority of eyes (71%) demonstrating no detectable clinical abnormalities, and the remainder (29%) showing minor pigmentary changes. However, drusen regression areas were associated with local changes in FAF that were significantly more prominent than changes on fundus photography. A majority of eyes (64%-66%) demonstrated a predominant decrease in overall FAF signal, while 14%-21% of eyes demonstrated a predominant increase in overall FAF signal. FAF imaging demonstrated that drusen regression in intermediate AMD was often accompanied by changes in local autofluorescence signal. Drusen regression may be associated with concurrent structural and physiologic changes in the outer retina. Published by Elsevier Inc.

An investigation of correlation between pilot scanning behavior and workload using stepwise regression analysis

NASA Technical Reports Server (NTRS)

Waller, M. C.

1976-01-01

An electro-optical device called an oculometer which tracks a subject's lookpoint as a time function has been used to collect data in a real-time simulation study of instrument landing system (ILS) approaches. The data describing the scanning behavior of a pilot during the instrument approaches have been analyzed by use of a stepwise regression analysis technique. A statistically significant correlation between pilot workload, as indicated by pilot ratings, and scanning behavior has been established. In addition, it was demonstrated that parameters derived from the scanning behavior data can be combined in a mathematical equation to provide a good representation of pilot workload.

Methods for estimating annual exceedance probability discharges for streams in Arkansas, based on data through water year 2013

USGS Publications Warehouse

Wagner, Daniel M.; Krieger, Joshua D.; Veilleux, Andrea G.

2016-08-04

In 2013, the U.S. Geological Survey initiated a study to update regional skew, annual exceedance probability discharges, and regional regression equations used to estimate annual exceedance probability discharges for ungaged locations on streams in the study area with the use of recent geospatial data, new analytical methods, and available annual peak-discharge data through the 2013 water year. An analysis of regional skew using Bayesian weighted least-squares/Bayesian generalized-least squares regression was performed for Arkansas, Louisiana, and parts of Missouri and Oklahoma. The newly developed constant regional skew of -0.17 was used in the computation of annual exceedance probability discharges for 281 streamgages used in the regional regression analysis. Based on analysis of covariance, four flood regions were identified for use in the generation of regional regression models. Thirty-nine basin characteristics were considered as potential explanatory variables, and ordinary least-squares regression techniques were used to determine the optimum combinations of basin characteristics for each of the four regions. Basin characteristics in candidate models were evaluated based on multicollinearity with other basin characteristics (variance inflation factor < 2.5) and statistical significance at the 95-percent confidence level (p ≤ 0.05). Generalized least-squares regression was used to develop the final regression models for each flood region. Average standard errors of prediction of the generalized least-squares models ranged from 32.76 to 59.53 percent, with the largest range in flood region D. Pseudo coefficients of determination of the generalized least-squares models ranged from 90.29 to 97.28 percent, with the largest range also in flood region D. The regional regression equations apply only to locations on streams in Arkansas where annual peak discharges are not substantially affected by regulation, diversion, channelization, backwater, or urbanization. The applicability and accuracy of the regional regression equations depend on the basin characteristics measured for an ungaged location on a stream being within range of those used to develop the equations.

Improving Students' Self-Efficacy in Strategic Management: The Relative Impact of Cases and Simulations.

ERIC Educational Resources Information Center

Tompson, George H.; Dass, Parshotam

2000-01-01

Investigates the relative contribution of computer simulations and case studies for improving undergraduate students' self-efficacy in strategic management courses. Results of pre-and post-test data, regression analysis, and analysis of variance show that simulations result in significantly higher improvement in self-efficacy than case studies.…

The Partitioning of Variance Habits of Correlational and Experimental Psychologists: The Two Disciplines of Scientific Psychology Revisited

ERIC Educational Resources Information Center

Krus, David J.; Krus, Patricia H.

1978-01-01

The conceptual differences between coded regression analysis and traditional analysis of variance are discussed. Also, a modification of several SPSS routines is proposed which allows for direct interpretation of ANOVA and ANCOVA results in a form stressing the strength and significance of scrutinized relationships. (Author)

Explorative spatial analysis of traffic accident statistics and road mortality among the provinces of Turkey.

PubMed

Erdogan, Saffet

2009-10-01

The aim of the study is to describe the inter-province differences in traffic accidents and mortality on roads of Turkey. Two different risk indicators were used to evaluate the road safety performance of the provinces in Turkey. These indicators are the ratios between the number of persons killed in road traffic accidents (1) and the number of accidents (2) (nominators) and their exposure to traffic risk (denominator). Population and the number of registered motor vehicles in the provinces were used as denominators individually. Spatial analyses were performed to the mean annual rate of deaths and to the number of fatal accidents that were calculated for the period of 2001-2006. Empirical Bayes smoothing was used to remove background noise from the raw death and accident rates because of the sparsely populated provinces and small number of accident and death rates of provinces. Global and local spatial autocorrelation analyses were performed to show whether the provinces with high rates of deaths-accidents show clustering or are located closer by chance. The spatial distribution of provinces with high rates of deaths and accidents was nonrandom and detected as clustered with significance of P<0.05 with spatial autocorrelation analyses. Regions with high concentration of fatal accidents and deaths were located in the provinces that contain the roads connecting the Istanbul, Ankara, and Antalya provinces. Accident and death rates were also modeled with some independent variables such as number of motor vehicles, length of roads, and so forth using geographically weighted regression analysis with forward step-wise elimination. The level of statistical significance was taken as P<0.05. Large differences were found between the rates of deaths and accidents according to denominators in the provinces. The geographically weighted regression analyses did significantly better predictions for both accident rates and death rates than did ordinary least regressions, as indicated by adjusted R(2) values. Geographically weighted regression provided values of 0.89-0.99 adjusted R(2) for death and accident rates, compared with 0.88-0.95, respectively, by ordinary least regressions. Geographically weighted regression has the potential to reveal local patterns in the spatial distribution of rates, which would be ignored by the ordinary least regression approach. The application of spatial analysis and modeling of accident statistics and death rates at provincial level in Turkey will help to identification of provinces with outstandingly high accident and death rates. This could help more efficient road safety management in Turkey.

Comparative Efficacy of Tongxinluo Capsule and Beta-Blockers in Treating Angina Pectoris: Meta-Analysis of Randomized Controlled Trials.

PubMed

Jia, Yongliang; Leung, Siu-wai

2015-11-01

There have been no systematic reviews, let alone meta-analyses, of randomized controlled trials (RCTs) comparing tongxinluo capsule (TXL) and beta-blockers in treating angina pectoris. This study aimed to evaluate the efficacy of TXL and beta-blockers in treating angina pectoris by a meta-analysis of eligible RCTs. The RCTs comparing TXL with beta-blockers (including metoprolol) in treating angina pectoris were searched and retrieved from databases including PubMed, Chinese National Knowledge Infrastructure, and WanFang Data. Eligible RCTs were selected according to prespecified criteria. Meta-analysis was performed on the odds ratios (OR) of symptomatic and electrocardiographic (ECG) improvements after treatment. Subgroup analysis, sensitivity analysis, meta-regression, and publication biases analysis were conducted to evaluate the robustness of the results. Seventy-three RCTs published between 2000 and 2014 with 7424 participants were eligible. Overall ORs comparing TXL with beta-blockers were 3.40 (95% confidence interval [CI], 2.97-3.89; p<0.0001) for symptomatic improvement and 2.63 (95% CI, 2.29-3.02; p<0.0001) for ECG improvement. Subgroup analysis and sensitivity analysis found no statistically significant dependence of overall ORs on specific study characteristics except efficacy criteria. Meta-regression found no significant except sample sizes for data on symptomatic improvement. Publication biases were statistically significant. TXL seems to be more effective than beta-blockers in treating angina pectoris, on the basis of the eligible RCTs. Further RCTs are warranted to reduce publication bias and verify efficacy.

Women, Physical Activity, and Quality of Life: Self-concept as a Mediator.

PubMed

Gonzalo Silvestre, Tamara; Ubillos Landa, Silvia

2016-02-22

The objectives of this research are: (a) analyze the incremental validity of physical activity's (PA) influence on perceived quality of life (PQL); (b) determine if PA's predictive power is mediated by self-concept; and (c) study if results vary according to a unidimensional or multidimensional approach to self-concept measurement. The sample comprised 160 women from Burgos, Spain aged 18 to 45 years old. Non-probability sampling was used. Two three-step hierarchical regression analyses were applied to forecast PQL. The hedonic quality-of-life indicators, self-concept, self-esteem, and PA were included as independent variables. The first regression analysis included global self-concept as predictor variable, while the second included its five dimensions. Two mediation analyses were conducted to see if PA's ability to predict PQL was mediated by global and physical self-concept. Results from the first regression shows that self-concept, satisfaction with life, and PA were significant predictors. PA slightly but significantly increased explained variance in PQL (2.1%). In the second regression, substituting global self-concept with its five constituent factors, only the physical dimension and satisfaction with life predicted PQL, while PA ceased to be a significant predictor. Mediation analysis revealed that only physical self-concept mediates the relationship between PA and PQL (z = 1.97, p < .050), and not global self-concept. Physical self-concept was the strongest predictor and approximately 32.45 % of PA's effect on PQL was mediated by it. This study's findings support a multidimensional view of self-concept, and represent a more accurate image of the relationship between PQL, PA, and self-concept.

Serum Irisin Predicts Mortality Risk in Acute Heart Failure Patients.

PubMed

Shen, Shutong; Gao, Rongrong; Bei, Yihua; Li, Jin; Zhang, Haifeng; Zhou, Yanli; Yao, Wenming; Xu, Dongjie; Zhou, Fang; Jin, Mengchao; Wei, Siqi; Wang, Kai; Xu, Xuejuan; Li, Yongqin; Xiao, Junjie; Li, Xinli

2017-01-01

Irisin is a peptide hormone cleaved from a plasma membrane protein fibronectin type III domain containing protein 5 (FNDC5). Emerging studies have indicated association between serum irisin and many major chronic diseases including cardiovascular diseases. However, the role of serum irisin as a predictor for mortality risk in acute heart failure (AHF) patients is not clear. AHF patients were enrolled and serum was collected at the admission and all patients were followed up for 1 year. Enzyme-linked immunosorbent assay was used to measure serum irisin levels. To explore predictors for AHF mortality, the univariate and multivariate logistic regression analysis, and receiver-operator characteristic (ROC) curve analysis were used. To determine the role of serum irisin levels in predicting survival, Kaplan-Meier survival analysis was used. In this study, 161 AHF patients were enrolled and serum irisin level was found to be significantly higher in patients deceased in 1-year follow-up. The univariate logistic regression analysis identified 18 variables associated with all-cause mortality in AHF patients, while the multivariate logistic regression analysis identified 2 variables namely blood urea nitrogen and serum irisin. ROC curve analysis indicated that blood urea nitrogen and the most commonly used biomarker, NT-pro-BNP, displayed poor prognostic value for AHF (AUCs ≤ 0.700) compared to serum irisin (AUC = 0.753). Kaplan-Meier survival analysis demonstrated that AHF patients with higher serum irisin had significantly higher mortality (P<0.001). Collectively, our study identified serum irisin as a predictive biomarker for 1-year all-cause mortality in AHF patients though large multicenter studies are highly needed. © 2017 The Author(s). Published by S. Karger AG, Basel.

A quantitative study of factors influencing quality of life in rural Mexican women diagnosed with HIV.

PubMed

Holtz, Carol; Sowell, Richard; VanBrackle, Lewis; Velasquez, Gabriela; Hernandez-Alonso, Virginia

2014-01-01

This quantitative study explored the level of Quality of Life (QoL) in indigenous Mexican women and identified psychosocial factors that significantly influenced their QoL, using face-to-face interviews with 101 women accessing care in an HIV clinic in Oaxaca, Mexico. Variables included demographic characteristics, levels of depression, coping style, family functioning, HIV-related beliefs, and QoL. Descriptive statistics were used to analyze participant characteristics, and women's scores on data collection instruments. Pearson's R correlational statistics were used to determine the level of significance between study variables. Multiple regression analysis examined all variables that were significantly related to QoL. Pearson's correlational analysis of relationships between Spirituality, Educating Self about HIV, Family Functioning, Emotional Support, Physical Care, and Staying Positive demonstrated positive correlation to QoL. Stigma, depression, and avoidance coping were significantly and negatively associated with QoL. The final regression model indicated that depression and avoidance coping were the best predictor variables for QoL. Copyright © 2014 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

Diagnostic accuracy of the aspartate aminotransferase-to-platelet ratio index for the prediction of hepatitis B-related fibrosis: a leading meta-analysis

PubMed Central

2012-01-01

Background The aspartate aminotransferase-to-platelet ratio index (APRI), a tool with limited expense and widespread availability, is a promising noninvasive alternative to liver biopsy for detecting hepatic fibrosis. The objective of this study was to systematically review the performance of the APRI in predicting significant fibrosis and cirrhosis in hepatitis B-related fibrosis. Methods Areas under summary receiver operating characteristic curves (AUROC), sensitivity and specificity were used to examine the accuracy of the APRI for the diagnosis of hepatitis B-related significant fibrosis and cirrhosis. Heterogeneity was explored using meta-regression. Results Nine studies were included in this meta-analysis (n = 1,798). Prevalence of significant fibrosis and cirrhosis were 53.1% and 13.5%, respectively. The summary AUCs of the APRI for significant fibrosis and cirrhosis were 0.79 and 0.75, respectively. For significant fibrosis, an APRI threshold of 0.5 was 84% sensitive and 41% specific. At the cutoff of 1.5, the summary sensitivity and specificity were 49% and 84%, respectively. For cirrhosis, an APRI threshold of 1.0-1.5 was 54% sensitive and 78% specific. At the cutoff of 2.0, the summary sensitivity and specificity were 28% and 87%, respectively. Meta-regression analysis indicated that the APRI accuracy for both significant fibrosis and cirrhosis was affected by histological classification systems, but not influenced by the interval between Biopsy & APRI or blind biopsy. Conclusion Our meta-analysis suggests that APRI show limited value in identifying hepatitis B-related significant fibrosis and cirrhosis. PMID:22333407

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis

PubMed Central

Rahman, Md. Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D. W.; Labrique, Alain B.; Rashid, Mahbubur; Christian, Parul; West, Keith P.

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 − -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset. PMID:29261760

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis.

PubMed

Kabir, Alamgir; Rahman, Md Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D W; Labrique, Alain B; Rashid, Mahbubur; Christian, Parul; West, Keith P

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 - -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset.

Regression Analysis by Example. 5th Edition

ERIC Educational Resources Information Center

Chatterjee, Samprit; Hadi, Ali S.

2012-01-01

Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…

[Logistic regression model of noninvasive prediction for portal hypertensive gastropathy in patients with hepatitis B associated cirrhosis].

PubMed

Wang, Qingliang; Li, Xiaojie; Hu, Kunpeng; Zhao, Kun; Yang, Peisheng; Liu, Bo

2015-05-12

To explore the risk factors of portal hypertensive gastropathy (PHG) in patients with hepatitis B associated cirrhosis and establish a Logistic regression model of noninvasive prediction. The clinical data of 234 hospitalized patients with hepatitis B associated cirrhosis from March 2012 to March 2014 were analyzed retrospectively. The dependent variable was the occurrence of PHG while the independent variables were screened by binary Logistic analysis. Multivariate Logistic regression was used for further analysis of significant noninvasive independent variables. Logistic regression model was established and odds ratio was calculated for each factor. The accuracy, sensitivity and specificity of model were evaluated by the curve of receiver operating characteristic (ROC). According to univariate Logistic regression, the risk factors included hepatic dysfunction, albumin (ALB), bilirubin (TB), prothrombin time (PT), platelet (PLT), white blood cell (WBC), portal vein diameter, spleen index, splenic vein diameter, diameter ratio, PLT to spleen volume ratio, esophageal varices (EV) and gastric varices (GV). Multivariate analysis showed that hepatic dysfunction (X1), TB (X2), PLT (X3) and splenic vein diameter (X4) were the major occurring factors for PHG. The established regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4. The accuracy of model for PHG was 79.1% with a sensitivity of 77.2% and a specificity of 80.8%. Hepatic dysfunction, TB, PLT and splenic vein diameter are risk factors for PHG and the noninvasive predicted Logistic regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4.

Comparison of energy expenditure to walk or run a mile in adult normal weight and overweight men and women.

PubMed

Loftin, Mark; Waddell, Dwight E; Robinson, James H; Owens, Scott G

2010-10-01

We compared the energy expenditure to walk or run a mile in adult normal weight walkers (NWW), overweight walkers (OW), and marathon runners (MR). The sample consisted of 19 NWW, 11 OW, and 20 MR adults. Energy expenditure was measured at preferred walking speed (NWW and OW) and running speed of a recently completed marathon. Body composition was assessed via dual-energy x-ray absorptiometry. Analysis of variance was used to compare groups with the Scheffe's procedure used for post hoc analysis. Multiple regression analysis was used to predict energy expenditure. Results that indicated OW exhibited significantly higher (p < 0.05) mass and fat weight than NWW or MR. Similar values were found between NWW and MR. Absolute energy expenditure to walk or run a mile was similar between groups (NWW 93.9 ± 15.0, OW 98.4 ± 29.9, MR 99.3 ± 10.8 kcal); however, significant differences were noted when energy expenditure was expressed relative to mass (MR > NWW > OW). When energy expenditure was expressed per kilogram of fat-free mass, similar values were found across groups. Multiple regression analysis yielded mass and gender as significant predictors of energy expenditure (R = 0.795, SEE = 10.9 kcal). We suggest that walking is an excellent physical activity for energy expenditure in overweight individuals that are capable of walking without predisposed conditions such as osteoarthritis or cardiovascular risk factors. Moreover, from a practical perspective, our regression equation (kcal = mass (kg) × 0.789 - gender (men = 1, women = 2) × 7.634 + 51.109) allows for the prediction of energy expenditure for a given distance (mile) rather than predicting energy expenditure for a given time (minutes).

Chordee and Penile Shortening Rather Than Voiding Function Are Associated With Patient Dissatisfaction After Urethroplasty.

PubMed

Maciejewski, Conrad C; Haines, Trevor; Rourke, Keith F

2017-05-01

To identify factors that predict patient satisfaction after urethroplasty by prospectively examining patient-reported quality of life scores using 3 validated instruments. A 3-part prospective survey consisting of the International Prostate Symptom Score (IPSS), the International Index of Erectile Function (IIEF) score, and a urethroplasty quality of life survey was completed by patients who underwent urethroplasty preoperatively and at 6 months postoperatively. The quality of life score included questions on genitourinary pain, urinary tract infection (UTI), postvoid dribbling, chordee, shortening, overall satisfaction, and overall health. Data were analyzed using descriptive statistics, paired t test, univariate and multivariate logistic regression analyses, and Wilcoxon signed-rank analysis. Patients were enrolled in the study from February 2011 to December 2014, and a total of 94 patients who underwent a total of 102 urethroplasties completed the study. Patients reported statistically significant improvements in IPSS (P < .001). Ordinal linear regression analysis revealed no association between age, IPSS, or IIEF score and patient satisfaction. Wilcoxon signed-rank analysis revealed significant improvements in pain scores (P = .02), UTI (P < .001), perceived overall health (P = .01), and satisfaction (P < .001). Univariate logistic regression identified a length >4 cm and the absence of UTI, pain, shortening, and chordee as predictors of patient satisfaction. Multivariate analysis of quality of life domain scores identified absence of shortening and absence of chordee as independent predictors of patient satisfaction following urethroplasty (P < .01). Patient voiding function and quality of life improve significantly following urethroplasty, but improvement in voiding function is not associated with patient satisfaction. Chordee status and perceived penile shortening impact patient satisfaction, and should be included in patient-reported outcome measures. Copyright © 2017 Elsevier Inc. All rights reserved.

Collaborative Chronic Care Models for Mental Health Conditions: Cumulative Meta-Analysis and Meta-Regression to Guide Future Research and Implementation

PubMed Central

Grogan-Kaylor, Andrew; Perron, Brian E.; Kilbourne, Amy M.; Woltmann, Emily; Bauer, Mark S.

2013-01-01

Objective Prior meta-analysis indicates that collaborative chronic care models (CCMs) improve mental and physical health outcomes for individuals with mental disorders. This study aimed to investigate the stability of evidence over time and identify patient and intervention factors associated with CCM effects in order to facilitate implementation and sustainability of CCMs in clinical practice. Method We reviewed 53 CCM trials that analyzed depression, mental quality of life (QOL), or physical QOL outcomes. Cumulative meta-analysis and meta-regression were supplemented by descriptive investigations across and within trials. Results Most trials targeted depression in the primary care setting, and cumulative meta-analysis indicated that effect sizes favoring CCM quickly achieved significance for depression outcomes, and more recently achieved significance for mental and physical QOL. Four of six CCM elements (patient self-management support, clinical information systems, system redesign, and provider decision support) were common among reviewed trials, while two elements (healthcare organization support and linkages to community resources) were rare. No single CCM element was statistically associated with the success of the model. Similarly, meta-regression did not identify specific factors associated with CCM effectiveness. Nonetheless, results within individual trials suggest that increased illness severity predicts CCM outcomes. Conclusions Significant CCM trials have been derived primarily from four original CCM elements. Nonetheless, implementing and sustaining this established model will require healthcare organization support. While CCMs have typically been tested as population-based interventions, evidence supports stepped care application to more severely ill individuals. Future priorities include developing implementation strategies to support adoption and sustainability of the model in clinical settings while maximizing fit of this multi-component framework to local contextual factors. PMID:23938600

Regression modeling plan for 29 biochemical indicators of diet and nutrition measured in NHANES 2003-2006.

PubMed

Sternberg, Maya R; Schleicher, Rosemary L; Pfeiffer, Christine M

2013-06-01

The collection of articles in this supplement issue provides insight into the association of various covariates with concentrations of biochemical indicators of diet and nutrition (biomarkers), beyond age, race, and sex, using linear regression. We studied 10 specific sociodemographic and lifestyle covariates in combination with 29 biomarkers from NHANES 2003-2006 for persons aged ≥ 20 y. The covariates were organized into 2 sets or "chunks": sociodemographic (age, sex, race-ethnicity, education, and income) and lifestyle (dietary supplement use, smoking, alcohol consumption, BMI, and physical activity) and fit in hierarchical fashion by using each category or set of related variables to determine how covariates, jointly, are related to biomarker concentrations. In contrast to many regression modeling applications, all variables were retained in a full regression model regardless of significance to preserve the interpretation of the statistical properties of β coefficients, P values, and CIs and to keep the interpretation consistent across a set of biomarkers. The variables were preselected before data analysis, and the data analysis plan was designed at the outset to minimize the reporting of false-positive findings by limiting the amount of preliminary hypothesis testing. Although we generally found that demographic differences seen in biomarkers were over- or underestimated when ignoring other key covariates, the demographic differences generally remained significant after adjusting for sociodemographic and lifestyle variables. These articles are intended to provide a foundation to researchers to help them generate hypotheses for future studies or data analyses and/or develop predictive regression models using the wealth of NHANES data.

Leukemia in Iran: Epidemiology and Morphology Trends.

PubMed

Koohi, Fatemeh; Salehiniya, Hamid; Shamlou, Reza; Eslami, Soheyla; Ghojogh, Ziyaeddin Mahery; Kor, Yones; Rafiemanesh, Hosein

2015-01-01

Leukemia accounts for 8% of total cancer cases and involves all age groups with different prevalence and incidence rates in Iran and the entire world and causes a significant death toll and heavy expenses for diagnosis and treatment processes. This study was done to evaluate epidemiology and morphology of blood cancer during 2003-2008. This cross- sectional study was carried out based on re- analysis of the Cancer Registry Center report of the Health Deputy in Iran during a 6-year period (2003 - 2008). Statistical analysis for incidence time trends and morphology change percentage was performed with joinpoint regression analysis using the software Joinpoint Regression Program. During the studied years a total of 18,353 hematopoietic and reticuloendothelial system cancers were recorded. Chi square test showed significant difference between sex and morphological types of blood cancer (P-value<0.001). Joinpoint analysis showed a significant increasing trend for the adjusted standard incidence rate (ASIR) for both sexes (P-value<0.05). Annual percent changes (APC) for women and men were 18.7 and 19.9, respectively. The most common morphological blood cancers were ALL, ALM, MM and CLL which accounted for 60% of total hematopoietic system cancers. Joinpoint analyze showed a significant decreasing trend for ALM in both sexes (P-value<0.05). Hematopoietic system cancers in Iran demonstrate an increasing trend for incidence rate and decreasing trend for ALL, ALM and CLL morphology.

Quality of life of patients who undergo breast reconstruction after mastectomy: effects of personality characteristics.

PubMed

Bellino, Silvio; Fenocchio, Marina; Zizza, Monica; Rocca, Giuseppe; Bogetti, Paolo; Bogetto, Filippo

2011-01-01

Reconstruction after mastectomy has become an integral part of breast cancer treatment. The effects of psychological factors on quality of life after reconstruction have been poorly investigated. The authors examined clinical and personality characteristics related to quality of life in patients receiving reconstructive surgery. All patients received immediate reconstruction and were evaluated in the week before tissue expander implantation (T0) with a semistructured interview for demographic and clinical characteristics, the Temperament and Character Inventory, the Inventory of Interpersonal Problems, the Short Form Health Survey, the Severity Item of the Clinical Global Impression, the Hamilton Depression Rating Scale, and the Hamilton Anxiety Rating Scale. Assessment with the Short Form was repeated 3 months after expander placement (T1). Statistics were calculated with univariate regression and analysis of variance. Significant variables were included in a multiple regression analysis to identify factors related to the change T1-T0 of the mean of the Short Form-transformed scores. Results were significant when p was less than or equal to 0.05. Fifty-seven women were enrolled. Results of multiple regression analysis showed that the Temperament and Character Inventory personality dimension harm avoidance and the Inventory of Interpersonal Problems domain vindictive/self-centered were significantly and independently related to the change in Short Form mean score. Personality dimensions and patterns of interpersonal functioning produce significant effects on patients' quality of life during breast reconstruction. Patients with high harm avoidance are apprehensive and doubtful. Restoration of body image could help them to reduce social anxiety and insecurity. Vindictive/self-centered patients are resentful and aggressive. Breast reconstruction could symbolize the conclusion of a reparative process and fulfill the desire of revenge on cancer.

An evaluation of treatment strategies for head and neck cancer in an African American population.

PubMed

Ignacio, D N; Griffin, J J; Daniel, M G; Serlemitsos-Day, M T; Lombardo, F A; Alleyne, T A

2013-07-01

This study evaluated treatment strategies for head and neck cancers in a predominantly African American population. Data were collected utilizing medical records and the tumour registry at the Howard University Hospital. Kaplan-Meier method was used for survival analysis and Cox proportional hazards regression analysis predicted the hazard of death. Analysis revealed that the main treatment strategy was radiation combined with platinum for all stages except stage I. Cetuximab was employed in only 1% of cases. Kaplan-Meier analysis revealed stage II patients had poorer outcome than stage IV while Cox proportional hazard regression analysis (p = 0.4662) showed that stage I had a significantly lower hazard of death than stage IV (HR = 0.314; p = 0.0272). Contributory factors included tobacco and alcohol but body mass index (BMI) was inversely related to hazard of death. There was no difference in survival using any treatment modality for African Americans.

[On the effectiveness of the homeopathic remedy Arnica montana].

PubMed

Lüdtke, Rainer; Hacke, Daniela

2005-11-01

Arnica montana is a homeopathic remedy often prescribed after traumata and injuries. To assess whether Arnica is effective beyond placebo and to identify factors which support or contradict this effectiveness. All prospective, controlled trials on the effectiveness of homeopathic Arnica were included. Overall effectiveness was assessed by meta-analysis and meta-regression techniques. 68 comparisons from 49 clinical trials show a significant effectiveness of Arnica in traumatic injuries in random effects meta-analysis (odds ratio [OR], 0.36; 95% confidence interval [CI], 0.24-0.55), but not in meta-regression models (OR, 0.37; CI, 0.11-1.24). We found no evidence for publication bias. Studies from Medline-listed journals and high-quality studies are less likely to report positive results (p = 0.0006 and p = 0.0167). The hypothesis that homeopathic Arnica is effective could neither be proved nor rejected. All trials were highly heterogeneous, meta-regression does not help to explain this heterogeneity substantially.

New insights into old methods for identifying causal rare variants.

PubMed

Wang, Haitian; Huang, Chien-Hsun; Lo, Shaw-Hwa; Zheng, Tian; Hu, Inchi

2011-11-29

The advance of high-throughput next-generation sequencing technology makes possible the analysis of rare variants. However, the investigation of rare variants in unrelated-individuals data sets faces the challenge of low power, and most methods circumvent the difficulty by using various collapsing procedures based on genes, pathways, or gene clusters. We suggest a new way to identify causal rare variants using the F-statistic and sliced inverse regression. The procedure is tested on the data set provided by the Genetic Analysis Workshop 17 (GAW17). After preliminary data reduction, we ranked markers according to their F-statistic values. Top-ranked markers were then subjected to sliced inverse regression, and those with higher absolute coefficients in the most significant sliced inverse regression direction were selected. The procedure yields good false discovery rates for the GAW17 data and thus is a promising method for future study on rare variants.

Forecasting urban water demand: A meta-regression analysis.

PubMed

Sebri, Maamar

2016-12-01

Water managers and planners require accurate water demand forecasts over the short-, medium- and long-term for many purposes. These range from assessing water supply needs over spatial and temporal patterns to optimizing future investments and planning future allocations across competing sectors. This study surveys the empirical literature on the urban water demand forecasting using the meta-analytical approach. Specifically, using more than 600 estimates, a meta-regression analysis is conducted to identify explanations of cross-studies variation in accuracy of urban water demand forecasting. Our study finds that accuracy depends significantly on study characteristics, including demand periodicity, modeling method, forecasting horizon, model specification and sample size. The meta-regression results remain robust to different estimators employed as well as to a series of sensitivity checks performed. The importance of these findings lies in the conclusions and implications drawn out for regulators and policymakers and for academics alike. Copyright © 2016. Published by Elsevier Ltd.

Modelling lecturer performance index of private university in Tulungagung by using survival analysis with multivariate adaptive regression spline

NASA Astrophysics Data System (ADS)

Hasyim, M.; Prastyo, D. D.

2018-03-01

Survival analysis performs relationship between independent variables and survival time as dependent variable. In fact, not all survival data can be recorded completely by any reasons. In such situation, the data is called censored data. Moreover, several model for survival analysis requires assumptions. One of the approaches in survival analysis is nonparametric that gives more relax assumption. In this research, the nonparametric approach that is employed is Multivariate Regression Adaptive Spline (MARS). This study is aimed to measure the performance of private university’s lecturer. The survival time in this study is duration needed by lecturer to obtain their professional certificate. The results show that research activities is a significant factor along with developing courses material, good publication in international or national journal, and activities in research collaboration.

Abdominal girth, vertebral column length, and spread of spinal anesthesia in 30 minutes after plain bupivacaine 5 mg/mL.

PubMed

Zhou, Qing-he; Xiao, Wang-pin; Shen, Ying-yan

2014-07-01

The spread of spinal anesthesia is highly unpredictable. In patients with increased abdominal girth and short stature, a greater cephalad spread after a fixed amount of subarachnoidally administered plain bupivacaine is often observed. We hypothesized that there is a strong correlation between abdominal girth/vertebral column length and cephalad spread. Age, weight, height, body mass index, abdominal girth, and vertebral column length were recorded for 114 patients. The L3-L4 interspace was entered, and 3 mL of 0.5% plain bupivacaine was injected into the subarachnoid space. The cephalad spread (loss of temperature sensation and loss of pinprick discrimination) was assessed 30 minutes after intrathecal injection. Linear regression analysis was performed for age, weight, height, body mass index, abdominal girth, vertebral column length, and the spread of spinal anesthesia, and the combined linear contribution of age up to 55 years, weight, height, abdominal girth, and vertebral column length was tested by multiple regression analysis. Linear regression analysis showed that there was a significant univariate correlation among all 6 patient characteristics evaluated and the spread of spinal anesthesia (all P < 0.039) except for age and loss of temperature sensation (P > 0.068). Multiple regression analysis showed that abdominal girth and the vertebral column length were the key determinants for spinal anesthesia spread (both P < 0.0001), whereas age, weight, and height could be omitted without changing the results (all P > 0.059, all 95% confidence limits < 0.372). Multiple regression analysis revealed that the combination of a patient's 5 general characteristics, especially abdominal girth and vertebral column length, had a high predictive value for the spread of spinal anesthesia after a given dose of plain bupivacaine.

Use of generalized ordered logistic regression for the analysis of multidrug resistance data.

PubMed

Agga, Getahun E; Scott, H Morgan

2015-10-01

Statistical analysis of antimicrobial resistance data largely focuses on individual antimicrobial's binary outcome (susceptible or resistant). However, bacteria are becoming increasingly multidrug resistant (MDR). Statistical analysis of MDR data is mostly descriptive often with tabular or graphical presentations. Here we report the applicability of generalized ordinal logistic regression model for the analysis of MDR data. A total of 1,152 Escherichia coli, isolated from the feces of weaned pigs experimentally supplemented with chlortetracycline (CTC) and copper, were tested for susceptibilities against 15 antimicrobials and were binary classified into resistant or susceptible. The 15 antimicrobial agents tested were grouped into eight different antimicrobial classes. We defined MDR as the number of antimicrobial classes to which E. coli isolates were resistant ranging from 0 to 8. Proportionality of the odds assumption of the ordinal logistic regression model was violated only for the effect of treatment period (pre-treatment, during-treatment and post-treatment); but not for the effect of CTC or copper supplementation. Subsequently, a partially constrained generalized ordinal logistic model was built that allows for the effect of treatment period to vary while constraining the effects of treatment (CTC and copper supplementation) to be constant across the levels of MDR classes. Copper (Proportional Odds Ratio [Prop OR]=1.03; 95% CI=0.73-1.47) and CTC (Prop OR=1.1; 95% CI=0.78-1.56) supplementation were not significantly associated with the level of MDR adjusted for the effect of treatment period. MDR generally declined over the trial period. In conclusion, generalized ordered logistic regression can be used for the analysis of ordinal data such as MDR data when the proportionality assumptions for ordered logistic regression are violated. Published by Elsevier B.V.

The status of diabetes control in Kurdistan province, west of Iran.

PubMed

Esmailnasab, Nader; Afkhamzadeh, Abdorrahim; Roshani, Daem; Moradi, Ghobad

2013-09-17

Based on some estimation more than two million peoples in Iran are affected by Type 2 diabetes. The present study was designed to evaluate the status of diabetes control among Type 2 diabetes patients in Kurdistan, west of Iran and its associated factors. In our cross sectional study conducted in 2010, 411 Type 2 diabetes patients were randomly recruited from Sanandaj, Capital of Kurdistan. Chi square test was used in univariate analysis to address the association between HgAlc and FBS status and other variables. The significant results from Univariate analysis were entered in multivariate analysis and multinomial logistic regression model. In 38% of patients, FBS was in normal range (70-130) and in 47% HgA1c was <7% which is normal range for HgA1c. In univariate analysis, FBS level was associated with educational levels (P=0.001), referral style (P=0.001), referral time (P=0.009), and insulin injection (P=0.016). In addition, HgA1c had a relationship with sex (P=0.023), age (P=0.035), education (P=0.001), referral style (P=0.001), and insulin injection (P=0.008). After using multinomial logistic regression for significant results of univariate analysis, it was found that FBS was significantly associated with referral style. In addition HgA1c was significantly associated with referral style and Insulin injection. Although some of patients were under the coverage of specialized cares, but their diabetes were not properly controlled.

Prediction of anthropometric foot characteristics in children.

PubMed

Morrison, Stewart C; Durward, Brian R; Watt, Gordon F; Donaldson, Malcolm D C

2009-01-01

The establishment of growth reference values is needed in pediatric practice where pathologic conditions can have a detrimental effect on the growth and development of the pediatric foot. This study aims to use multiple regression to evaluate the effects of multiple predictor variables (height, age, body mass, and gender) on anthropometric characteristics of the peripubescent foot. Two hundred children aged 9 to 12 years were recruited, and three anthropometric measurements of the pediatric foot were recorded (foot length, forefoot width, and navicular height). Multiple regression analysis was conducted, and coefficients for gender, height, and body mass all had significant relationships for the prediction of forefoot width and foot length (P < or = .05, r > or = 0.7). The coefficients for gender and body mass were not significant for the prediction of navicular height (P > or = .05), whereas height was (P < or = .05). Normative growth reference values and prognostic regression equations are presented for the peripubescent foot.

Father and adolescent son variables related to son's HIV prevention.

PubMed

Glenn, Betty L; Demi, Alice; Kimble, Laura P

2008-02-01

The purpose of this study was to examine the relationship between fathers' influences and African American male adolescents' perceptions of self-efficacy to reduce high-risk sexual behavior. A convenience sample of 70 fathers was recruited from churches in a large metropolitan area in the South. Hierarchical multiple linear regression analysis indicated father-related factors and son-related factors were associated with 26.1% of the variance in son's self-efficacy to be abstinent. In the regression model greater son's perception of the communication of sexual standards and greater father's perception of his son's self-efficacy were significantly related to greater son's self-efficacy for abstinence. The second regression model with son's self-efficacy for safer sex as the criterion was not statistically significant. Data support the need for fathers to express confidence in their sons' ability to be abstinent or practice safer sex and to communicate with their sons regarding sexual issues and standards.

Estimation of Sensory Pork Loin Tenderness Using Warner-Bratzler Shear Force and Texture Profile Analysis Measurements

PubMed Central

Choe, Jee-Hwan; Choi, Mi-Hee; Rhee, Min-Suk; Kim, Byoung-Chul

2016-01-01

This study investigated the degree to which instrumental measurements explain the variation in pork loin tenderness as assessed by the sensory evaluation of trained panelists. Warner-Bratzler shear force (WBS) had a significant relationship with the sensory tenderness variables, such as softness, initial tenderness, chewiness, and rate of breakdown. In a regression analysis, WBS could account variations in these sensory variables, though only to a limited proportion of variation. On the other hand, three parameters from texture profile analysis (TPA)—hardness, gumminess, and chewiness—were significantly correlated with all sensory evaluation variables. In particular, from the result of stepwise regression analysis, TPA hardness alone explained over 15% of variation in all sensory evaluation variables, with the exception of perceptible residue. Based on these results, TPA analysis was found to be better than WBS measurement, with the TPA parameter hardness likely to prove particularly useful, in terms of predicting pork loin tenderness as rated by trained panelists. However, sensory evaluation should be conducted to investigate practical pork tenderness perceived by consumer, because both instrumental measurements could explain only a small portion (less than 20%) of the variability in sensory evaluation. PMID:26954174

Estimation of Sensory Pork Loin Tenderness Using Warner-Bratzler Shear Force and Texture Profile Analysis Measurements.

PubMed

Choe, Jee-Hwan; Choi, Mi-Hee; Rhee, Min-Suk; Kim, Byoung-Chul

2016-07-01

This study investigated the degree to which instrumental measurements explain the variation in pork loin tenderness as assessed by the sensory evaluation of trained panelists. Warner-Bratzler shear force (WBS) had a significant relationship with the sensory tenderness variables, such as softness, initial tenderness, chewiness, and rate of breakdown. In a regression analysis, WBS could account variations in these sensory variables, though only to a limited proportion of variation. On the other hand, three parameters from texture profile analysis (TPA)-hardness, gumminess, and chewiness-were significantly correlated with all sensory evaluation variables. In particular, from the result of stepwise regression analysis, TPA hardness alone explained over 15% of variation in all sensory evaluation variables, with the exception of perceptible residue. Based on these results, TPA analysis was found to be better than WBS measurement, with the TPA parameter hardness likely to prove particularly useful, in terms of predicting pork loin tenderness as rated by trained panelists. However, sensory evaluation should be conducted to investigate practical pork tenderness perceived by consumer, because both instrumental measurements could explain only a small portion (less than 20%) of the variability in sensory evaluation.

Direct evidence on the immune-mediated spontaneous regression of human cancer: an incentive for pharmaceutical companies to develop a novel anti-cancer vaccine.

PubMed

Saleh, F; Renno, W; Klepacek, I; Ibrahim, G; Dashti, H; Asfar, S; Behbehani, A; Al-Sayer, H; Dashti, A; Kerry, Crotty

2005-01-01

To develop an effective pharmaceutical treatment for a disease, we need to fully understand the biological behavior of that disease, especially when dealing with cancer. The current available treatment for cancer may help in lessening the burden of the disease or, on certain occasions, in increasing the survival of the patient. However, a total eradication of cancer remains the researchers' hope. Some of the discoveries in the field of medicine relied on observations of natural events. Among these events is the spontaneous regression of cancer. It has been argued that such regression could be immunologically-mediated, but no direct evidence has been shown to support such an argument. We, hereby, provide compelling evidence that spontaneous cancer regression in humans is immunologically-mediated, hoping that the results from this study would stimulate the pharmaceutical industry to focus more on cancer vaccine immunotherapy. Our results showed that patients with >3 primary melanomas (very rare group among cancer patients) develop significant histopathological spontaneous regression of further melanomas that they could acquire during their life (P=0.0080) as compared to patients with single primary melanoma where the phenomenon of spontaneous regression is absent or minimal. It seems that such regression resulted from the repeated exposure to the tumor which mimics a self-immunization process. Analysis of the regressing tumors revealed heavy infiltration by T lymphocytes as compared to non-regressing tumors (P<0.0001), the predominant of which were T cytotoxic rather than T helper. Mature dendritic cells were also found in significant number (P<0.0001) in the regressing tumors as compared to the non regressing ones, which demonstrate an active involvement of the different arms of the immune system in the multiple primary melanoma patients in the process of tumor regression. Also, MHC expression was significantly higher in the regressing versus the non-regressing tumors (P <0.0001), which reflects a proper tumor antigen expression. Associated with tumor regression was also loss of the melanoma common tumor antigen Melan A/ MART-1 in the multiple primary melanoma patients as compared to the single primary ones (P=0.0041). Furthermore, loss of Melan A/ MART-1 in the regressing tumors significantly correlated with the presence of Melan A/ MART-1-specific CTLs in the peripheral blood of these patients (P=0.03), which adds to the evidence that the phenomenon of regression seen in these patients was immunologically-mediated and tumor-specific. Such correlation was also seen in another rare group of melanoma patients, namely those with occult primary melanoma. The lesson that we could learn from nature in this study is that inducing cancer regression using the different arms of the immune system is possible. Also, developing a novel cancer vaccine is not out of reach.

Effect of partition board color on mood and autonomic nervous function.

PubMed

Sakuragi, Sokichi; Sugiyama, Yoshiki

2011-12-01

The purpose of this study was to evaluate the effects of the presence or absence (control) of a partition board and its color (red, yellow, blue) on subjective mood ratings and changes in autonomic nervous system indicators induced by a video game task. The increase in the mean Profile of Mood States (POMS) Fatigue score and mean Oppressive feeling rating after the task was lowest with the blue partition board. Multiple-regression analysis identified oppressive feeling and error scores on the second half of the task as statistically significant contributors to Fatigue. While explanatory variables were limited to the physiological indices, multiple-regression analysis identified a significant contribution of autonomic reactivity (assessed by heart rate variability) to Fatigue. These results suggest that a blue partition board would reduce task-induced subjective fatigue, in part by lowering the oppressive feeling of being enclosed during the task, possibly by increasing autonomic reactivity.

The use of bulk collectors in monitoring wet deposition at high-altitude sites in winter

USGS Publications Warehouse

Ranalli, A.J.; Turk, J.T.; Campbell, D.H.

1997-01-01

Concentrations of dissolved ions from samples collected by wet/dry collectors were compared to those collected by bulk collectors at Halfmoon Creek and Ned Wilson Lake in western Colorado to determine if bulk collectors can be used to monitor wet deposition chemistry in remote, high-altitude regions in winter. Hydrogen-ion concentration was significantly lower (p 0.05) at Halfmoon Creek. Wet deposition concentrations were predicated from bulk deposition concentrations through linear regression analysis. Results indicate that anions (chloride, nitrate and sulfate) can be predicted with a high degree of confidence. Lack of significant differences between seasonal (winter and summer) ratios of bulk to wet deposition concentrations indicates that at sites where operation of a wet/dry collector during the winter is not practical, wet deposition concentrations can be predicted from bulk collector samples through regression analysis of wet and bulk deposition data collected during the summer.

Viewing the viewers: how adults with attentional deficits watch educational videos.

PubMed

Hassner, Tal; Wolf, Lior; Lerner, Anat; Leitner, Yael

2014-10-01

Knowing how adults with ADHD interact with prerecorded video lessons at home may provide a novel means of early screening and long-term monitoring for ADHD. Viewing patterns of 484 students with known ADHD were compared with 484 age, gender, and academically matched controls chosen from 8,699 non-ADHD students. Transcripts generated by their video playback software were analyzed using t tests and regression analysis. ADHD students displayed significant tendencies (p ≤ .05) to watch videos with more pauses and more reviews of previously watched parts. Other parameters showed similar tendencies. Regression analysis indicated that attentional deficits remained constant for age and gender but varied for learning experience. There were measurable and significant differences between the video-viewing habits of the ADHD and non-ADHD students. This provides a new perspective on how adults cope with attention deficits and suggests a novel means of early screening for ADHD. © 2011 SAGE Publications.

Sibling dilution hypothesis: a regression surface analysis.

PubMed

Marjoribanks, K

2001-08-01

This study examined relationships between sibship size (the number of children in a family), birth order, and measures of academic performance, academic self-concept, and educational aspirations at different levels of family educational resources. As part of a national longitudinal study of Australian secondary school students data were collected from 2,530 boys and 2,450 girls in Years 9 and 10. Regression surfaces were constructed from models that included terms to account for linear, interaction, and curvilinear associations among the variables. Analysis suggests the general propositions (a) family educational resources have significant associations with children's school-related outcomes at different levels of sibling variables, the relationships for girls being curvilinear, and (b) sibling variables continue to have small significant associations with affective and cognitive outcomes, after taking into account variations in family educational resources. That is, the investigation provides only partial support for the sibling dilution hypothesis.

Bim may be a poor prognostic biomarker in breast cancer patients especially in those with luminal A tumors.

PubMed

Maimaiti, Yusufu; Dong, Lingling; Aili, Aikebaier; Maimaitiaili, Maimaitiaili; Huang, Tao; Abudureyimu, Kelimu

2017-07-04

Bcl-2 interacting mediator of cell death (Bim) appears to have contradictory roles in cancer. It is uncertain whether Bim show prognostic significance in patients with breast cancer. To investigate the correlation between Bim expression and clinicopathological characteristics of breast cancer and to evaluate Bim's effect on overall survival (OS). We used immunohistochemistry (IHC) technique to detect the expression of Bim via tissue microarray in 275 breast cancer samples, Kaplan-Meier analysis to perform survival analysis, and Cox proportional hazards regression model to explore the risk factors of breast cancer. The results revealed that Bim expression was significantly correlated with age, estrogen receptor (ER) and/or progesterone receptor (PR), human epidermal growth factor receptor (HER2) and Ki67 expression (P< 0.05). Bim expression was significantly different in the four molecular subtypes (P= 0.000). Survival analysis showed that Bim positive expression contributed to a shorter OS (P= 0.034), especially in patients with luminal A tumors (P= 0.039). Univariate and multivariate regression analysis showed that Bim was an independent prognostic factor for breast cancer (P< 0.05). Bim may serve as an effective predictive factor for lower OS in breast cancer patients, especially in those with luminal A tumors.

An Examination of Safety Management Systems and Aviation Technologies in the Helicopter Emergency Medical Services Industry

NASA Astrophysics Data System (ADS)

Buckner, Steven A.

The Helicopter Emergency Medical Service (HEMS) industry has a significant role in the transportation of injured patients, but has experienced more accidents than all other segments of the aviation industry combined. With the objective of addressing this discrepancy, this study assesses the effect of safety management systems implementation and aviation technologies utilization on the reduction of HEMS accident rates. Participating were 147 pilots from Federal Aviation Regulations Part 135 HEMS operators, who completed a survey questionnaire based on the Safety Culture and Safety Management System Survey (SCSMSS). The study assessed the predictor value of SMS implementation and aviation technologies to the frequency of HEMS accident rates with correlation and multiple linear regression. The correlation analysis identified three significant positive relationships. HEMS years of experience had a high significant positive relationship with accident rate (r=.90; p<.05); SMS had a moderate significant positive relationship to Night Vision Goggles (NVG) (r=.38; p<.05); and SMS had a slight significant positive relationship with Terrain Avoidance Warning System (TAWS) (r=.234; p<.05). Multiple regression analysis suggested that when combined with NVG, TAWS, and SMS, HEMS years of experience explained 81.4% of the variance in accident rate scores (p<.05), and HEMS years of experience was found to be a significant predictor of accident rates (p<.05). Additional quantitative regression analysis was recommended to replicate the results of this study and to consider the influence of these variables for continued reduction of HEMS accidents, and to induce execution of SMS and aviation technologies from a systems engineering application. Recommendations for practice included the adoption of existing regulatory guidance for a SMS program. A qualitative analysis was also recommended for future study SMS implementation and HEMS accident rate from the pilot's perspective. A quantitative longitudinal study would further explore inferential relationships between the study variables. Current strategies should include the increased utilization of available aviation technology resources as this proactive stance may be beneficial for the establishment of an effective safety culture within the HEMS industry.

Factors associated with active commuting to work among women.

PubMed

Bopp, Melissa; Child, Stephanie; Campbell, Matthew

2014-01-01

Active commuting (AC), the act of walking or biking to work, has notable health benefits though rates of AC remain low among women. This study used a social-ecological framework to examine the factors associated with AC among women. A convenience sample of employed, working women (n = 709) completed an online survey about their mode of travel to work. Individual, interpersonal, institutional, community, and environmental influences were assessed. Basic descriptive statistics and frequencies described the sample. Simple logistic regression models examined associations with the independent variables with AC participation and multiple logistic regression analysis determined the relative influence of social ecological factors on AC participation. The sample was primarily middle-aged (44.09±11.38 years) and non-Hispanic White (92%). Univariate analyses revealed several individual, interpersonal, institutional, community and environmental factors significantly associated with AC. The multivariable logistic regression analysis results indicated that significant factors associated with AC included number of children, income, perceived behavioral control, coworker AC, coworker AC normative beliefs, employer and community supports for AC, and traffic. The results of this study contribute to the limited body of knowledge on AC participation for women and may help to inform gender-tailored interventions to enhance AC behavior and improve health.

Principal components and iterative regression analysis of geophysical series: Application to Sunspot number (1750 2004)

NASA Astrophysics Data System (ADS)

Nordemann, D. J. R.; Rigozo, N. R.; de Souza Echer, M. P.; Echer, E.

2008-11-01

We present here an implementation of a least squares iterative regression method applied to the sine functions embedded in the principal components extracted from geophysical time series. This method seems to represent a useful improvement for the non-stationary time series periodicity quantitative analysis. The principal components determination followed by the least squares iterative regression method was implemented in an algorithm written in the Scilab (2006) language. The main result of the method is to obtain the set of sine functions embedded in the series analyzed in decreasing order of significance, from the most important ones, likely to represent the physical processes involved in the generation of the series, to the less important ones that represent noise components. Taking into account the need of a deeper knowledge of the Sun's past history and its implication to global climate change, the method was applied to the Sunspot Number series (1750-2004). With the threshold and parameter values used here, the application of the method leads to a total of 441 explicit sine functions, among which 65 were considered as being significant and were used for a reconstruction that gave a normalized mean squared error of 0.146.

Serum S100B Is Related to Illness Duration and Clinical Symptoms in Schizophrenia—A Meta-Regression Analysis

PubMed Central

Schümberg, Katharina; Polyakova, Maryna; Steiner, Johann; Schroeter, Matthias L.

2016-01-01

S100B has been linked to glial pathology in several psychiatric disorders. Previous studies found higher S100B serum levels in patients with schizophrenia compared to healthy controls, and a number of covariates influencing the size of this effect have been proposed in the literature. Here, we conducted a meta-analysis and meta-regression analysis on alterations of serum S100B in schizophrenia in comparison with healthy control subjects. The meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement to guarantee a high quality and reproducibility. With strict inclusion criteria 19 original studies could be included in the quantitative meta-analysis, comprising a total of 766 patients and 607 healthy control subjects. The meta-analysis confirmed higher values of the glial serum marker S100B in schizophrenia if compared with control subjects. Meta-regression analyses revealed significant effects of illness duration and clinical symptomatology, in particular the total score of the Positive and Negative Syndrome Scale (PANSS), on serum S100B levels in schizophrenia. In sum, results confirm glial pathology in schizophrenia that is modulated by illness duration and related to clinical symptomatology. Further studies are needed to investigate mechanisms and mediating factors related to these findings. PMID:26941608

Analysis of a Rocket Based Combined Cycle Engine during Rocket Only Operation

NASA Technical Reports Server (NTRS)

Smith, T. D.; Steffen, C. J., Jr.; Yungster, S.; Keller, D. J.

1998-01-01

The all rocket mode of operation is a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. However, outside of performing experiments or a full three dimensional analysis, there are no first order parametric models to estimate performance. As a result, an axisymmetric RBCC engine was used to analytically determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and statistical regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, percent of injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inject diameter ratio. A perfect gas computational fluid dynamics analysis was performed to obtain values of vacuum specific impulse. Statistical regression analysis was performed based on both full flow and gas generator engine cycles. Results were also found to be dependent upon the entire cycle assumptions. The statistical regression analysis determined that there were five significant linear effects, six interactions, and one second-order effect. Two parametric models were created to provide performance assessments of an RBCC engine in the all rocket mode of operation.

High Expression of EphA4 Predicted Lesser Degree of Tumor Regression after Neoadjuvant Chemoradiotherapy in Rectal Cancer.

PubMed

Lin, Ching-Yih; Lee, Ying-En; Tian, Yu-Feng; Sun, Ding-Ping; Sheu, Ming-Jen; Lin, Chen-Yi; Li, Chien-Feng; Lee, Sung-Wei; Lin, Li-Ching; Chang, I-Wei; Wang, Chieh-Tien; He, Hong-Lin

2017-01-01

Background: Numerous transmembrane receptor tyrosine kinase pathways have been found to play an important role in tumor progression in some cancers. This study was aimed to evaluate the clinical impact of Eph receptor A4 (EphA4) in patients with rectal cancer treated with neoadjuvant concurrent chemoradiotherapy (CCRT) combined with mesorectal excision, with special emphasis on tumor regression. Methods: Analysis of the publicly available expression profiling dataset of rectal cancer disclosed that EphA4 was the top-ranking, significantly upregulated, transmembrane receptor tyrosine kinase pathway-associated gene in the non-responders to CCRT, compared with the responders. Immunohistochemical study was conducted to assess the EphA4 expression in pre-treatment biopsy specimens from 172 rectal cancer patients without distant metastasis. The relationships between EphA4 expression and various clinicopathological factors or survival were statistically analyzed. Results: EphA4 expression was significantly associated with vascular invasion ( P =0.015), post-treatment depth of tumor invasion ( P =0.006), pre-treatment and post-treatment lymph node metastasis ( P =0.004 and P =0.011, respectively). More importantly, high EphA4 expression was significantly predictive for lesser degree of tumor regression after CCRT ( P =0.031). At univariate analysis, high EphA4 expression was a negative prognosticator for disease-specific survival ( P =0.0009) and metastasis-free survival ( P =0.0001). At multivariate analysis, high expression of EphA4 still served as an independent adverse prognostic factor for disease-specific survival (HR, 2.528; 95% CI, 1.131-5.651; P =0.024) and metastasis-free survival (HR, 3.908; 95% CI, 1.590-9.601; P =0.003). Conclusion: High expression of EphA4 predicted lesser degree of tumor regression after CCRT and served as an independent negative prognostic factor in patients with rectal cancer.

Locomotive syndrome is associated not only with physical capacity but also degree of depression.

PubMed

Ikemoto, Tatsunori; Inoue, Masayuki; Nakata, Masatoshi; Miyagawa, Hirofumi; Shimo, Kazuhiro; Wakabayashi, Toshiko; Arai, Young-Chang P; Ushida, Takahiro

2016-05-01

Reports of locomotive syndrome (LS) have recently been increasing. Although physical performance measures for LS have been well investigated to date, studies including psychiatric assessment are still scarce. Hence, the aim of this study was to investigate both physical and mental parameters in relation to presence and severity of LS using a 25-question geriatric locomotive function scale (GLFS-25) questionnaire. 150 elderly people aged over 60 years who were members of our physical-fitness center and displayed well-being were enrolled in this study. Firstly, using the previously determined GLFS-25 cutoff value (=16 points), subjects were divided into two groups accordingly: an LS and non-LS group in order to compare each parameter (age, grip strength, timed-up-and-go test (TUG), one-leg standing with eye open, back muscle and leg muscle strength, degree of depression and cognitive impairment) between the groups using the Mann-Whitney U-test followed by multiple logistic regression analysis. Secondly, a multiple linear regression was conducted to determine which variables showed the strongest correlation with severity of LS. We confirmed 110 people for non-LS (73%) and 40 people for LS using the GLFS-25 cutoff value. Comparative analysis between LS and non-LS revealed significant differences in parameters in age, grip strength, TUG, one-leg standing, back muscle strength and degree of depression (p < 0.006, after Bonferroni correction). Multiple logistic regression revealed that functional decline in grip strength, TUG and one-leg standing and degree of depression were significantly associated with LS. On the other hand, we observed that the significant contributors towards the GLFS-25 score were TUG and degree of depression in multiple linear regression analysis. The results indicate that LS is associated with not only the capacity of physical performance but also the degree of depression although most participants fell under the criteria of LS. Copyright © 2016 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Association between metabolic syndrome and intravesical prostatic protrusion in patients with benign prostatic enlargement and lower urinary tract symptoms (MIPS Study).

PubMed

Russo, Giorgio I; Regis, Federica; Spatafora, Pietro; Frizzi, Jacopo; Urzì, Daniele; Cimino, Sebastiano; Serni, Sergio; Carini, Marco; Gacci, Mauro; Morgia, Giuseppe

2018-05-01

To investigate the association between metabolic syndrome (MetS) and morphological features of benign prostatic enlargement (BPE), including total prostate volume (TPV), transitional zone volume (TZV) and intravesical prostatic protrusion (IPP). Between January 2015 and January 2017, 224 consecutive men aged >50 years presenting with lower urinary tract symptoms (LUTS) suggestive of BPE were recruited to this multicentre cross-sectional study. MetS was defined according to International Diabetes Federation criteria. Multivariate linear and logistic regression models were performed to verify factors associated with IPP, TZV and TPV. Patients with MetS were observed to have a significant increase in IPP (P < 0.01), TPV (P < 0.01) and TZV (P = 0.02). On linear regression analysis, adjusted for age and metabolic factors of MetS, we found that high-density lipoprotein (HDL) cholesterol was negatively associated with IPP (r = -0.17), TPV (r = -0.19) and TZV (r = -0.17), while hypertension was positively associated with IPP (r = 0.16), TPV (r = 0.19) and TZV (r = 0.16). On multivariate logistic regression analysis adjusted for age and factors of MetS, hypertension (categorical; odds ratio [OR] 2.95), HDL cholesterol (OR 0.94) and triglycerides (OR 1.01) were independent predictors of TPV ≥ 40 mL. We also found that HDL cholesterol (OR 0.86), hypertension (OR 2.0) and waist circumference (OR 1.09) were significantly associated with TZV ≥ 20 mL. On age-adjusted logistic regression analysis, MetS was significantly associated with IPP ≥ 10 mm (OR 34.0; P < 0.01), TZV ≥ 20 mL (OR 4.40; P < 0.01) and TPV ≥ 40 mL (OR 5.89; P = 0.03). We found an association between MetS and BPE, demonstrating a relationship with IPP. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Influential factors of red-light running at signalized intersection and prediction using a rare events logistic regression model.

PubMed

Ren, Yilong; Wang, Yunpeng; Wu, Xinkai; Yu, Guizhen; Ding, Chuan

2016-10-01

Red light running (RLR) has become a major safety concern at signalized intersection. To prevent RLR related crashes, it is critical to identify the factors that significantly impact the drivers' behaviors of RLR, and to predict potential RLR in real time. In this research, 9-month's RLR events extracted from high-resolution traffic data collected by loop detectors from three signalized intersections were applied to identify the factors that significantly affect RLR behaviors. The data analysis indicated that occupancy time, time gap, used yellow time, time left to yellow start, whether the preceding vehicle runs through the intersection during yellow, and whether there is a vehicle passing through the intersection on the adjacent lane were significantly factors for RLR behaviors. Furthermore, due to the rare events nature of RLR, a modified rare events logistic regression model was developed for RLR prediction. The rare events logistic regression method has been applied in many fields for rare events studies and shows impressive performance, but so far none of previous research has applied this method to study RLR. The results showed that the rare events logistic regression model performed significantly better than the standard logistic regression model. More importantly, the proposed RLR prediction method is purely based on loop detector data collected from a single advance loop detector located 400 feet away from stop-bar. This brings great potential for future field applications of the proposed method since loops have been widely implemented in many intersections and can collect data in real time. This research is expected to contribute to the improvement of intersection safety significantly. Copyright © 2016 Elsevier Ltd. All rights reserved.

Skeletal height estimation from regression analysis of sternal lengths in a Northwest Indian population of Chandigarh region: a postmortem study.

PubMed

Singh, Jagmahender; Pathak, R K; Chavali, Krishnadutt H

2011-03-20

Skeletal height estimation from regression analysis of eight sternal lengths in the subjects of Chandigarh zone of Northwest India is the topic of discussion in this study. Analysis of eight sternal lengths (length of manubrium, length of mesosternum, combined length of manubrium and mesosternum, total sternal length and first four intercostals lengths of mesosternum) measured from 252 male and 91 female sternums obtained at postmortems revealed that mean cadaver stature and sternal lengths were more in North Indians and males than the South Indians and females. Except intercostal lengths, all the sternal lengths were positively correlated with stature of the deceased in both sexes (P < 0.001). The multiple regression analysis of sternal lengths was found more useful than the linear regression for stature estimation. Using multivariate regression analysis, the combined length of manubrium and mesosternum in both sexes and the length of manubrium along with 2nd and 3rd intercostal lengths of mesosternum in males were selected as best estimators of stature. Nonetheless, the stature of males can be predicted with SEE of 6.66 (R(2) = 0.16, r = 0.318) from combination of MBL+BL_3+LM+BL_2, and in females from MBL only, it can be estimated with SEE of 6.65 (R(2) = 0.10, r = 0.318), whereas from the multiple regression analysis of pooled data, stature can be known with SEE of 6.97 (R(2) = 0.387, r = 575) from the combination of MBL+LM+BL_2+TSL+BL_3. The R(2) and F-ratio were found to be statistically significant for almost all the variables in both the sexes, except 4th intercostal length in males and 2nd to 4th intercostal lengths in females. The 'major' sternal lengths were more useful than the 'minor' ones for stature estimation The universal regression analysis used by Kanchan et al. [39] when applied to sternal lengths, gave satisfactory estimates of stature for males only but female stature was comparatively better estimated from simple linear regressions. But they are not proposed for the subjects of known sex, as they underestimate the male and overestimate female stature. However, intercostal lengths were found to be the poor estimators of stature (P < 0.05). And also sternal lengths exhibit weaker correlation coefficients and higher standard errors of estimate. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

[Academic burnout and selection-optimization-compensation strategy in medical students].

PubMed

Chun, Kyung Hee; Park, Young Soon; Lee, Young Hwan; Kim, Seong Yong

2014-12-01

This study was conducted to examine the relationship between academic demand, academic burnout, and the selection-optimization-compensation (SOC) strategy in medical students. A total of 317 students at Yeungnam University, comprising 90 premedical course students, 114 medical course students, and 113 graduate course students, completed a survey that addressed the factors of academic burnout and the selection-optimization-compensation strategy. We analyzed variances of burnout and SOC strategy use by group, and stepwise multiple regression analysis was conducted. There were significant differences in emotional exhaustion and cynicism between groups and year in school. In the SOC strategy, there were no significant differences between groups except for elective selection. The second-year medical and graduate students experienced significantly greater exhaustion (p<0.001), and first-year premedical students experienced significantly higher cynicism (p<0.001). By multiple regression analysis, subfactors of academic burnout and emotional exhaustion were significantly affected by academic demand (p<0.001), and 46% of the variance was explained. Cynicism was significantly affected by elective selection (p<0.05), and inefficacy was significantly influenced by optimization (p<0.001). To improve adaptation, prescriptive strategies and preventive support should be implemented with regard to academic burnout in medical school. Longitudinal and qualitative studies on burnout must be conducted.

The correlations between alteration of p16 gene and clinicopathological factors and prognosis in squamous cell carcinomas of the buccal mucosa.

PubMed

Dong, Yuying; Wang, Jie; Dong, Fusheng; Wang, Xu; Zhang, Yinghuai

2012-07-01

To evaluate relationships between the alteration of p16 gene and the clinical status and prognosis of the patients with squamous cell carcinoma of the buccal mucosa. Thirty buccal cancers were included in the analysis. Deletion analysis was performed by PCR. Point mutation analysis was used by PCR-SSCP and direct sequencing. Methylation-specific PCR methods were adopted for the evaluation of p16 methylation. The correlation between alteration of p16 gene and clinicopathological factors buccal cancer was evaluated by Fisher's exact test. Kaplan-Meier and Cox regression were used to investigate the relationship between p16 alteration and survival time. The frequency of p16 alteration was 63.3% in buccal carcinomas. P16 deletion was associated significantly with tumor size (P = 0.01). P16 point mutation was associated significantly with differentiation (P = 0.006). P16 methylation was associated significantly with nodes metastasis (P = 0.027). The overall survival rate of 30 buccal carcinomas was 53.3%. The Log-rank test (P = 0.021) and univariate Cox regression analysis (P = 0.030) revealed that p16 methylation was significantly associated with the overall survival rate. Multivariate analysis showed that p16 deletion, p16 mutation, and p16 methylation were not statistically significant. The alterations of p16 gene may play a major role in malignancy and development and metastases of buccal carcinoma and may be an excellent marker of aggressive clinical behavior. P16 methylation has a prognostic value in buccal carcinoma but not an independent prognosis factor. P16 point mutation and p16 deletion have not prognostic significance in buccal carcinoma. © 2012 John Wiley & Sons A/S.

Benchmark Dose for Urinary Cadmium based on a Marker of Renal Dysfunction: A Meta-Analysis

PubMed Central

Woo, Hae Dong; Chiu, Weihsueh A.; Jo, Seongil; Kim, Jeongseon

2015-01-01

Background Low doses of cadmium can cause adverse health effects. Benchmark dose (BMD) and the one-sided 95% lower confidence limit of BMD (BMDL) to derive points of departure for urinary cadmium exposure have been estimated in several previous studies, but the methods to derive BMD and the estimated BMDs differ. Objectives We aimed to find the associated factors that affect BMD calculation in the general population, and to estimate the summary BMD for urinary cadmium using reported BMDs. Methods A meta-regression was performed and the pooled BMD/BMDL was estimated using studies reporting a BMD and BMDL, weighted by sample size, that were calculated from individual data based on markers of renal dysfunction. Results BMDs were highly heterogeneous across studies. Meta-regression analysis showed that a significant predictor of BMD was the cut-off point which denotes an abnormal level. Using the 95th percentile as a cut off, BMD5/BMDL5 estimates for 5% benchmark responses (BMR) of β2-microglobulinuria (β2-MG) estimated was 6.18/4.88 μg/g creatinine in conventional quantal analysis and 3.56/3.13 μg/g creatinine in the hybrid approach, and BMD5/BMDL5 estimates for 5% BMR of N-acetyl-β-d-glucosaminidase (NAG) was 10.31/7.61 μg/g creatinine in quantal analysis and 3.21/2.24 g/g creatinine in the hybrid approach. However, the meta-regression showed that BMD and BMDL were significantly associated with the cut-off point, but BMD calculation method did not significantly affect the results. The urinary cadmium BMDL5 of β2-MG was 1.9 μg/g creatinine in the lowest cut-off point group. Conclusion The BMD was significantly associated with the cut-off point defining the abnormal level of renal dysfunction markers. PMID:25970611

Trend Analysis of Cancer Mortality and Incidence in Panama, Using Joinpoint Regression Analysis.

PubMed

Politis, Michael; Higuera, Gladys; Chang, Lissette Raquel; Gomez, Beatriz; Bares, Juan; Motta, Jorge

2015-06-01

Cancer is one of the leading causes of death worldwide and its incidence is expected to increase in the future. In Panama, cancer is also one of the leading causes of death. In 1964, a nationwide cancer registry was started and it was restructured and improved in 2012. The aim of this study is to utilize Joinpoint regression analysis to study the trends of the incidence and mortality of cancer in Panama in the last decade. Cancer mortality was estimated from the Panamanian National Institute of Census and Statistics Registry for the period 2001 to 2011. Cancer incidence was estimated from the Panamanian National Cancer Registry for the period 2000 to 2009. The Joinpoint Regression Analysis program, version 4.0.4, was used to calculate trends by age-adjusted incidence and mortality rates for selected cancers. Overall, the trend of age-adjusted cancer mortality in Panama has declined over the last 10 years (-1.12% per year). The cancers for which there was a significant increase in the trend of mortality were female breast cancer and ovarian cancer; while the highest increases in incidence were shown for breast cancer, liver cancer, and prostate cancer. Significant decrease in the trend of mortality was evidenced for the following: prostate cancer, lung and bronchus cancer, and cervical cancer; with respect to incidence, only oral and pharynx cancer in both sexes had a significant decrease. Some cancers showed no significant trends in incidence or mortality. This study reveals contrasting trends in cancer incidence and mortality in Panama in the last decade. Although Panama is considered an upper middle income nation, this study demonstrates that some cancer mortality trends, like the ones seen in cervical and lung cancer, behave similarly to the ones seen in high income countries. In contrast, other types, like breast cancer, follow a pattern seen in countries undergoing a transition to a developed economy with its associated lifestyle, nutrition, and body weight changes.

Effect of soy isoflavone supplementation on plasma lipoprotein(a) concentrations: A meta-analysis.

PubMed

Simental-Mendía, Luis E; Gotto, Antonio M; Atkin, Stephen L; Banach, Maciej; Pirro, Matteo; Sahebkar, Amirhossein

Soy supplementation has been shown to reduce total and low-density lipoprotein cholesterol, while increasing high-density lipoprotein cholesterol. However, contradictory effects of soy isoflavone supplementation on lipoprotein(a) [Lp(a)] have been reported suggesting the need for a meta-analysis to be undertaken. The aim of the study was to investigate the impact of supplementation with soy isoflavones on plasma Lp(a) levels through a systematic review and meta-analysis of eligible randomized placebo-controlled trials. The search included PubMed-Medline, Scopus, ISI Web of Knowledge, and Google Scholar databases (by March 26, 2017), and quality of studies was evaluated according to Cochrane criteria. Quantitative data synthesis was performed using a random-effects model, with standardized mean difference and 95% confidence interval as summary statistics. Meta-regression and leave-one-out sensitivity analysis were performed to assess the modifiers of treatment response. Ten eligible studies comprising 11 treatment arms with 973 subjects were selected for the meta-analysis. Meta-analysis did not suggest any significant alteration of plasma Lp(a) levels after supplementation with soy isoflavones (standardized mean difference: 0.08, 95% confidence interval: -0.05, 0.20, P = .228). The effect size was robust in the leave-one-out sensitivity analysis. In meta-regression analysis, neither dose nor duration of supplementation with soy isoflavones was significantly associated with the effect size. This meta-analysis of the 10 available randomized placebo-controlled trials revealed no significant effect of soy isoflavones treatment on plasma Lp(a) concentrations. Copyright © 2017 National Lipid Association. Published by Elsevier Inc. All rights reserved.

Least median of squares and iteratively re-weighted least squares as robust linear regression methods for fluorimetric determination of α-lipoic acid in capsules in ideal and non-ideal cases of linearity.

PubMed

Korany, Mohamed A; Gazy, Azza A; Khamis, Essam F; Ragab, Marwa A A; Kamal, Miranda F

2018-06-01

This study outlines two robust regression approaches, namely least median of squares (LMS) and iteratively re-weighted least squares (IRLS) to investigate their application in instrument analysis of nutraceuticals (that is, fluorescence quenching of merbromin reagent upon lipoic acid addition). These robust regression methods were used to calculate calibration data from the fluorescence quenching reaction (∆F and F-ratio) under ideal or non-ideal linearity conditions. For each condition, data were treated using three regression fittings: Ordinary Least Squares (OLS), LMS and IRLS. Assessment of linearity, limits of detection (LOD) and quantitation (LOQ), accuracy and precision were carefully studied for each condition. LMS and IRLS regression line fittings showed significant improvement in correlation coefficients and all regression parameters for both methods and both conditions. In the ideal linearity condition, the intercept and slope changed insignificantly, but a dramatic change was observed for the non-ideal condition and linearity intercept. Under both linearity conditions, LOD and LOQ values after the robust regression line fitting of data were lower than those obtained before data treatment. The results obtained after statistical treatment indicated that the linearity ranges for drug determination could be expanded to lower limits of quantitation by enhancing the regression equation parameters after data treatment. Analysis results for lipoic acid in capsules, using both fluorimetric methods, treated by parametric OLS and after treatment by robust LMS and IRLS were compared for both linearity conditions. Copyright © 2018 John Wiley & Sons, Ltd.

Effect of caffeic acid phenethyl ester on the regression of endometrial explants in an experimental rat model.

PubMed

Güney, Mehmet; Nasir, Serdar; Oral, Baha; Karahan, Nermin; Mungan, Tamer

2007-04-01

The objective of this study is to determine the effects of antioxidant and anti-inflammatory caffeic acid phenethyl ester (CAPE) on experimental endometriosis, peritoneal superoxide dismutase (SOD) and catalase (CAT) activities, and malondialdehyde (MDA) levels in the rat endometriosis model. Thirty rats with experimentally induced endometriosis were randomly divided into 2 groups and treated for 4 weeks with intraperitoneal CAPE (CAPE-treated group; 10 micromol/kg/d, n = 13) or vehicle (control group; n = 13). The volume and weight changes of the implants were calculated. Immunohistochemical and histologic examinations of endometriotic explants by semiquantitative analysis and measurements of peritoneal SOD, CAT, and MDA levels were made. Following 4 weeks of treatment with CAPE, there were significant differences in posttreatment spherical volumes (37.4 +/- 14.7 mm(3) vs 147.5 +/- 41.2 mm(3)) and explant weights (49.1 +/- 28.5 mg vs 158.9 +/- 50.3 mg) between the CAPE-treated groups and controls. The mean evaluation nomogram levels in glandular epithelium for COX-2 positivity by scoring system were 2.1 +/- 0.3 in the CAPE-treated group and 3.9 +/- 0.3 in the control group. In the CAPE-treated group, peritoneal levels of MDA and activities of SOD and CAT significantly decreased when compared with the control group (P < .01). Histologic analysis of the explants demonstrated mostly atrophy and regression in the treatment group, and semiquantitative analysis showed significantly lower scores in rats treated with CAPE compared with the control group. CAPE appeared to cause regression of experimental endometriosis.

Use of streamflow data to estimate base flowground-water recharge for Wisconsin

USGS Publications Warehouse

Gebert, W.A.; Radloff, M.J.; Considine, E.J.; Kennedy, J.L.

2007-01-01

The average annual base flow/recharge was determined for streamflow-gaging stations throughout Wisconsin by base-flow separation. A map of the State was prepared that shows the average annual base flow for the period 1970-99 for watersheds at 118 gaging stations. Trend analysis was performed on 22 of the 118 streamflow-gaging stations that had long-term records, unregulated flow, and provided aerial coverage of the State. The analysis found that a statistically significant increasing trend was occurring for watersheds where the primary land use was agriculture. Most gaging stations where the land cover was forest had no significant trend. A method to estimate the average annual base flow at ungaged sites was developed by multiple-regression analysis using basin characteristics. The equation with the lowest standard error of estimate, 9.5%, has drainage area, soil infiltration and base flow factor as independent variables. To determine the average annual base flow for smaller watersheds, estimates were made at low-flow partial-record stations in 3 of the 12 major river basins in Wisconsin. Regression equations were developed for each of the three major river basins using basin characteristics. Drainage area, soil infiltration, basin storage and base-flow factor were the independent variables in the regression equations with the lowest standard error of estimate. The standard error of estimate ranged from 17% to 52% for the three river basins. ?? 2007 American Water Resources Association.

Independent Prognostic Factors for Acute Organophosphorus Pesticide Poisoning.

PubMed

Tang, Weidong; Ruan, Feng; Chen, Qi; Chen, Suping; Shao, Xuebo; Gao, Jianbo; Zhang, Mao

2016-07-01

Acute organophosphorus pesticide poisoning (AOPP) is becoming a significant problem and a potential cause of human mortality because of the abuse of organophosphate compounds. This study aims to determine the independent prognostic factors of AOPP by using multivariate logistic regression analysis. The clinical data for 71 subjects with AOPP admitted to our hospital were retrospectively analyzed. This information included the Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, 6-h post-admission blood lactate levels, post-admission 6-h lactate clearance rates, admission blood cholinesterase levels, 6-h post-admission blood cholinesterase levels, cholinesterase activity, blood pH, and other factors. Univariate analysis and multivariate logistic regression analyses were conducted to identify all prognostic factors and independent prognostic factors, respectively. A receiver operating characteristic curve was plotted to analyze the testing power of independent prognostic factors. Twelve of 71 subjects died. Admission blood lactate levels, 6-h post-admission blood lactate levels, post-admission 6-h lactate clearance rates, blood pH, and APACHE II scores were identified as prognostic factors for AOPP according to the univariate analysis, whereas only 6-h post-admission blood lactate levels, post-admission 6-h lactate clearance rates, and blood pH were independent prognostic factors identified by multivariate logistic regression analysis. The receiver operating characteristic analysis suggested that post-admission 6-h lactate clearance rates were of moderate diagnostic value. High 6-h post-admission blood lactate levels, low blood pH, and low post-admission 6-h lactate clearance rates were independent prognostic factors identified by multivariate logistic regression analysis. Copyright © 2016 by Daedalus Enterprises.

Techniques for estimating flood-peak discharges of rural, unregulated streams in Ohio

USGS Publications Warehouse

Koltun, G.F.; Roberts, J.W.

1990-01-01

Multiple-regression equations are presented for estimating flood-peak discharges having recurrence intervals of 2, 5, 10, 25, 50, and 100 years at ungaged sites on rural, unregulated streams in Ohio. The average standard errors of prediction for the equations range from 33.4% to 41.4%. Peak discharge estimates determined by log-Pearson Type III analysis using data collected through the 1987 water year are reported for 275 streamflow-gaging stations. Ordinary least-squares multiple-regression techniques were used to divide the State into three regions and to identify a set of basin characteristics that help explain station-to- station variation in the log-Pearson estimates. Contributing drainage area, main-channel slope, and storage area were identified as suitable explanatory variables. Generalized least-square procedures, which include historical flow data and account for differences in the variance of flows at different gaging stations, spatial correlation among gaging station records, and variable lengths of station record were used to estimate the regression parameters. Weighted peak-discharge estimates computed as a function of the log-Pearson Type III and regression estimates are reported for each station. A method is provided to adjust regression estimates for ungaged sites by use of weighted and regression estimates for a gaged site located on the same stream. Limitations and shortcomings cited in an earlier report on the magnitude and frequency of floods in Ohio are addressed in this study. Geographic bias is no longer evident for the Maumee River basin of northwestern Ohio. No bias is found to be associated with the forested-area characteristic for the range used in the regression analysis (0.0 to 99.0%), nor is this characteristic significant in explaining peak discharges. Surface-mined area likewise is not significant in explaining peak discharges, and the regression equations are not biased when applied to basins having approximately 30% or less surface-mined area. Analyses of residuals indicate that the equations tend to overestimate flood-peak discharges for basins having approximately 30% or more surface-mined area. (USGS)

Influence of Health Behaviors and Occupational Stress on Prediabetic State among Male Office Workers.

PubMed

Ryu, Hosihn; Moon, Jihyeon; Jung, Jiyeon

2018-06-14

This study examined the influence of health behaviors and occupational stress on the prediabetic state of male office workers, and identified related risks and influencing factors. The study used a cross-sectional design and performed an integrative analysis on data from regular health checkups, health questionnaires, and a health behavior-related survey of employees of a company, using Spearman’s correlation coefficients and multiple logistic regression analysis. The results showed significant relationships of prediabetic state with health behaviors and occupational stress. Among health behaviors, a diet without vegetables and fruits (Odds Ratio (OR) = 3.74, 95% Confidence Interval (CI) = 1.93⁻7.66) was associated with a high risk of prediabetic state. In the subscales on occupational stress, organizational system in the 4th quartile (OR = 4.83, 95% CI = 2.40⁻9.70) was significantly associated with an increased likelihood of prediabetic state. To identify influencing factors of prediabetic state, the multiple logistic regression was performed using regression models. The results showed that dietary habits (β = 1.20, p = 0.002), total occupational stress score (β = 1.33, p = 0.024), and organizational system (β = 1.13, p = 0.009) were significant influencing factors. The present findings indicate that active interventions are needed at workplace for the systematic and comprehensive management of health behaviors and occupational stress that influence prediabetic state of office workers.

Valuing avoided morbidity using meta-regression analysis: what can health status measures and QALYs tell us about WTP?

PubMed

Van Houtven, George; Powers, John; Jessup, Amber; Yang, Jui-Chen

2006-08-01

Many economists argue that willingness-to-pay (WTP) measures are most appropriate for assessing the welfare effects of health changes. Nevertheless, the health evaluation literature is still dominated by studies estimating nonmonetary health status measures (HSMs), which are often used to assess changes in quality-adjusted life years (QALYs). Using meta-regression analysis, this paper combines results from both WTP and HSM studies applied to acute morbidity, and it tests whether a systematic relationship exists between HSM and WTP estimates. We analyze over 230 WTP estimates from 17 different studies and find evidence that QALY-based estimates of illness severity--as measured by the Quality of Well-Being (QWB) Scale--are significant factors in explaining variation in WTP, as are changes in the duration of illness and the average income and age of the study populations. In addition, we test and reject the assumption of a constant WTP per QALY gain. We also demonstrate how the estimated meta-regression equations can serve as benefit transfer functions for policy analysis. By specifying the change in duration and severity of the acute illness and the characteristics of the affected population, we apply the regression functions to predict average WTP per case avoided. Copyright 2006 John Wiley & Sons, Ltd.

Quantitative assessment of cervical vertebral maturation using cone beam computed tomography in Korean girls.

PubMed

Byun, Bo-Ram; Kim, Yong-Il; Yamaguchi, Tetsutaro; Maki, Koutaro; Son, Woo-Sung

2015-01-01

This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6-18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R (2) had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status.

Fine and Gray competing risk regression model to study the cause-specific under-five child mortality in Bangladesh.

PubMed

Mohammad, Khandoker Akib; Fatima-Tuz-Zahura, Most; Bari, Wasimul

2017-01-28

The cause-specific under-five mortality of Bangladesh has been studied by fitting cumulative incidence function (CIF) based Fine and Gray competing risk regression model (1999). For the purpose of analysis, Bangladesh Demographic and Health Survey (BDHS), 2011 data set was used. Three types of mode of mortality for the under-five children are considered. These are disease, non-disease and other causes. Product-Limit survival probabilities for the under-five child mortality with log-rank test were used to select a set of covariates for the regression model. The covariates found to have significant association in bivariate analysis were only considered in the regression analysis. Potential determinants of under-five child mortality due to disease is size of child at birth, while gender of child, NGO (non-government organization) membership of mother, mother's education level, and size of child at birth are due to non-disease and age of mother at birth, NGO membership of mother, and mother's education level are for the mortality due to other causes. Female participation in the education programs needs to be increased because of the improvement of child health and government should arrange family and social awareness programs as well as health related programs for women so that they are aware of their child health.

Partial Least Squares Regression Can Aid in Detecting Differential Abundance of Multiple Features in Sets of Metagenomic Samples

PubMed Central

Libiger, Ondrej; Schork, Nicholas J.

2015-01-01

It is now feasible to examine the composition and diversity of microbial communities (i.e., “microbiomes”) that populate different human organs and orifices using DNA sequencing and related technologies. To explore the potential links between changes in microbial communities and various diseases in the human body, it is essential to test associations involving different species within and across microbiomes, environmental settings and disease states. Although a number of statistical techniques exist for carrying out relevant analyses, it is unclear which of these techniques exhibit the greatest statistical power to detect associations given the complexity of most microbiome datasets. We compared the statistical power of principal component regression, partial least squares regression, regularized regression, distance-based regression, Hill's diversity measures, and a modified test implemented in the popular and widely used microbiome analysis methodology “Metastats” across a wide range of simulated scenarios involving changes in feature abundance between two sets of metagenomic samples. For this purpose, simulation studies were used to change the abundance of microbial species in a real dataset from a published study examining human hands. Each technique was applied to the same data, and its ability to detect the simulated change in abundance was assessed. We hypothesized that a small subset of methods would outperform the rest in terms of the statistical power. Indeed, we found that the Metastats technique modified to accommodate multivariate analysis and partial least squares regression yielded high power under the models and data sets we studied. The statistical power of diversity measure-based tests, distance-based regression and regularized regression was significantly lower. Our results provide insight into powerful analysis strategies that utilize information on species counts from large microbiome data sets exhibiting skewed frequency distributions obtained on a small to moderate number of samples. PMID:26734061

Evidence-based identification of key beliefs explaining adult male circumcision motivation in Zimbabwe: targets for behavior change messaging.

PubMed

Montaño, Daniel E; Kasprzyk, Danuta; Hamilton, Deven T; Tshimanga, Mufuta; Gorn, Gerald

2014-05-01

Male circumcision (MC) reduces HIV acquisition among men, leading WHO/UNAIDS to recommend a goal to circumcise 80 % of men in high HIV prevalence countries. Significant investment to increase MC capacity in priority countries was made, yet only 5 % of the goal has been achieved in Zimbabwe. The integrated behavioral model (IBM) was used as a framework to investigate the factors affecting MC motivation among men in Zimbabwe. A survey instrument was designed based on elicitation study results, and administered to a representative household-based sample of 1,201 men aged 18-30 from two urban and two rural areas in Zimbabwe. Multiple regression analysis found all five IBM constructs significantly explained MC Intention. Nearly all beliefs underlying the IBM constructs were significantly correlated with MC Intention. Stepwise regression analysis of beliefs underlying each construct respectively found that 13 behavioral beliefs, 5 normative beliefs, 4 descriptive norm beliefs, 6 efficacy beliefs, and 10 control beliefs were significant in explaining MC Intention. A final stepwise regression of the five sets of significant IBM construct beliefs identified 14 key beliefs that best explain Intention. Similar analyses were carried out with subgroups of men by urban-rural and age. Different sets of behavioral, normative, efficacy, and control beliefs were significant for each sub-group, suggesting communication messages need to be targeted to be most effective for sub-groups. Implications for the design of effective MC demand creation messages are discussed. This study demonstrates the application of theory-driven research to identify evidence-based targets for intervention messages to increase men's motivation to get circumcised and thereby improve demand for male circumcision.

The impact of a standardized program on short and long-term outcomes in bariatric surgery.

PubMed

Aird, Lisa N F; Hong, Dennis; Gmora, Scott; Breau, Ruth; Anvari, Mehran

2017-02-01

The purpose of this study was to determine whether there has been an improvement in short- and long-term clinical outcomes since 2010, when the Ontario Bariatric Network led a province-wide initiative to establish a standardized system of care for bariatric patients. The system includes nine bariatric centers, a centralized referral system, and a research registry. Standardization of procedures has progressed yearly, including guidelines for preoperative assessment and perioperative care. Analysis of the OBN registry data was performed by fiscal year between April 2010 and March 2015. Three-month overall postoperative complication rates and 30 day postoperative mortality were calculated. The mean percentage of weight loss at 1, 2, and 3 years postoperative, and regression of obesity-related diseases were calculated. The analysis of continuous and nominal data was performed using ANOVA, Chi-square, and McNemar's testing. A multiple logistic regression analysis was performed for factors affecting postoperative complication rate. Eight thousand and forty-three patients were included in the bariatric registry between April 2010 and March 2015. Thirty-day mortality was rare (<0.075 %) and showed no significant difference between years. Three-month overall postoperative complication rates significantly decreased with standardization (p < 0.001), as did intra-operative complication rates (p < -0.001). Regression analysis demonstrated increasing standardization to be a predictor of 3 month complication rate OR of 0.59 (95 %CI 0.41-0.85, p = 0.00385). The mean percentage of weight loss at 1, 2, and 3 years postoperative showed stability at 33.2 % (9.0 SD), 34.1 % (10.1 SD), and 32.7 % (10.1 SD), respectively. Sustained regression in obesity-related comorbidities was demonstrated at 1, 2, and 3 years postoperative. Evidence indicates the implementation of a standardized system of bariatric care has contributed to improvements in complication rates and supported prolonged weight loss and regression of obesity-related diseases in patients undergoing bariatric surgery in Ontario.

Comparison of Logistic Regression and Artificial Neural Network in Low Back Pain Prediction: Second National Health Survey

PubMed Central

Parsaeian, M; Mohammad, K; Mahmoudi, M; Zeraati, H

2012-01-01

Background: The purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. Methods: Data from the second national health survey were considered in this investigation. This data includes the information of low back pain and its associated risk factors among Iranian people aged 15 years and older. Artificial neural network and logistic regression models were developed using a set of 17294 data and they were validated in a test set of 17295 data. Hosmer and Lemeshow recommendation for model selection was used in fitting the logistic regression. A three-layer perceptron with 9 inputs, 3 hidden and 1 output neurons was employed. The efficiency of two models was compared by receiver operating characteristic analysis, root mean square and -2 Loglikelihood criteria. Results: The area under the ROC curve (SE), root mean square and -2Loglikelihood of the logistic regression was 0.752 (0.004), 0.3832 and 14769.2, respectively. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the artificial neural network was 0.754 (0.004), 0.3770 and 14757.6, respectively. Conclusions: Based on these three criteria, artificial neural network would give better performance than logistic regression. Although, the difference is statistically significant, it does not seem to be clinically significant. PMID:23113198

Comparison of logistic regression and artificial neural network in low back pain prediction: second national health survey.

PubMed

Parsaeian, M; Mohammad, K; Mahmoudi, M; Zeraati, H

2012-01-01

The purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. Data from the second national health survey were considered in this investigation. This data includes the information of low back pain and its associated risk factors among Iranian people aged 15 years and older. Artificial neural network and logistic regression models were developed using a set of 17294 data and they were validated in a test set of 17295 data. Hosmer and Lemeshow recommendation for model selection was used in fitting the logistic regression. A three-layer perceptron with 9 inputs, 3 hidden and 1 output neurons was employed. The efficiency of two models was compared by receiver operating characteristic analysis, root mean square and -2 Loglikelihood criteria. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the logistic regression was 0.752 (0.004), 0.3832 and 14769.2, respectively. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the artificial neural network was 0.754 (0.004), 0.3770 and 14757.6, respectively. Based on these three criteria, artificial neural network would give better performance than logistic regression. Although, the difference is statistically significant, it does not seem to be clinically significant.

Extramural vascular invasion and response to neoadjuvant chemoradiotherapy in rectal cancer: Influence of the CpG island methylator phenotype

PubMed Central

Williamson, Jeremy Stuart; Jones, Huw Geraint; Williams, Namor; Griffiths, Anthony Paul; Jenkins, Gareth; Beynon, John; Harris, Dean Anthony

2017-01-01

AIM To identify whether CpG island methylator phenotype (CIMP) is predictive of response to neoadjuvant chemoradiotherapy (NACRT) and outcomes in rectal cancer. METHODS Patients undergoing NACRT and surgical resection for rectal cancer in a tertiary referral centre between 2002-2011 were identified. Pre-treatment tumour biopsies were analysed for CIMP status (high, intermediate or low) using methylation specific PCR. KRAS and BRAF status were also determined using pyrosequencing analysis. Clinical information was extracted from case records and cancer services databases. Response to radiotherapy was measured by tumour regression scores determined upon histological examination of the resected specimen. The relationship between these molecular features, response to NACRT and oncological outcomes were analysed. RESULTS There were 160 patients analysed with a median follow-up time of 46.4 mo. Twenty-one (13%) patients demonstrated high levels of CIMP methylation (CIMP-H) and this was significantly associated with increased risk of extramural vascular invasion (EMVI) compared with CIMP-L [8/21 (38%) vs 15/99 (15%), P = 0.028]. CIMP status was not related to tumour regression after radiotherapy or survival, however EMVI was significantly associated with adverse survival (P < 0.001). Intermediate CIMP status was significantly associated with KRAS mutation (P = 0.01). There were 14 (9%) patients with a pathological complete response (pCR) compared to 116 (73%) patients having no or minimal regression after neoadjuvant chemoradiotherapy. Those patients with pCR had median survival of 106 mo compared to 65.8 mo with minimal regression, although this was not statistically significant (P = 0.26). Binary logistic regression analysis of the relationship between EMVI and other prognostic features revealed, EMVI positivity was associated with poor overall survival, advanced “T” stage and CIMP-H but not nodal status, age, sex, KRAS mutation status and presence of local or systemic recurrence. CONCLUSION We report a novel association of pre-treatment characterisation of CIMP-H with EMVI status which has prognostic implications and is not readily detectable on pre-treatment histological examination. PMID:28567185

Extramural vascular invasion and response to neoadjuvant chemoradiotherapy in rectal cancer: Influence of the CpG island methylator phenotype.

PubMed

Williamson, Jeremy Stuart; Jones, Huw Geraint; Williams, Namor; Griffiths, Anthony Paul; Jenkins, Gareth; Beynon, John; Harris, Dean Anthony

2017-05-15

To identify whether CpG island methylator phenotype (CIMP) is predictive of response to neoadjuvant chemoradiotherapy (NACRT) and outcomes in rectal cancer. Patients undergoing NACRT and surgical resection for rectal cancer in a tertiary referral centre between 2002-2011 were identified. Pre-treatment tumour biopsies were analysed for CIMP status (high, intermediate or low) using methylation specific PCR. KRAS and BRAF status were also determined using pyrosequencing analysis. Clinical information was extracted from case records and cancer services databases. Response to radiotherapy was measured by tumour regression scores determined upon histological examination of the resected specimen. The relationship between these molecular features, response to NACRT and oncological outcomes were analysed. There were 160 patients analysed with a median follow-up time of 46.4 mo. Twenty-one (13%) patients demonstrated high levels of CIMP methylation (CIMP-H) and this was significantly associated with increased risk of extramural vascular invasion (EMVI) compared with CIMP-L [8/21 (38%) vs 15/99 (15%), P = 0.028]. CIMP status was not related to tumour regression after radiotherapy or survival, however EMVI was significantly associated with adverse survival ( P < 0.001). Intermediate CIMP status was significantly associated with KRAS mutation ( P = 0.01). There were 14 (9%) patients with a pathological complete response (pCR) compared to 116 (73%) patients having no or minimal regression after neoadjuvant chemoradiotherapy. Those patients with pCR had median survival of 106 mo compared to 65.8 mo with minimal regression, although this was not statistically significant ( P = 0.26). Binary logistic regression analysis of the relationship between EMVI and other prognostic features revealed, EMVI positivity was associated with poor overall survival, advanced "T" stage and CIMP-H but not nodal status, age, sex, KRAS mutation status and presence of local or systemic recurrence. We report a novel association of pre-treatment characterisation of CIMP-H with EMVI status which has prognostic implications and is not readily detectable on pre-treatment histological examination.

Association between sociability and diffusion tensor imaging in BALB/cJ mice.

PubMed

Kim, Sungheon; Pickup, Stephen; Fairless, Andrew H; Ittyerah, Ranjit; Dow, Holly C; Abel, Ted; Brodkin, Edward S; Poptani, Harish

2012-01-01

The purpose of this study was to use high-resolution diffusion tensor imaging (DTI) to investigate the association between DTI metrics and sociability in BALB/c inbred mice. The sociability of prepubescent (30-day-old) BALB/cJ mice was operationally defined as the time that the mice spent sniffing a stimulus mouse in a social choice test. High-resolution ex vivo DTI data on 12 BALB/cJ mouse brains were acquired using a 9.4-T vertical-bore magnet. Regression analysis was conducted to investigate the association between DTI metrics and sociability. Significant positive regression (p < 0.001) between social sniffing time and fractional anisotropy was found in 10 regions located in the thalamic nuclei, zona incerta/substantia nigra, visual/orbital/somatosensory cortices and entorhinal cortex. In addition, significant negative regression (p < 0.001) between social sniffing time and mean diffusivity was found in five areas located in the sensory cortex, motor cortex, external capsule and amygdaloid region. In all regions showing significant regression with either the mean diffusivity or fractional anisotropy, the tertiary eigenvalue correlated negatively with the social sniffing time. This study demonstrates the feasibility of using DTI to detect brain regions associated with sociability in a mouse model system. Copyright © 2011 John Wiley & Sons, Ltd.

The effectiveness of manual and mechanical instrumentation for the retreatment of three different root canal filling materials.

PubMed

Somma, Francesco; Cammarota, Giuseppe; Plotino, Gianluca; Grande, Nicola M; Pameijer, Cornelis H

2008-04-01

The aim of this study was to compare the effectiveness of the Mtwo R (Sweden & Martina, Padova, Italy), ProTaper retreatment files (Dentsply-Maillefer, Ballaigues, Switzerland), and a Hedström manual technique in the removal of three different filling materials (gutta-percha, Resilon [Resilon Research LLC, Madison, CT], and EndoRez [Ultradent Products Inc, South Jordan, UT]) during retreatment. Ninety single-rooted straight premolars were instrumented and randomly divided into 9 groups of 10 teeth each (n = 10) with regards to filling material and instrument used. For all roots, the following data were recorded: procedural errors, time of retreatment, apically extruded material, canal wall cleanliness through optical stereomicroscopy (OSM), and scanning electron microscopy (SEM). A linear regression analysis and three logistic regression analyses were performed to assess the level of significance set at p = 0.05. The results indicated that the overall regression models were statistically significant. The Mtwo R, ProTaper retreatment files, and Resilon filling material had a positive impact in reducing the time for retreatment. Both ProTaper retreatment files and Mtwo R showed a greater extrusion of debris. For both OSM and SEM logistic regression models, the root canal apical third had the greatest impact on the score values. EndoRez filling material resulted in cleaner root canal walls using OSM analysis, whereas Resilon filling material and both engine-driven NiTi rotary techniques resulted in less clean root canal walls according to SEM analysis. In conclusion, all instruments left remnants of filling material and debris on the root canal walls irrespective of the root filling material used. Both the engine-driven NiTi rotary systems proved to be safe and fast devices for the removal of endodontic filling material.

Generating linear regression model to predict motor functions by use of laser range finder during TUG.

PubMed

Adachi, Daiki; Nishiguchi, Shu; Fukutani, Naoto; Hotta, Takayuki; Tashiro, Yuto; Morino, Saori; Shirooka, Hidehiko; Nozaki, Yuma; Hirata, Hinako; Yamaguchi, Moe; Yorozu, Ayanori; Takahashi, Masaki; Aoyama, Tomoki

2017-05-01

The purpose of this study was to investigate which spatial and temporal parameters of the Timed Up and Go (TUG) test are associated with motor function in elderly individuals. This study included 99 community-dwelling women aged 72.9 ± 6.3 years. Step length, step width, single support time, variability of the aforementioned parameters, gait velocity, cadence, reaction time from starting signal to first step, and minimum distance between the foot and a marker placed to 3 in front of the chair were measured using our analysis system. The 10-m walk test, five times sit-to-stand (FTSTS) test, and one-leg standing (OLS) test were used to assess motor function. Stepwise multivariate linear regression analysis was used to determine which TUG test parameters were associated with each motor function test. Finally, we calculated a predictive model for each motor function test using each regression coefficient. In stepwise linear regression analysis, step length and cadence were significantly associated with the 10-m walk test, FTSTS and OLS test. Reaction time was associated with the FTSTS test, and step width was associated with the OLS test. Each predictive model showed a strong correlation with the 10-m walk test and OLS test (P < 0.01), which was not significant higher correlation than TUG test time. We showed which TUG test parameters were associated with each motor function test. Moreover, the TUG test time regarded as the lower extremity function and mobility has strong predictive ability in each motor function test. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

A logistic regression analysis of factors related to the treatment compliance of infertile patients with polycystic ovary syndrome.

PubMed

Li, Saijiao; He, Aiyan; Yang, Jing; Yin, TaiLang; Xu, Wangming

2011-01-01

To investigate factors that can affect compliance with treatment of polycystic ovary syndrome (PCOS) in infertile patients and to provide a basis for clinical treatment, specialist consultation and health education. Patient compliance was assessed via a questionnaire based on the Morisky-Green test and the treatment principles of PCOS. Then interviews were conducted with 99 infertile patients diagnosed with PCOS at Renmin Hospital of Wuhan University in China, from March to September 2009. Finally, these data were analyzed using logistic regression analysis. Logistic regression analysis revealed that a total of 23 (25.6%) of the participants showed good compliance. Factors that significantly (p < 0.05) affected compliance with treatment were the patient's body mass index, convenience of medical treatment and concerns about adverse drug reactions. Patients who are obese, experience inconvenient medical treatment or are concerned about adverse drug reactions are more likely to exhibit noncompliance. Treatment education and intervention aimed at these patients should be strengthened in the clinic to improve treatment compliance. Further research is needed to better elucidate the compliance behavior of patients with PCOS.

The antagonistic effect between STAT1 and Survivin and its clinical significance in gastric cancer.

PubMed

Deng, Hao; Zhen, Hongyan; Fu, Zhengqi; Huang, Xuan; Zhou, Hongyan; Liu, Lijiang

2012-01-01

In previous studies, we observed that STAT1 and Survivin correlated negatively with gastric cancer tissues, and that the functions of the IFN-γ-STAT1 pathway and Survivin in gastric cancer are the same as those reported for other types of cancer. In this study, the SGC7901 gastric cancer cell line and 83 gastric cancer specimens were used to confirm the relationship between STAT1 and Survivin, as well as the clinical significance of this relationship in gastric cancer. IFN-γ and STAT1 and Survivin antisense oligonucleotides (ASONs) were used to knock down the expression in SGC7901 cells. The protein expression of STAT1 and Survivin was tested by immunocytochemical and image analysis methods. A gastric cancer tissue microarray was prepared and tested by immunohistochemical methods. Data were analyzed by the Spearman's rank correlation analysis, the χ(2) test and Cox's multivariate regression analysis. Upon knockdown of IFN-γ, STAT1 and Survivin expression by ASON in the SGC7901 cell line, an antagonistic effect was observed between STAT1 and Survivin. In gastric cancer tissues, STAT1 showed a negative correlation with depth of invasion (p<0.05) in gastric cancer tissues exhibiting a negative Survivin protein expression. Furthermore, in tissues exhibiting a negative STAT1 protein expression, Survivin correlated negatively with N stage (p<0.05). Pathological and molecular markers were used to conduct Cox's multivariate regression analysis, and depth of invasion and N stage were found to be prognostic factors (p<0.05). On the other hand, in tissues exhibiting a negative Survivin protein expression, Cox's multivariate regression analysis revealed that the differentiation type and STAT1 protein expression were prognostic factors (p<0.05). There is an antagonistic effect between STAT1 and Survivin in gastric cancer, and this antagonistic effect is of clinical significance in gastric cancer.

Standardized Regression Coefficients as Indices of Effect Sizes in Meta-Analysis

ERIC Educational Resources Information Center

Kim, Rae Seon

2011-01-01

When conducting a meta-analysis, it is common to find many collected studies that report regression analyses, because multiple regression analysis is widely used in many fields. Meta-analysis uses effect sizes drawn from individual studies as a means of synthesizing a collection of results. However, indices of effect size from regression analyses…

Review and statistical analysis of the use of ultrasonic velocity for estimating the porosity fraction in polycrystalline materials

NASA Technical Reports Server (NTRS)

Roth, D. J.; Swickard, S. M.; Stang, D. B.; Deguire, M. R.

1991-01-01

A review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials is presented. Initially, a semiempirical model is developed showing the origin of the linear relationship between ultrasonic velocity and porosity fraction. Then, from a compilation of data produced by many researchers, scatter plots of velocity versus percent porosity data are shown for Al2O3, MgO, porcelain-based ceramics, PZT, SiC, Si3N4, steel, tungsten, UO2,(U0.30Pu0.70)C, and YBa2Cu3O(7-x). Linear regression analysis produces predicted slope, intercept, correlation coefficient, level of significance, and confidence interval statistics for the data. Velocity values predicted from regression analysis of fully-dense materials are in good agreement with those calculated from elastic properties.

Quantitative analysis of aircraft multispectral-scanner data and mapping of water-quality parameters in the James River in Virginia

NASA Technical Reports Server (NTRS)

Johnson, R. W.; Bahn, G. S.

1977-01-01

Statistical analysis techniques were applied to develop quantitative relationships between in situ river measurements and the remotely sensed data that were obtained over the James River in Virginia on 28 May 1974. The remotely sensed data were collected with a multispectral scanner and with photographs taken from an aircraft platform. Concentration differences among water quality parameters such as suspended sediment, chlorophyll a, and nutrients indicated significant spectral variations. Calibrated equations from the multiple regression analysis were used to develop maps that indicated the quantitative distributions of water quality parameters and the dispersion characteristics of a pollutant plume entering the turbid river system. Results from further analyses that use only three preselected multispectral scanner bands of data indicated that regression coefficients and standard errors of estimate were not appreciably degraded compared with results from the 10-band analysis.

Review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials

NASA Technical Reports Server (NTRS)

Roth, D. J.; Swickard, S. M.; Stang, D. B.; Deguire, M. R.

1990-01-01

A review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials is presented. Initially, a semi-empirical model is developed showing the origin of the linear relationship between ultrasonic velocity and porosity fraction. Then, from a compilation of data produced by many researchers, scatter plots of velocity versus percent porosity data are shown for Al2O3, MgO, porcelain-based ceramics, PZT, SiC, Si3N4, steel, tungsten, UO2,(U0.30Pu0.70)C, and YBa2Cu3O(7-x). Linear regression analysis produced predicted slope, intercept, correlation coefficient, level of significance, and confidence interval statistics for the data. Velocity values predicted from regression analysis for fully-dense materials are in good agreement with those calculated from elastic properties.

a Comparison Between Two Ols-Based Approaches to Estimating Urban Multifractal Parameters

NASA Astrophysics Data System (ADS)

Huang, Lin-Shan; Chen, Yan-Guang

Multifractal theory provides a new spatial analytical tool for urban studies, but many basic problems remain to be solved. Among various pending issues, the most significant one is how to obtain proper multifractal dimension spectrums. If an algorithm is improperly used, the parameter spectrums will be abnormal. This paper is devoted to investigating two ordinary least squares (OLS)-based approaches for estimating urban multifractal parameters. Using empirical study and comparative analysis, we demonstrate how to utilize the adequate linear regression to calculate multifractal parameters. The OLS regression analysis has two different approaches. One is that the intercept is fixed to zero, and the other is that the intercept is not limited. The results of comparative study show that the zero-intercept regression yields proper multifractal parameter spectrums within certain scale range of moment order, while the common regression method often leads to abnormal multifractal parameter values. A conclusion can be reached that fixing the intercept to zero is a more advisable regression method for multifractal parameters estimation, and the shapes of spectral curves and value ranges of fractal parameters can be employed to diagnose urban problems. This research is helpful for scientists to understand multifractal models and apply a more reasonable technique to multifractal parameter calculations.

Publication bias in obesity treatment trials?

PubMed

Allison, D B; Faith, M S; Gorman, B S

1996-10-01

The present investigation examined the extent of publication bias (namely the tendency to publish significant findings and file away non-significant findings) within the obesity treatment literature. Quantitative literature synthesis of four published meta-analyses from the obesity treatment literature. Interventions in these studies included pharmacological, educational, child, and couples treatments. To assess publication bias, several regression procedures (for example weighted least-squares, random-effects multi-level modeling, and robust regression methods) were used to regress effect sizes onto their standard errors, or proxies thereof, within each of the four meta-analysis. A significant positive beta weight in these analyses signified publication bias. There was evidence for publication bias within two of the four published meta-analyses, such that reviews of published studies were likely to overestimate clinical efficacy. The lack of evidence for publication bias within the two other meta-analyses might have been due to insufficient statistical power rather than the absence of selection bias. As in other disciplines, publication bias appears to exist in the obesity treatment literature. Suggestions are offered for managing publication bias once identified or reducing its likelihood in the first place.

Using within-day hive weight changes to measure environmental effects on honey bee colonies

PubMed Central

Holst, Niels; Weiss, Milagra; Carroll, Mark J.; McFrederick, Quinn S.; Barron, Andrew B.

2018-01-01

Patterns in within-day hive weight data from two independent datasets in Arizona and California were modeled using piecewise regression, and analyzed with respect to honey bee colony behavior and landscape effects. The regression analysis yielded information on the start and finish of a colony’s daily activity cycle, hive weight change at night, hive weight loss due to departing foragers and weight gain due to returning foragers. Assumptions about the meaning of the timing and size of the morning weight changes were tested in a third study by delaying the forager departure times from one to three hours using screen entrance gates. A regression of planned vs. observed departure delays showed that the initial hive weight loss around dawn was largely due to foragers. In a similar experiment in Australia, hive weight loss due to departing foragers in the morning was correlated with net bee traffic (difference between the number of departing bees and the number of arriving bees) and from those data the payload of the arriving bees was estimated to be 0.02 g. The piecewise regression approach was then used to analyze a fifth study involving hives with and without access to natural forage. The analysis showed that, during a commercial pollination event, hives with previous access to forage had a significantly higher rate of weight gain as the foragers returned in the afternoon, and, in the weeks after the pollination event, a significantly higher rate of weight loss in the morning, as foragers departed. This combination of continuous weight data and piecewise regression proved effective in detecting treatment differences in foraging activity that other methods failed to detect. PMID:29791462

Regression Rates Following the Treatment of Aggressive Posterior Retinopathy of Prematurity with Bevacizumab Versus Laser: 8-Year Retrospective Analysis

PubMed Central

Nicoară, Simona D.; Ştefănuţ, Anne C.; Nascutzy, Constanta; Zaharie, Gabriela C.; Toader, Laura E.; Drugan, Tudor C.

2016-01-01

Background Retinopathy is a serious complication related to prematurity and a leading cause of childhood blindness. The aggressive posterior form of retinopathy of prematurity (APROP) has a worse anatomical and functional outcome following laser therapy, as compared with the classic form of the disease. The main outcome measures are the APROP regression rate, structural outcomes, and complications associated with intravitreal bevacizumab (IVB) versus laser photocoagulation in APROP. Material/Methods This is a retrospective case series that includes infants with APROP who received either IVB or laser photocoagulation and had a follow-up of at least 60 weeks (for the laser photocoagulation group) and 80 weeks (for the IVB group). In the first group, laser photocoagulation of the retina was carried out and in the second group, 1 bevacizumab injection was administered intravitreally. The following parameters were analyzed in each group: sex, gestational age, birth weight, postnatal age and postmenstrual age at treatment, APROP regression, sequelae, and complications. Statistical analysis was performed using Microsoft Excel and IBM SPSS (version 23.0). Results The laser photocoagulation group consisted of 6 premature infants (12 eyes) and the IVB group consisted of 17 premature infants (34 eyes). Within the laser photocoagulation group, the evolution was favorable in 9 eyes (75%) and unfavorable in 3 eyes (25%). Within the IVB group, APROP regressed in 29 eyes (85.29%) and failed to regress in 5 eyes (14.71%). These differences are statistically significant, as proved by the McNemar test (P<0.001). Conclusions The IVB group had a statistically significant better outcome compared with the laser photocoagulation group, in APROP in our series. PMID:27062023

Stature Estimation from Lower Limb Anthropometry using Linear Regression Analysis: A Study on the Malaysian Population.

PubMed

Abu Bakar, S N; Aspalilah, A; AbdelNasser, I; Nurliza, A; Hairuliza, M J; Swarhib, M; Das, S; Mohd Nor, F

2017-01-01

Stature is one of the characteristics that could be used to identify human, besides age, sex and racial affiliation. This is useful when the body found is either dismembered, mutilated or even decomposed, and helps in narrowing down the missing person's identity. The main aim of the present study was to construct regression functions for stature estimation by using lower limb bones in the Malaysian population. The sample comprised 87 adult individuals (81 males, 6 females) aged between 20 to 79 years. The parameters such as thigh length, lower leg length, leg length, foot length, foot height and foot breadth were measured. They were measured by a ruler and measuring tape. Statistical analysis involved independent t-test to analyse the difference between lower limbs in male and female. The Pearson's correlation test was used to analyse correlations between lower limb parameters and stature, and the linear regressions were used to form equations. The paired t-test was used to compare between actual stature and estimated stature by using the equations formed. Using independent t-test, there was a significant difference (p< 0.05) in the measurement between males and females with regard to leg length, thigh length, lower leg length, foot length and foot breadth. The thigh length, leg length and foot length were observed to have strong correlations with stature with p= 0.75, p= 0.81 and p= 0.69, respectively. Linear regressions were formulated for stature estimation. Paired t-test showed no significant difference between actual stature and estimated stature. It is concluded that regression functions can be used to estimate stature to identify skeletal remains in the Malaysia population.

Using within-day hive weight changes to measure environmental effects on honey bee colonies.

PubMed

Meikle, William G; Holst, Niels; Colin, Théotime; Weiss, Milagra; Carroll, Mark J; McFrederick, Quinn S; Barron, Andrew B

2018-01-01

Patterns in within-day hive weight data from two independent datasets in Arizona and California were modeled using piecewise regression, and analyzed with respect to honey bee colony behavior and landscape effects. The regression analysis yielded information on the start and finish of a colony's daily activity cycle, hive weight change at night, hive weight loss due to departing foragers and weight gain due to returning foragers. Assumptions about the meaning of the timing and size of the morning weight changes were tested in a third study by delaying the forager departure times from one to three hours using screen entrance gates. A regression of planned vs. observed departure delays showed that the initial hive weight loss around dawn was largely due to foragers. In a similar experiment in Australia, hive weight loss due to departing foragers in the morning was correlated with net bee traffic (difference between the number of departing bees and the number of arriving bees) and from those data the payload of the arriving bees was estimated to be 0.02 g. The piecewise regression approach was then used to analyze a fifth study involving hives with and without access to natural forage. The analysis showed that, during a commercial pollination event, hives with previous access to forage had a significantly higher rate of weight gain as the foragers returned in the afternoon, and, in the weeks after the pollination event, a significantly higher rate of weight loss in the morning, as foragers departed. This combination of continuous weight data and piecewise regression proved effective in detecting treatment differences in foraging activity that other methods failed to detect.

A study of home deaths in Japan from 1951 to 2002

PubMed Central

Yang, Limin; Sakamoto, Naoko; Marui, Eiji

2006-01-01

Background Several surveys in Japan have indicated that most terminally ill Japanese patients would prefer to die at home or in a homelike setting. However, there is a great disparity between this stated preference and the reality, since most Japanese die in hospital. We report here national changes in home deaths in Japan over the last 5 decades. Using prefecture data, we also examined the factors in the medical service associated with home death in Japan. Methods Published data on place of death was obtained from the vital statistics compiled by the Ministry of Health, Labor and Welfare of Japan. We analyzed trends of home deaths from 1951 to 2002, and describe the changes in the proportion of home deaths by region, sex, age, and cause of death. Joinpoint regression analysis was used for trend analysis. Logistic regression analysis was performed to identify secular trends in home deaths, and the impact of age, sex, year of deaths and cause of deaths on home death. We also examined the association between home death and medical service factors by multiple regression analysis, using home death rate by prefectures in 2002 as a dependent variable. Results A significant decrease in the percentage of patients dying at home was observed in the results of joinpoint regression analysis. Older patients and males were more likely to die at home. Patients who died from cancer were less likely to die at home. The results of multiple regression analysis indicated that home death was related to the number of beds in hospital, ratio of daily occupied beds in general hospital, the number of families in which the elderly were living alone, and dwelling rooms. Conclusion The pattern of the place of death has not only been determined by social and demographic characteristics of the decedent, but also associated with the medical service in the community. PMID:16524485

Regression and Sentinel Lymph Node Status in Melanoma Progression

PubMed Central

Letca, Alina Florentina; Ungureanu, Loredana; Şenilă, Simona Corina; Grigore, Lavinia Elena; Pop, Ştefan; Fechete, Oana; Vesa, Ştefan Cristian

2018-01-01

Background The purpose of this study was to assess the role of regression and other clinical and histological features for the prognosis and the progression of cutaneous melanoma. Material/Methods Between 2005 and 2016, 403 patients with melanoma were treated and followed at our Department of Dermatology. Of the 403 patients, 173 patients had cutaneous melanoma and underwent sentinel lymph node (SLN) biopsy and thus were included in this study. Results Histological regression was found in 37 cases of melanoma (21.3%). It was significantly associated with marked and moderate tumor-infiltrating lymphocyte (TIL) and with negative SLN. Progression of the disease occurred in 42 patients (24.2%). On multivariate analysis, we found that a positive lymph node and a Breslow index higher than 2 mm were independent variables associated with disease free survival (DFS). These variables together with a mild TIL were significantly correlated with overall survival (OS). The presence of regression was not associated with DFS or OS. Conclusions We could not demonstrate an association between regression and the outcome of patients with cutaneous melanoma. Tumor thickness greater than 2 mm and a positive SLN were associated with recurrence. Survival was influenced by a Breslow thickness >2 mm, the presence of a mild TIL and a positive SLN status. PMID:29507279

Age estimation using pulp/tooth area ratio in maxillary canines-A digital image analysis.

PubMed

Juneja, Manjushree; Devi, Yashoda B K; Rakesh, N; Juneja, Saurabh

2014-09-01

Determination of age of a subject is one of the most important aspects of medico-legal cases and anthropological research. Radiographs can be used to indirectly measure the rate of secondary dentine deposition which is depicted by reduction in the pulp area. In this study, 200 patients of Karnataka aged between 18-72 years were selected for the study. Panoramic radiographs were made and indirectly digitized. Radiographic images of maxillary canines (RIC) were processed using a computer-aided drafting program (ImageJ). The variables pulp/root length (p), pulp/tooth length (r), pulp/root width at enamel-cementum junction (ECJ) level (a), pulp/root width at mid-root level (c), pulp/root width at midpoint level between ECJ level and mid-root level (b) and pulp/tooth area ratio (AR) were recorded. All the morphological variables including gender were statistically analyzed to derive regression equation for estimation of age. It was observed that 2 variables 'AR' and 'b' contributed significantly to the fit and were included in the regression model, yielding the formula: Age = 87.305-480.455(AR)+48.108(b). Statistical analysis indicated that the regression equation with selected variables explained 96% of total variance with the median of the residuals of 0.1614 years and standard error of estimate of 3.0186 years. There is significant correlation between age and morphological variables 'AR' and 'b' and the derived population specific regression equation can be potentially used for estimation of chronological age of individuals of Karnataka origin.

The effects of texting on driving performance in a driving simulator: the influence of driver age.

PubMed

Rumschlag, Gordon; Palumbo, Theresa; Martin, Amber; Head, Doreen; George, Rajiv; Commissaris, Randall L

2015-01-01

Distracted driving is a significant contributor to motor vehicle accidents and fatalities, and texting is a particularly significant form of driver distraction that continues to be on the rise. The present study examined the influence of driver age (18-59 years old) and other factors on the disruptive effects of texting on simulated driving behavior. While 'driving' the simulator, subjects were engaged in a series of brief text conversations with a member of the research team. The primary dependent variable was the occurrence of Lane Excursions (defined as any time the center of the vehicle moved outside the directed driving lane, e.g., into the lane for oncoming traffic or onto the shoulder of the road), measured as (1) the percent of subjects that exhibited Lane Excursions, (2) the number of Lane Excursions occurring and (3) the percent of the texting time in Lane Excursions. Multiple Regression analyses were used to assess the influence of several factors on driving performance while texting, including text task duration, texting skill level (subject-reported), texting history (#texts/week), driver gender and driver age. Lane Excursions were not observed in the absence of texting, but 66% of subjects overall exhibited Lane Excursions while texting. Multiple Regression analysis for all subjects (N=50) revealed that text task duration was significantly correlated with the number of Lane Excursions, and texting skill level and driver age were significantly correlated with the percent of subjects exhibiting Lane Excursions. Driver gender was not significantly correlated with Lane Excursions during texting. Multiple Regression analysis of only highly skilled texters (N=27) revealed that driver age was significantly correlated with the number of Lane Excursions, the percent of subjects exhibiting Lane Excursions and the percent of texting time in Lane Excursions. In contrast, Multiple Regression analysis of those drivers who self-identified as not highly skilled texters (N=23) revealed that text task duration was significantly correlated with the number of Lane Excursions. The present studies confirm past reports that texting impairs driving simulator performance. Moreover, the present study demonstrates that for highly skilled texters, the effects of texting on driving are actually worse for older drivers. Given the increasing frequency of texting while driving within virtually all age groups, these data suggest that 'no texting while driving' education and public service messages need to be continued, and they should be expanded to target older drivers as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

K-12 System Reforms across Studies: The Significance of Change, Meta-Analysis, and Logistics Regression

ERIC Educational Resources Information Center

Almutairi, Mashal

2013-01-01

The main purpose of this research was to survey the literature about the U.S. education system and synthesize the important conclusions that could be identified as the main features of the education system in general as they relate to student achievement. The criteria were set and the meta-analysis procedures were carefully followed. This process…

Orthodontic bracket bonding without previous adhesive priming: A meta-regression analysis.

PubMed

Altmann, Aline Segatto Pires; Degrazia, Felipe Weidenbach; Celeste, Roger Keller; Leitune, Vicente Castelo Branco; Samuel, Susana Maria Werner; Collares, Fabrício Mezzomo

2016-05-01

To determine the consensus among studies that adhesive resin application improves the bond strength of orthodontic brackets and the association of methodological variables on the influence of bond strength outcome. In vitro studies were selected to answer whether adhesive resin application increases the immediate shear bond strength of metal orthodontic brackets bonded with a photo-cured orthodontic adhesive. Studies included were those comparing a group having adhesive resin to a group without adhesive resin with the primary outcome measurement shear bond strength in MPa. A systematic electronic search was performed in PubMed and Scopus databases. Nine studies were included in the analysis. Based on the pooled data and due to a high heterogeneity among studies (I(2)  =  93.3), a meta-regression analysis was conducted. The analysis demonstrated that five experimental conditions explained 86.1% of heterogeneity and four of them had significantly affected in vitro shear bond testing. The shear bond strength of metal brackets was not significantly affected when bonded with adhesive resin, when compared to those without adhesive resin. The adhesive resin application can be set aside during metal bracket bonding to enamel regardless of the type of orthodontic adhesive used.

Laboratory test variables useful for distinguishing upper from lower gastrointestinal bleeding.

PubMed

Tomizawa, Minoru; Shinozaki, Fuminobu; Hasegawa, Rumiko; Shirai, Yoshinori; Motoyoshi, Yasufumi; Sugiyama, Takao; Yamamoto, Shigenori; Ishige, Naoki

2015-05-28

To distinguish upper from lower gastrointestinal (GI) bleeding. Patient records between April 2011 and March 2014 were analyzed retrospectively (3296 upper endoscopy, and 1520 colonoscopy). Seventy-six patients had upper GI bleeding (Upper group) and 65 had lower GI bleeding (Lower group). Variables were compared between the groups using one-way analysis of variance. Logistic regression was performed to identify variables significantly associated with the diagnosis of upper vs lower GI bleeding. Receiver-operator characteristic (ROC) analysis was performed to determine the threshold value that could distinguish upper from lower GI bleeding. Hemoglobin (P = 0.023), total protein (P = 0.0002), and lactate dehydrogenase (P = 0.009) were significantly lower in the Upper group than in the Lower group. Blood urea nitrogen (BUN) was higher in the Upper group than in the Lower group (P = 0.0065). Logistic regression analysis revealed that BUN was most strongly associated with the diagnosis of upper vs lower GI bleeding. ROC analysis revealed a threshold BUN value of 21.0 mg/dL, with a specificity of 93.0%. The threshold BUN value for distinguishing upper from lower GI bleeding was 21.0 mg/dL.

Laboratory test variables useful for distinguishing upper from lower gastrointestinal bleeding

PubMed Central

Tomizawa, Minoru; Shinozaki, Fuminobu; Hasegawa, Rumiko; Shirai, Yoshinori; Motoyoshi, Yasufumi; Sugiyama, Takao; Yamamoto, Shigenori; Ishige, Naoki

2015-01-01

AIM: To distinguish upper from lower gastrointestinal (GI) bleeding. METHODS: Patient records between April 2011 and March 2014 were analyzed retrospectively (3296 upper endoscopy, and 1520 colonoscopy). Seventy-six patients had upper GI bleeding (Upper group) and 65 had lower GI bleeding (Lower group). Variables were compared between the groups using one-way analysis of variance. Logistic regression was performed to identify variables significantly associated with the diagnosis of upper vs lower GI bleeding. Receiver-operator characteristic (ROC) analysis was performed to determine the threshold value that could distinguish upper from lower GI bleeding. RESULTS: Hemoglobin (P = 0.023), total protein (P = 0.0002), and lactate dehydrogenase (P = 0.009) were significantly lower in the Upper group than in the Lower group. Blood urea nitrogen (BUN) was higher in the Upper group than in the Lower group (P = 0.0065). Logistic regression analysis revealed that BUN was most strongly associated with the diagnosis of upper vs lower GI bleeding. ROC analysis revealed a threshold BUN value of 21.0 mg/dL, with a specificity of 93.0%. CONCLUSION: The threshold BUN value for distinguishing upper from lower GI bleeding was 21.0 mg/dL. PMID:26034359

p.Q192R SNP of PON1 seems not to be Associated with Carotid Atherosclerosis Risk Factors in an Asymptomatic and Normolipidemic Brazilian Population Sample

PubMed Central

Scherrer, Daniel Zanetti; Zago, Vanessa Helena de Souza; Vieira, Isabela Calanca; Parra, Eliane Soler; Panzoldo, Natália Baratella; Alexandre, Fernanda; Secolin, Rodrigo; Baracat, Jamal; Quintão, Eder Carlos Rocha; de Faria, Eliana Cotta

2015-01-01

Background Evidences suggest that paraoxonase 1 (PON1) confers important antioxidant and anti-inflammatory properties when associated with high-density lipoprotein (HDL). Objective To investigate the relationships between p.Q192R SNP of PON1, biochemical parameters and carotid atherosclerosis in an asymptomatic, normolipidemic Brazilian population sample. Methods We studied 584 volunteers (females n = 326, males n = 258; 19-75 years of age). Total genomic DNA was extracted and SNP was detected in the TaqMan® SNP OpenArray® genotyping platform (Applied Biosystems, Foster City, CA). Plasma lipoproteins and apolipoproteins were determined and PON1 activity was measured using paraoxon as a substrate. High-resolution β-mode ultrasonography was used to measure cIMT and the presence of carotid atherosclerotic plaques in a subgroup of individuals (n = 317). Results The presence of p.192Q was associated with a significant increase in PON1 activity (RR = 12.30 (11.38); RQ = 46.96 (22.35); QQ = 85.35 (24.83) μmol/min; p < 0.0001), HDL-C (RR= 45 (37); RQ = 62 (39); QQ = 69 (29) mg/dL; p < 0.001) and apo A-I (RR = 140.76 ± 36.39; RQ = 147.62 ± 36.92; QQ = 147.49 ± 36.65 mg/dL; p = 0.019). Stepwise regression analysis revealed that heterozygous and p.192Q carriers influenced by 58% PON1 activity towards paraoxon. The univariate linear regression analysis demonstrated that p.Q192R SNP was not associated with mean cIMT; as a result, in the multiple regression analysis, no variables were selected with 5% significance. In logistic regression analysis, the studied parameters were not associated with the presence of carotid plaques. Conclusion In low-risk individuals, the presence of the p.192Q variant of PON1 is associated with a beneficial plasma lipid profile but not with carotid atherosclerosis. PMID:26039660

Clinical benefit from pharmacological elevation of high-density lipoprotein cholesterol: meta-regression analysis.

PubMed

Hourcade-Potelleret, F; Laporte, S; Lehnert, V; Delmar, P; Benghozi, Renée; Torriani, U; Koch, R; Mismetti, P

2015-06-01

Epidemiological evidence that the risk of coronary heart disease is inversely associated with the level of high-density lipoprotein cholesterol (HDL-C) has motivated several phase III programmes with cholesteryl ester transfer protein (CETP) inhibitors. To assess alternative methods to predict clinical response of CETP inhibitors. Meta-regression analysis on raising HDL-C drugs (statins, fibrates, niacin) in randomised controlled trials. 51 trials in secondary prevention with a total of 167,311 patients for a follow-up >1 year where HDL-C was measured at baseline and during treatment. The meta-regression analysis showed no significant association between change in HDL-C (treatment vs comparator) and log risk ratio (RR) of clinical endpoint (non-fatal myocardial infarction or cardiac death). CETP inhibitors data are consistent with this finding (RR: 1.03; P5-P95: 0.99-1.21). A prespecified sensitivity analysis by drug class suggested that the strength of relationship might differ between pharmacological groups. A significant association for both statins (p<0.02, log RR=-0.169-0.0499*HDL-C change, R(2)=0.21) and niacin (p=0.02, log RR=1.07-0.185*HDL-C change, R(2)=0.61) but not fibrates (p=0.18, log RR=-0.367+0.077*HDL-C change, R(2)=0.40) was shown. However, the association was no longer detectable after adjustment for low-density lipoprotein cholesterol for statins or exclusion of open trials for niacin. Meta-regression suggested that CETP inhibitors might not influence coronary risk. The relation between change in HDL-C level and clinical endpoint may be drug dependent, which limits the use of HDL-C as a surrogate marker of coronary events. Other markers of HDL function may be more relevant. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

p.Q192R SNP of PON1 seems not to be Associated with Carotid Atherosclerosis Risk Factors in an Asymptomatic and Normolipidemic Brazilian Population Sample.

PubMed

Scherrer, Daniel Zanetti; Zago, Vanessa Helena de Souza; Vieira, Isabela Calanca; Parra, Eliane Soler; Panzoldo, Natália Baratella; Alexandre, Fernanda; Secolin, Rodrigo; Baracat, Jamal; Quintão, Eder Carlos Rocha; Faria, Eliana Cotta de

2015-07-01

Evidences suggest that paraoxonase 1 (PON1) confers important antioxidant and anti-inflammatory properties when associated with high-density lipoprotein (HDL). To investigate the relationships between p.Q192R SNP of PON1, biochemical parameters and carotid atherosclerosis in an asymptomatic, normolipidemic Brazilian population sample. We studied 584 volunteers (females n = 326, males n = 258; 19-75 years of age). Total genomic DNA was extracted and SNP was detected in the TaqMan® SNP OpenArray® genotyping platform (Applied Biosystems, Foster City, CA). Plasma lipoproteins and apolipoproteins were determined and PON1 activity was measured using paraoxon as a substrate. High-resolution β-mode ultrasonography was used to measure cIMT and the presence of carotid atherosclerotic plaques in a subgroup of individuals (n = 317). The presence of p.192Q was associated with a significant increase in PON1 activity (RR = 12.30 (11.38); RQ = 46.96 (22.35); QQ = 85.35 (24.83) μmol/min; p < 0.0001), HDL-C (RR= 45 (37); RQ = 62 (39); QQ = 69 (29) mg/dL; p < 0.001) and apo A-I (RR = 140.76 ± 36.39; RQ = 147.62 ± 36.92; QQ = 147.49 ± 36.65 mg/dL; p = 0.019). Stepwise regression analysis revealed that heterozygous and p.192Q carriers influenced by 58% PON1 activity towards paraoxon. The univariate linear regression analysis demonstrated that p.Q192R SNP was not associated with mean cIMT; as a result, in the multiple regression analysis, no variables were selected with 5% significance. In logistic regression analysis, the studied parameters were not associated with the presence of carotid plaques. In low-risk individuals, the presence of the p.192Q variant of PON1 is associated with a beneficial plasma lipid profile but not with carotid atherosclerosis.

Neuropsychometric tests in cross sectional and longitudinal studies - a regression analysis of ADAS - cog, SKT and MMSE.

PubMed

Ihl, R; Grass-Kapanke, B; Jänner, M; Weyer, G

1999-11-01

In clinical and drug studies, different neuropsychometric tests are used. So far, no empirical data have been published to compare studies using different tests. The purpose of this study was to calculate a regression formula allowing a comparison of cross-sectional and longitudinal data from three neuropsychometric tests that are frequently used in drug studies (Alzheimer's Disease Assessment Scale, ADAS-cog; Syndrom Kurz Test, SKT; Mini Mental State Examination, MMSE). 177 patients with dementia according to ICD10 criteria were studied for the cross sectional and 61 for the longitudinal analysis. Correlations and linear regressions were calculated between tests. Significance was proven with ANOVA and t-tests using the SPSS statistical package. Significant Spearman correlations and slopes in the regression occurred in the cross sectional analysis (ADAS-cog-SKT r(s) = 0.77, slope = 0.45, SKT-ADAS-cog slope = 1.3, r2 = 0.59; ADAS-cog-MMSE r2 = 0.76, slope = -0.42, MMSE-ADAS-cog slope = -1.5, r2 = 0.64; MMSE-SKT r(s) = -0.79, slope = -0.87, SKT-MMSE slope = -0.71, r2 = 0.62; p<0.001 after Bonferroni correction; N = 177) and in the longitudinal analysis (SKT-ADAS-cog, r(s) = 0.48, slope = 0.69, ADAS-cog-SKT slope = 0.69, p<0.001, r2 = 0.32, MMSE-SKT, r(s) = 0.44, slope = -0.41, SKT-MMSE, slope = -0.55, p<0.001, r2 = 0.21). The results allow calculation of ADAS-scores when SKT scores are given, and vice versa. In longitudinal studies or in the course of the disease, scores assessed with the ADAS-cog and the SKT may now be statistically compared. In all comparisons, bottom and ceiling effects of the tests have to be taken into account.

Quantitative genetic analysis of the body composition and blood pressure association in two ethnically diverse populations.

PubMed

Ghosh, Sudipta; Dosaev, Tasbulat; Prakash, Jai; Livshits, Gregory

2017-04-01

The major aim of this study was to conduct comparative quantitative-genetic analysis of the body composition (BCP) and somatotype (STP) variation, as well as their correlations with blood pressure (BP) in two ethnically, culturally and geographically different populations: Santhal, indigenous ethnic group from India and Chuvash, indigenous population from Russia. Correspondently two pedigree-based samples were collected from 1,262 Santhal and1,558 Chuvash individuals, respectively. At the first stage of the study, descriptive statistics and a series of univariate regression analyses were calculated. Finally, multiple and multivariate regression (MMR) analyses, with BP measurements as dependent variables and age, sex, BCP and STP as independent variables were carried out in each sample separately. The significant and independent covariates of BP were identified and used for re-examination in pedigree-based variance decomposition analysis. Despite clear and significant differences between the populations in BCP/STP, both Santhal and Chuvash were found to be predominantly mesomorphic irrespective of their sex. According to MMR analyses variation of BP significantly depended on age and mesomorphic component in both samples, and in addition on sex, ectomorphy and fat mass index in Santhal and on fat free mass index in Chuvash samples, respectively. Additive genetic component contributes to a substantial proportion of blood pressure and body composition variance. Variance component analysis in addition to above mentioned results suggests that additive genetic factors influence BP and BCP/STP associations significantly. © 2017 Wiley Periodicals, Inc.

Using Dominance Analysis to Determine Predictor Importance in Logistic Regression

ERIC Educational Resources Information Center

Azen, Razia; Traxel, Nicole

2009-01-01

This article proposes an extension of dominance analysis that allows researchers to determine the relative importance of predictors in logistic regression models. Criteria for choosing logistic regression R[superscript 2] analogues were determined and measures were selected that can be used to perform dominance analysis in logistic regression. A…

Influence of ozone and meteorological parameters on levels of polycyclic aromatic hydrocarbons in the air

NASA Astrophysics Data System (ADS)

Pehnec, Gordana; Jakovljević, Ivana; Šišović, Anica; Bešlić, Ivan; Vađić, Vladimira

2016-04-01

Concentrations of ten polycyclic aromatic hydrocarbons (PAHs) in the PM10 particle fraction were measured together with ozone and meteorological parameters at an urban site (Zagreb, Croatia) over a one-year period. Data were subjected to regression analysis in order to determine the relationship between the measured pollutants and selected meteorological variables. All of the PAHs showed seasonal variations with high concentrations in winter and autumn and very low concentrations during summer and spring. All of the ten PAHs concentrations also correlated well with each other. A statistically significant negative correlation was found between the concentrations of PAHs and ozone concentrations and concentrations of PAHs and temperature, as well as a positive correlation between concentrations of PAHs and PM10 mass concentration and relative humidity. Multiple regression analysis showed that concentrations of PM10 and ozone, temperature, relative humidity and pressure accounted for 43-70% of PAHs variability. Concentrations of PM10 and temperature were significant variables for all of the measured PAH's concentrations in all seasons. Ozone concentrations were significant for only some of the PAHs, particularly 6-ring PAHs.

Correlates of HIV knowledge and Sexual risk behaviors among Female Military Personnel

PubMed Central

Essien, E. James; Monjok, Emmanuel; Chen, Hua; Abughosh, Susan; Ekong, Ernest; Peters, Ronald J.; Holmes, Laurens; Holstad, Marcia M.; Mgbere, Osaro

2010-01-01

Objective Uniformed services personnel are at an increased risk of HIV infection. We examined the HIV/AIDS knowledge and sexual risk behaviors among female military personnel to determine the correlates of HIV risk behaviors in this population. Method The study used a cross-sectional design to examine HIV/AIDS knowledge and sexual risk behaviors in a sample of 346 females drawn from two military cantonments in Southwestern Nigeria. Data was collected between 2006 and 2008. Using bivariate analysis and multivariate logistic regression, HIV/AIDS knowledge and sexual behaviors were described in relation to socio-demographic characteristics of the participants. Results Multivariate logistic regression analysis revealed that level of education and knowing someone with HIV/AIDS were significant (p<0.05) predictors of HIV knowledge in this sample. HIV prevention self-efficacy was significantly (P<0.05) predicted by annual income and race/ethnicity. Condom use attitudes were also significantly (P<0.05) associated with number of children, annual income, and number of sexual partners. Conclusion Data indicates the importance of incorporating these predictor variables into intervention designs. PMID:20387111

Utility-Based Instruments for People with Dementia: A Systematic Review and Meta-Regression Analysis.

PubMed

Li, Li; Nguyen, Kim-Huong; Comans, Tracy; Scuffham, Paul

2018-04-01

Several utility-based instruments have been applied in cost-utility analysis to assess health state values for people with dementia. Nevertheless, concerns and uncertainty regarding their performance for people with dementia have been raised. To assess the performance of available utility-based instruments for people with dementia by comparing their psychometric properties and to explore factors that cause variations in the reported health state values generated from those instruments by conducting meta-regression analyses. A literature search was conducted and psychometric properties were synthesized to demonstrate the overall performance of each instrument. When available, health state values and variables such as the type of instrument and cognitive impairment levels were extracted from each article. A meta-regression analysis was undertaken and available covariates were included in the models. A total of 64 studies providing preference-based values were identified and included. The EuroQol five-dimension questionnaire demonstrated the best combination of feasibility, reliability, and validity. Meta-regression analyses suggested that significant differences exist between instruments, type of respondents, and mode of administration and the variations in estimated utility values had influences on incremental quality-adjusted life-year calculation. This review finds that the EuroQol five-dimension questionnaire is the most valid utility-based instrument for people with dementia, but should be replaced by others under certain circumstances. Although no utility estimates were reported in the article, the meta-regression analyses that examined variations in utility estimates produced by different instruments impact on cost-utility analysis, potentially altering the decision-making process in some circumstances. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis

NASA Astrophysics Data System (ADS)

Oguntunde, Philip G.; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease ( P < 0.001) in rice yield, pan evaporation, solar radiation, and wind speed declined significantly. Eight principal components exhibited an eigenvalue > 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.

Depression-related differences in lean body mass distribution from National Health and Nutrition Examination Survey 2005-2006.

PubMed

Li, Ying; Meng, Lu; Li, Yue; Sato, Yasuto

2014-03-01

Although the association between depression and body composition has been widely discussed, the effects of depression on lean body mass (LBM) are unclear. The present study aimed to investigate the association of depression with LBM. The study included 2406 participants aged 18-69 years. The sex and body mass index (BMI) stratified analysis of covariance was performed to compare total LBM and percentage LBM (%LBM) in subjects with different depression score levels. Multiple linear regression analysis was conducted to estimate the association between depression score and serum albumin level. An analysis of covariance stratified by sex showed that participants with moderate-to-severe depression had significantly decreased total LBM and total and regional %LBM in men, except for total LBM and percentage gynoid LBM, which was observed in women. In the BMI stratified analysis of covariance, depression was significantly associated with decreased total and regional %LBM and with increased total and regional percentage fat body mass. In people with BMI≥25kg/m(2), the associations between depression or depressive syndrome and LBM, and total and regional %LBM are stronger compared to those with BMI<25kg/m(2). Multiple linear regression analysis showed that depression score was significantly negatively associated with serum albumin level. This is a cross-sectional study based on a general population, some information about clinical diagnosis and medication use is not available. Depression had a significant negative association with LBM and serum albumin level. Copyright © 2014 Elsevier B.V. All rights reserved.

Initial depressive episodes affect the risk of suicide attempts in Korean patients with bipolar disorder.

PubMed

Ryu, Vin; Jon, Duk-In; Cho, Hyun Sang; Kim, Se Joo; Lee, Eun; Kim, Eun Joo; Seok, Jeong-Ho

2010-09-01

Suicide is a major concern for increasing mortality in bipolar patients, but risk factors for suicide in bipolar disorder remain complex, including Korean patients. Medical records of bipolar patients were retrospectively reviewed to detect significant clinical characteristics associated with suicide attempts. A total of 579 medical records were retrospectively reviewed. Bipolar patients were divided into two groups with the presence of a history of suicide attempts. We compared demographic characteristics and clinical features between the two groups using an analysis of covariance and chi-square tests. Finally, logistic regression was performed to evaluate significant risk factors associated with suicide attempts in bipolar disorder. The prevalence of suicide attempt was 13.1% in our patient group. The presence of a depressive first episode was significantly different between attempters and nonattempters. Logistic regression analysis revealed that depressive first episodes and bipolar II disorder were significantly associated with suicide attempts in those patients. Clinicians should consider the polarity of the first mood episode when evaluating suicide risk in bipolar patients. This study has some limitations as a retrospective study and further studies with a prospective design are needed to replicate and evaluate risk factors for suicide in patients with bipolar disorder.

Outcomes of an intervention to improve hospital antibiotic prescribing: interrupted time series with segmented regression analysis.

PubMed

Ansari, Faranak; Gray, Kirsteen; Nathwani, Dilip; Phillips, Gabby; Ogston, Simon; Ramsay, Craig; Davey, Peter

2003-11-01

To evaluate an intervention to reduce inappropriate use of key antibiotics with interrupted time series analysis. The intervention is a policy for appropriate use of Alert Antibiotics (carbapenems, glycopeptides, amphotericin, ciprofloxacin, linezolid, piperacillin-tazobactam and third-generation cephalosporins) implemented through concurrent, patient-specific feedback by clinical pharmacists. Statistical significance and effect size were calculated by segmented regression analysis of interrupted time series of drug use and cost for 2 years before and after the intervention started. Use of Alert Antibiotics increased before the intervention started but decreased steadily for 2 years thereafter. The changes in slope of the time series were 0.27 defined daily doses/100 bed-days per month (95% CI 0.19-0.34) and pound 1908 per month (95% CI pound 1238- pound 2578). The cost of development, dissemination and implementation of the intervention ( pound 20133) was well below the most conservative estimate of the reduction in cost ( pound 133296), which is the lower 95% CI of effect size assuming that cost would not have continued to increase without the intervention. However, if use had continued to increase, the difference between predicted and actual cost of Alert Antibiotics was pound 572448 (95% CI pound 435696- pound 709176) over the 24 months after the intervention started. Segmented regression analysis of pharmacy stock data is a simple, practical and robust method for measuring the impact of interventions to change prescribing. The Alert Antibiotic Monitoring intervention was associated with significant decreases in total use and cost in the 2 years after the programme was implemented. In our hospital, the value of the data far exceeded the cost of processing and analysis.

Impact of Uncertainties in Exposure Assessment on Thyroid Cancer Risk among Persons in Belarus Exposed as Children or Adolescents Due to the Chernobyl Accident.

PubMed

Little, Mark P; Kwon, Deukwoo; Zablotska, Lydia B; Brenner, Alina V; Cahoon, Elizabeth K; Rozhko, Alexander V; Polyanskaya, Olga N; Minenko, Victor F; Golovanov, Ivan; Bouville, André; Drozdovitch, Vladimir

2015-01-01

The excess incidence of thyroid cancer in Ukraine and Belarus observed a few years after the Chernobyl accident is considered to be largely the result of 131I released from the reactor. Although the Belarus thyroid cancer prevalence data has been previously analyzed, no account was taken of dose measurement error. We examined dose-response patterns in a thyroid screening prevalence cohort of 11,732 persons aged under 18 at the time of the accident, diagnosed during 1996-2004, who had direct thyroid 131I activity measurement, and were resident in the most radio-actively contaminated regions of Belarus. Three methods of dose-error correction (regression calibration, Monte Carlo maximum likelihood, Bayesian Markov Chain Monte Carlo) were applied. There was a statistically significant (p<0.001) increasing dose-response for prevalent thyroid cancer, irrespective of regression-adjustment method used. Without adjustment for dose errors the excess odds ratio was 1.51 Gy- (95% CI 0.53, 3.86), which was reduced by 13% when regression-calibration adjustment was used, 1.31 Gy- (95% CI 0.47, 3.31). A Monte Carlo maximum likelihood method yielded an excess odds ratio of 1.48 Gy- (95% CI 0.53, 3.87), about 2% lower than the unadjusted analysis. The Bayesian method yielded a maximum posterior excess odds ratio of 1.16 Gy- (95% BCI 0.20, 4.32), 23% lower than the unadjusted analysis. There were borderline significant (p = 0.053-0.078) indications of downward curvature in the dose response, depending on the adjustment methods used. There were also borderline significant (p = 0.102) modifying effects of gender on the radiation dose trend, but no significant modifying effects of age at time of accident, or age at screening as modifiers of dose response (p>0.2). In summary, the relatively small contribution of unshared classical dose error in the current study results in comparatively modest effects on the regression parameters.

Resection of complex pancreatic injuries: Benchmarking postoperative complications using the Accordion classification

PubMed Central

Krige, Jake E; Jonas, Eduard; Thomson, Sandie R; Kotze, Urda K; Setshedi, Mashiko; Navsaria, Pradeep H; Nicol, Andrew J

2017-01-01

AIM To benchmark severity of complications using the Accordion Severity Grading System (ASGS) in patients undergoing operation for severe pancreatic injuries. METHODS A prospective institutional database of 461 patients with pancreatic injuries treated from 1990 to 2015 was reviewed. One hundred and thirty patients with AAST grade 3, 4 or 5 pancreatic injuries underwent resection (pancreatoduodenectomy, n = 20, distal pancreatectomy, n = 110), including 30 who had an initial damage control laparotomy (DCL) and later definitive surgery. AAST injury grades, type of pancreatic resection, need for DCL and incidence and ASGS severity of complications were assessed. Uni- and multivariate logistic regression analysis was applied. RESULTS Overall 238 complications occurred in 95 (73%) patients of which 73% were ASGS grades 3-6. Nineteen patients (14.6%) died. Patients more likely to have complications after pancreatic resection were older, had a revised trauma score (RTS) < 7.8, were shocked on admission, had grade 5 injuries of the head and neck of the pancreas with associated vascular and duodenal injuries, required a DCL, received a larger blood transfusion, had a pancreatoduodenectomy (PD) and repeat laparotomies. Applying univariate logistic regression analysis, mechanism of injury, RTS < 7.8, shock on admission, DCL, increasing AAST grade and type of pancreatic resection were significant variables for complications. Multivariate logistic regression analysis however showed that only age and type of pancreatic resection (PD) were significant. CONCLUSION This ASGS-based study benchmarked postoperative morbidity after pancreatic resection for trauma. The detailed outcome analysis provided may serve as a reference for future institutional comparisons. PMID:28396721

The impact of mother's literacy on child dental caries: Individual data or aggregate data analysis?

PubMed

Haghdoost, Ali-Akbar; Hessari, Hossein; Baneshi, Mohammad Reza; Rad, Maryam; Shahravan, Arash

2017-01-01

To evaluate the impact of mother's literacy on child dental caries based on a national oral health survey in Iran and to investigate the possibility of ecological fallacy in aggregate data analysis. Existing data were from second national oral health survey that was carried out in 2004, which including 8725 6 years old participants. The association of mother's literacy with caries occurrence (DMF (Decayed, Missing, Filling) total score >0) of her child was assessed using individual data by logistic regression model. Then the association of the percentages of mother's literacy and the percentages of decayed teeth in each 30 provinces of Iran was assessed using aggregated data retrieved from the data of second national oral health survey of Iran and alternatively from census of "Statistical Center of Iran" using linear regression model. The significance level was set at 0.05 for all analysis. Individual data analysis showed a statistically significant association between mother's literacy and decayed teeth of children ( P = 0.02, odds ratio = 0.83). There were not statistical significant association between mother's literacy and child dental caries in aggregate data analysis of oral health survey ( P = 0.79, B = 0.03) and census of "Statistical Center of Statistics" ( P = 0.60, B = 0.14). Literate mothers have a preventive effect on occurring dental caries of children. According to the high percentage of illiterate parents in Iran, it's logical to consider suitable methods of oral health education which do not need reading or writing. Aggregate data analysis and individual data analysis had completely different results in this study.

Individual memory change after anterior temporal lobectomy: a base rate analysis using regression-based outcome methodology.

PubMed

Martin, R C; Sawrie, S M; Roth, D L; Gilliam, F G; Faught, E; Morawetz, R B; Kuzniecky, R

1998-10-01

To characterize patterns of base rate change on measures of verbal and visual memory after anterior temporal lobectomy (ATL) using a newly developed regression-based outcome methodology that accounts for effects of practice and regression towards the mean, and to comment on the predictive utility of baseline memory measures on postoperative memory outcome. Memory change was operationalized using regression-based change norms in a group of left (n = 53) and right (n = 48) ATL patients. All patients were administered tests of episodic verbal (prose recall, list learning) and visual (figure reproduction) memory, and semantic memory before and after ATL. ATL patients displayed a wide range of memory outcome across verbal and visual memory domains. Significant performance declines were noted for 25-50% of left ATL patients on verbal semantic and episodic memory tasks, while one-third of right ATL patients displayed significant declines in immediate and delayed episodic prose recall. Significant performance improvement was noted in an additional one-third of right ATL patients on delayed prose recall. Base rate change was similar between the two ATL groups across immediate and delayed visual memory. Approximately one-fourth of all patients displayed clinically meaningful losses on the visual memory task following surgery. Robust relationships between preoperative memory measures and nonstandardized change scores were attenuated or reversed using standardized memory outcome techniques. Our results demonstrated substantial group variability in memory outcome for ATL patients. These results extend previous research by incorporating known effects of practice and regression to the mean when addressing meaningful neuropsychological change following epilepsy surgery. Our findings also suggest that future neuropsychological outcome studies should take steps towards controlling for regression-to-the-mean before drawing predictive conclusions.

Total body weight loss of ≥ 10 % is associated with improved hepatic fibrosis in patients with nonalcoholic steatohepatitis.

PubMed

Glass, Lisa M; Dickson, Rolland C; Anderson, Joseph C; Suriawinata, Arief A; Putra, Juan; Berk, Brian S; Toor, Arifa

2015-04-01

Given the rising epidemics of obesity and metabolic syndrome, nonalcoholic steatohepatitis (NASH) is now the most common cause of liver disease in the developed world. Effective treatment for NASH, either to reverse or prevent the progression of hepatic fibrosis, is currently lacking. To define the predictors associated with improved hepatic fibrosis in NASH patients undergoing serial liver biopsies at prolonged biopsy interval. This is a cohort study of 45 NASH patients undergoing serial liver biopsies for clinical monitoring in a tertiary care setting. Biopsies were scored using the NASH Clinical Research Network guidelines. Fibrosis regression was defined as improvement in fibrosis score ≥1 stage. Univariate analysis utilized Fisher's exact or Student's t test. Multivariate regression models determined independent predictors for regression of fibrosis. Forty-five NASH patients with biopsies collected at a mean interval of 4.6 years (±1.4) were included. The mean initial fibrosis stage was 1.96, two patients had cirrhosis and 12 patients (26.7 %) underwent bariatric surgery. There was a significantly higher rate of fibrosis regression among patients who lost ≥10 % total body weight (TBW) (63.2 vs. 9.1 %; p = 0.001) and who underwent bariatric surgery (47.4 vs. 4.5 %; p = 0.003). Factors such as age, gender, glucose intolerance, elevated ferritin, and A1AT heterozygosity did not influence fibrosis regression. On multivariate analysis, only weight loss of ≥10 % TBW predicted fibrosis regression [OR 8.14 (CI 1.08-61.17)]. Results indicate that regression of fibrosis in NASH is possible, even in advanced stages. Weight loss of ≥10 % TBW predicts fibrosis regression.

Prevalence of abortion and stillbirth in a beef cattle system in Southeastern Mexico.

PubMed

Segura-Correa, José C; Segura-Correa, Victor M

2009-12-01

Prenatal mortality is an important cause of production losses in the livestock industry. This study estimates the prevalences of abortion and stillbirth in a beef cattle system and determines the significance of some risk factors, in the tropics of Mexico. Data were obtained from a Zebu cattle herd and their crosses with Bos taurus breeds, in Yucatan, Mexico. The logit of the probability of an abortion or stillbirth was modeled using binary logistic regression. The risk factors tested were: year of abortion (or calving), season of abortion (or calving), parity number and dam breed group. The effect of twins on stillbirth was tested using Fisher exact test. Of the 4175 calvings studied 49 were abortions (1.17%). Significant factors in the logistic regression analysis for abortions were season of abortion and parity number. The risk of abortion was lower in the dry seasons compared to the rainy and windy seasons (P = 0.009). The risk of abortion was higher in second parity cows followed by the third and first parity cows, as compared to older cows (P = 0.015). Of the 4126 births, 87 were stillbirths (2.11%). Significant factors in the logistic regression analysis for stillbirth were year of calving (P = 0.0001) and parity number (P < 0.001). The risk of stillbirth in first parity cows was 2.6 times that of old cows. Of the total births, 15 were twins (0.36%) of which 7 were born dead calves. Herd owners must focus on the significant risk factors under their control to reduce the prevalence of prenatal mortality.

Knowledge, attitudes and practices survey on organ donation among a selected adult population of Pakistan

PubMed Central

Saleem, Taimur; Ishaque, Sidra; Habib, Nida; Hussain, Syedda Saadia; Jawed, Areeba; Khan, Aamir Ali; Ahmad, Muhammad Imran; Iftikhar, Mian Omer; Mughal, Hamza Pervez; Jehan, Imtiaz

2009-01-01

Background To determine the knowledge, attitudes and practices regarding organ donation in a selected adult population in Pakistan. Methods Convenience sampling was used to generate a sample of 440; 408 interviews were successfully completed and used for analysis. Data collection was carried out via a face to face interview based on a pre-tested questionnaire in selected public areas of Karachi, Pakistan. Data was analyzed using SPSS v.15 and associations were tested using the Pearson's Chi square test. Multiple logistic regression was used to find independent predictors of knowledge status and motivation of organ donation. Results Knowledge about organ donation was significantly associated with education (p = 0.000) and socioeconomic status (p = 0.038). 70/198 (35.3%) people expressed a high motivation to donate. Allowance of organ donation in religion was significantly associated with the motivation to donate (p = 0.000). Multiple logistic regression analysis revealed that higher level of education and higher socioeconomic status were significant (p < 0.05) independent predictors of knowledge status of organ donation. For motivation, multiple logistic regression revealed that higher socioeconomic status, adequate knowledge score and belief that organ donation is allowed in religion were significant (p < 0.05) independent predictors. Television emerged as the major source of information. Only 3.5% had themselves donated an organ; with only one person being an actual kidney donor. Conclusion Better knowledge may ultimately translate into the act of donation. Effective measures should be taken to educate people with relevant information with the involvement of media, doctors and religious scholars. PMID:19534793

STATISTICAL METHOD FOR DETECTION OF A TREND IN ATMOSPHERIC SULFATE

EPA Science Inventory

Daily atmospheric concentrations of sulfate collected in northeastern Pennsylvania are regressed against meteorological factors, ozone, and time in order to determine if a significant trend in sulfate can be detected. he data used in this analysis were collected during the Sulfat...

Influence of anthropometric parameters on ultrasound measurements of Os calcis.

PubMed

Hans, D; Schott, A M; Arlot, M E; Sornay, E; Delmas, P D; Meunier, P J

1995-01-01

Few data have been published concerning the influence of height, weight and body mass index (BMI) on broadband ultrasound attenuation (BUA), speed of sound (SOS) and Lunar "stiffness" index, and always in small population samples. The first ain of the present cross-sectional study was to determine whether anthropometric factors have a significant influence on ultrasound measurements. The second objective was to establish whether these parameters have real effect on whether their influence is due only to measurement errors. We measured, in 271 healthy French women (mean age 77 +/- 11 years; range 31-97 years), the following parameters: age, height, weight, lean and fat body mass, heel width, foot length, knee height and external malleolus (HEM). Simple linear regression analyses between ultrasound and anthropometric parameters were performed. Age, height, and heel width were significant predictors of SOS; age, height, weight, foot length, heel width, HEM, fat mass and lean mass were significant predictors of BUA; age, height, weight, heel width, HEM, fat mass and lean mass were significant predictors of stiffness. In the multiple regression analysis, once the analysis had been adjusted for age, only heel width was a significant predictor for SOS (p = 0.0007), weight for BUA (p = 0.0001), and weight (p = 0.0001) and heel width (p = 0.004) for the stiffness index. Besides their statistical meaning, the regression coefficients have a more clinically relevant interpretation which is developed in the text. These results confirm the influence of anthropometric factors on the ultrasonic parameter values, because BUA and SOS were in part dependent on heel width and weight. The influence of the position of the transducer on the calcaneus should be taken into account to optimize the methods of measurement using ultrasound.

Regression Analysis to Identify Factors Associated with Urinary Iodine Concentration at the Sub-National Level in India, Ghana, and Senegal

PubMed Central

Knowles, Jacky; Kupka, Roland; Dumble, Sam; Garrett, Greg S.; Pandav, Chandrakant S.; Yadav, Kapil; Touré, Ndeye Khady; Foriwa Amoaful, Esi; Gorstein, Jonathan

2018-01-01

Single and multiple variable regression analyses were conducted using data from stratified, cluster sample design, iodine surveys in India, Ghana, and Senegal to identify factors associated with urinary iodine concentration (UIC) among women of reproductive age (WRA) at the national and sub-national level. Subjects were survey household respondents, typically WRA. For all three countries, UIC was significantly different (p < 0.05) by household salt iodine category. Other significant differences were by strata and by household vulnerability to poverty in India and Ghana. In multiple variable regression analysis, UIC was significantly associated with strata and household salt iodine category in India and Ghana (p < 0.001). Estimated UIC was 1.6 (95% confidence intervals (CI) 1.3, 2.0) times higher (India) and 1.4 (95% CI 1.2, 1.6) times higher (Ghana) among WRA from households using adequately iodised salt than among WRA from households using non-iodised salt. Other significant associations with UIC were found in India, with having heard of iodine deficiency (1.2 times higher; CI 1.1, 1.3; p < 0.001) and having improved dietary diversity (1.1 times higher, CI 1.0, 1.2; p = 0.015); and in Ghana, with the level of tomato paste consumption the previous week (p = 0.029) (UIC for highest consumption level was 1.2 times lowest level; CI 1.1, 1.4). No significant associations were found in Senegal. Sub-national data on iodine status are required to assess equity of access to optimal iodine intake and to develop strategic responses as needed. PMID:29690505

Ozone and sulfur dioxide effects on three tall fescue cultivars

DOE Office of Scientific and Technical Information (OSTI.GOV)

Flagler, R.B.; Youngner, V.B.

Although many reports have been published concerning differential susceptibility of various crops and/or cultivars to air pollutants, most have used foliar injury instead of the marketable yield as the factor that determined susceptibility for the crop. In an examination of screening in terms of marketable yield, three cultivars of tall fescue (Festuca arundinacea Schreb.), 'Alta,' 'Fawn,' and 'Kentucky 31,' were exposed to 0-0.40 ppm O/sub 3/ or 0-0.50 ppm SO/sub 2/ 6 h/d, once a week, for 7 and 9 weeks, respectively. Experimental design was a randomized complete block with three replications. Statistical analysis was by standard analysis of variancemore » and regression techniques. Three variables were analyzed: top dry weight (yield), tiller number, and weight per tiller. Ozone had a significant effect on all three variables. Significant linear decreases in yield and weight per tiller occurred with increasing O/sub 3/ concentrations. Linear regressions of these variables on O/sub 3/ concentration produced significantly different regression coefficients. The coefficient for Kentucky 31 was significantly greater than Alta or Fawn, which did not differ from each other. This indicated that Kentucky 31 was more susceptible to O/sub 3/ than either of the other cultivars. Percent reductions in dry weight for the three cultivars at highest O/sub 3/ level were 35, 44, and 53%, respectively, for Fawn, Alta, and Kentucky 31. For weight per tiller, Kentucky 31 had a higher percent reduction than the other cultivars (59 vs. 46 and 44%). Tiller number was generally increased by O/sub 3/, but this variable was not useful for determining differential susceptibility to the pollutant. Sulfur dioxide treatments produced no significant effects on any of the variables analyzed.« less

Vocal mechanics in Darwin's finches: correlation of beak gape and song frequency.

PubMed

Podos, Jeffrey; Southall, Joel A; Rossi-Santos, Marcos R

2004-02-01

Recent studies of vocal mechanics in songbirds have identified a functional role for the beak in sound production. The vocal tract (trachea and beak) filters harmonic overtones from sounds produced by the syrinx, and birds can fine-tune vocal tract resonance properties through changes in beak gape. In this study, we examine patterns of beak gape during song production in seven species of Darwin's finches of the Galápagos Islands. Our principal goals were to characterize the relationship between beak gape and vocal frequency during song production and to explore the possible influence therein of diversity in beak morphology and body size. Birds were audio and video recorded (at 30 frames s(-1)) as they sang in the field, and 164 song sequences were analyzed. We found that song frequency regressed significantly and positively on beak gape for 38 of 56 individuals and for all seven species examined. This finding provides broad support for a resonance model of vocal tract function in Darwin's finches. Comparison among species revealed significant variation in regression y-intercept values. Body size correlated negatively with y-intercept values, although not at a statistically significant level. We failed to detect variation in regression slopes among finch species, although the regression slopes of Darwin's finch and two North American sparrow species were found to differ. Analysis within one species (Geospiza fortis) revealed significant inter-individual variation in regression parameters; these parameters did not correlate with song frequency features or plumage scores. Our results suggest that patterns of beak use during song production were conserved during the Darwin's finch adaptive radiation, despite the evolution of substantial variation in beak morphology and body size.

[Obesity in Brazilian women: association with parity and socioeconomic status].

PubMed

Ferreira, Regicely Aline Brandão; Benicio, Maria Helena D'Aquino

2015-05-01

To determine the influence of reproductive history on the prevalence of obesity in Brazilian women and the possible modifying effect of socioeconomic variables on the association between parity and excess weight. A retrospective analysis of complex sample data collected as part of the 2006 Brazilian National Survey on Demography and Health, which included a group representative of women of childbearing age in Brazil was conducted. The study included 11 961 women aged 20 to 49 years. The association between the study factor (parity) and the outcome of interest (obesity) was tested using logistic regression analysis. The adjusted effect of parity on obesity was assessed in a multiple regression model containing control variables: age, family purchasing power, as defined by the Brazilian Association of Research Enterprises (ABEP), schooling, and health care. Significance level was set at below 0.05. The prevalence of obesity in the study population was 18.6%. The effect of parity on obesity was significant (P for trend < 0.001). Unadjusted analysis showed a positive association of obesity with parity and age. Family purchase power had a significant odds ratio for obesity only in the unadjusted analysis. In the adjusted model, this variable did not explain obesity. The present findings suggest that parity has an influence on obesity in Brazilian women of childbearing age, with higher prevalence in women vs. without children.

[Effect of occupational stress on mental health].

PubMed

Yu, Shan-fa; Zhang, Rui; Ma, Liang-qing; Gu, Gui-zhen; Yang, Yan; Li, Kui-rong

2003-02-01

To study the effect of job psychological demands and job control on mental health and their interaction. 93 male freight train dispatchers were evaluated by using revised Job Demand-Control Scale and 7 strain scales. Stepwise regression analysis, Univariate ANOVA, Kruskal-Wallis H and Modian methods were used in statistic analysis. Kruskal-Wallis H and Modian methods analysis revealed the difference in mental health scores among groups of decision latitude (mean rank 55.57, 47.95, 48.42, 33.50, P < 0.05), the differences in scores of mental health (37.45, 40.01, 58.35), job satisfaction (53.18, 46.91, 32.43), daily life strains (33.00, 44.96, 56.12) and depression (36.45, 42.25, 53.61) among groups of job time demands (P < 0.05) were all statistically significant. ANOVA showed that job time demands and decision latitude had interaction effects on physical complains (R(2) = 0.24), state-anxiety (R(2) = 0.26), and daytime fatigue (R(2) = 0.28) (P < 0.05). Regression analysis revealed a significant job time demands and job decision latitude interaction effect as well as significant main effects of the some independent variables on different job strains (R(2) > 0.05). Job time demands and job decision latitude have direct and interactive effects on psychosomatic health, the more time demands, the more psychological strains, the effect of job time demands is greater than that of job decision latitude.

Evaluation of ocular movements in patients with dyslexia.

PubMed

Vagge, Aldo; Cavanna, Margherita; Traverso, Carlo Enrico; Iester, Michele

2015-04-01

The aims of this study were to analyze the relationship between dyslexia and eye movements and to assess whether this method can be added to the workup of dyslexic patients. The sample was comprised of 11 children with a diagnosis of dyslexia and 11 normal between 8 and 13 years of age. All subjects underwent orthoptic evaluation, ophthalmological examinations, and eye movement analysis, specifically, stability analysis on fixating a still target, tracking saccades, analysis of fixation pauses, speed reading, saccades, and regressions through the reading of a text. Stability analysis on fixating a still target showed a significant (p < 0.001) difference between the two groups showing an increased amount of loss of fixation among dyslexic subjects (5.36 ± 2.5 s and 0.82 ± 2.1, respectively). Tracking saccades (left and right horizontal axis) did not show a significant difference. When reading parameters were looked into (number of saccades, number of regressions, reading time through the reading of a text), a significant (p < 0.001) difference was found between the groups. This study supports the belief that the alteration of eye movement does not depend on oculo-motor dysfunction but is secondary to a defect in the visual processing of linguistic material. Inclusion of assessment of this defect might prove beneficial in determining the presence of dyslexia in young children at a younger age, and an earlier intervention could be initiated.

Robustness of meta-analyses in finding gene × environment interactions

PubMed Central

Shi, Gang; Nehorai, Arye

2017-01-01

Meta-analyses that synthesize statistical evidence across studies have become important analytical tools for genetic studies. Inspired by the success of genome-wide association studies of the genetic main effect, researchers are searching for gene × environment interactions. Confounders are routinely included in the genome-wide gene × environment interaction analysis as covariates; however, this does not control for any confounding effects on the results if covariate × environment interactions are present. We carried out simulation studies to evaluate the robustness to the covariate × environment confounder for meta-regression and joint meta-analysis, which are two commonly used meta-analysis methods for testing the gene × environment interaction or the genetic main effect and interaction jointly. Here we show that meta-regression is robust to the covariate × environment confounder while joint meta-analysis is subject to the confounding effect with inflated type I error rates. Given vast sample sizes employed in genome-wide gene × environment interaction studies, non-significant covariate × environment interactions at the study level could substantially elevate the type I error rate at the consortium level. When covariate × environment confounders are present, type I errors can be controlled in joint meta-analysis by including the covariate × environment terms in the analysis at the study level. Alternatively, meta-regression can be applied, which is robust to potential covariate × environment confounders. PMID:28362796

Calibration and Data Analysis of the MC-130 Air Balance

NASA Technical Reports Server (NTRS)

Booth, Dennis; Ulbrich, N.

2012-01-01

Design, calibration, calibration analysis, and intended use of the MC-130 air balance are discussed. The MC-130 balance is an 8.0 inch diameter force balance that has two separate internal air flow systems and one external bellows system. The manual calibration of the balance consisted of a total of 1854 data points with both unpressurized and pressurized air flowing through the balance. A subset of 1160 data points was chosen for the calibration data analysis. The regression analysis of the subset was performed using two fundamentally different analysis approaches. First, the data analysis was performed using a recently developed extension of the Iterative Method. This approach fits gage outputs as a function of both applied balance loads and bellows pressures while still allowing the application of the iteration scheme that is used with the Iterative Method. Then, for comparison, the axial force was also analyzed using the Non-Iterative Method. This alternate approach directly fits loads as a function of measured gage outputs and bellows pressures and does not require a load iteration. The regression models used by both the extended Iterative and Non-Iterative Method were constructed such that they met a set of widely accepted statistical quality requirements. These requirements lead to reliable regression models and prevent overfitting of data because they ensure that no hidden near-linear dependencies between regression model terms exist and that only statistically significant terms are included. Finally, a comparison of the axial force residuals was performed. Overall, axial force estimates obtained from both methods show excellent agreement as the differences of the standard deviation of the axial force residuals are on the order of 0.001 % of the axial force capacity.

Weather variability and the incidence of cryptosporidiosis: comparison of time series poisson regression and SARIMA models.

PubMed

Hu, Wenbiao; Tong, Shilu; Mengersen, Kerrie; Connell, Des

2007-09-01

Few studies have examined the relationship between weather variables and cryptosporidiosis in Australia. This paper examines the potential impact of weather variability on the transmission of cryptosporidiosis and explores the possibility of developing an empirical forecast system. Data on weather variables, notified cryptosporidiosis cases, and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics for the period of January 1, 1996-December 31, 2004, respectively. Time series Poisson regression and seasonal auto-regression integrated moving average (SARIMA) models were performed to examine the potential impact of weather variability on the transmission of cryptosporidiosis. Both the time series Poisson regression and SARIMA models show that seasonal and monthly maximum temperature at a prior moving average of 1 and 3 months were significantly associated with cryptosporidiosis disease. It suggests that there may be 50 more cases a year for an increase of 1 degrees C maximum temperature on average in Brisbane. Model assessments indicated that the SARIMA model had better predictive ability than the Poisson regression model (SARIMA: root mean square error (RMSE): 0.40, Akaike information criterion (AIC): -12.53; Poisson regression: RMSE: 0.54, AIC: -2.84). Furthermore, the analysis of residuals shows that the time series Poisson regression appeared to violate a modeling assumption, in that residual autocorrelation persisted. The results of this study suggest that weather variability (particularly maximum temperature) may have played a significant role in the transmission of cryptosporidiosis. A SARIMA model may be a better predictive model than a Poisson regression model in the assessment of the relationship between weather variability and the incidence of cryptosporidiosis.

Examination of Relationships among Organizational Characteristics and Organizational Commitment of Nurses in Western and Eastern Region of Nepal.

PubMed

Joshi, A S; Namba, M; Pokharela, T

2015-01-01

The objective of this study is to identify relationships between three components of organizational commitment and organizational characteristics of nurses in the western and the eastern region of Nepal. A self-administrated questionnaire was used to collect data from 310 nurses currently working at various hospitals in the eastern and the western region of the country. The questionnaire included three sections namely 1) personal characteristics 2) organizational characteristics and 3) organizational commitments scale. Descriptive analysis and multiple regression analysis were performed to identify significance in various relationships. Out of the 240 completed questionnaires, 226 were found valid for analysis. The mean age was 27.4 years. For each depended variable affective, continuance and normative commitment, multiple regression analysis was performed with personal Characteristics and organizational characteristics as independent variables. All independent variables were found significantly related to each of the two dependent variables; affective commitment and normative commitment (R2 adjusted=0.24, p<0.01 and R2 adjusted=0.05, p<0.01 respectively). However, they were not significantly related to the continuance commitment. Both support from boss (β=0.138, p<0.05) and satisfaction with training (β=0.301, p<0.05) were found to be positive and significant with affective commitment. On the other hand, satisfaction with training (β=0.191, p<0.05) was also positive and significant with normative commitment. Since both support from boss and training program were found to be positive and significant with affective commitment, hospitals must encourage supervisors to provide more assistance to the subordinate nurses. Moreover, hospitals should develop more training programs to keep nurses motivated.

Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Logistic LASSO regression for the diagnosis of breast cancer using clinical demographic data and the BI-RADS lexicon for ultrasonography.

PubMed

Kim, Sun Mi; Kim, Yongdai; Jeong, Kuhwan; Jeong, Heeyeong; Kim, Jiyoung

2018-01-01

The aim of this study was to compare the performance of image analysis for predicting breast cancer using two distinct regression models and to evaluate the usefulness of incorporating clinical and demographic data (CDD) into the image analysis in order to improve the diagnosis of breast cancer. This study included 139 solid masses from 139 patients who underwent a ultrasonography-guided core biopsy and had available CDD between June 2009 and April 2010. Three breast radiologists retrospectively reviewed 139 breast masses and described each lesion using the Breast Imaging Reporting and Data System (BI-RADS) lexicon. We applied and compared two regression methods-stepwise logistic (SL) regression and logistic least absolute shrinkage and selection operator (LASSO) regression-in which the BI-RADS descriptors and CDD were used as covariates. We investigated the performances of these regression methods and the agreement of radiologists in terms of test misclassification error and the area under the curve (AUC) of the tests. Logistic LASSO regression was superior (P<0.05) to SL regression, regardless of whether CDD was included in the covariates, in terms of test misclassification errors (0.234 vs. 0.253, without CDD; 0.196 vs. 0.258, with CDD) and AUC (0.785 vs. 0.759, without CDD; 0.873 vs. 0.735, with CDD). However, it was inferior (P<0.05) to the agreement of three radiologists in terms of test misclassification errors (0.234 vs. 0.168, without CDD; 0.196 vs. 0.088, with CDD) and the AUC without CDD (0.785 vs. 0.844, P<0.001), but was comparable to the AUC with CDD (0.873 vs. 0.880, P=0.141). Logistic LASSO regression based on BI-RADS descriptors and CDD showed better performance than SL in predicting the presence of breast cancer. The use of CDD as a supplement to the BI-RADS descriptors significantly improved the prediction of breast cancer using logistic LASSO regression.

Factors Associated With Work Ability in Patients Undergoing Surgery for Cervical Radiculopathy.

PubMed

Ng, Eunice; Johnston, Venerina; Wibault, Johanna; Löfgren, Håkan; Dedering, Åsa; Öberg, Birgitta; Zsigmond, Peter; Peolsson, Anneli

2015-08-15

Cross-sectional study. To investigate the factors associated with work ability in patients undergoing surgery for cervical radiculopathy. Surgery is a common treatment of cervical radiculopathy in people of working age. However, few studies have investigated the impact on the work ability of these patients. Patients undergoing surgery for cervical radiculopathy (n = 201) were recruited from spine centers in Sweden to complete a battery of questionnaires and physical measures the day before surgery. The associations between various individual, psychological, and work-related factors and self-reported work ability were investigated by Spearman rank correlation coefficient, multivariate linear regression, and forward stepwise regression analyses. Factors that were significant (P < 0.05) in each statistical analysis were entered into the successive analysis to reveal the factors most related to work ability. Work ability was assessed using the Work Ability Index. The mean Work Ability Index score was 28 (SD, 9.0). The forward stepwise regression analysis revealed 6 factors significantly associated with work ability, which explained 62% of the variance in the Work Ability Index. Factors highly correlated with greater work ability included greater self-efficacy in performing self-cares, lower physical load on the neck at work, greater self-reported chance of being able to work in 6 months' time, greater use of active coping strategies, lower frequency of hand weakness, and higher health-related quality of life. Psychological, work-related and individual factors were significantly associated with work ability in patients undergoing surgery for cervical radiculopathy. High self-efficacy was most associated with greater work ability. Consideration of these factors by surgeons preoperatively may provide optimal return to work outcomes after surgery. 3.

Malignant testicular tumour incidence and mortality trends

PubMed Central

Wojtyła-Buciora, Paulina; Więckowska, Barbara; Krzywinska-Wiewiorowska, Małgorzata; Gromadecka-Sutkiewicz, Małgorzata

2016-01-01

Aim of the study In Poland testicular tumours are the most frequent cancer among men aged 20–44 years. Testicular tumour incidence since the 1980s and 1990s has been diversified geographically, with an increased risk of mortality in Wielkopolska Province, which was highlighted at the turn of the 1980s and 1990s. The aim of the study was the comparative analysis of the tendencies in incidence and death rates due to malignant testicular tumours observed among men in Poland and in Wielkopolska Province. Material and methods Data from the National Cancer Registry were used for calculations. The incidence/mortality rates among men due to malignant testicular cancer as well as the tendencies in incidence/death ratio observed in Poland and Wielkopolska were established based on regression equation. The analysis was deepened by adopting the multiple linear regression model. A p-value < 0.05 was arbitrarily adopted as the criterion of statistical significance, and for multiple comparisons it was modified according to the Bonferroni adjustment to a value of p < 0.0028. Calculations were performed with the use of PQStat v1.4.8 package. Results The incidence of malignant testicular neoplasms observed among men in Poland and in Wielkopolska Province indicated a significant rising tendency. The multiple linear regression model confirmed that the year variable is a strong incidence forecast factor only within the territory of Poland. A corresponding analysis of mortality rates among men in Poland and in Wielkopolska Province did not show any statistically significant correlations. Conclusions Late diagnosis of Polish patients calls for undertaking appropriate educational activities that would facilitate earlier reporting of the patients, thus increasing their chances for recovery. Introducing preventive examinations in the regions of increased risk of testicular tumour may allow earlier diagnosis. PMID:27095941

Trust, confidence, procedural fairness, outcome fairness, moral conviction, and the acceptance of GM field experiments.

PubMed

Siegrist, Michael; Connor, Melanie; Keller, Carmen

2012-08-01

In 2005, Swiss citizens endorsed a moratorium on gene technology, resulting in the prohibition of the commercial cultivation of genetically modified crops and the growth of genetically modified animals until 2013. However, scientific research was not affected by this moratorium, and in 2008, GMO field experiments were conducted that allowed us to examine the factors that influence their acceptance by the public. In this study, trust and confidence items were analyzed using principal component analysis. The analysis revealed the following three factors: "economy/health and environment" (value similarity based trust), "trust and honesty of industry and scientists" (value similarity based trust), and "competence" (confidence). The results of a regression analysis showed that all the three factors significantly influenced the acceptance of GM field experiments. Furthermore, risk communication scholars have suggested that fairness also plays an important role in the acceptance of environmental hazards. We, therefore, included measures for outcome fairness and procedural fairness in our model. However, the impact of fairness may be moderated by moral conviction. That is, fairness may be significant for people for whom GMO is not an important issue, but not for people for whom GMO is an important issue. The regression analysis showed that, in addition to the trust and confidence factors, moral conviction, outcome fairness, and procedural fairness were significant predictors. The results suggest that the influence of procedural fairness is even stronger for persons having high moral convictions compared with persons having low moral convictions. © 2012 Society for Risk Analysis.

Association of nitrogen compounds in drinking water with incidence of esophageal squamous cell carcinoma in Shexian, China.

PubMed

Zhang, Nan; Yu, Cao; Wen, Denggui; Chen, Jun; Ling, Yiwei; Terajima, Kenshi; Akazawa, Kohei; Shan, Baoen; Wang, Shijie

2012-01-01

The incidence of esophageal squamous cell carcinoma (ESCC), which is the eighth most common malignancy worldwide, is highest in China. The purpose of this study was to investigate the association between nitrogen compounds in drinking water with the incidence of ESCC by geographical spatial analysis. The incidence of ESCC is high in Shexian county, China, and environmental factors, particularly nitrogen-contaminated drinking water, are the main suspected risk factors. This study focuses on three nitrogen compounds in drinking water, namely, nitrates, nitrites, and ammonia, all of which are derived mainly from domestic garbage and agricultural fertilizer. The study surveyed 48 villages in the Shexian area with a total population of 54,716 (661 adults with ESCC and 54,055 non-cancer subjects). Hot-spot analysis was used to identify spatial clusters with a high incidence of ESCC and a high concentration of nitrogen compounds. Logistic regression analysis was used to detect risk factors for ESCC incidence. Most areas with high concentrations of nitrate nitrogen in drinking water had a high incidence of ESCC. Correlation analysis revealed a significant positive relationship between nitrate concentration and ESCC (P = 0.01). Logistic regression analysis also confirmed that nitrate nitrogen has a significantly higher odds ratio. The results indicate that nitrate nitrogen is associated with ESCC incidence in Shexian county. In conclusion, high concentrations of nitrate nitrogen in drinking water may be a significant risk factor for the incidence of ESCC.

In vitro chemo-sensitivity assay guided chemotherapy is associated with prolonged overall survival in cancer patients.

PubMed

Udelnow, Andrej; Schönfęlder, Manfred; Würl, Peter; Halloul, Zuhir; Meyer, Frank; Lippert, Hans; Mroczkowski, Paweł

2013-06-01

The overall survival (OS) of patients suffering From various tumour entities was correlated with the results of in vitro-chemosensitivity assay (CSA) of the in vivo applied drugs. Tumour specimen (n=611) were dissected in 514 patients and incubated for primary tumour cell culture. The histocytological regression assay was performed 5 days after adding chemotherapeutic substances to the cell cultures. n=329 patients undergoing chemotherapy were included in the in vitro/in vivo associations. OS was assessed and in vitro response groups compared using survival analysis. Furthermore Cox-regression analysis was performed on OS including CSA, age, TNM classification and treatment course. The growth rate of the primary was 73-96% depending on tumour entity. The in-vitro response rate varied with histology and drugs (e.g. 8-18% for methotrexate and 33-83% for epirubicine). OS was significantly prolonged for patients treated with in vitro effective drugs compared to empiric therapy (log-rank-test, p=0.0435). Cox-regression revealed that application of in vitro effective drugs, residual tumour and postoperative radiotherapy determined the death risk independently. When patients were treated with drugs effective in our CSA, OS was significantly prolonged compared to empiric therapy. CSA guided chemotherapy should be compared to empiric treatment by a prospective randomized trial.

Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region.

PubMed

Li, Tianyu; Meng, Qingmin

2017-05-01

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.

Predicting athletic success motivation using mental skin and emotional intelligence and its components in male athletes.

PubMed

Kajbafnezhad, H; Ahadi, H; Heidarie, A; Askari, P; Enayati, M

2012-10-01

The aim of this study was to predict athletic success motivation by mental skills, emotional intelligence and its components. The research sample consisted of 153 male athletes who were selected through random multistage sampling. The subjects completed the Mental Skills Questionnaire, Bar-On Emotional Intelligence questionnaire and the perception of sport success questionnaire. Data were analyzed using Pearson correlation coefficient and multiple regressions. Regression analysis shows that between the two variables of mental skill and emotional intelligence, mental skill is the best predictor for athletic success motivation and has a better ability to predict the success rate of the participants. Regression analysis results showed that among all the components of emotional intelligence, self-respect had a significantly higher ability to predict athletic success motivation. The use of psychological skills and emotional intelligence as an mediating and regulating factor and organizer cause leads to improved performance and can not only can to help athletes in making suitable and effective decisions for reaching a desired goal.

[The Influence of Subjective Health Status, Post-Traumatic Growth, and Social Support on Successful Aging in Middle-Aged Women].

PubMed

Lee, Seung Hee; Jang, Hyung Suk; Yang, Young Hee

2016-10-01

This study was done to investigate factors influencing successful aging in middle-aged women. A convenience sample of 103 middle-aged women was selected from the community. Data were collected using a structured questionnaire and analyzed using descriptive statistics, two-sample t-test, one-way ANOVA, Kruskal Wallis test, Pearson correlations, Spearman correlations and multiple regression analysis with the SPSS/WIN 22.0 program. Results of regression analysis showed that significant factors influencing successful aging were post-traumatic growth and social support. This regression model explained 48% of the variance in successful aging. Findings show that the concept 'post-traumatic growth' is an important factor influencing successful aging in middle-aged women. In addition, social support from friends/co-workers had greater influence on successful aging than social support from family. Thus, we need to consider the positive impact of post-traumatic growth and increase the chances of social participation in a successful aging program for middle-aged women.

Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region

NASA Astrophysics Data System (ADS)

Li, Tianyu; Meng, Qingmin

2017-05-01

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.

A consistent framework for Horton regression statistics that leads to a modified Hack's law

USGS Publications Warehouse

Furey, P.R.; Troutman, B.M.

2008-01-01

A statistical framework is introduced that resolves important problems with the interpretation and use of traditional Horton regression statistics. The framework is based on a univariate regression model that leads to an alternative expression for Horton ratio, connects Horton regression statistics to distributional simple scaling, and improves the accuracy in estimating Horton plot parameters. The model is used to examine data for drainage area A and mainstream length L from two groups of basins located in different physiographic settings. Results show that confidence intervals for the Horton plot regression statistics are quite wide. Nonetheless, an analysis of covariance shows that regression intercepts, but not regression slopes, can be used to distinguish between basin groups. The univariate model is generalized to include n > 1 dependent variables. For the case where the dependent variables represent ln A and ln L, the generalized model performs somewhat better at distinguishing between basin groups than two separate univariate models. The generalized model leads to a modification of Hack's law where L depends on both A and Strahler order ??. Data show that ?? plays a statistically significant role in the modified Hack's law expression. ?? 2008 Elsevier B.V.

Optimizing the time-frame for the definition of bleeding-related death after acute variceal bleeding in cirrhosis.

PubMed

Merkel, C; Gatta, A; Bellumat, A; Bolognesi, M; Borsato, L; Caregaro, L; Cavallarin, G; Cielo, R; Cristina, P; Cucci, E; Donada, C; Donadon, V; Enzo, E; Martin, R; Mazzaro, C; Sacerdoti, D; Torboli, P

1996-01-01

To identify the best time-frame for defining bleeding-related death after variceal bleeding in patients with cirrhosis. Prospective long-term evaluation of a cohort of 155 patients admitted with variceal bleeding. Eight medical departments in seven hospitals in north-eastern Italy. Non-linear regression analysis of a hazard curve for death, and Cox's multiple regression analyses using different zero-time points. Cumulative hazard plots gave two slopes, the first corresponding to the risk of death from acute bleeding, the second a baseline risk of death. The first 30 days were outside the confidence limits of the regression curve for the baseline risk of death. Using Cox's regression analysis, the significant predictors of overall mortality risk were balanced between factors related to severity of bleeding and those related to severity of liver disease. If only deaths occurring after 30 days were considered, only predictors related to the severity of liver disease were found to be of importance. Thirty days after bleeding is considered to be a reasonable time-frame for the definition of bleeding-related death in patients with cirrhosis and variceal bleeding.

A New SEYHAN's Approach in Case of Heterogeneity of Regression Slopes in ANCOVA.

PubMed

Ankarali, Handan; Cangur, Sengul; Ankarali, Seyit

2018-06-01

In this study, when the assumptions of linearity and homogeneity of regression slopes of conventional ANCOVA are not met, a new approach named as SEYHAN has been suggested to use conventional ANCOVA instead of robust or nonlinear ANCOVA. The proposed SEYHAN's approach involves transformation of continuous covariate into categorical structure when the relationship between covariate and dependent variable is nonlinear and the regression slopes are not homogenous. A simulated data set was used to explain SEYHAN's approach. In this approach, we performed conventional ANCOVA in each subgroup which is constituted according to knot values and analysis of variance with two-factor model after MARS method was used for categorization of covariate. The first model is a simpler model than the second model that includes interaction term. Since the model with interaction effect has more subjects, the power of test also increases and the existing significant difference is revealed better. We can say that linearity and homogeneity of regression slopes are not problem for data analysis by conventional linear ANCOVA model by helping this approach. It can be used fast and efficiently for the presence of one or more covariates.

Factors affecting cognitive function according to gender in community-dwelling elderly individuals.

PubMed

Kim, Miwon; Park, Jeong-Mo

2017-01-01

This study aimed to identify the factors affecting the cognitive function of elderly people in a community by gender. We obtained 4,878 secondary data of people aged ≥65 years in 2016 at a dementia prevention center in Gyeyang-gu, Incheon. Data were obtained through Mini-Mental Status Examination optimized for screening dementia and a questionnaire. The data were statistically analyzed using analysis of variance, analysis of covariance, and hierarchical regression. There were significant differences in cognitive function according to gender, and the differences were significant even when age was controlled, but gender differences disappeared when education was controlled. Age, education, social activities, number of comorbid diseases, and alcohol drinking affected cognitive function through interaction with gender, but interaction with gender disappeared when education was controlled. Regression analysis showed that depression, cohabitant, social activities etc., had a significant impact on both men and women under controlled education and age. In men, the effect of social activities was greater than that of women, and hyperlipidemia had the effect only in women. The differences in gender-related cognitive functions were due to differences in gender education period. The period of education is considered to have a great influence on cognitive function in relation to the economic level, occupation, and social activity.

Factors affecting cognitive function according to gender in community-dwelling elderly individuals

PubMed Central

2017-01-01

OBJECTIVES This study aimed to identify the factors affecting the cognitive function of elderly people in a community by gender. METHODS We obtained 4,878 secondary data of people aged ≥65 years in 2016 at a dementia prevention center in Gyeyang-gu, Incheon. Data were obtained through Mini-Mental Status Examination optimized for screening dementia and a questionnaire. The data were statistically analyzed using analysis of variance, analysis of covariance, and hierarchical regression. RESULTS There were significant differences in cognitive function according to gender, and the differences were significant even when age was controlled, but gender differences disappeared when education was controlled. Age, education, social activities, number of comorbid diseases, and alcohol drinking affected cognitive function through interaction with gender, but interaction with gender disappeared when education was controlled. Regression analysis showed that depression, cohabitant, social activities etc., had a significant impact on both men and women under controlled education and age. In men, the effect of social activities was greater than that of women, and hyperlipidemia had the effect only in women. CONCLUSIONS The differences in gender-related cognitive functions were due to differences in gender education period. The period of education is considered to have a great influence on cognitive function in relation to the economic level, occupation, and social activity. PMID:29141399

The predicting roles of reasons for living and social support on depression, anxiety and stress among young people in Malaysia.

PubMed

Amit, N; Ibrahim, N; Aga Mohd Jaladin, R; Che Din, N

2017-10-01

This research examined the predicting roles of reasons for living and social support on depression, anxiety and stress in Malaysia. This research was carried out on a sample of 263 participants (age range 12-24 years old), from Klang Valley, Selangor. The survey package comprises demographic information, a measure of reasons for living, social support, depression, anxiety and stress. To analyse the data, correlation analysis and a series of linear multiple regression analysis were carried out. Findings showed that there were low negative relationships between all subdomains and the total score of reasons for living and depression. There were also low negative relationships between domain-specific of social support (family and friends) and total social support and depression. In terms of the family alliance, self-acceptance and total score of reasons for living, they were negatively associated with anxiety, whereas family social support was negatively associated with stress. The linear regression analysis showed that only future optimism and family social support found to be the significant predictors for depression. Family alliance and total reasons for living were significant in predicting anxiety, whereas family social support was significant in predicting stress. These findings have the potential to promote awareness related to depression, anxiety, and stress among youth in Malaysia.

Searching for a neurologic injury's Wechsler Adult Intelligence Scale-Third Edition profile.

PubMed

Gonçalves, Marta A; Moura, Octávio; Castro-Caldas, Alexandre; Simões, Mário R

2017-01-01

This study aimed to investigate the presence of a Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) cognitive profile in a Portuguese neurologic injured sample. The Portuguese WAIS-III was administered to 81 mixed neurologic patients and 81 healthy matched controls selected from the Portuguese standardization sample. Although the mixed neurologic injury group performed significantly lower than the healthy controls for the majority of the WAIS-III scores (i.e., composite measures, discrepancies, and subtests), the mean scores were within the normal range and, therefore, at risk of being unobserved in a clinical evaluation. ROC curves analysis showed poor to acceptable diagnostic accuracy for the WAIS-III composite measures and subtests (Working Memory Index and Digit Span revealed the highest accuracy for discriminating between participants, respectively). Multiple regression analysis showed that both literacy and the presence of brain injury were significant predictors for all of the composite measures. In addition, multiple regression analysis also showed that literacy, age of injury onset, and years of survival predicted all seven composite measures for the mixed neurologic injured group. Despite the failure to find a WAIS-III cognitive profile for mixed neurologic patients, the results showed a significant influence of brain lesion and literacy in the performance of the WAIS-III.

The impact of hyperglycemia on survival in glioblastoma: A systematic review and meta-analysis.

PubMed

Lu, Victor M; Goyal, Anshit; Vaughan, Lachlin S; McDonald, Kerrie L

2018-07-01

In the management of glioblastoma (GBM), there is a considerable predisposition to hyperglycemia due to significant integration of corticosteroid therapy to treat predictable clinical sequelae following diagnosis and treatment. The aim of this study was to quantify effect of hyperglycemia during the management of GBM on overall survival (OS). Searches of seven electronic databases from inception to January 2018 were conducted following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. There were 1475 articles identified for screening. Prognostic hazard ratios (HRs) derived from multivariate regression analysis were extracted, and analyzed using meta-analysis of proportions and linear regression. Six observational studies reporting prognostic HRs in 10 cohorts were included. They described 1481 GBM diagnoses, all surveyed for hyperglycemia during management. Hyperglycemia was found to confer a statistically significant poorer OS outcome (HR, 1.671; p < 0.001). This trend and its significance was not modified by study year, size or proportion of pre-diagnostic diabetes mellitus. Hyperglycemia in GBM is an independent poor prognostic factor for OS. Heterogeneity in clinical course limits inter-study comparability. Future, prospective, randomized studies will validate the findings of this study, and ascertain the potential benefit of more rigorous monitoring for hyperglycemia and glycemic control. Copyright © 2018 Elsevier B.V. All rights reserved.

Comparison of air displacement plethysmography to hydrostatic weighing for estimating total body density in children.

PubMed

Claros, Geo; Hull, Holly R; Fields, David A

2005-09-09

The purpose of this study was to examine the accuracy of total body density and percent body fat (% fat) using air displacement plethysmography (ADP) and hydrostatic weighing (HW) in children. Sixty-six male and female subjects (40 males: 12.4 +/- 1.3 yrs, 47.4 +/- 14.8 kg, 155.4 +/- 11.9 cm, 19.3 +/- 4.1 kg/m2; 26 females: 12.0 +/- 1.9 yrs, 41.4 +/- 7.7 kg, 152.1 +/- 8.9 cm, 17.7 +/- 1.7 kg/m2) were tested using ADP and HW with ADP always preceding HW. Accuracy, precision, and bias were examined in ADP with HW serving as the criterion method. Lohman's equations that are child specific for age and gender were used to convert body density to % fat. Regression analysis determined the accuracy of ADP and potential bias between ADP and HW using Bland-Altman analysis. For the entire group (Y = 0.835x + 0.171, R2 = 0.84, SEE = 0.007 g/cm3) and for the males (Y = 0.837x + 0.174, R2 = 0.90, SEE = 0.006 g/cm3) the regression between total body density by HW and by ADP significantly deviated from the line of identity. However in females, the regression between total body density by HW and ADP did not significantly deviate from the line of identity (Y = 0.750x + 0.258, R2 = 0.55, SEE = 0.008 g/cm3). The regression between % fat by HW and ADP for the group (Y = 0.84x + 3.81, R2 = 0.83, SEE = 3.35 % fat) and for the males (Y = 0.84x + 3.25, R2 = 0.90, SEE = 3.00 % fat) significantly deviated from the line of identity. However, in females the regression between % fat by HW and ADP did not significantly deviate from the line of identity (Y = 0.81x + 5.17, R2 = 0.56, SEE = 3.80 % fat). Bland-Altman analysis revealed no bias between HW total body density and ADP total body density for the entire group (R = 0.-22; P = 0.08) or for females (R = 0.02; P = 0.92), however bias existed in males (R = -0.37; P < or = 0.05). Bland-Altman analysis revealed no bias between HW and ADP % fat for the entire group (R = 0.21; P = 0.10) or in females (R = 0.10; P = 0.57), however bias was indicated for males by a significant correlation (R = 0.36; P < or = 0.05), with ADP underestimating % fat at lower fat values and overestimating at the higher % fat values. A significant difference in total body density and % fat was observed between ADP and HW in children 10-15 years old with a potential gender difference being detected. Upon further investigation it was revealed that the study was inadequately powered, thus we recommend that larger studies that are appropriately powered be conducted to better understand this potential gender difference.

Comparison of air displacement plethysmography to hydrostatic weighing for estimating total body density in children

PubMed Central

Claros, Geo; Hull, Holly R; Fields, David A

2005-01-01

Background The purpose of this study was to examine the accuracy of total body density and percent body fat (% fat) using air displacement plethysmography (ADP) and hydrostatic weighing (HW) in children. Methods Sixty-six male and female subjects (40 males: 12.4 ± 1.3 yrs, 47.4 ± 14.8 kg, 155.4 ± 11.9 cm, 19.3 ± 4.1 kg/m2; 26 females: 12.0 ± 1.9 yrs, 41.4 ± 7.7 kg, 152.1 ± 8.9 cm, 17.7 ± 1.7 kg/m2) were tested using ADP and HW with ADP always preceding HW. Accuracy, precision, and bias were examined in ADP with HW serving as the criterion method. Lohman's equations that are child specific for age and gender were used to convert body density to % fat. Regression analysis determined the accuracy of ADP and potential bias between ADP and HW using Bland-Altman analysis. Results For the entire group (Y = 0.835x + 0.171, R2 = 0.84, SEE = 0.007 g/cm3) and for the males (Y = 0.837x + 0.174, R2 = 0.90, SEE = 0.006 g/cm3) the regression between total body density by HW and by ADP significantly deviated from the line of identity. However in females, the regression between total body density by HW and ADP did not significantly deviate from the line of identity (Y = 0.750x + 0.258, R2 = 0.55, SEE = 0.008 g/cm3). The regression between % fat by HW and ADP for the group (Y = 0.84x + 3.81, R2 = 0.83, SEE = 3.35 % fat) and for the males (Y = 0.84x + 3.25, R2 = 0.90, SEE = 3.00 % fat) significantly deviated from the line of identity. However, in females the regression between % fat by HW and ADP did not significantly deviate from the line of identity (Y = 0.81x + 5.17, R2 = 0.56, SEE = 3.80 % fat). Bland-Altman analysis revealed no bias between HW total body density and ADP total body density for the entire group (R = 0.-22; P = 0.08) or for females (R = 0.02; P = 0.92), however bias existed in males (R = -0.37; P ≤ 0.05). Bland-Altman analysis revealed no bias between HW and ADP % fat for the entire group (R = 0.21; P = 0.10) or in females (R = 0.10; P = 0.57), however bias was indicated for males by a significant correlation (R = 0.36; P ≤ 0.05), with ADP underestimating % fat at lower fat values and overestimating at the higher % fat values. Conclusion A significant difference in total body density and % fat was observed between ADP and HW in children 10–15 years old with a potential gender difference being detected. Upon further investigation it was revealed that the study was inadequately powered, thus we recommend that larger studies that are appropriately powered be conducted to better understand this potential gender difference. PMID:16153297

Calorimetric analysis of fungal degraded wood

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blankenhorn, P.R.; Baldwin, R.C.; Merrill, W. Jr.

1980-01-01

Endothermic transition and gross heat of combustion of aspenwood subjected to degradation by Lenzites trabea and Polyporus versicolor were determined by using differential scanning calorimetry (DSC) and an adiabatic O bomb. Endothermic peak areas of undegraded and fungi-degraded wood differed from each other at all levels of weight loss. The regression analysis of the DSC data vs. weight loss revealed a significant relations, although not highly correlated, for P. versicolor-degraded specimens and a nonsignificant relation for L. trabea-degraded specimens; weight loss and gross heat of combustion values of degraded specimens were significantly correlated.

Quantitative Assessment of Cervical Vertebral Maturation Using Cone Beam Computed Tomography in Korean Girls

PubMed Central

Byun, Bo-Ram; Kim, Yong-Il; Maki, Koutaro; Son, Woo-Sung

2015-01-01

This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6–18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R 2 had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status. PMID:25878721

Hybrid ICA-Regression: Automatic Identification and Removal of Ocular Artifacts from Electroencephalographic Signals.

PubMed

Mannan, Malik M Naeem; Jeong, Myung Y; Kamran, Muhammad A

2016-01-01

Electroencephalography (EEG) is a portable brain-imaging technique with the advantage of high-temporal resolution that can be used to record electrical activity of the brain. However, it is difficult to analyze EEG signals due to the contamination of ocular artifacts, and which potentially results in misleading conclusions. Also, it is a proven fact that the contamination of ocular artifacts cause to reduce the classification accuracy of a brain-computer interface (BCI). It is therefore very important to remove/reduce these artifacts before the analysis of EEG signals for applications like BCI. In this paper, a hybrid framework that combines independent component analysis (ICA), regression and high-order statistics has been proposed to identify and eliminate artifactual activities from EEG data. We used simulated, experimental and standard EEG signals to evaluate and analyze the effectiveness of the proposed method. Results demonstrate that the proposed method can effectively remove ocular artifacts as well as it can preserve the neuronal signals present in EEG data. A comparison with four methods from literature namely ICA, regression analysis, wavelet-ICA (wICA), and regression-ICA (REGICA) confirms the significantly enhanced performance and effectiveness of the proposed method for removal of ocular activities from EEG, in terms of lower mean square error and mean absolute error values and higher mutual information between reconstructed and original EEG.

Hybrid ICA—Regression: Automatic Identification and Removal of Ocular Artifacts from Electroencephalographic Signals

PubMed Central

Mannan, Malik M. Naeem; Jeong, Myung Y.; Kamran, Muhammad A.

2016-01-01

Electroencephalography (EEG) is a portable brain-imaging technique with the advantage of high-temporal resolution that can be used to record electrical activity of the brain. However, it is difficult to analyze EEG signals due to the contamination of ocular artifacts, and which potentially results in misleading conclusions. Also, it is a proven fact that the contamination of ocular artifacts cause to reduce the classification accuracy of a brain-computer interface (BCI). It is therefore very important to remove/reduce these artifacts before the analysis of EEG signals for applications like BCI. In this paper, a hybrid framework that combines independent component analysis (ICA), regression and high-order statistics has been proposed to identify and eliminate artifactual activities from EEG data. We used simulated, experimental and standard EEG signals to evaluate and analyze the effectiveness of the proposed method. Results demonstrate that the proposed method can effectively remove ocular artifacts as well as it can preserve the neuronal signals present in EEG data. A comparison with four methods from literature namely ICA, regression analysis, wavelet-ICA (wICA), and regression-ICA (REGICA) confirms the significantly enhanced performance and effectiveness of the proposed method for removal of ocular activities from EEG, in terms of lower mean square error and mean absolute error values and higher mutual information between reconstructed and original EEG. PMID:27199714

A reconnaissance method for delineation of tracts for regional-scale mineral-resource assessment based on geologic-map data

USGS Publications Warehouse

Raines, G.L.; Mihalasky, M.J.

2002-01-01

The U.S. Geological Survey (USGS) is proposing to conduct a global mineral-resource assessment using geologic maps, significant deposits, and exploration history as minimal data requirements. Using a geologic map and locations of significant pluton-related deposits, the pluton-related-deposit tract maps from the USGS national mineral-resource assessment have been reproduced with GIS-based analysis and modeling techniques. Agreement, kappa, and Jaccard's C correlation statistics between the expert USGS and calculated tract maps of 87%, 40%, and 28%, respectively, have been achieved using a combination of weights-of-evidence and weighted logistic regression methods. Between the experts' and calculated maps, the ranking of states measured by total permissive area correlates at 84%. The disagreement between the experts and calculated results can be explained primarily by tracts defined by geophysical evidence not considered in the calculations, generalization of tracts by the experts, differences in map scales, and the experts' inclusion of large tracts that are arguably not permissive. This analysis shows that tracts for regional mineral-resource assessment approximating those delineated by USGS experts can be calculated using weights of evidence and weighted logistic regression, a geologic map, and the location of significant deposits. Weights of evidence and weighted logistic regression applied to a global geologic map could provide quickly a useful reconnaissance definition of tracts for mineral assessment that is tied to the data and is reproducible. ?? 2002 International Association for Mathematical Geology.

Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA

USGS Publications Warehouse

Ohlmacher, G.C.; Davis, J.C.

2003-01-01

Landslides in the hilly terrain along the Kansas and Missouri rivers in northeastern Kansas have caused millions of dollars in property damage during the last decade. To address this problem, a statistical method called multiple logistic regression has been used to create a landslide-hazard map for Atchison, Kansas, and surrounding areas. Data included digitized geology, slopes, and landslides, manipulated using ArcView GIS. Logistic regression relates predictor variables to the occurrence or nonoccurrence of landslides within geographic cells and uses the relationship to produce a map showing the probability of future landslides, given local slopes and geologic units. Results indicated that slope is the most important variable for estimating landslide hazard in the study area. Geologic units consisting mostly of shale, siltstone, and sandstone were most susceptible to landslides. Soil type and aspect ratio were considered but excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression. Soil types were highly correlated with the geologic units, and no significant relationships existed between landslides and slope aspect. ?? 2003 Elsevier Science B.V. All rights reserved.

Predicting risk for portal vein thrombosis in acute pancreatitis patients: A comparison of radical basis function artificial neural network and logistic regression models.

PubMed

Fei, Yang; Hu, Jian; Gao, Kun; Tu, Jianfeng; Li, Wei-Qin; Wang, Wei

2017-06-01

To construct a radical basis function (RBF) artificial neural networks (ANNs) model to predict the incidence of acute pancreatitis (AP)-induced portal vein thrombosis. The analysis included 353 patients with AP who had admitted between January 2011 and December 2015. RBF ANNs model and logistic regression model were constructed based on eleven factors relevant to AP respectively. Statistical indexes were used to evaluate the value of the prediction in two models. The predict sensitivity, specificity, positive predictive value, negative predictive value and accuracy by RBF ANNs model for PVT were 73.3%, 91.4%, 68.8%, 93.0% and 87.7%, respectively. There were significant differences between the RBF ANNs and logistic regression models in these parameters (P<0.05). In addition, a comparison of the area under receiver operating characteristic curves of the two models showed a statistically significant difference (P<0.05). The RBF ANNs model is more likely to predict the occurrence of PVT induced by AP than logistic regression model. D-dimer, AMY, Hct and PT were important prediction factors of approval for AP-induced PVT. Copyright © 2017 Elsevier Inc. All rights reserved.

Discrimination and Acculturative Stress among First-Generation Dominicans

ERIC Educational Resources Information Center

Dawson, Beverly Araujo; Panchanadeswaran, Subadra

2010-01-01

The present study examined the relationship between discriminatory experiences and acculturative stress levels among a sample of 283 Dominican immigrants. Findings from a linear regression analysis revealed that experiences of daily racial discrimination and major racist events were significant predictors of acculturative stress after controlling…

Statistical correlations of crime with arrests

NASA Astrophysics Data System (ADS)

Kuelling, Albert C.

1997-01-01

Regression analysis shows that the overall crime rate correlates with the overall arrest rate. Violent crime only weakly correlates with the violent arrest rate, but strongly correlates with the property arrest rate. Contrary to common impressions, increasing arrest rates do not significantly increase loading on incarceration facilities.

A phenomenological biological dose model for proton therapy based on linear energy transfer spectra.

PubMed

Rørvik, Eivind; Thörnqvist, Sara; Stokkevåg, Camilla H; Dahle, Tordis J; Fjaera, Lars Fredrik; Ytre-Hauge, Kristian S

2017-06-01

The relative biological effectiveness (RBE) of protons varies with the radiation quality, quantified by the linear energy transfer (LET). Most phenomenological models employ a linear dependency of the dose-averaged LET (LET d ) to calculate the biological dose. However, several experiments have indicated a possible non-linear trend. Our aim was to investigate if biological dose models including non-linear LET dependencies should be considered, by introducing a LET spectrum based dose model. The RBE-LET relationship was investigated by fitting of polynomials from 1st to 5th degree to a database of 85 data points from aerobic in vitro experiments. We included both unweighted and weighted regression, the latter taking into account experimental uncertainties. Statistical testing was performed to decide whether higher degree polynomials provided better fits to the data as compared to lower degrees. The newly developed models were compared to three published LET d based models for a simulated spread out Bragg peak (SOBP) scenario. The statistical analysis of the weighted regression analysis favored a non-linear RBE-LET relationship, with the quartic polynomial found to best represent the experimental data (P = 0.010). The results of the unweighted regression analysis were on the borderline of statistical significance for non-linear functions (P = 0.053), and with the current database a linear dependency could not be rejected. For the SOBP scenario, the weighted non-linear model estimated a similar mean RBE value (1.14) compared to the three established models (1.13-1.17). The unweighted model calculated a considerably higher RBE value (1.22). The analysis indicated that non-linear models could give a better representation of the RBE-LET relationship. However, this is not decisive, as inclusion of the experimental uncertainties in the regression analysis had a significant impact on the determination and ranking of the models. As differences between the models were observed for the SOBP scenario, both non-linear LET spectrum- and linear LET d based models should be further evaluated in clinically realistic scenarios. © 2017 American Association of Physicists in Medicine.

Association between schizotypal and borderline personality disorder traits, and cannabis use in young adults.

PubMed

Raynal, Patrick; Chabrol, Henri

2016-09-01

The aim of the study was to examine the association of schizotypal and borderline personality traits to cannabis use. Participants were 476 college students (95 males; 381 females; mean age of males=21; mean age of females=20.7) who completed self-report questionnaires assessing cannabis use, schizotypal and borderline personality traits. Problematic cannabis use, depressive symptoms, borderline and schizotypal traits were significantly inter-correlated. A logistic regression analysis showed that only borderline traits contributed significantly to cannabis use in the total sample. A multiple regression analysis showed that only schizotypal traits were positively and uniquely associated to problematic cannabis use symptoms among users. These results may imply that schizotypal traits are not a risk factor for initiating use, but may facilitate the development of problematic use symptoms among users. This study showed the necessity of taking into account schizotypal traits when exploring the relationships between depressive symptoms, borderline traits and cannabis use. Copyright © 2016 Elsevier Ltd. All rights reserved.

SOCIAL STABILITY AND HIV RISK BEHAVIOR: EVALUATING THE ROLE OF ACCUMULATED VULNERABILITY

PubMed Central

German, Danielle; Latkin, Carl A.

2011-01-01

This study evaluated a cumulative and syndromic relationship among commonly co-occurring vulnerabilites (homelessness, incarceration, low-income, residential transition) in association with HIV-related risk behaviors among 635 low-income women in Baltimore. Analysis included descriptive statistics, logistic regression, latent class analysis and latent class regression. Both methods of assessing multidimensional instability showed significant associations with risk indicators. Risk of multiple partners, sex exchange, and drug use decreased significantly with each additional domain. Higher stability class membership (77%) was associated with decreased likelihood of multiple partners, exchange partners, recent drug use, and recent STI. Multidimensional social vulnerabilities were cumulatively and synergistically linked to HIV risk behavior. Independent instability measures may miss important contextual determinants of risk. Social stability offers a useful framework to understand the synergy of social vulnerabilities that shape sexual risk behavior. Social policies and programs aiming to enhance housing and overall social stability are likely to be beneficial for HIV prevention. PMID:21259043

The relationship between apical root resorption and orthodontic tooth movement in growing subjects.

PubMed

Xu, Tianmin; Baumrind, S

2002-07-01

To investigate the relationship between apical root resorption and orthodontic tooth movement in growing subjects. 58 growing subjects were collected randomly into the study sample and another 40 non-treated cases were used as control. The apical resoption of the upper central incisors was measured on periapical film and the incisor displacement was measured on lateral cephalogram. Using multiple linear regression analysis to examine the relationship between root resoption and the displacement of the upper incisor apex in each of four direction (retraction, advancement, intrusion and extrusion). The statistically significant negative association were found between resorption and both intrusion (P < 0.001) and extrusion (P < 0.05), but no significant association was found between resorption and both retraction and advancement. The regression analysis implied an average of 2.29 mm resorption in the absence of apical displacement. The likelihood that the magnitude of displacement of the incisor root is positively associated with root resoption in the population of treated growing subjects is very small.

Hypomagnesemia predicts postoperative biochemical hypocalcemia after thyroidectomy.

PubMed

Luo, Han; Yang, Hongliu; Zhao, Wanjun; Wei, Tao; Su, Anping; Wang, Bin; Zhu, Jingqiang

2017-05-25

To investigate the role of magnesium in biochemical and symptomatic hypocalcemia, a retrospective study was conducted. Less-than-total thyroidectomy patients were excluded from the final analysis. Identified the risk factors of biochemical and symptomatic hypocalcemia, and investigated the correlation by logistic regression and correlation test respectively. A total of 304 patients were included in the final analysis. General incidence of hypomagnesemia was 23.36%. Logistic regression showed that gender (female) (OR = 2.238, p = 0.015) and postoperative hypomagnesemia (OR = 2.010, p = 0.017) were independent risk factors for biochemical hypocalcemia. Both Pearson and partial correlation tests indicated there was indeed significant relation between calcium and magnesium. However, relative decreasing of iPTH (>70%) (6.691, p < 0.001) and hypocalcemia (2.222, p = 0.046) were identified as risk factors of symptomatic hypocalcemia. The difference remained significant even in normoparathyroidism patients. Postoperative hypomagnesemia was independent risk factor of biochemical hypocalcemia. Relative decline of iPTH was predominating in predicting symptomatic hypocalcemia.

Marital quality and self-efficacy: influence on disease management among individuals with rheumatoid arthritis.

PubMed

Tewary, Sweta; Farber, Naomi

2014-01-01

Individuals with rheumatoid arthritis (RA) struggle to maintain improved functional ability and reduced pain levels. Health education emphasizing self-efficacy helps individuals to adjust with the disease outcome and progression. As a basis to develop comprehensive evidence-based patient education programs, the aim of the study was to examine the role of marriage as a predictor of pain and functional self-efficacy among individuals with RA. Review of the regression analysis did not provide support for the relationships between marital quality and self-efficacy. Relationships were not observed between marital quality, length of marriage, and self-efficacy as predicted by the first hypothesis. Additional regression analysis examination found that marital quality, length of marriage, pain, and health assessment together reported significant variance in self-efficacy. However, only health assessment significantly predicted self-efficacy. Other nonexamined variables could have influenced the independent marital quality effects. Future longitudinal studies with larger sample sizes can further validate the current findings.

Ataque de nervios: relationship to anxiety sensitivity and dissociation predisposition.

PubMed

Hinton, Devon E; Chong, Roberto; Pollack, Mark H; Barlow, David H; McNally, Richard J

2008-01-01

We investigated the relative importance of "fear of arousal symptoms" (i.e., anxiety sensitivity) and "dissociation tendency" in generating ataque de nervios. Puerto Rican patients attending an outpatient psychiatric clinic were assessed for ataque de nervios frequency in the previous month, and they completed the Anxiety Sensitivity Index (ASI) and the Dissociation Experiences Scale (DES). ASI scores were especially high in the ataque-positive group (M=41.6, SD=12.8) as compared with the ataque-negative group (M=27.2, SD=11.7), t(2, 68)=4.6, P<.001. Among the whole sample (N=70), in a logistic regression analysis, the ASI significantly predicted (odds ratio=2.6) the presence of ataque de nervios, but the DES did not. In a linear regression analysis, ataque severity was significantly predicted by both the ASI (beta=.46) and the DES (beta=.29). The theoretical and clinical implications of the strong relationship of the ASI to ataque severity are discussed.

Relationship of physical activity to fundamental movement skills among adolescents.

PubMed

Okely, A D; Booth, M L; Patterson, J W

2001-11-01

To determine the relationship of participation in organized and nonorganized physical activity with fundamental movement skills among adolescents. Male and female children in Grade 8 (mean age, 13.3 yr) and Grade 10 (mean age, 15.3 yr) were assessed on six fundamental movement skills (run, vertical jump, catch, overhand throw, forehand strike, and kick). Physical activity was assessed using a self-report recall measure where students reported the type, duration, and frequency of participation in organized physical activity and nonorganized physical activity during a usual week. Multiple regression analysis indicated that fundamental movement skills significantly predicted time in organized physical activity, although the percentage of variance it could explain was small. This prediction was stronger for girls than for boys. Multiple regression analysis showed no relationship between time in nonorganized physical activity and fundamental movement skills. Fundamental movement skills are significantly associated with adolescents' participation in organized physical activity, but predict only a small portion of it.

Analysis of the effectiveness of fertilizer subsidy policy and its effect on rice production in Karanganyar Regency

NASA Astrophysics Data System (ADS)

Mulyadiana, A. T.; Marwanti, S.; Rahayu, W.

2018-03-01

The research aims to know the factors which affecting rice production, and to know the effectiveness of fertilizer subsidy policy on rice production in Karanganyar Regency. The fertilizer subsidy policy was based on four indicators of fertilizer subsidy namely exact price, exact place, exact time, and exact quantity. Data was analyzed using descriptive quantitative and qualitative and multiple linear regression. The result of research showed that fertilizer subsidy policy in Karanganyar Regency evaluated from four indicators was not effective because the distribution of fertilizer subsidy to farmers still experience some mistakes. The result of regression analysis showed that production factors such as land area, use of urea fertilizer, use of NPK fertilizer, and effectiveness of fertilizer subsidy policy had positive correlation and significant influence on rice production, while labor utilization and use of seeds factors had no significant effect on rice production in Karanganyar Regency. This means that if the fertilizer subsidy policy is more effective, rice production is also increased.

[Childbirth pain, perinatal dissociation and perinatal distress as predictors of posttraumatic stress symptoms].

PubMed

Boudou, M; Séjourné, N; Chabrol, H

2007-11-01

This prospective, longitudinal study investigated the contributive role of childbirth pain, perinatal distress and perinatal dissociation to the development of PTSD symptoms following childbirth. One hundred and seventeen women participated at the study. The first day after delivery they completed a questionnaire to evaluate pain, the peritraumatic distress inventory (PDI) and the peritraumatic dissociative experience questionnaire (PDEQ). Six weeks after birth, they completed the impact of event scale-revised (IES-R) to measure posttraumatic stress symptoms and the Edinburgh Postnatal Depression Scale (EPDS) to assess maternal depression. A multiple regression analysis revealed that only both components of perinatal distress, life-threat perception and dysphoric emotions were significant predictors of posttraumatic stress symptoms. In another multiple regression analysis predicting dysphoric emotions, affective dimension of pain was the only significant predictor. Perinatal distress was the best predictor of posttraumatic stress symptoms. Dysphoric emotions were associated with affective dimension of pain, suggesting that women distressed by the childbirth pain would have higher risk to develop posttraumatic stress symptoms.

[Association of mineral and bone disorder with increasing PWV in CKD 1-5 patients].

PubMed

Shiota, Jun; Watanabe, Mitsuhiro

2007-01-01

The association between pulse wave velocity(PWV) and chronic kidney disease mineral and bone disorder(CKD-MBD) was investigated in CKD 1-5 patients without dialysis. Pulse pressure(PP), PWV, serum Cr, non-HDL-cholesterol, Alb, Ca, Pi, calcitriol, intact-PTH and BAP were measured in sixty patients not receiving a phosphate binder or vitamin D. Using the relationship between age and baPWV in healthy subjects, we determined delta baPWV(measured baPWV-calculated baPWV) as an index for the effect of CKD-related factors. delta baPWV was significantly higher in diabetic patients (p < 0.00001). Simple regression analysis revealed that delta baPWV was positively correlated with PP (p < 0.05) and Log(intact-PTH) (p < 0.01), but negatively correlated with Log(estimated GFR) and Log(calcitriol) (p < 0.01). Multiple regression analysis revealed that delta baPWV was significantly associated with PP and calcitriol, or PP and intact-PTH. These results suggest a relationship between PWV and CKD-MBD.

Prediction of all-cause death in hemodialysis patients using elevated postdialysis pulse wave velocity.

PubMed

Fu, Xiaohong; Yang, Jihong; Fan, Zhaoxin; Chen, Xianguang; Wu, Jie; Li, Jie; Wu, Hua

2016-02-01

To identify the relationship between predialysis pulse wave velocity (PWV), postdialysis PWV during 1 hemodialysis (HD) session, and deaths in maintenance HD patients. 43 patients were recruited. PWV was measured before and after one HD session and dialysis- related data were recorded. Clinical data such as blood pressure, blood lipids, and blood glucose, were carefully observed and managed in a 5-year follow-up. The association between all-cause death, predialysis PWV, postdialysis PWV, change of PWV (ΔPWV), and other related variables were analyzed. After 5 years, 17 patients (39.5%) died. Univariate Cox regression analysis showed that all-cause death of the patients significantly correlated with age, postdialysis PWV, and ΔPWV. Multivariate Cox regression analysis revealed that postdialysis PWV was an independent predictor for all-cause death in these patients (HR: 1.377, 95% CI: 1.146 - 1.656, p = 0.001). Elevated postdialysis PWV significantly correlated with and was an independent predictor for all-cause death in maintenance HD patients.

Applied Multiple Linear Regression: A General Research Strategy

ERIC Educational Resources Information Center

Smith, Brandon B.

1969-01-01

Illustrates some of the basic concepts and procedures for using regression analysis in experimental design, analysis of variance, analysis of covariance, and curvilinear regression. Applications to evaluation of instruction and vocational education programs are illustrated. (GR)

Association between breastfeeding duration, non-nutritive sucking habits and dental arch dimensions in deciduous dentition: a cross-sectional study.

PubMed

Agarwal, Shiv Shankar; Nehra, Karan; Sharma, Mohit; Jayan, Balakrishna; Poonia, Anish; Bhattal, Hiteshwar

2014-10-31

This cross-sectional retrospective study was conducted to determine association between breastfeeding duration, non-nutritive sucking habits, dental arch transverse diameters, posterior crossbite and anterior open bite in deciduous dentition. 415 children (228 males and 187 females), 4 to 6 years old, from a mixed Indian population were clinically examined. Based on written questionnaire answered by parents, children were divided into two groups: group 1 (breastfed for <6 months (n = 158)) and group 2 (breastfed for ≥6 months (n = 257)). The associations were analysed using chi-square test (P < 0.05 taken as statistically significant). Odds ratio (OR) was calculated to determine the strength of associations tested. Multivariate logistic regression analysis was done for obtaining independent predictors of posterior crossbite and maxillary and mandibular IMD (Inter-molar distance) and ICD (Inter-canine distance). Non-nutritive sucking (NNS) was present in 15.18% children (20.3% in group 1 as compared to 12.1% in group 2 (P = 0.024)). The average ICD and IMD in maxilla and average IMD in mandible were significantly higher among group 2 as compared to group 1 (P < 0.01). In mandible, average ICD did not differ significantly between the two groups (P = 0.342). The distribution of anterior open bite did not differ significantly between the two groups (P = 0.865). The distribution of posterior crossbite was significantly different between the two groups (P = 0.001). OR assessment (OR = 1.852) revealed that group 1 had almost twofold higher prevalence of NNS habits than group 2. Multivariate logistic regression analysis revealed that the first group had independently fourfold increased risk of developing crossbite compared to the second group (OR = 4.3). Multivariate linear regression analysis also revealed that age and breastfeeding duration were the most significant determinants of ICD and IMD. An increased prevalence of NNS in the first group suggests that NNS is a dominant variable in the association between breastfeeding duration and reduced intra-arch transverse diameters which leads to increased prevalence of posterior crossbites as seen in our study. Mandibular inter-canine width is however unaffected due to a lowered tongue posture seen in these children.

An Attempt at Quantifying Factors that Affect Efficiency in the Management of Solid Waste Produced by Commercial Businesses in the City of Tshwane, South Africa

PubMed Central

Worku, Yohannes; Muchie, Mammo

2012-01-01

Objective. The objective was to investigate factors that affect the efficient management of solid waste produced by commercial businesses operating in the city of Pretoria, South Africa. Methods. Data was gathered from 1,034 businesses. Efficiency in solid waste management was assessed by using a structural time-based model designed for evaluating efficiency as a function of the length of time required to manage waste. Data analysis was performed using statistical procedures such as frequency tables, Pearson's chi-square tests of association, and binary logistic regression analysis. Odds ratios estimated from logistic regression analysis were used for identifying key factors that affect efficiency in the proper disposal of waste. Results. The study showed that 857 of the 1,034 businesses selected for the study (83%) were found to be efficient enough with regards to the proper collection and disposal of solid waste. Based on odds ratios estimated from binary logistic regression analysis, efficiency in the proper management of solid waste was significantly influenced by 4 predictor variables. These 4 influential predictor variables are lack of adherence to waste management regulations, wrong perception, failure to provide customers with enough trash cans, and operation of businesses by employed managers, in a decreasing order of importance. PMID:23209483

External Tank Liquid Hydrogen (LH2) Prepress Regression Analysis Independent Review Technical Consultation Report

NASA Technical Reports Server (NTRS)

Parsons, Vickie s.

2009-01-01

The request to conduct an independent review of regression models, developed for determining the expected Launch Commit Criteria (LCC) External Tank (ET)-04 cycle count for the Space Shuttle ET tanking process, was submitted to the NASA Engineering and Safety Center NESC on September 20, 2005. The NESC team performed an independent review of regression models documented in Prepress Regression Analysis, Tom Clark and Angela Krenn, 10/27/05. This consultation consisted of a peer review by statistical experts of the proposed regression models provided in the Prepress Regression Analysis. This document is the consultation's final report.

Methods for estimating the magnitude and frequency of floods for urban and small, rural streams in Georgia, South Carolina, and North Carolina, 2011

USGS Publications Warehouse

Feaster, Toby D.; Gotvald, Anthony J.; Weaver, J. Curtis

2014-01-01

Reliable estimates of the magnitude and frequency of floods are essential for the design of transportation and water-conveyance structures, flood-insurance studies, and flood-plain management. Such estimates are particularly important in densely populated urban areas. In order to increase the number of streamflow-gaging stations (streamgages) available for analysis, expand the geographical coverage that would allow for application of regional regression equations across State boundaries, and build on a previous flood-frequency investigation of rural U.S Geological Survey streamgages in the Southeast United States, a multistate approach was used to update methods for determining the magnitude and frequency of floods in urban and small, rural streams that are not substantially affected by regulation or tidal fluctuations in Georgia, South Carolina, and North Carolina. The at-site flood-frequency analysis of annual peak-flow data for urban and small, rural streams (through September 30, 2011) included 116 urban streamgages and 32 small, rural streamgages, defined in this report as basins draining less than 1 square mile. The regional regression analysis included annual peak-flow data from an additional 338 rural streamgages previously included in U.S. Geological Survey flood-frequency reports and 2 additional rural streamgages in North Carolina that were not included in the previous Southeast rural flood-frequency investigation for a total of 488 streamgages included in the urban and small, rural regression analysis. The at-site flood-frequency analyses for the urban and small, rural streamgages included the expected moments algorithm, which is a modification of the Bulletin 17B log-Pearson type III method for fitting the statistical distribution to the logarithms of the annual peak flows. Where applicable, the flood-frequency analysis also included low-outlier and historic information. Additionally, the application of a generalized Grubbs-Becks test allowed for the detection of multiple potentially influential low outliers. Streamgage basin characteristics were determined using geographical information system techniques. Initial ordinary least squares regression simulations reduced the number of basin characteristics on the basis of such factors as statistical significance, coefficient of determination, Mallow’s Cp statistic, and ease of measurement of the explanatory variable. Application of generalized least squares regression techniques produced final predictive (regression) equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probability flows for urban and small, rural ungaged basins for three hydrologic regions (HR1, Piedmont–Ridge and Valley; HR3, Sand Hills; and HR4, Coastal Plain), which previously had been defined from exploratory regression analysis in the Southeast rural flood-frequency investigation. Because of the limited availability of urban streamgages in the Coastal Plain of Georgia, South Carolina, and North Carolina, additional urban streamgages in Florida and New Jersey were used in the regression analysis for this region. Including the urban streamgages in New Jersey allowed for the expansion of the applicability of the predictive equations in the Coastal Plain from 3.5 to 53.5 square miles. Average standard error of prediction for the predictive equations, which is a measure of the average accuracy of the regression equations when predicting flood estimates for ungaged sites, range from 25.0 percent for the 10-percent annual exceedance probability regression equation for the Piedmont–Ridge and Valley region to 73.3 percent for the 0.2-percent annual exceedance probability regression equation for the Sand Hills region.

Cytologic regression in women with atypical squamous cells of unknown significance and negative human papillomavirus test.

PubMed

Wang, Shu; Lang, Jing He; Cheng, Xue Mei

2009-12-01

The aim of this study was to investigate the cytologic regression in women with atypical squamous cells of unknown significance and negative high-risk human papillomavirus test. The 45 women with atypical squamous cells of unknown significance and negative high-risk human papillomavirus at baseline were analyzed about the cytologic regression during 2 years of follow-up. The cumulative rate of cytologic regression was calculated by Kaplan-Meier curves. Of 45 women, the cumulative rates were as follows: 55.6% obtained cytologic regression before 6 months, 84.4% by 1 year, and 95.6% at 2 years. Cytologic regression was not influenced by age, menopausal status, and baseline human papillomavirus load. However, the 1-year cumulative regression rate in women with previous cervical lesions was significantly lower than those without (P=.02), even much lower in women with high-grade intraepithelial neoplasia or worse (P=.008). Most women with atypical squamous cells of unknown significance and negative high-risk human papillomavirus could obtain cytologic regression within 2 years. Women with antecedent cervical lesions need longer time to reach this regression.

Comparison of enzyme-linked immunosorbent assay and gas chromatography procedures for the detection of cyanazine and metolachlor in surface water samples

USGS Publications Warehouse

Schraer, S.M.; Shaw, D.R.; Boyette, M.; Coupe, R.H.; Thurman, E.M.

2000-01-01

Enzyme-linked immunosorbent assay (ELISA) data from surface water reconnaissance were compared to data from samples analyzed by gas chromatography for the pesticide residues cyanazine (2-[[4-chloro-6-(ethylamino)-l,3,5-triazin-2-yl]amino]-2-methylpropanenitrile ) and metolachlor (2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)acetamide). When ELISA analyses were duplicated, cyanazine and metolachlor detection was found to have highly reproducible results; adjusted R2s were 0.97 and 0.94, respectively. When ELISA results for cyanazine were regressed against gas chromatography results, the models effectively predicted cyanazine concentrations from ELISA analyses (adjusted R2s ranging from 0.76 to 0.81). The intercepts and slopes for these models were not different from 0 and 1, respectively. This indicates that cyanazine analysis by ELISA is expected to give the same results as analysis by gas chromatography. However, regressing ELISA analyses for metolachlor against gas chromatography data provided more variable results (adjusted R2s ranged from 0.67 to 0.94). Regression models for metolachlor analyses had two of three intercepts that were not different from 0. Slopes for all metolachlor regression models were significantly different from 1. This indicates that as metolachlor concentrations increase, ELISA will over- or under-estimate metolachlor concentration, depending on the method of comparison. ELISA can be effectively used to detect cyanazine and metolachlor in surface water samples. However, when detections of metolachlor have significant consequences or implications it may be necessary to use other analytical methods.

Regression-based adaptive sparse polynomial dimensional decomposition for sensitivity analysis

NASA Astrophysics Data System (ADS)

Tang, Kunkun; Congedo, Pietro; Abgrall, Remi

2014-11-01

Polynomial dimensional decomposition (PDD) is employed in this work for global sensitivity analysis and uncertainty quantification of stochastic systems subject to a large number of random input variables. Due to the intimate structure between PDD and Analysis-of-Variance, PDD is able to provide simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to polynomial chaos (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of the standard method unaffordable for real engineering applications. In order to address this problem of curse of dimensionality, this work proposes a variance-based adaptive strategy aiming to build a cheap meta-model by sparse-PDD with PDD coefficients computed by regression. During this adaptive procedure, the model representation by PDD only contains few terms, so that the cost to resolve repeatedly the linear system of the least-square regression problem is negligible. The size of the final sparse-PDD representation is much smaller than the full PDD, since only significant terms are eventually retained. Consequently, a much less number of calls to the deterministic model is required to compute the final PDD coefficients.

MicroCT angiography detects vascular formation and regression in skin wound healing

PubMed Central

Urao, Norifumi; Okonkwo, Uzoagu A.; Fang, Milie M.; Zhuang, Zhen W.; Koh, Timothy J.; DiPietro, Luisa A.

2016-01-01

Properly regulated angiogenesis and arteriogenesis are essential for effective wound healing. Tissue injury induces robust new vessel formation and subsequent vessel maturation, which involves vessel regression and remodeling. Although formation of functional vasculature is essential for healing, alterations in vascular structure over the time course of skin wound healing are not well understood. Here, using high-resolution ex vivo X-ray micro-computed tomography (microCT), we describe the vascular network during healing of skin excisional wounds with highly detailed three-dimensional (3D) reconstructed images and associated quantitative analysis. We found that relative vessel volume, surface area and branching number are significantly decreased in wounds from day 7 to day 14 and 21. Segmentation and skeletonization analysis of selected branches from high-resolution images as small as 2.5 μm voxel size show that branching orders are decreased in the wound vessels during healing. In histological analysis, we found that the contrast agent fills mainly arterioles, but not small capillaries nor large veins. In summary, high-resolution microCT revealed dynamic alterations of vessel structures during wound healing. This technique may be useful as a key tool in the study of the formation and regression of wound vessels. PMID:27009591

Men's Alcohol Expectancies at Selected Community Colleges

ERIC Educational Resources Information Center

Derby, Dustin C.

2011-01-01

Men's alcohol expectancies are an important cognitive-behavioral component of their consumption; yet, sparse research details such behaviors for men in two-year colleges. Selected for inclusion with the current study were 563 men from seven Illinois community colleges. Logistic regression analysis indicated four significant, positive relationships…

Behavioral Cues in the Judgment of Marital Satisfaction: A Linear Regression Analysis

ERIC Educational Resources Information Center

Royce, W. Stephen; Weiss, Robert L.

1975-01-01

Forty undergraduate judges watched videotaped interactions of couples and rated their marital satisfaction based on certain behavioral cues. Results indicate: untrained judges were able to discriminate marital satisfaction/distress with significant validity; judges' ratings were correlated with couples' aversive behavior; and the actuarial…

Predictors of condom use and refusal among the population of Free State province in South Africa

PubMed Central

2012-01-01

Background This study investigated the extent and predictors of condom use and condom refusal in the Free State province in South Africa. Methods Through a household survey conducted in the Free Sate province of South Africa, 5,837 adults were interviewed. Univariate and multivariate survey logistic regressions and classification trees (CT) were used for analysing two response variables ‘ever used condom’ and ‘ever refused condom’. Results Eighty-three per cent of the respondents had ever used condoms, of which 38% always used them; 61% used them during the last sexual intercourse and 9% had ever refused to use them. The univariate logistic regression models and CT analysis indicated that a strong predictor of condom use was its perceived need. In the CT analysis, this variable was followed in importance by ‘knowledge of correct use of condom’, condom availability, young age, being single and higher education. ‘Perceived need’ for condoms did not remain significant in the multivariate analysis after controlling for other variables. The strongest predictor of condom refusal, as shown by the CT, was shame associated with condoms followed by the presence of sexual risk behaviour, knowing one’s HIV status, older age and lacking knowledge of condoms (i.e., ability to prevent sexually transmitted diseases and pregnancy, availability, correct and consistent use and existence of female condoms). In the multivariate logistic regression, age was not significant for condom refusal while affordability and perceived need were additional significant variables. Conclusions The use of complementary modelling techniques such as CT in addition to logistic regressions adds to a better understanding of condom use and refusal. Further improvement in correct and consistent use of condoms will require targeted interventions. In addition to existing social marketing campaigns, tailored approaches should focus on establishing the perceived need for condom-use and improving skills for correct use. They should also incorporate interventions to reduce the shame associated with condoms and individual counselling of those likely to refuse condoms. PMID:22639964

Effect of oral isoflavone supplementation on vascular endothelial function in postmenopausal women: a meta-analysis of randomized placebo-controlled trials.

PubMed

Li, Shao-Hua; Liu, Xu-Xia; Bai, Yong-Yi; Wang, Xiao-Jian; Sun, Kai; Chen, Jing-Zhou; Hui, Ru-Tai

2010-02-01

The effect of isoflavone on endothelial function in postmenopausal women is controversial. The objective of this study was to evaluate the effect of oral isoflavone supplementation on endothelial function, as measured by flow-mediated dilation (FMD), in postmenopausal women. A meta-analysis of randomized placebo-controlled trials was conducted to evaluate the effect of oral isoflavone supplementation on endothelial function in postmenopausal women. Trials were searched in PubMed, Embase, the Cochrane Library database, and reviews and reference lists of relevant articles. Summary estimates of weighted mean differences (WMDs) and 95% CIs were obtained by using random-effects models. Meta-regression and subgroup analyses were performed to identify the source of heterogeneity. A total of 9 trials were reviewed in the present meta-analysis. Overall, the results of the 9 trials showed that isoflavone significantly increased FMD (WMD: 1.75%; 95% CI: 0.83%, 2.67%; P = 0.0002). Meta-regression analysis indicated that the age-adjusted baseline FMD was inversely related to effect size. Subgroup analysis showed that oral supplementation of isoflavone had no influence on FMD if the age-adjusted baseline FMD was > or = 5.2% (4 trials; WMD: 0.24%; 95% CI: -0.94%, 1.42%; P = 0.69). This improvement seemed to be significant when the age-adjusted baseline FMD levels were <5.2% (5 trials; WMD: 2.22%; 95% CI: 1.15%, 3.30%; P < 0.0001), although significant heterogeneity was still detected in this low-baseline-FMD subgroup. Oral isoflavone supplementation does not improve endothelial function in postmenopausal women with high baseline FMD levels but leads to significant improvement in women with low baseline FMD levels.

Preoperative Fasting C-Peptide Predicts Type 2 Diabetes Mellitus Remission in Low-BMI Chinese Patients After Roux-en-Y Gastric Bypass.

PubMed

Zhao, Lei; Li, Weizheng; Su, Zhihong; Liu, Yong; Zhu, Liyong; Zhu, Shaihong

2018-05-29

This study investigated the role of preoperative fasting C-peptide (FCP) levels in predicting diabetic outcomes in low-BMI Chinese patients following Roux-en-Y gastric bypass (RYGB) by comparing the metabolic outcomes of patients with FCP > 1 ng/ml versus FCP ≤ 1 ng/ml. The study sample included 78 type 2 diabetes mellitus patients with an average BMI < 30 kg/m 2 at baseline. Patients' parameters were analyzed before and after surgery, with a 2-year follow-up. A univariate logistic regression analysis and multivariate analysis of variance between the remission and improvement group were performed to determine factors that were associated with type 2 diabetes remission after RYGB. Linear correlation analyses between FCP and metabolic parameters were performed. Patients were divided into two groups: FCP > 1 ng/ml and FCP ≤ 1 ng/ml, with measured parameters compared between the groups. Patients' fasting plasma glucose, 2-h postprandial plasma glucose, FCP, and HbA1c improved significantly after surgery (p < 0.05). Factors associated with type 2 diabetes remission were BMI, 2hINS, and FCP at the univariate logistic regression analysis (p < 0.05). Multivariate logistic regression analysis was performed then showed the results were more related to FCP (OR = 2.39). FCP showed a significant linear correlation with fasting insulin and BMI (p < 0.05). There was a significant difference in remission rate between the FCP > 1 ng/ml and FCP ≤ 1 ng/ml groups (p = 0.01). The parameters of patients with FCP > 1 ng/ml, including BMI, plasma glucose, HbA1c, and plasma insulin, decreased markedly after surgery (p < 0.05). FCP level is a significant predictor of diabetes outcomes after RYGB in low-BMI Chinese patients. An FCP level of 1 ng/ml may be a useful threshold for predicting surgical prognosis, with FCP > 1 ng/ml predicting better clinical outcomes following RYGB.

Early Change in Stroke Size Performs Best in Predicting Response to Therapy.

PubMed

Simpkins, Alexis Nétis; Dias, Christian; Norato, Gina; Kim, Eunhee; Leigh, Richard

2017-01-01

Reliable imaging biomarkers of response to therapy in acute stroke are needed. The final infarct volume and percent of early reperfusion have been used for this purpose. Early fluctuation in stroke size is a recognized phenomenon, but its utility as a biomarker for response to therapy has not been established. This study examined the clinical relevance of early change in stroke volume and compared it with the final infarct volume and percent of early reperfusion in identifying early neurologic improvement (ENI). Acute stroke patients, enrolled between 2013 and 2014 with serial magnetic resonance imaging (MRI) scans (pretreatment baseline, 2 h post, and 24 h post), who received thrombolysis were included in the analysis. Early change in stroke volume, infarct volume at 24 h on diffusion, and percent of early reperfusion were calculated from the baseline and 2 h MRI scans were compared. ENI was defined as ≥4 point decrease in National Institutes of Health Stroke Scales within 24 h. Logistic regression models and receiver operator characteristics analysis were used to compare the efficacy of 3 imaging biomarkers. Serial MRIs of 58 acute stroke patients were analyzed. Early change in stroke volume was significantly associated with ENI by logistic regression analysis (OR 0.93, p = 0.048) and remained significant after controlling for stroke size and severity (OR 0.90, p = 0.032). Thus, for every 1 mL increase in stroke volume, there was a 10% decrease in the odds of ENI, while for every 1 mL decrease in stroke volume, there was a 10% increase in the odds of ENI. Neither infarct volume at 24 h nor percent of early reperfusion were significantly associated with ENI by logistic regression. Receiver-operator characteristic analysis identified early change in stroke volume as the only biomarker of the 3 that performed significantly different than chance (p = 0.03). Early fluctuations in stroke size may represent a more reliable biomarker for response to therapy than the more traditional measures of final infarct volume and percent of early reperfusion. © 2017 S. Karger AG, Basel.

Relationships among body weight, joint moments generated during functional activities, and hip bone mass in older adults

PubMed Central

Wang, Man-Ying; Flanagan, Sean P.; Song, Joo-Eun; Greendale, Gail A.; Salem, George J.

2012-01-01

Objective To investigate the relationships among hip joint moments produced during functional activities and hip bone mass in sedentary older adults. Methods Eight male and eight female older adults (70–85 yr) performed functional activities including walking, chair sit–stand–sit, and stair stepping at a self-selected pace while instrumented for biomechanical analysis. Bone mass at proximal femur, femoral neck, and greater trochanter were measured by dual-energy X-ray absorptiometry. Three-dimensional hip moments were obtained using a six-camera motion analysis system, force platforms, and inverse dynamics techniques. Pearson’s correlation coefficients were employed to assess the relationships among hip bone mass, height, weight, age, and joint moments. Stepwise regression analyses were performed to determine the factors that significantly predicted bone mass using all significant variables identified in the correlation analysis. Findings Hip bone mass was not significantly correlated with moments during activities in men. Conversely, in women bone mass at all sites were significantly correlated with weight, moments generated with stepping, and moments generated with walking (p < 0.05 to p < 0.001). Regression analysis results further indicated that the overall moments during stepping independently predicted up to 93% of the variability in bone mass at femoral neck and proximal femur; whereas weight independently predicted up to 92% of the variability in bone mass at greater trochanter. Interpretation Submaximal loading events produced during functional activities were highly correlated with hip bone mass in sedentary older women, but not men. The findings may ultimately be used to modify exercise prescription for the preservation of bone mass. PMID:16631283

Analysis of Radiation Effects in Digital Subtraction Angiography of Intracranial Artery Stenosis.

PubMed

Guo, Chaoqun; Shi, Xiaolei; Ding, Xianhui; Zhou, Zhiming

2018-04-21

Intracranial artery stenosis (IAS) is the most common cause for acute cerebral accidents. Digital subtraction angiography (DSA) is the gold standard to detect IAS and usually brings excess radiation exposure to examinees and examiners. The artery pathology might influence the interventional procedure, causing prolonged radiation effects. However, no studies on the association between IAS pathology and operational parameters are available. A retrospective analysis was conducted on 93 patients with first-ever stroke/transient ischemic attack, who received DSA examination within 3 months from onset in this single center. Comparison of baseline characteristics was determined by 2-tailed Student's t-test or the chi-square test between subjects with and without IAS. A binary logistic regression analysis was performed to determine the association between IAS pathology and the items with a P value <0.05 in Student's t-test or chi-square test. There were 93 candidates (42 with IAS and 51 without IAS) in this study. The 2 groups shared no significance of the baseline characteristics (P > 0.05). We found a significantly higher total time, higher kerma area product, greater total dose, and greater DSA dose in the IAS group than in those without IAS (P < 0.05). A binary logistic regression analysis indicated the significant association between total time and IAS pathology (P < 0.05) but no significance in kerma area product, radiation dose, and DSA dose (P > 0.05). IAS pathology would indicate a prolonged total time of DSA procedure in clinical practice. However, the radiation effects would not change with pathologic changes. Copyright © 2018 Elsevier Inc. All rights reserved.

Predictors of exercise capacity following exercise-based rehabilitation in patients with coronary heart disease and heart failure: A meta-regression analysis.

PubMed

Uddin, Jamal; Zwisler, Ann-Dorthe; Lewinter, Christian; Moniruzzaman, Mohammad; Lund, Ken; Tang, Lars H; Taylor, Rod S

2016-05-01

The aim of this study was to undertake a comprehensive assessment of the patient, intervention and trial-level factors that may predict exercise capacity following exercise-based rehabilitation in patients with coronary heart disease and heart failure. Meta-analysis and meta-regression analysis. Randomized controlled trials of exercise-based rehabilitation were identified from three published systematic reviews. Exercise capacity was pooled across trials using random effects meta-analysis, and meta-regression used to examine the association between exercise capacity and a range of patient (e.g. age), intervention (e.g. exercise frequency) and trial (e.g. risk of bias) factors. 55 trials (61 exercise-control comparisons, 7553 patients) were included. Following exercise-based rehabilitation compared to control, overall exercise capacity was on average 0.95 (95% CI: 0.76-1.41) standard deviation units higher, and in trials reporting maximum oxygen uptake (VO2max) was 3.3 ml/kg.min(-1) (95% CI: 2.6-4.0) higher. There was evidence of a high level of statistical heterogeneity across trials (I(2) statistic > 50%). In multivariable meta-regression analysis, only exercise intervention intensity was found to be significantly associated with VO2max (P = 0.04); those trials with the highest average exercise intensity had the largest mean post-rehabilitation VO2max compared to control. We found considerable heterogeneity across randomized controlled trials in the magnitude of improvement in exercise capacity following exercise-based rehabilitation compared to control among patients with coronary heart disease or heart failure. Whilst higher exercise intensities were associated with a greater level of post-rehabilitation exercise capacity, there was no strong evidence to support other intervention, patient or trial factors to be predictive. © The European Society of Cardiology 2015.

Evaluation of the magnitude and frequency of floods in urban watersheds in Phoenix and Tucson, Arizona

USGS Publications Warehouse

Kennedy, Jeffrey R.; Paretti, Nicholas V.

2014-01-01

Flooding in urban areas routinely causes severe damage to property and often results in loss of life. To investigate the effect of urbanization on the magnitude and frequency of flood peaks, a flood frequency analysis was carried out using data from urbanized streamgaging stations in Phoenix and Tucson, Arizona. Flood peaks at each station were predicted using the log-Pearson Type III distribution, fitted using the expected moments algorithm and the multiple Grubbs-Beck low outlier test. The station estimates were then compared to flood peaks estimated by rural-regression equations for Arizona, and to flood peaks adjusted for urbanization using a previously developed procedure for adjusting U.S. Geological Survey rural regression peak discharges in an urban setting. Only smaller, more common flood peaks at the 50-, 20-, 10-, and 4-percent annual exceedance probabilities (AEPs) demonstrate any increase in magnitude as a result of urbanization; the 1-, 0.5-, and 0.2-percent AEP flood estimates are predicted without bias by the rural-regression equations. Percent imperviousness was determined not to account for the difference in estimated flood peaks between stations, either when adjusting the rural-regression equations or when deriving urban-regression equations to predict flood peaks directly from basin characteristics. Comparison with urban adjustment equations indicates that flood peaks are systematically overestimated if the rural-regression-estimated flood peaks are adjusted upward to account for urbanization. At nearly every streamgaging station in the analysis, adjusted rural-regression estimates were greater than the estimates derived using station data. One likely reason for the lack of increase in flood peaks with urbanization is the presence of significant stormwater retention and detention structures within the watershed used in the study.

A model for predicting sulcus-to-sulcus diameter in posterior chamber phakic intraocular lens candidates: correlation between ocular biometric parameters.

PubMed

Ghoreishi, Mohammad; Abdi-Shahshahani, Mehdi; Peyman, Alireza; Pourazizi, Mohsen

2018-02-21

The aim of this study was to determine the correlation between ocular biometric parameters and sulcus-to-sulcus (STS) diameter. This was a cross-sectional study of preoperative ocular biometry data of patients who were candidates for phakic intraocular lens (IOL) surgery. Subjects underwent ocular biometry analysis, including refraction error evaluation using an autorefractor and Orbscan topography for white-to-white (WTW) corneal diameter and measurement. Pentacam was used to perform WTW corneal diameter and measurements of minimum and maximum keratometry (K). Measurements of STS and angle-to-angle (ATA) were obtained using a 50-MHz B-mode ultrasound device. Anterior optical coherence tomography was performed for anterior chamber depth measurement. Pearson's correlation test and stepwise linear regression analysis were used to find a model to predict STS. Fifty-eight eyes of 58 patients were enrolled. Mean age ± standard deviation of sample was 28.95 ± 6.04 years. The Pearson's correlation coefficient between STS with WTW, ATA, mean K was 0.383, 0.492, and - 0.353, respectively, which was statistically significant (all P < 0.001). Using stepwise linear regression analysis, there is a statistically significant association between STS with WTW (P = 0.011) and mean K (P = 0.025). The standardized coefficient was 0.323 and - 0.284 for WTW and mean K, respectively. The stepwise linear regression analysis equation was: (STS = 9.549 + 0.518 WTW - 0.083 mean K). Based on our result, given the correlation of STS with WTW and mean K and potential of direct and essay measurement of WTW and mean K, it seems that current IOL sizing protocols could be estimating with WTW and mean K.

[Gender difference in risk factors for depression in community-dwelling elders].

PubMed

Kim, Chul-Gyu; Park, Seungmi

2012-02-01

This study was conducted to compare the degree of depression between men and women and to identify factors influencing their depression. Participants in this cross-sectional descriptive study were 263 persons over 65 years old (men: 103, women: 160). Data were collected through face to face interviews using questionnaires and were done in two urban areas in 2010. Research instruments utilized in this study were SGDS, MMSE-K, SRH, FILE, sleep pattern scale, family and friend support scale, and social support scale. Multivariate regression analysis was performed to identify factors influencing depression in elders. The proportions of participants with depression were significantly different between men and women (52.4% vs. 67.5%). Regression model for depression in elderly men significantly accounted for 54%; disease stress (32%), economic stress (10%), perceived health status (4%), and family support, educational level, age, and hypertension. Regression model for depression in elderly women significantly accounted for 47%; disease stress (25%), perceived social loneliness (8%), friend support (5%), family stress (4%), and sleep satisfaction, and family support. Results demonstrate that depression is an important health problem for elders, and show gender differences for factors influencing depression. These results could be used in the developing depression prevention programs.

Maintenance Operations in Mission Oriented Protective Posture Level IV (MOPPIV)

DTIC Science & Technology

1987-10-01

Repair FADAC Printed Circuit Board ............. 6 3. Data Analysis Techniques ............................. 6 a. Multiple Linear Regression... ANALYSIS /DISCUSSION ............................... 12 1. Exa-ple of Regression Analysis ..................... 12 S2. Regression results for all tasks...6 * TABLE 9. Task Grouping for Analysis ........................ 7 "TABXLE 10. Remove/Replace H60A3 Power Pack................. 8 TABLE

Using regression analysis to predict emergency patient volume at the Indianapolis 500 mile race.

PubMed

Bowdish, G E; Cordell, W H; Bock, H C; Vukov, L F

1992-10-01

Emergency physicians often plan and provide on-site medical care for mass gatherings. Most of the mass gathering literature is descriptive. Only a few studies have looked at factors such as crowd size, event characteristics, or weather in predicting numbers and types of patients at mass gatherings. We used regression analysis to relate patient volume on Race Day at the Indianapolis Motor Speedway to weather conditions and race characteristics. Race Day weather data for the years 1983 to 1989 were obtained from the National Oceanic and Atmospheric Administration. Data regarding patients treated on 1983 to 1989 Race Days were obtained from the facility hospital (Hannah Emergency Medical Center) data base. Regression analysis was performed using weather factors and race characteristics as independent variables and number of patients seen as the dependent variable. Data from 1990 were used to test the validity of the model. There was a significant relationship between dew point (which is calculated from temperature and humidity) and patient load (P less than .01). Dew point, however, failed to predict patient load during the 1990 race. No relationships could be established between humidity, sunshine, wind, or race characteristics and number of patients. Although higher dew point was associated with higher patient load during the 1983 to 1989 races, dew point was a poor predictor of patient load during the 1990 race. Regression analysis may be useful in identifying relationships between event characteristics and patient load but is probably inadequate to explain the complexities of crowd behavior and too simplified to use as a prediction tool.

Interactions between cadmium and decabrominated diphenyl ether on blood cells count in rats-Multiple factorial regression analysis.

PubMed

Curcic, Marijana; Buha, Aleksandra; Stankovic, Sanja; Milovanovic, Vesna; Bulat, Zorica; Đukić-Ćosić, Danijela; Antonijević, Evica; Vučinić, Slavica; Matović, Vesna; Antonijevic, Biljana

2017-02-01

The objective of this study was to assess toxicity of Cd and BDE-209 mixture on haematological parameters in subacutely exposed rats and to determine the presence and type of interactions between these two chemicals using multiple factorial regression analysis. Furthermore, for the assessment of interaction type, an isobologram based methodology was applied and compared with multiple factorial regression analysis. Chemicals were given by oral gavage to the male Wistar rats weighing 200-240g for 28days. Animals were divided in 16 groups (8/group): control vehiculum group, three groups of rats were treated with 2.5, 7.5 or 15mg Cd/kg/day. These doses were chosen on the bases of literature data and reflect relatively high Cd environmental exposure, three groups of rats were treated with 1000, 2000 or 4000mg BDE-209/kg/bw/day, doses proved to induce toxic effects in rats. Furthermore, nine groups of animals were treated with different mixtures of Cd and BDE-209 containing doses of Cd and BDE-209 stated above. Blood samples were taken at the end of experiment and red blood cells, white blood cells and platelets counts were determined. For interaction assessment multiple factorial regression analysis and fitted isobologram approach were used. In this study, we focused on multiple factorial regression analysis as a method for interaction assessment. We also investigated the interactions between Cd and BDE-209 by the derived model for the description of the obtained fitted isobologram curves. Current study indicated that co-exposure to Cd and BDE-209 can result in significant decrease in RBC count, increase in WBC count and decrease in PLT count, when compared with controls. Multiple factorial regression analysis used for the assessment of interactions type between Cd and BDE-209 indicated synergism for the effect on RBC count and no interactions i.e. additivity for the effects on WBC and PLT counts. On the other hand, isobologram based approach showed slight antagonism for the effects on RBC and WBC while no interactions were proved for the joint effect on PLT count. These results confirm that the assessment of interactions between chemicals in the mixture greatly depends on the concept or method used for this evaluation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Logistic regression analysis of risk factors for postoperative recurrence of spinal tumors and analysis of prognostic factors.

PubMed

Zhang, Shanyong; Yang, Lili; Peng, Chuangang; Wu, Minfei

2018-02-01

The aim of the present study was to investigate the risk factors for postoperative recurrence of spinal tumors by logistic regression analysis and analysis of prognostic factors. In total, 77 male and 48 female patients with spinal tumor were selected in our hospital from January, 2010 to December, 2015 and divided into the benign (n=76) and malignant groups (n=49). All the patients underwent microsurgical resection of spinal tumors and were reviewed regularly 3 months after operation. The McCormick grading system was used to evaluate the postoperative spinal cord function. Data were subjected to statistical analysis. Of the 125 cases, 63 cases showed improvement after operation, 50 cases were stable, and deterioration was found in 12 cases. The improvement rate of patients with cervical spine tumor, which reached 56.3%, was the highest. Fifty-two cases of sensory disturbance, 34 cases of pain, 30 cases of inability to exercise, 26 cases of ataxia, and 12 cases of sphincter disorders were found after operation. Seventy-two cases (57.6%) underwent total resection, 18 cases (14.4%) received subtotal resection, 23 cases (18.4%) received partial resection, and 12 cases (9.6%) were only treated with biopsy/decompression. Postoperative recurrence was found in 57 cases (45.6%). The mean recurrence time of patients in the malignant group was 27.49±6.09 months, and the mean recurrence time of patients in the benign group was 40.62±4.34. The results were significantly different (P<0.001). Recurrence was found in 18 cases of the benign group and 39 cases of the malignant group, and results were significantly different (P<0.001). Tumor recurrence was shorter in patients with a higher McCormick grade (P<0.001). Recurrence was found in 13 patients with resection and all the patients with partial resection or biopsy/decompression. The results were significantly different (P<0.001). Logistic regression analysis of total resection-related factors showed that total resection should be the preferred treatment for patients with benign tumors, thoracic and lumbosacral tumors, and lower McCormick grade, as well as patients without syringomyelia and intramedullary tumors. Logistic regression analysis of recurrence-related factors revealed that the recurrence rate was relatively higher in patients with malignant, cervical, thoracic and lumbosacral, intramedullary tumors, and higher McCormick grade and patient received partial resection or biopsy. Tumor property, tumor location, McCormick grade, tumor resection, and intramedullary tumors are risk factors for the recurrence of spinal tumors. Clinical assessment of these risk factors may be helpful in selecting appropriate treatment strategies.

Logistic regression analysis of risk factors for postoperative recurrence of spinal tumors and analysis of prognostic factors

PubMed Central

Zhang, Shanyong; Yang, Lili; Peng, Chuangang; Wu, Minfei

2018-01-01

The aim of the present study was to investigate the risk factors for postoperative recurrence of spinal tumors by logistic regression analysis and analysis of prognostic factors. In total, 77 male and 48 female patients with spinal tumor were selected in our hospital from January, 2010 to December, 2015 and divided into the benign (n=76) and malignant groups (n=49). All the patients underwent microsurgical resection of spinal tumors and were reviewed regularly 3 months after operation. The McCormick grading system was used to evaluate the postoperative spinal cord function. Data were subjected to statistical analysis. Of the 125 cases, 63 cases showed improvement after operation, 50 cases were stable, and deterioration was found in 12 cases. The improvement rate of patients with cervical spine tumor, which reached 56.3%, was the highest. Fifty-two cases of sensory disturbance, 34 cases of pain, 30 cases of inability to exercise, 26 cases of ataxia, and 12 cases of sphincter disorders were found after operation. Seventy-two cases (57.6%) underwent total resection, 18 cases (14.4%) received subtotal resection, 23 cases (18.4%) received partial resection, and 12 cases (9.6%) were only treated with biopsy/decompression. Postoperative recurrence was found in 57 cases (45.6%). The mean recurrence time of patients in the malignant group was 27.49±6.09 months, and the mean recurrence time of patients in the benign group was 40.62±4.34. The results were significantly different (P<0.001). Recurrence was found in 18 cases of the benign group and 39 cases of the malignant group, and results were significantly different (P<0.001). Tumor recurrence was shorter in patients with a higher McCormick grade (P<0.001). Recurrence was found in 13 patients with resection and all the patients with partial resection or biopsy/decompression. The results were significantly different (P<0.001). Logistic regression analysis of total resection-related factors showed that total resection should be the preferred treatment for patients with benign tumors, thoracic and lumbosacral tumors, and lower McCormick grade, as well as patients without syringomyelia and intramedullary tumors. Logistic regression analysis of recurrence-related factors revealed that the recurrence rate was relatively higher in patients with malignant, cervical, thoracic and lumbosacral, intramedullary tumors, and higher McCormick grade and patient received partial resection or biopsy. Tumor property, tumor location, McCormick grade, tumor resection, and intramedullary tumors are risk factors for the recurrence of spinal tumors. Clinical assessment of these risk factors may be helpful in selecting appropriate treatment strategies. PMID:29434866

Creep-Rupture Data Analysis - Engineering Application of Regression Techniques. Ph.D. Thesis - North Carolina State Univ.

NASA Technical Reports Server (NTRS)

Rummler, D. R.

1976-01-01

The results are presented of investigations to apply regression techniques to the development of methodology for creep-rupture data analysis. Regression analysis techniques are applied to the explicit description of the creep behavior of materials for space shuttle thermal protection systems. A regression analysis technique is compared with five parametric methods for analyzing three simulated and twenty real data sets, and a computer program for the evaluation of creep-rupture data is presented.

To Identify the Important Soil Properties Affecting Dinoseb Adsorption with Statistical Analysis

PubMed Central

Guan, Yiqing; Wei, Jianhui; Zhang, Danrong; Zu, Mingjuan; Zhang, Liru

2013-01-01

Investigating the influences of soil characteristic factors on dinoseb adsorption parameter with different statistical methods would be valuable to explicitly figure out the extent of these influences. The correlation coefficients and the direct, indirect effects of soil characteristic factors on dinoseb adsorption parameter were analyzed through bivariate correlation analysis, and path analysis. With stepwise regression analysis the factors which had little influence on the adsorption parameter were excluded. Results indicate that pH and CEC had moderate relationship and lower direct effect on dinoseb adsorption parameter due to the multicollinearity with other soil factors, and organic carbon and clay contents were found to be the most significant soil factors which affect the dinoseb adsorption process. A regression is thereby set up to explore the relationship between the dinoseb adsorption parameter and the two soil factors: the soil organic carbon and clay contents. A 92% of the variation of dinoseb sorption coefficient could be attributed to the variation of the soil organic carbon and clay contents. PMID:23737715

Health utility of patients with Crohn's disease and ulcerative colitis: a systematic review and meta-analysis.

PubMed

Malinowski, Krzysztof Piotr; Kawalec, Paweł

2016-08-01

The aim of this systematic review was to collect and summarize the current data on the utilities of patients with Crohn's disease (CD) and ulcerative colitis (UC). A meta-analysis of the obtained utilities was performed using a random-effects model and meta-regression by the disease type and severity. A bootstrap analysis was performed as it does not require assumption on distribution of the data. The highest utility among patients with CD and UC was observed when the diseases were in remission. The meta-regression analysis showed that both disease severity and an instrument/method/questionnaire used to obtain utilities were significant predictors of utility. Utility was the lowest for severe disease and the highest for disease in remission, the association was more notable in patients with CD compared with UC. Expert commentary: The issue of patients' utility is important for healthcare decision makers but it has not been fully investigated and requires further study.

Youth tobacco sales in a metropolitan county: factors associated with compliance.

PubMed

Pearson, Dave C; Song, Lin; Valdez, Roger B; Angulo, Antoinette S

2007-08-01

To describe and identify factors associated with tobacco sales in a metropolitan county. King County, Washington is the largest county in Washington State with an estimated population of 1.8 million or about 30% of the state's population. The data analysis is based on compliance checks in King County between January 2001 and March 2005. The 8879 checks were conducted by 91 youth operatives aged 14-17. Analysis of data was completed in 2006. The outcome variable for this analysis was whether "a sale was made" to a youth operative during a compliance check. Associations between independent variables and the outcome variable were examined using 2 x 2 tables, univariate (unadjusted) logistic regression, and multivariate (adjusted) logistic regression analysis. Overall tobacco sales during the 4-year and 3-month period was 7.7%. Convenience stores selling gas were significantly more likely to sell tobacco products to minors, whereas restaurants, bars, and tobacco discount stores were less likely to sell to minors. Other factors that were significantly associated with sales are described. In a county that has adopted many of the required youth access laws, opportunities still exist to reduce sales of tobacco products to minors. Asking for age and photo identification still appears to be an effective strategy in reducing sales of tobacco products to minors.

Role of Surgical Services in Profitability of Hospitals in California: An Analysis of Office of Statewide Health Planning and Development Annual Financial Data.

PubMed

Moazzez, Ashkan; de Virgilio, Christian

2016-10-01

With constant changes in health-care laws and payment methods, profitability, and financial sustainability of hospitals are of utmost importance. The purpose of this study is to determine the relationship between surgical services and hospital profitability. The Office of Statewide Health Planning and Development annual financial databases for the years 2009 to 2011 were used for this study. The hospitals' characteristics and income statement elements were extracted for statistical analysis using bivariate and multivariate linear regression. A total of 989 financial records of 339 hospitals were included. On bivariate analysis, the number of inpatient and ambulatory operating rooms (ORs), the number of cases done both as inpatient and outpatient in each OR, and the average minutes used in inpatient ORs were significantly related with the net income of the hospital. On multivariate regression analysis, when controlling for hospitals' payer mix and the study year, only the number of inpatient cases done in the inpatient ORs (β = 832, P = 0.037), and the number of ambulatory ORs (β = 1,485, 466, P = 0.001) were significantly related with the net income of the hospital. These findings suggest that hospitals can maximize their profitability by diverting and allocating outpatient surgeries to ambulatory ORs, to allow for more inpatient surgeries.

Global Prevalence of Elder Abuse: A Meta-analysis and Meta-regression.

PubMed

Ho, C Sh; Wong, S Y; Chiu, M M; Ho, R Cm

2017-06-01

Elder abuse is increasingly recognised as a global public health and social problem. There has been limited inter-study comparison of the prevalence and risk factors for elder abuse. This study aimed to estimate the pooled and subtype prevalence of elder abuse worldwide and identify significant associated risk factors. We conducted a meta-analysis and meta-regression of 34 population-based and 17 non-population-based studies. The pooled prevalences of elder abuse were 10.0% (95% confidence interval, 5.2%-18.6%) and 34.3% (95% confidence interval, 22.9%-47.8%) in population-based studies and third party- or caregiver-reported studies, respectively. Being in a marital relationship was found to be a significant moderator using random-effects model. This meta-analysis revealed that third parties or caregivers were more likely to report abuse than older abused adults. Subgroup analyses showed that females and those resident in non-western countries were more likely to be abused. Emotional abuse was the most prevalent elder abuse subtype and financial abuse was less commonly reported by third parties or caregivers. Heterogeneity in the prevalence was due to the high proportion of married older adults in the sample. Subgroup analysis showed that cultural factors, subtypes of abuse, and gender also contributed to heterogeneity in the pooled prevalence of elder abuse.

Genetic Polymorphisms in RNA Binding Proteins Contribute to Breast Cancer Survival

PubMed Central

Upadhyay, Rohit; Sanduja, Sandhya; Kaza, Vimala; Dixon, Dan A.

2012-01-01

The RNA-binding proteins TTP and HuR control expression of numerous genes associated with breast cancer pathogenesis by regulating mRNA stability. However, the role of genetic variation in TTP (ZFP36) and HuR (ELAVL1) genes is unknown in breast cancer prognosis. A total of 251 breast cancer patients (170 Caucasians and 81 African-Americans) were enrolled and followed-up from 2001 to 2011 (or until death). Genotyping was performed for 10 SNPs in ZFP36 and 7 in ELAVL1 genes. On comparing both races with one another, significant differences were found for clinical and genetic variables. The influence of genetic polymorphisms on survival was analyzed by using Cox-regression, Kaplan-Meier analysis, and the log-rank test. Univariate (Kaplan-Meier/Cox-regression) and multivariate (Cox-regression) analysis showed that the TTP gene polymorphism ZFP36*2 A>G was significantly associated with poor prognosis of Caucasian patients (HR = 2.03; 95% CI = 1.09–3.76; P = 0.025; log-rank P = 0.022). None of the haplotypes, but presence of more than six risk genotypes in Caucasian patients, was significantly associated with poor prognosis (HR=2.42; 95% CI=1.17–4.99; P = 0.017; log-rank P = 0.007). The effect of ZFP36*2 A>G on gene expression was evaluated from patients' tissue samples. Both TTP mRNA and protein expression was significantly decreased in ZFP36*2 G allele carriers compared to A allele homozygotes. Conversely, upregulation of the TTP-target gene COX-2 was observed ZFP36*2 G allele carriers. Through its ability to attenuate TTP gene expression, the ZFP36*2 A>G gene polymorphism has appeared as a novel prognostic breast cancer marker in Caucasian patients. PMID:22907529

Epistasis Analysis for Estrogen Metabolic and Signaling Pathway Genes on Young Ischemic Stroke Patients

PubMed Central

Hsieh, Yi-Chen; Jeng, Jiann-Shing; Lin, Huey-Juan; Hu, Chaur-Jong; Yu, Chia-Chen; Lien, Li-Ming; Peng, Giia-Sheun; Chen, Chin-I; Tang, Sung-Chun; Chi, Nai-Fang; Tseng, Hung-Pin; Chern, Chang-Ming; Hsieh, Fang-I; Bai, Chyi-Huey; Chen, Yi-Rhu; Chiou, Hung-Yi; Jeng, Jiann-Shing; Tang, Sung-Chun; Yeh, Shin-Joe; Tsai, Li-Kai; Kong, Shin; Lien, Li-Ming; Chiu, Hou-Chang; Chen, Wei-Hung; Bai, Chyi-Huey; Huang, Tzu-Hsuan; Chi-Ieong, Lau; Wu, Ya-Ying; Yuan, Rey-Yue; Hu, Chaur-Jong; Sheu, Jau- Jiuan; Yu, Jia-Ming; Ho, Chun-Sum; Chen, Chin-I; Sung, Jia-Ying; Weng, Hsing-Yu; Han, Yu-Hsuan; Huang, Chun-Ping; Chung, Wen-Ting; Ke, Der-Shin; Lin, Huey-Juan; Chang, Chia-Yu; Yeh, Poh-Shiow; Lin, Kao-Chang; Cheng, Tain-Junn; Chou, Chih-Ho; Yang, Chun-Ming; Peng, Giia-Sheun; Lin, Jiann-Chyun; Hsu, Yaw-Don; Denq, Jong-Chyou; Lee, Jiunn-Tay; Hsu, Chang-Hung; Lin, Chun-Chieh; Yen, Che-Hung; Cheng, Chun-An; Sung, Yueh-Feng; Chen, Yuan-Liang; Lien, Ming-Tung; Chou, Chung-Hsing; Liu, Chia-Chen; Yang, Fu-Chi; Wu, Yi-Chung; Tso, An-Chen; Lai, Yu- Hua; Chiang, Chun-I; Tsai, Chia-Kuang; Liu, Meng-Ta; Lin, Ying-Che; Hsu, Yu-Chuan; Chen, Chih-Hung; Sung, Pi-Shan; Chern, Chang-Ming; Hu, Han-Hwa; Wong, Wen-Jang; Luk, Yun-On; Hsu, Li-Chi; Chung, Chih-Ping; Tseng, Hung-Pin; Liu, Chin-Hsiung; Lin, Chun-Liang; Lin, Hung-Chih; Hu, Chaur-Jong

2012-01-01

Background Endogenous estrogens play an important role in the overall cardiocirculatory system. However, there are no studies exploring the hormone metabolism and signaling pathway genes together on ischemic stroke, including sulfotransferase family 1E (SULT1E1), catechol-O-methyl-transferase (COMT), and estrogen receptor α (ESR1). Methods A case-control study was conducted on 305 young ischemic stroke subjects aged ≦ 50 years and 309 age-matched healthy controls. SULT1E1 -64G/A, COMT Val158Met, ESR1 c.454−397 T/C and c.454−351 A/G genes were genotyped and compared between cases and controls to identify single nucleotide polymorphisms associated with ischemic stroke susceptibility. Gene-gene interaction effects were analyzed using entropy-based multifactor dimensionality reduction (MDR), classification and regression tree (CART), and traditional multiple regression models. Results COMT Val158Met polymorphism showed a significant association with susceptibility of young ischemic stroke among females. There was a two-way interaction between SULT1E1 -64G/A and COMT Val158Met in both MDR and CART analysis. The logistic regression model also showed there was a significant interaction effect between SULT1E1 -64G/A and COMT Val158Met on ischemic stroke of the young (P for interaction = 0.0171). We further found that lower estradiol level could increase the risk of young ischemic stroke for those who carry either SULT1E1 or COMT risk genotypes, showing a significant interaction effect (P for interaction = 0.0174). Conclusions Our findings support that a significant epistasis effect exists among estrogen metabolic and signaling pathway genes and gene-environment interactions on young ischemic stroke subjects. PMID:23112845

Evaluation of Relationship between Trunk Muscle Endurance and Static Balance in Male Students

PubMed Central

Barati, Amirhossein; SafarCherati, Afsaneh; Aghayari, Azar; Azizi, Faeze; Abbasi, Hamed

2013-01-01

Purpose Fatigue of trunk muscle contributes to spinal instability over strenuous and prolonged physical tasks and therefore may lead to injury, however from a performance perspective, relation between endurance efficient core muscles and optimal balance control has not been well-known. The purpose of this study was to examine the relationship of trunk muscle endurance and static balance. Methods Fifty male students inhabitant of Tehran university dormitory (age 23.9±2.4, height 173.0±4.5 weight 70.7±6.3) took part in the study. Trunk muscle endurance was assessed using Sørensen test of trunk extensor endurance, trunk flexor endurance test, side bridge endurance test and static balance was measured using single-limb stance test. A multiple linear regression analysis was applied to test if the trunk muscle endurance measures significantly predicted the static balance. Results There were positive correlations between static balance level and trunk flexor, extensor and lateral endurance measures (Pearson correlation test, r=0.80 and P<0.001; r=0.71 and P<0.001; r=0.84 and P<0.001, respectively). According to multiple regression analysis for variables predicting static balance, the linear combination of trunk muscle endurance measures was significantly related to the static balance (F (3,46) = 66.60, P<0.001). Endurance of trunk flexor, extensor and lateral muscles were significantly associated with the static balance level. The regression model which included these factors had the sample multiple correlation coefficient of 0.902, indicating that approximately 81% of the variance of the static balance is explained by the model. Conclusion There is a significant relationship between trunk muscle endurance and static balance. PMID:24800004

The relationship between 25-hydroxyvitamin D levels and ambulatory arterial stiffness index in newly diagnosed and never-treated hypertensive patients.

PubMed

Malçok Gürel, Özgül; Bilgiç, Ayşe; Demirçelik, Bora; Özaydin, Meltem; Bozduman, Fadime; Aytürk, Zübeyde; Yilmaz, Hakki; Atar, Asli; Selçoki, Yusuf; Eryonucu, Beyhan

2016-02-01

Vitamin D insufficiency has been shown to be associated with cardiac dysfunctions, such as cardiac hypertrophy and hypertension, in animal studies. Arterial stiffness is a prognostic marker for cardiovascular disease. Previous studies have demonstrated that 25-hydroxyvitamin D [25(OH)D] levels were negatively correlated with arterial stiffness index. The aim of this study was to investigate the relationship between 25(OH)D levels and arterial stiffness, which is evaluated using an ambulatory arterial stiffness index (AASI), in patients who have untreated and newly diagnosed essential hypertension. A total of 123 consecutive patients with newly diagnosed and untreated essential hypertension were included. Patients were divided into two groups according to their 25(OH)D levels. Vitamin D insufficiency was defined by 25(OH)D levels less than 20 ng/ml. All patients were referred for ambulatory blood pressure monitoring. The regression slope of diastolic and systolic blood pressure was computed for each individual on the basis of ambulatory blood pressure readings. AASI was described as one minus the respective regression slope. The mean AASI was significantly higher in patients with 25(OH)D levels less than 20 as compared with patients with 25(OH)D levels greater than or equal to 20 (0.50±0.20 vs. 0.34±0.17, P<0.001). In Pearson's correlation analysis, AASI had a significantly strong negative correlation with vitamin D levels (r=-0.385, P<0.001). In multivariate linear regression analysis, vitamin D levels were found to be significantly and independently associated with AASI (β=-0.317, P=0.035). Arterial stiffness measured by AASI in newly diagnosed and untreated patients with essential hypertension were significantly related to vitamin D levels.

Innovating patient care delivery: DSRIP's interrupted time series analysis paradigm.

PubMed

Shenoy, Amrita G; Begley, Charles E; Revere, Lee; Linder, Stephen H; Daiger, Stephen P

2017-12-08

Adoption of Medicaid Section 1115 waiver is one of the many ways of innovating healthcare delivery system. The Delivery System Reform Incentive Payment (DSRIP) pool, one of the two funding pools of the waiver has four categories viz. infrastructure development, program innovation and redesign, quality improvement reporting and lastly, bringing about population health improvement. A metric of the fourth category, preventable hospitalization (PH) rate was analyzed in the context of eight conditions for two time periods, pre-reporting years (2010-2012) and post-reporting years (2013-2015) for two hospital cohorts, DSRIP participating and non-participating hospitals. The study explains how DSRIP impacted Preventable Hospitalization (PH) rates of eight conditions for both hospital cohorts within two time periods. Eight PH rates were regressed as the dependent variable with time, intervention and post-DSRIP Intervention as independent variables. PH rates of eight conditions were then consolidated into one rate for regressing with the above independent variables to evaluate overall impact of DSRIP. An interrupted time series regression was performed after accounting for auto-correlation, stationarity and seasonality in the dataset. In the individual regression model, PH rates showed statistically significant coefficients for seven out of eight conditions in DSRIP participating hospitals. In the combined regression model, the coefficient of the PH rate showed a statistically significant decrease with negative p-values for regression coefficients in DSRIP participating hospitals compared to positive/increased p-values for regression coefficients in DSRIP non-participating hospitals. Several macro- and micro-level factors may have likely contributed DSRIP hospitals outperforming DSRIP non-participating hospitals. Healthcare organization/provider collaboration, support from healthcare professionals, DSRIP's design, state reimbursement and coordination in care delivery methods may have led to likely success of DSRIP. IV, a retrospective cohort study based on longitudinal data. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparison of naïve Bayes and logistic regression for computer-aided diagnosis of breast masses using ultrasound imaging

NASA Astrophysics Data System (ADS)

Cary, Theodore W.; Cwanger, Alyssa; Venkatesh, Santosh S.; Conant, Emily F.; Sehgal, Chandra M.

2012-03-01

This study compares the performance of two proven but very different machine learners, Naïve Bayes and logistic regression, for differentiating malignant and benign breast masses using ultrasound imaging. Ultrasound images of 266 masses were analyzed quantitatively for shape, echogenicity, margin characteristics, and texture features. These features along with patient age, race, and mammographic BI-RADS category were used to train Naïve Bayes and logistic regression classifiers to diagnose lesions as malignant or benign. ROC analysis was performed using all of the features and using only a subset that maximized information gain. Performance was determined by the area under the ROC curve, Az, obtained from leave-one-out cross validation. Naïve Bayes showed significant variation (Az 0.733 +/- 0.035 to 0.840 +/- 0.029, P < 0.002) with the choice of features, but the performance of logistic regression was relatively unchanged under feature selection (Az 0.839 +/- 0.029 to 0.859 +/- 0.028, P = 0.605). Out of 34 features, a subset of 6 gave the highest information gain: brightness difference, margin sharpness, depth-to-width, mammographic BI-RADs, age, and race. The probabilities of malignancy determined by Naïve Bayes and logistic regression after feature selection showed significant correlation (R2= 0.87, P < 0.0001). The diagnostic performance of Naïve Bayes and logistic regression can be comparable, but logistic regression is more robust. Since probability of malignancy cannot be measured directly, high correlation between the probabilities derived from two basic but dissimilar models increases confidence in the predictive power of machine learning models for characterizing solid breast masses on ultrasound.

Influence of storage conditions on the stability of monomeric anthocyanins studied by reversed-phase high-performance liquid chromatography.

PubMed

Morais, Helena; Ramos, Cristina; Forgács, Esther; Cserháti, Tibor; Oliviera, José

2002-04-25

The effect of light, storage time and temperature on the decomposition rate of monomeric anthocyanin pigments extracted from skins of grape (Vitis vinifera var. Red globe) was determined by reversed-phase high-performance liquid chromatography (RP-HPLC). The impact of various storage conditions on the pigment stability was assessed by stepwise regression analysis. RP-HPLC separated well the five anthocyanins identified and proved the presence of other unidentified pigments at lower concentrations. Stepwise regression analysis confirmed that the overall decomposition rate of monomeric anthocyanins, peonidin-3-glucoside and malvidin-3-glucoside significantly depended on the time and temperature of storage, the effect of storage time being the most important. The presence or absence of light exerted a negligible impact on the decomposition rate.

Influence factors and forecast of carbon emission in China: structure adjustment for emission peak

NASA Astrophysics Data System (ADS)

Wang, B.; Cui, C. Q.; Li, Z. P.

2018-02-01

This paper introduced Principal Component Analysis and Multivariate Linear Regression Model to verify long-term balance relationships between Carbon Emissions and the impact factors. The integrated model of improved PCA and multivariate regression analysis model is attainable to figure out the pattern of carbon emission sources. Main empirical results indicate that among all selected variables, the role of energy consumption scale was largest. GDP and Population follow and also have significant impacts on carbon emission. Industrialization rate and fossil fuel proportion, which is the indicator of reflecting the economic structure and energy structure, have a higher importance than the factor of urbanization rate and the dweller consumption level of urban areas. In this way, some suggestions are put forward for government to achieve the peak of carbon emissions.

Private prayer among Alzheimer's caregivers: mediating burden and resiliency.

PubMed

Wilks, Scott E; Vonk, M Elizabeth

2008-01-01

This study examined whether the coping method of private prayer served as a protective factor of resiliency among a sample (N = 304) of Alzheimer's caregivers. Participants in caregiver support groups completed questionnaires that assessed a number of constructs, including caregiving burden; prayer frequency; use of private prayer as a means of coping; and perceived resiliency. The sample averaged a moderate level of burden and a great extent of prayer usage. Caregiving burden had positively affected the extent of prayer usage and negatively influenced perceived resiliency. Findings from hierarchical regression analysis showed that caregiving burden and private prayer significantly influenced variation in perceived resiliency scores. Results from a regression equation series and path analysis provided support for prayer as a mediator between burden and perceived resiliency. Implications for social work practice and education are discussed.

Predictors of Dropout by Female Obese Patients Treated with a Group Cognitive Behavioral Therapy to Promote Weight Loss.

PubMed

Sawamoto, Ryoko; Nozaki, Takehiro; Furukawa, Tomokazu; Tanahashi, Tokusei; Morita, Chihiro; Hata, Tomokazu; Komaki, Gen; Sudo, Nobuyuki

2016-01-01

To investigate predictors of dropout from a group cognitive behavioral therapy (CBT) intervention for overweight or obese women. 119 overweight and obese Japanese women aged 25-65 years who attended an outpatient weight loss intervention were followed throughout the 7-month weight loss phase. Somatic characteristics, socioeconomic status, obesity-related diseases, diet and exercise habits, and psychological variables (depression, anxiety, self-esteem, alexithymia, parenting style, perfectionism, and eating attitude) were assessed at baseline. Significant variables, extracted by univariate statistical analysis, were then used as independent variables in a stepwise multiple logistic regression analysis with dropout as the dependent variable. 90 participants completed the weight loss phase, giving a dropout rate of 24.4%. The multiple logistic regression analysis demonstrated that compared to completers the dropouts had significantly stronger body shape concern, tended to not have jobs, perceived their mothers to be less caring, and were more disorganized in temperament. Of all these factors, the best predictor of dropout was shape concern. Shape concern, job condition, parenting care, and organization predicted dropout from the group CBT weight loss intervention for overweight or obese Japanese women. © 2016 S. Karger GmbH, Freiburg.

Predictors of Dropout by Female Obese Patients Treated with a Group Cognitive Behavioral Therapy to Promote Weight Loss

PubMed Central

Sawamoto, Ryoko; Nozaki, Takehiro; Furukawa, Tomokazu; Tanahashi, Tokusei; Morita, Chihiro; Hata, Tomokazu; Komaki, Gen; Sudo, Nobuyuki

2016-01-01

Objective To investigate predictors of dropout from a group cognitive behavioral therapy (CBT) intervention for overweight or obese women. Methods 119 overweight and obese Japanese women aged 25-65 years who attended an outpatient weight loss intervention were followed throughout the 7-month weight loss phase. Somatic characteristics, socioeconomic status, obesity-related diseases, diet and exercise habits, and psychological variables (depression, anxiety, self-esteem, alexithymia, parenting style, perfectionism, and eating attitude) were assessed at baseline. Significant variables, extracted by univariate statistical analysis, were then used as independent variables in a stepwise multiple logistic regression analysis with dropout as the dependent variable. Results 90 participants completed the weight loss phase, giving a dropout rate of 24.4%. The multiple logistic regression analysis demonstrated that compared to completers the dropouts had significantly stronger body shape concern, tended to not have jobs, perceived their mothers to be less caring, and were more disorganized in temperament. Of all these factors, the best predictor of dropout was shape concern. Conclusion Shape concern, job condition, parenting care, and organization predicted dropout from the group CBT weight loss intervention for overweight or obese Japanese women. PMID:26745715

Do antipsychotics lead to cognitive impairment in dementia? A meta-analysis of randomised placebo-controlled trials.

PubMed

Wolf, Alexander; Leucht, Stefan; Pajonk, Frank-Gerald

2017-04-01

Behavioural and psychological symptoms in dementia (BPSD) are common and often treated with antipsychotics, which are known to have small efficacy and to cause many side effects. One potential side effect might be cognitive decline. We searched MEDLINE, Scopus, CENTRAL and www.ClincalStudyResult.org for randomized, double-blind, placebo-controlled trials using antipsychotics for treating BPSD and evaluated cognitive functioning. The studies identified were summarized in a meta-analysis with the standardized mean difference (SMD, Hedges's g) as the effect size. Meta-regression was additionally performed to identify associated factors. Ten studies provided data on the course of cognitive functioning. The random effects model of the pooled analysis showed a not significant effect (SMD = -0.065, 95 % CI -0.186 to 0.057, I 2  = 41 %). Meta-regression revealed a significant correlation between cognitive impairment and treatment duration (R 2  = 0.78, p < 0.02) as well as baseline MMSE (R 2  = 0.92, p < 0.005). These correlations depend on only two out of ten studies and should interpret cautiously.

Using Social Network Analysis to Better Understand Compulsive Exercise Behavior Among a Sample of Sorority Members.

PubMed

Patterson, Megan S; Goodson, Patricia

2017-05-01

Compulsive exercise, a form of unhealthy exercise often associated with prioritizing exercise and feeling guilty when exercise is missed, is a common precursor to and symptom of eating disorders. College-aged women are at high risk of exercising compulsively compared with other groups. Social network analysis (SNA) is a theoretical perspective and methodology allowing researchers to observe the effects of relational dynamics on the behaviors of people. SNA was used to assess the relationship between compulsive exercise and body dissatisfaction, physical activity, and network variables. Descriptive statistics were conducted using SPSS, and quadratic assignment procedure (QAP) analyses were conducted using UCINET. QAP regression analysis revealed a statistically significant model (R 2 = .375, P < .0001) predicting compulsive exercise behavior. Physical activity, body dissatisfaction, and network variables were statistically significant predictor variables in the QAP regression model. In our sample, women who are connected to "important" or "powerful" people in their network are likely to have higher compulsive exercise scores. This result provides healthcare practitioners key target points for intervention within similar groups of women. For scholars researching eating disorders and associated behaviors, this study supports looking into group dynamics and network structure in conjunction with body dissatisfaction and exercise frequency.

The association between GGCX, miR-133 genetic polymorphisms and warfarin stable dosage in Han Chinese patients with mechanical heart valve replacement.

PubMed

Tang, X-Y; Zhang, J; Peng, J; Tan, S-L; Zhang, W; Song, G-B; Liu, L-M; Li, C-L; Ren, H; Zeng, L; Liu, Z-Q; Chen, X-P; Zhou, X-M; Zhou, H-H; Hu, J-X; Li, Z

2017-08-01

Warfarin is a widely used anticoagulant with a narrow therapeutic index. Polymorphisms in the VKORC1, CYP2C9 and CYP4F2 genes have been verified to correlate with warfarin stable dosage (WSD). Whether any other genes or variants affect the dosage is unknown. The aim of our study was to investigate the relationship between GGCX, miR-133 variants and the WSD in Han Chinese patients with mechanical heart valve replacement (MHVR). A total of 231 patients were enrolled in the study. Blood samples were collected for genotyping. The average WSD among subjects with different GGCX or miR-133 genotypes was compared. Regression analyses were performed to test for any association of genetic polymorphisms with WSD. The warfarin dosage in patients with the GGCX rs699664 TT and rs12714145 TT genotypes was 3.77±0.93 (95% CI: 3.35-4.19) mg/d and 3.70±1.00 (95% CI: 3.32-4.09) mg/d, respectively. The GGCX rs699664 and rs12714145 genotypes were significantly associated with WSD (P<.05). But they were ruled out in the multivariate regression analysis. There were no significant differences in the average warfarin stable dosage between subjects with MIR133B rs142410335 wild-type and variant genotypes (P>.05). The genotypes of GGCX rs699644 and rs12714145 were significantly associated with WSD (P<.05), but their contributions were not significant after accounting for other factors. MIR133B rs142410335 makes no significant contributions to warfarin stable dosage in Han Chinese patients with MHVR neither in univariate regression nor in multivariate regression analyses. © 2017 John Wiley & Sons Ltd.

Relationship between negative mental adjustment to cancer and distress in thyroid cancer patients.

PubMed

Seok, Jeong-Ho; Choi, Won-Jung; Lee, Yong Sang; Park, Cheong Soo; Oh, Young-Ja; Kim, Jong-Sun; Chang, Hang-Seok

2013-05-01

Previous studies have reported that over a third of cancer patients experience significant psychological distress with diagnosis and treatment of cancer. Mental adjustment to cancer as well as other biologic and demographic factors may be associated with their distress. We investigated the relationship between mental adjustment and distress in patients with thyroid cancer prior to thyroidectomy. One hundred and fifty-two thyroid cancer patients were included in the final analysis. After global distress levels were screened with a distress thermometer, patients were evaluated concerning mental adjustment to cancer, as well as demographic and cancer-related characteristics. A thyroid function test was also performed. Regression analysis was performed to discern significant factors associated with distress in thyroid cancer patients. Our regression model was significant and explained 38.5% of the total variance in distress of this patient group. Anxious-preoccupation and helpless-hopeless factors on the mental adjustment to cancer scale were significantly associated with distress in thyroid cancer patients. Negative emotional response to cancer diagnosis may be associated with distress in thyroid cancer patients awaiting thyroidectomy. Screening of mental coping strategies at the beginning of cancer treatment may predict psychological distress in cancer patients. Further studies on the efficacy of psychiatric intervention during cancer treatment may be needed for patients showing maladaptive psychological responses to cancer.

Association between kyphosis and subacromial impingement syndrome: LOHAS study.

PubMed

Otoshi, Kenichi; Takegami, Misa; Sekiguchi, Miho; Onishi, Yoshihiro; Yamazaki, Shin; Otani, Koji; Shishido, Hiroaki; Kikuchi, Shinichi; Konno, Shinichi

2014-12-01

Kyphosis is a cause of scapular dyskinesis, which can induce various shoulder disorders, including subacromial impingement syndrome (SIS). This study aimed to clarify the impact of kyphosis on SIS with use of cross-sectional data from the Locomotive Syndrome and Health Outcome in Aizu Cohort Study (LOHAS). The study enrolled 2144 participants who were older than 40 years and participated in health checkups in 2010. Kyphosis was assessed by the wall-occiput test (WOT) for thoracic kyphosis and the rib-pelvic distance test (RPDT) for lumbar kyphosis. The associations between kyphosis, SIS, and reduction in shoulder elevation (RSE) were investigated. Age- and gender-adjusted logistic regression analysis demonstrated significant association between SIS and WOT (odds ratio, 1.65; 95% confidence interval, 1.02, 2.64; P < .05), whereas there was no significant association between SIS and RPDT. Multivariable logistic regression analysis demonstrated no significant association between SIS and both WOT and RPDT, whereas there was significant association between SIS and RSE. RSE plays a key role in the development of SIS, and thoracic kyphosis might influence the development of SIS indirectly by reducing shoulder elevation induced by the restriction of the thoracic spine extension and scapular dyskinesis. Copyright © 2014 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

The effect of hospital mergers on long-term sickness absence among hospital employees: a fixed effects multivariate regression analysis using panel data.

PubMed

Kjekshus, Lars Erik; Bernstrøm, Vilde Hoff; Dahl, Espen; Lorentzen, Thomas

2014-02-03

Hospitals are merging to become more cost-effective. Mergers are often complex and difficult processes with variable outcomes. The aim of this study was to analyze the effect of mergers on long-term sickness absence among hospital employees. Long-term sickness absence was analyzed among hospital employees (N = 107 209) in 57 hospitals involved in 23 mergers in Norway between 2000 and 2009. Variation in long-term sickness absence was explained through a fixed effects multivariate regression analysis using panel data with years-since-merger as the independent variable. We found a significant but modest effect of mergers on long-term sickness absence in the year of the merger, and in years 2, 3 and 4; analyzed by gender there was a significant effect for women, also for these years, but only in year 4 for men. However, men are less represented among the hospital workforce; this could explain the lack of significance. Mergers has a significant effect on employee health that should be taken into consideration when deciding to merge hospitals. This study illustrates the importance of analyzing the effects of mergers over several years and the need for more detailed analyses of merger processes and of the changes that may occur as a result of such mergers.

Determinants of plasma NT-pro-BNP levels in patients with atrial fibrillation and preserved left ventricular ejection fraction.

PubMed

Letsas, Konstantinos P; Filippatos, Gerasimos S; Pappas, Loukas K; Mihas, Constantinos C; Markou, Virginia; Alexanian, Ioannis P; Efremidis, Michalis; Sideris, Antonios; Maisel, Alan S; Kardaras, Fotios

2009-02-01

The present study aimed to investigate the clinical and echocardiographic determinants of plasma NT-pro-BNP levels in patients with atrial fibrillation (AF) and preserved left ventricular ejection fraction (LVEF). NT-pro-BNP levels were measured in 45 patients with paroxysmal AF, 41 patients with permanent AF and 48 controls. NT-pro-BNP levels were found significantly elevated in patients with paroxysmal (215+/-815 pg/ml) and permanent AF (1,086+/-835 pg/ml) in relation to control population (86.3+/-77.9 pg/ml) (P<0.001). According to the univariate linear regression analysis, age, hypertension, beta-blocker use, left atrial diameter (LAD), LVEF and AF status (paroxysmal or permanent or both) were significantly associated with NT-pro-BNP levels (P<0.05). In multiple linear regression analysis, LVEF (B coefficient: -53.030; CI: -95.738 to -10.322; P: 0.015) and LAD (B coefficient: 285.858; CI: 23.731-547.986; P: 0.033) were significant and independent determinants of NT-pro-BNP levels. Plasma NT-pro-BNP levels were significantly higher in patients with paroxysmal and permanent AF compared to those with sinus rhythm in the setting of preserved left ventricular systolic function. LVEF and LAD were independent predictors of NT-pro-BNP levels.

Creativity, Bipolar Disorder Vulnerability and Psychological Well-Being: A Preliminary Study

ERIC Educational Resources Information Center

Gostoli, Sara; Cerini, Veronica; Piolanti, Antonio; Rafanelli, Chiara

2017-01-01

The aim of this research was to investigate the relationships between creativity, subclinical bipolar disorder symptomatology, and psychological well-being. The study method was of descriptive, correlational type. Significant tests were performed using multivariate regression analysis. Students of the 4th grade of 6 different Italian colleges…

Role of the Big Five Personality Traits in Predicting College Students' Academic Motivation and Achievement

ERIC Educational Resources Information Center

Komarraju, Meera; Karau, Steven J.; Schmeck, Ronald R.

2009-01-01

College students (308 undergraduates) completed the Five Factor Inventory and the Academic Motivations Scale, and reported their college grade point average (GPA). A correlation analysis revealed an interesting pattern of significant relationships. Further, regression analyses indicated that conscientiousness and openness explained 17% of the…

The Role of Spirituality in Coping with Visual Impairment

ERIC Educational Resources Information Center

Yampolsky, Maya A.; Wittich, Walter; Webb, Gail; Overbury, Olga

2008-01-01

Spirituality and coping behaviors were measured in 85 individuals with visual impairments aged 23 to 97. A regression analysis indicated that the religious well-being subscale of the Spiritual Well-Being Scale is a significant predictor of adaptive coping behaviors, indicating that higher religious well-being facilitates adaptive coping. (Contains…

Self-Efficacy for Resolving Environmental Uncertainties: Implications for Entrepreneurial Educational and Support Programs

ERIC Educational Resources Information Center

Pushkarskaya, Helen; Usher, Ellen L.

2010-01-01

Using a unique sample of rural Kentucky residents, we demonstrated that, in the domain of operational and competitive environmental uncertainties, self-efficacy beliefs are significantly higher among nascent entrepreneurs than among non-entrepreneurs. We employed the hierarchical logistic regression analysis to demonstrate that this result is…

Intraorganizational versus Interorganizational Uses and Benefits of Electronic Mail.

ERIC Educational Resources Information Center

McManus, Denise J.; Sankar, Chetan S.; Carr, Houston H.; Ford, F. Nelson

2002-01-01

Discussion of communication within organizations and with the outside world focuses on results of a survey of managers in 41 companies that assessed intraorganizational and interorganizational uses of email. Describes the use of factor analysis and regression methodologies to investigate whether a significant relationship existed between internal…

An Examination of the Roles of Rationalization and Narcissism in Facilitating Academic Dishonesty

ERIC Educational Resources Information Center

Faulkner, Karen

2012-01-01

Academic dishonesty is a significant problem among college students. Numerous factors affect levels of cheating. This study utilized an original survey on cheating and rationalization along with the Narcissistic Personality Inventory and multiple regression analysis to examine the relationships between rationalization, narcissism, and academic…

Getting Answers to Natural Language Questions on the Web.

ERIC Educational Resources Information Center

Radev, Dragomir R.; Libner, Kelsey; Fan, Weiguo

2002-01-01

Describes a study that investigated the use of natural language questions on Web search engines. Highlights include query languages; differences in search engine syntax; and results of logistic regression and analysis of variance that showed aspects of questions that predicted significantly different performances, including the number of words,…

Academic Admission Requirements as Predictors of Counseling Knowledge, Personal Development, and Counseling Skills

ERIC Educational Resources Information Center

Smaby, Marlowe H.; Maddux, Cleborne D.; Richmond, Aaron S.; Lepkowski, William J.; Packman, Jill

2005-01-01

The authors investigated whether undergraduates' scores on the Verbal and Quantitative tests of the Graduate Record Examinations and their undergraduate grade point average can be used to predict knowledge, personal development, and skills of graduates of counseling programs. Multiple regression analysis produced significant models predicting…

Environmental factors affecting understory diversity in second-growth deciduous forests

Treesearch

Cynthia D. Huebner; J.C. Randolph; G.R. Parker

1995-01-01

The purpose of this study was to determine the most important nonanthropogenic factors affecting understory (herbs, shrubs and low-growing vines) diversity in forested landscapes of southern Indiana. Fourteen environmental variables were measured for 46 sites. Multiple regression analysis showed significant positive correlation between understory diversity and tree...

Role of Social Performance in Predicting Learning Problems: Prediction of Risk Using Logistic Regression Analysis

ERIC Educational Resources Information Center

Del Prette, Zilda Aparecida Pereira; Prette, Almir Del; De Oliveira, Lael Almeida; Gresham, Frank M.; Vance, Michael J.

2012-01-01

Social skills are specific behaviors that individuals exhibit in order to successfully complete social tasks whereas social competence represents judgments by significant others that these social tasks have been successfully accomplished. The present investigation identified the best sociobehavioral predictors obtained from different raters…

Standards for Standardized Logistic Regression Coefficients

ERIC Educational Resources Information Center

Menard, Scott

2011-01-01

Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

Linear regression analysis: part 14 of a series on evaluation of scientific publications.

PubMed

Schneider, Astrid; Hommel, Gerhard; Blettner, Maria

2010-11-01

Regression analysis is an important statistical method for the analysis of medical data. It enables the identification and characterization of relationships among multiple factors. It also enables the identification of prognostically relevant risk factors and the calculation of risk scores for individual prognostication. This article is based on selected textbooks of statistics, a selective review of the literature, and our own experience. After a brief introduction of the uni- and multivariable regression models, illustrative examples are given to explain what the important considerations are before a regression analysis is performed, and how the results should be interpreted. The reader should then be able to judge whether the method has been used correctly and interpret the results appropriately. The performance and interpretation of linear regression analysis are subject to a variety of pitfalls, which are discussed here in detail. The reader is made aware of common errors of interpretation through practical examples. Both the opportunities for applying linear regression analysis and its limitations are presented.

The Role of Habit and Perceived Control on Health Behavior among Pregnant Women.

PubMed

Mullan, Barbara; Henderson, Joanna; Kothe, Emily; Allom, Vanessa; Orbell, Sheina; Hamilton, Kyra

2016-05-01

Many pregnant women do not adhere to physical activity and dietary recommendations. Research investigating what psychological processes might predict physical activity and healthy eating (fruit and vegetable consumption) during pregnancy is scant. We explored the role of intention, habit, and perceived behavioral control as predictors of physical activity and healthy eating. Pregnant women (N = 195, Mage = 30.17, SDage = 4.46) completed questionnaires at 2 time points. At Time 1, participants completed measures of intention, habit, and perceived behavioral control. At Time 2, participants reported on their behavior (physical activity and healthy eating) within the intervening week. Regression analysis determined whether Time 1 variables predicted behavior at Time 2. Interaction terms also were tested. Final regression models indicated that only intention and habit explained significant variance in physical activity, whereas habit and the interaction between intention and habit explained significant variance in healthy eating. Simple slopes analysis indicated that the relationship between intention and healthy eating behavior was only significant at high levels of habit. Findings highlight the influence of habit on behavior and suggest that automaticity interventions may be useful in changing health behaviors during pregnancy.

Statistical analysis of the factors that influenced the mechanical properties improvement of cassava starch films

NASA Astrophysics Data System (ADS)

Monteiro, Mayra; Oliveira, Victor; Santos, Francisco; Barros Neto, Eduardo; Silva, Karyn; Silva, Rayane; Henrique, João; Chibério, Abimaelle

2017-08-01

In order to obtain cassava starch films with improved mechanical properties in relation to the synthetic polymer in the packaging production, a complete factorial design 23 was carried out in order to investigate which factor significantly influences the tensile strength of the biofilm. The factors to be investigated were cassava starch, glycerol and modified clay contents. Modified bentonite clay was used as a filling material of the biofilm. Glycerol was the plasticizer used to thermoplastify cassava starch. The factorial analysis suggested a regression model capable of predicting the optimal mechanical property of the cassava starch film from the maximization of the tensile strength. The reliability of the regression model was tested by the correlation established with the experimental data through the following statistical analyse: Pareto graph. The modified clay was the factor of greater statistical significance on the observed response variable, being the factor that contributed most to the improvement of the mechanical property of the starch film. The factorial experiments showed that the interaction of glycerol with both modified clay and cassava starch was significant for the reduction of biofilm ductility. Modified clay and cassava starch contributed to the maximization of biofilm ductility, while glycerol contributed to the minimization.

Language and hope in schizophrenia-spectrum disorders.

PubMed

Bonfils, Kelsey A; Luther, Lauren; Firmin, Ruth L; Lysaker, Paul H; Minor, Kyle S; Salyers, Michelle P

2016-11-30

Hope is integral to recovery for those with schizophrenia. Considering recent advancements in the examination of clients' lexical qualities, we were interested in how clients' words reflect hope. Using computerized lexical analysis, we examined social, emotion, and future words' relations to hope and its pathways and agency components. Forty-five clients provided detailed narratives about their life and mental illness. Transcripts were analyzed using the Linguistic Inquiry and Word Count program (LIWC), which assigns words to categories (e.g., "anxiety") based on a pre-existing dictionary. Correlations and linear multiple regression were used to examine relationships between lexical qualities and hope. Hope and its subcomponents had significant or trending bivariate correlations in expected directions with several emotion-related word categories (anger and sadness) but were not associated with expected categories such as social words, positive emotions, optimism, achievement, and future words. In linear multiple regressions, no LIWC variable significantly predicted hope agency, but anger words significantly predicted both total hope and hope pathways. Our findings indicate lexical analysis tools can be used to investigate recovery-oriented concepts such as hope, and results may inform clinical practice. Future research should aim to replicate our findings in larger samples. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

An improved multiple linear regression and data analysis computer program package

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

Regression discontinuity was a valid design for dichotomous outcomes in three randomized trials.

PubMed

van Leeuwen, Nikki; Lingsma, Hester F; Mooijaart, Simon P; Nieboer, Daan; Trompet, Stella; Steyerberg, Ewout W

2018-06-01

Regression discontinuity (RD) is a quasi-experimental design that may provide valid estimates of treatment effects in case of continuous outcomes. We aimed to evaluate validity and precision in the RD design for dichotomous outcomes. We performed validation studies in three large randomized controlled trials (RCTs) (Corticosteroid Randomization After Significant Head injury [CRASH], the Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries [GUSTO], and PROspective Study of Pravastatin in elderly individuals at risk of vascular disease [PROSPER]). To mimic the RD design, we selected patients above and below a cutoff (e.g., age 75 years) randomized to treatment and control, respectively. Adjusted logistic regression models using restricted cubic splines (RCS) and polynomials and local logistic regression models estimated the odds ratio (OR) for treatment, with 95% confidence intervals (CIs) to indicate precision. In CRASH, treatment increased mortality with OR 1.22 [95% CI 1.06-1.40] in the RCT. The RD estimates were 1.42 (0.94-2.16) and 1.13 (0.90-1.40) with RCS adjustment and local regression, respectively. In GUSTO, treatment reduced mortality (OR 0.83 [0.72-0.95]), with more extreme estimates in the RD analysis (OR 0.57 [0.35; 0.92] and 0.67 [0.51; 0.86]). In PROSPER, similar RCT and RD estimates were found, again with less precision in RD designs. We conclude that the RD design provides similar but substantially less precise treatment effect estimates compared with an RCT, with local regression being the preferred method of analysis. Copyright © 2018 Elsevier Inc. All rights reserved.

Vitrified-warmed embryo transfer is associated with mean higher singleton birth weight compared to fresh embryo transfer.

PubMed

Beyer, Daniel Alexander; Griesinger, Georg

2016-08-01

To test for differences in birth weight between singletons born after IVF with fresh embryo transfer vs. vitrified-warmed 2PN embryo transfer (vitrification protocol). Retrospective analysis of 464 singleton live births after IVF or ICSI during a 12 year period. University hospital. Fresh embryo transfer, vitrified-warmed 2PN embryo transfer (vitrification protocol). Birth weight standardized as a z-score, adjusting for gestational week at delivery and fetal sex. As a reference, birth weight means from regular deliveries from the same hospital were used. Multivariate regression analysis was used to investigate the relationship between the dependent variable z-score (fetal birth weight) and the independent predictor variables maternal age, weight, height, body mass index, RDS prophylaxis, transfer protocol, number of embryos transferred, indication for IVF treatment and sperm quality. The mean z-score was significantly lower after fresh transfer (-0.11±92) as compared to vitrification transfer (0.72±83) (p<0.001). Multivariate regression analysis indicated that only maternal height and maternal body mass index, but not type of cryopreservation protocol, was a significant predictor of birth weight. In this analysis focusing on 2PN oocytes, vitrified-warmed embryo transfer is associated with mean higher birth weight compared to fresh embryo transfer. Maternal height and body mass index are significant confounders of fetal birth weight and need to be taken into account when studying birth weight differences between ART protocols. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Mortality prediction of head Abbreviated Injury Score and Glasgow Coma Scale: analysis of 7,764 head injuries.

PubMed

Demetriades, Demetrios; Kuncir, Eric; Murray, James; Velmahos, George C; Rhee, Peter; Chan, Linda

2004-08-01

We assessed the prognostic value and limitations of Glasgow Coma Scale (GCS) and head Abbreviated Injury Score (AIS) and correlated head AIS with GCS. We studied 7,764 patients with head injuries. Bivariate analysis was performed to examine the relationship of GCS, head AIS, age, gender, and mechanism of injury with mortality. Stepwise logistic regression analysis was used to identify the independent risk factors associated with mortality. The overall mortality in the group of head injury patients with no other major extracranial injuries and no hypotension on admission was 9.3%. Logistic regression analysis identified head AIS, GCS, age, and mechanism of injury as significant independent risk factors of death. The prognostic value of GCS and head AIS was significantly affected by the mechanism of injury and the age of the patient. Patients with similar GCS or head AIS but different mechanisms of injury or ages had significantly different outcomes. The adjusted odds ratio of death in penetrating trauma was 5.2 (3.9, 7.0), p < 0.0001, and in the age group > or = 55 years the adjusted odds ratio was 3.4 (2.6, 4.6), p < 0.0001. There was no correlation between head AIS and GCS (correlation coefficient -0.31). Mechanism of injury and age have a major effect in the predictive value of GCS and head AIS. There is no good correlation between GCS and head AIS.

Effect of obstructive sleep apnea hypopnea syndrome on lipid profile: a meta-regression analysis.

PubMed

Nadeem, Rashid; Singh, Mukesh; Nida, Mahwish; Waheed, Irfan; Khan, Adnan; Ahmed, Saeed; Naseem, Jawed; Champeau, Daniel

2014-05-15

Obstructive sleep apnea (OSA) is associated with obesity, metabolic syndrome, and dyslipidemia, which may be related to decrease androgen levels found in OSA patients. Dyslipidemia may contribute to atherosclerosis leading to increasing risk of heart disease. Systematic review was conducted using PubMed and Cochrane library by utilizing different combinations of key words; sleep apnea, obstructive sleep apnea, serum lipids, dyslipidemia, cholesterol, total cholesterol, low density lipoprotein (LDL), high density lipoprotein (HDL), and triglyceride (TG). Inclusion criteria were: English articles, and studies with adult population in 2 groups of patients (patients with OSA and without OSA). A total 96 studies were reviewed for inclusion, with 25 studies pooled for analysis. Sixty-four studies were pooled for analysis; since some studies have more than one dataset, there were 107 datasets with 18,116 patients pooled for meta-analysis. All studies measured serum lipids. Total cholesterol pooled standardized difference in means was 0.267 (p = 0.001). LDL cholesterol pooled standardized difference in means was 0.296 (p = 0.001). HDL cholesterol pooled standardized difference in means was -0.433 (p = 0.001). Triglyceride pooled standardized difference in means was 0.603 (p = 0.001). Meta-regression for age, BMI, and AHI showed that age has significant effect for TC, LDL, and HDL. BMI had significant effect for LDL and HDL, while AHI had significant effect for LDL and TG. Patients with OSA appear to have increased dyslipidemia (high total cholesterol, LDL, TG, and low HDL).

Predicting Scientific Understanding of Prospective Elementary Teachers: Role of Gender, Education Level, Courses in Science, and Attitudes Toward Science and Mathematics

NASA Astrophysics Data System (ADS)

Kumar, David D.; Morris, John D.

2005-12-01

A multiple regression analysis of the relationship between prospective teachers' scientific understanding and Gender, Education Level (High School, College), Courses in Science (Biology, Chemistry, Physics, Earth Science, Astronomy, and Agriculture), Attitude Towards Science, and Attitude Towards Mathematics is reported. Undergraduate elementary science students ( N = 176) in an urban doctoral-level university in the United States participated in this study. The results of this study showed Gender, completion of courses in High School Chemistry and Physics, College Chemistry and Physics, and Attitudes Toward Mathematics and Science significantly correlated with scientific understanding. Based on a regression model, Gender, and College Chemistry and Physics experiences added significant predictive accuracy to scientific understanding among prospective elementary teachers compared to the other variables.

Methodologic considerations in the design and analysis of nested case-control studies: association between cytokines and postoperative delirium.

PubMed

Ngo, Long H; Inouye, Sharon K; Jones, Richard N; Travison, Thomas G; Libermann, Towia A; Dillon, Simon T; Kuchel, George A; Vasunilashorn, Sarinnapha M; Alsop, David C; Marcantonio, Edward R

2017-06-06

The nested case-control study (NCC) design within a prospective cohort study is used when outcome data are available for all subjects, but the exposure of interest has not been collected, and is difficult or prohibitively expensive to obtain for all subjects. A NCC analysis with good matching procedures yields estimates that are as efficient and unbiased as estimates from the full cohort study. We present methodological considerations in a matched NCC design and analysis, which include the choice of match algorithms, analysis methods to evaluate the association of exposures of interest with outcomes, and consideration of overmatching. Matched, NCC design within a longitudinal observational prospective cohort study in the setting of two academic hospitals. Study participants are patients aged over 70 years who underwent scheduled major non-cardiac surgery. The primary outcome was postoperative delirium from in-hospital interviews and medical record review. The main exposure was IL-6 concentration (pg/ml) from blood sampled at three time points before delirium occurred. We used nonparametric signed ranked test to test for the median of the paired differences. We used conditional logistic regression to model the risk of IL-6 on delirium incidence. Simulation was used to generate a sample of cohort data on which unconditional multivariable logistic regression was used, and the results were compared to those of the conditional logistic regression. Partial R-square was used to assess the level of overmatching. We found that the optimal match algorithm yielded more matched pairs than the greedy algorithm. The choice of analytic strategy-whether to consider measured cytokine levels as the predictor or outcome-- yielded inferences that have different clinical interpretations but similar levels of statistical significance. Estimation results from NCC design using conditional logistic regression, and from simulated cohort design using unconditional logistic regression, were similar. We found minimal evidence for overmatching. Using a matched NCC approach introduces methodological challenges into the study design and data analysis. Nonetheless, with careful selection of the match algorithm, match factors, and analysis methods, this design is cost effective and, for our study, yields estimates that are similar to those from a prospective cohort study design.

Physical Activity Level of Korean Adults with Chronic Diseases: The Korean National Health and Nutritional Examination Survey, 2010-2012.

PubMed

Jin, Ho-Seong; An, Ah-Reum; Choi, Ho-Chun; Lee, Sang-Hyun; Shin, Dong-Heon; Oh, Seung-Min; Seo, Young-Gyun; Cho, Be-Long

2015-11-01

Proper physical activities are known to be helpful in the prevention and management of chronic diseases. However, the physical activity level of patients with chronic diseases is low. Therefore, this study aimed to investigate the physical activity compliance of patients with hypertension, diabetes, and dyslipidemia in Korea. This study analyzed the 2010-2012 Fifth Korean National Health and Nutrition Examination Survey data. We included 13,873 individuals in the analysis. The level of physical activity compliance was measured by performing multivariate logistic regression analyses. In the univariate analysis, the subjects with hypertension or diabetes tended to comply with the physical activity guidelines less faithfully than their healthy counterparts. The proportion of subjects with hypertension who were insufficiently physically active was 65.4% among the men and 75.8% among the women. For diabetes, the proportions were 66.7% and 76.8%, respectively. No significant difference was found between the subjects with dyslipidemia and their healthy counterparts. In the multivariate logistic regression analysis, no significant difference in physical activity compliance was observed between the subjects with hypertension, diabetes, or dyslipidemia and their healthy counterparts for both sexes. The patients with hypertension or diabetes tended to have lower physical activity prevlaence than their healthy counterparts. However, for dyslipidemia, no significant difference was found between the two groups. Given the significance of physical activities in the management of chronic diseases, the physical activities of these patients need to be improved.

Correlates of gratitude disposition in middle school students: gender differences.

PubMed

Choi, Jung-hyun; Yu, Mi

2014-01-01

Gratitude disposition is positively associated with happiness. The purpose of this study was to identify influencing factors on gratitude disposition by gender differences in middle school students. Cross-sectional study using self-reported questionnaires were administered to participants (n=372) aged between 13 ∼ 15 years in Seoul and Chungnam Province in Korea. The collected data were analyzed with SPSS18.0 statistical program, and frequency analysis and logistic regression analysis were used in the research. The mean score of family abuse of boys was significantly higher than girls' score (t=3.016, p=0.003). In subscales of development assets, empowerment (t=2.264, p=0.024), boundaries and expectation (t=2.476, p=0.014), and commitment to learning (t=1.971, p=0.049) were significantly higher in boys. The results of logistic regression analysis showed that age (OR 0.334, CI 0.130∼0.862), peer relationship (OR 2.280, CI 1.124∼4.623), social support (OR 2.584, CI 1.176∼5.676), positive identity (OR 3.138, CI 1.256∼7.840) were significantly associated with gratitude disposition for boys, while school violence (OR 0.050, CI 0.003∼0.907) and positive identity (OR 2.937, CI 1.313∼6.567) were significantly associated with gratitude disposition for girls. This study suggests that it is important to protect adolescents from family abuse and school violence, furthermore, developmental assets should be developed to increase to gratitude disposition.

Time series regression-based pairs trading in the Korean equities market

NASA Astrophysics Data System (ADS)

Kim, Saejoon; Heo, Jun

2017-07-01

Pairs trading is an instance of statistical arbitrage that relies on heavy quantitative data analysis to profit by capitalising low-risk trading opportunities provided by anomalies of related assets. A key element in pairs trading is the rule by which open and close trading triggers are defined. This paper investigates the use of time series regression to define the rule which has previously been identified with fixed threshold-based approaches. Empirical results indicate that our approach may yield significantly increased excess returns compared to ones obtained by previous approaches on large capitalisation stocks in the Korean equities market.

Curcumin downregulates human tumor necrosis factor-α levels: A systematic review and meta-analysis ofrandomized controlled trials.

PubMed

Sahebkar, Amirhossein; Cicero, Arrigo F G; Simental-Mendía, Luis E; Aggarwal, Bharat B; Gupta, Subash C

2016-05-01

Tumor necrosis factor-α (TNF-α) is a key inflammatory mediator and its reduction is a therapeutic target in several inflammatory diseases. Curcumin, a bioactive polyphenol from turmeric, has been shown in several preclinical studies to block TNF-α effectively. However, clinical evidence has not been fully conclusive. The aim of the present meta-analysis was to evaluate the efficacy of curcumin supplementation on circulating levels of TNF-α in randomized controlled trials (RCTs). The search included PubMed-Medline, Scopus, Web of Science and Google Scholar databases by up to September 21, 2015, to identify RCTs investigating the impact of curcumin on circulating TNF-α concentration. Quantitative data synthesis was performed using a random-effects model, with weighed mean difference (WMD) and 95% confidence interval (CI) as summary statistics. Meta-regression and leave-one-out sensitivity analyses were performed to assess the modifiers of treatment response. Eight RCTs comprising nine treatment arms were finally selected for the meta-analysis. There was a significant reduction of circulating TNF-α concentrations following curcumin supplementation (WMD: -4.69pg/mL, 95% CI: -7.10, -2.28, p<0.001). This effect size was robust in sensitivity analysis. Meta-regression did not suggest any significant association between the circulating TNF-α-lowering effects of curcumin with either dose or duration (slope: 0.197; 95% CI: -1.73, 2.12; p=0.841) of treatment. This meta-analysis of RCTs suggested a significant effect of curcumin in lowering circulating TNF-α concentration. Copyright © 2016 Elsevier Ltd. All rights reserved.

Single-Nucleotide Polymorphisms Associated with Skin Naphthyl–Keratin Adduct Levels in Workers Exposed to Naphthalene

PubMed Central

Jiang, Rong; French, John E.; Stober, Vandy P.; Kang-Sickel, Juei-Chuan C.; Zou, Fei

2012-01-01

Background: Individual genetic variation that results in differences in systemic response to xenobiotic exposure is not accounted for as a predictor of outcome in current exposure assessment models. Objective: We developed a strategy to investigate individual differences in single-nucleotide polymorphisms (SNPs) as genetic markers associated with naphthyl–keratin adduct (NKA) levels measured in the skin of workers exposed to naphthalene. Methods: The SNP-association analysis was conducted in PLINK using candidate-gene analysis and genome-wide analysis. We identified significant SNP–NKA associations and investigated the potential impact of these SNPs along with personal and workplace factors on NKA levels using a multiple linear regression model and the Pratt index. Results: In candidate-gene analysis, a SNP (rs4852279) located near the CYP26B1 gene contributed to the 2-naphthyl–keratin adduct (2NKA) level. In the multiple linear regression model, the SNP rs4852279, dermal exposure, exposure time, task replacing foam, age, and ethnicity all were significant predictors of 2NKA level. In genome-wide analysis, no single SNP reached genome-wide significance for NKA levels (all p ≥ 1.05 × 10–5). Pathway and network analyses of SNPs associated with NKA levels were predicted to be involved in the regulation of cellular processes and homeostasis. Conclusions: These results provide evidence that a quantitative biomarker can be used as an intermediate phenotype when investigating the association between genetic markers and exposure–dose relationship in a small, well-characterized exposed worker population. PMID:22391508

[Chemical and sensory characterization of tea (Thea sinensis) consumed in Chile].

PubMed

Wittig de Penna, Emma; José Zúñiga, María; Fuenzalida, Regina; López-Planes, Reinaldo

2005-03-01

By means of descriptive analysis four varieties of tea (Thea sinensis) were assesed: Argentinean OP (orange pekoe) tea (black), Brazilian OP tea (black), Ceylan OP tea (black) and Darjeeling OP tea (green). The appearance of dry tea leaves were qualitatively characterized comparing with dry leaves standard. The attributes: colour, form, regularity of the leaves, fibre and stem cutting were evaluated The differences obtained were related to the differences produced by the effect of the fermentation process. Flavour and aroma descriptors of the tea liqueur were generated by a trained panel. Colour and astringency were evaluated in comparison with qualified standards using non structured linear scales. In order to relate the sensory analysis and the chemical composition for the different varieties of tea, following determinations were made: chemical moisture, dry material, aqueous extract, tannin and caffeine. Through multifactor regression analysis the equations in relation to the following chemical parameters were determined. Dry material, aqueous extract and tannins for colour and moisture, dry material and aqueous extract for astringency, respectively. Statistical analysis through ANOVA (3 variation sources: samples, judges and replications) showed for samples four significant different groups for astringency and three different groups for colour. No significant differences between judges or repetitions were found. By multifactor regression analysis of both, colour and astringency, on their dependence of chemist results were calculated in order to asses the corresponding equations.

[A SAS marco program for batch processing of univariate Cox regression analysis for great database].

PubMed

Yang, Rendong; Xiong, Jie; Peng, Yangqin; Peng, Xiaoning; Zeng, Xiaomin

2015-02-01

To realize batch processing of univariate Cox regression analysis for great database by SAS marco program. We wrote a SAS macro program, which can filter, integrate, and export P values to Excel by SAS9.2. The program was used for screening survival correlated RNA molecules of ovarian cancer. A SAS marco program could finish the batch processing of univariate Cox regression analysis, the selection and export of the results. The SAS macro program has potential applications in reducing the workload of statistical analysis and providing a basis for batch processing of univariate Cox regression analysis.

Exact Analysis of Squared Cross-Validity Coefficient in Predictive Regression Models

ERIC Educational Resources Information Center

Shieh, Gwowen

2009-01-01

In regression analysis, the notion of population validity is of theoretical interest for describing the usefulness of the underlying regression model, whereas the presumably more important concept of population cross-validity represents the predictive effectiveness for the regression equation in future research. It appears that the inference…

Selective principal component regression analysis of fluorescence hyperspectral image to assess aflatoxin contamination in corn

USDA-ARS?s Scientific Manuscript database

Selective principal component regression analysis (SPCR) uses a subset of the original image bands for principal component transformation and regression. For optimal band selection before the transformation, this paper used genetic algorithms (GA). In this case, the GA process used the regression co...

Understanding Child Stunting in India: A Comprehensive Analysis of Socio-Economic, Nutritional and Environmental Determinants Using Additive Quantile Regression

PubMed Central

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A.

2013-01-01

Background Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. Objective We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Design Using cross-sectional data for children aged 0–24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. Results At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Conclusions Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role. PMID:24223839

Understanding child stunting in India: a comprehensive analysis of socio-economic, nutritional and environmental determinants using additive quantile regression.

PubMed

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A

2013-01-01

Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Using cross-sectional data for children aged 0-24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role.

Novel Index (Hepatic Receptor: IHR) to Evaluate Hepatic Functional Reserve Using (99m)Tc-GSA Scintigraphy.

PubMed

Hasegawa, Daisuke; Onishi, Hideo; Matsutomo, Norikazu

2016-02-01

This study aimed to evaluate the novel index of hepatic receptor (IHR) on the regression analysis derived from time activity curve of the liver for hepatic functional reserve. Sixty patients had undergone (99m)Tc-galactosyl serum albumin ((99m)Tc-GSA) scintigraphy in the retrospective clinical study. Time activity curves for liver were obtained by region of interest (ROI) on the whole liver. A novel hepatic functional predictor was calculated with multiple regression analysis of time activity curves. In the multiple regression function, the objective variables were the indocyanine green (ICG) retention rate at 15 min, and the explanatory variables were the liver counts in 3-min intervals until end from beginning. Then, this result was defined by IHR, and we analyzed the correlation between IHR and ICG, uptake ratio of the heart at 15 minutes to that at 3 minutes (HH15), uptake ratio of the liver to the liver plus heart at 15 minutes (LHL15), and index of convexity (IOC). Regression function of IHR was derived as follows: IHR=0.025×L(6)-0.052×L(12)+0.027×L(27). The multiple regression analysis indicated that liver counts at 6 min, 12 min, and 27 min were significantly related to objective variables. The correlation coefficient between IHR and ICG was 0.774, and the correlation coefficient between ICG and conventional indices (HH15, LHL15, and IOC) were 0.837, 0.773, and 0.793, respectively. IHR had good correlation with HH15, LHL15, and IOC. The finding results suggested that IHR would provide clinical benefit for hepatic functional assessment in the (99m)Tc-GSA scintigraphy.

Detection of epistatic effects with logic regression and a classical linear regression model.

PubMed

Malina, Magdalena; Ickstadt, Katja; Schwender, Holger; Posch, Martin; Bogdan, Małgorzata

2014-02-01

To locate multiple interacting quantitative trait loci (QTL) influencing a trait of interest within experimental populations, usually methods as the Cockerham's model are applied. Within this framework, interactions are understood as the part of the joined effect of several genes which cannot be explained as the sum of their additive effects. However, if a change in the phenotype (as disease) is caused by Boolean combinations of genotypes of several QTLs, this Cockerham's approach is often not capable to identify them properly. To detect such interactions more efficiently, we propose a logic regression framework. Even though with the logic regression approach a larger number of models has to be considered (requiring more stringent multiple testing correction) the efficient representation of higher order logic interactions in logic regression models leads to a significant increase of power to detect such interactions as compared to a Cockerham's approach. The increase in power is demonstrated analytically for a simple two-way interaction model and illustrated in more complex settings with simulation study and real data analysis.

Urinary 8-iso-prostaglandin F2α as a marker of metabolic risks in the general Japanese population: The ROAD study.

PubMed

Mure, Kanae; Yoshimura, Noriko; Hashimoto, Marowa; Muraki, Shigeyuki; Oka, Hiroyuki; Tanaka, Sakae; Kawaguchi, Hiroshi; Nakamura, Kozo; Akune, Toru; Takeshita, Tatsuya

2015-07-01

To determine whether 8-iso-prostaglandin F2α (8-iso-PGF2α) is a reliable biomarker of the accumulation of metabolic risks [e.g., overweight, hypertension, impaired glucose tolerance (IGT), and dyslipidemia]. This was a cross-sectional study of the baseline characteristics of a Japanese general population cohort study: Research on Osteoarthritis/Osteoporosis Against Disability (ROAD). Of 1,690 participants, 1,527 fulfilled all questionnaires and examinations. Free and conjugated urinary 8-iso-PGF2α levels and metabolic syndrome (MetS) components including blood pressure, HbA1c, total cholesterol, high-density lipoprotein cholesterol (HDL-C), and non-HDL-C were analyzed. The data were analyzed by ANCOVA, multiple regression analysis, and multinomial logistic analysis. 8-iso-PGF2α was significantly associated with HbA1c and significantly inversely associated with total cholesterol and non-HDL-C. Notably, IGT with an HbA1c cut-off of 5.5% was significantly associated with 8-iso-PGF2α level in participants aged ≤50 years. Multinomial logistic regression analysis revealed 8-iso-PGF2α level was significantly associated with a greater number of MetS risks present; this association was stronger in younger participants. In participants aged ≥71 years, 8-iso-PGF2α was significantly associated with a greater number of MetS risks with higher IGT cut-offs. Urinary 8-iso-PGF2α can be a reliable marker of IGT and the accumulation of MetS risks, especially in younger people. © 2015 The Obesity Society.

Continuing or Temporarily Stopping Prestroke Antihypertensive Medication in Acute Stroke: An Individual Patient Data Meta-Analysis.

PubMed

Woodhouse, Lisa J; Manning, Lisa; Potter, John F; Berge, Eivind; Sprigg, Nikola; Wardlaw, Joanna; Lees, Kennedy R; Bath, Philip M; Robinson, Thompson G

2017-05-01

Over 50% of patients are already taking blood pressure-lowering therapy on hospital admission for acute stroke. An individual patient data meta-analysis from randomized controlled trials was undertaken to determine the effect of continuation versus temporarily stopping preexisting antihypertensive medication in acute stroke. Key databases were searched for trials against the following inclusion criteria: randomized design; stroke onset ≤48 hours; investigating the effect of continuation versus stopping prestroke antihypertensive medication; and follow-up of ≥2 weeks. Two randomized controlled trials were identified and included in this meta-analysis of individual patient data from 2860 patients with ≤48 hours of acute stroke. Risk of bias in each study was low. In adjusted logistic regression and multiple regression analyses (using random effects), we found no significant association between continuation of prestroke antihypertensive therapy (versus stopping) and risk of death or dependency at final follow-up: odds ratio 0.96 (95% confidence interval, 0.80-1.14). No significant associations were found between continuation (versus stopping) of therapy and secondary outcomes at final follow-up. Analyses for death and dependency in prespecified subgroups revealed no significant associations with continuation versus temporarily stopping therapy, with the exception of patients randomized ≤12 hours, in whom a difference favoring stopping treatment met statistical significance. We found no significant benefit with continuation of antihypertensive treatment in the acute stroke period. Therefore, there is no urgency to administer preexisting antihypertensive therapy in the first few hours or days after stroke, unless indicated for other comorbid conditions. © 2017 American Heart Association, Inc.

Soccer and sexual health education: a promising approach for reducing adolescent births in Haiti.

PubMed

Kaplan, Kathryn C; Lewis, Judy; Gebrian, Bette; Theall, Katherine

2015-05-01

To explore the effect of an innovative, integrative program in female sexual reproductive health (SRH) and soccer (or fútbol, in Haitian Creole) in rural Haiti by measuring the rate of births among program participants 15-19 years old and their nonparticipant peers. A retrospective cohort study using 2006-2009 data from the computerized data-tracking system of the Haitian Health Foundation (HHF), a U.S.-based nongovernmental organization serving urban and rural populations in Haiti, was used to assess births among girls 15-19 years old who participated in HHF's GenNext program, a combination education-soccer program for youth, based on SRH classes HHF nurses and community workers had been conducting in Haiti for mothers, fathers, and youth; girl-centered health screenings; and an all-female summer soccer league, during 2006-2009 (n = 4 251). Bivariate and multiple logistic regression analyses were carried out to assess differences in the rate of births among program participants according to their level of participation (SRH component only ("EDU") versus both the SRH and soccer components ("SO") compared to their village peers who did not participate. Hazard ratios (HRs) of birth rates were estimated using Cox regression analysis of childbearing data for the three different groups. In the multiple logistic regression analysis, only the girls in the "EDU" group had significantly fewer births than the nonparticipants after adjusting for confounders (odds ratio = 0.535; 95% confidence interval (CI) = 0.304, 0.940). The Cox regression analysis demonstrated that those in the EDU group (HR = 0.893; 95% CI = 0.802, 0.994) and to a greater degree those in the SO group (HR = 0.631; 95% CI = 0.558, 0.714) were significantly protected against childbearing between the ages of 15 and 19 years. HHF's GenNext program demonstrates the effectiveness of utilizing nurse educators, community mobilization, and youth participation in sports, education, and structured youth groups to promote and sustain health for adolescent girls and young women.

Plant selection for ethnobotanical uses on the Amalfi Coast (Southern Italy).

PubMed

Savo, V; Joy, R; Caneva, G; McClatchey, W C

2015-07-15

Many ethnobotanical studies have investigated selection criteria for medicinal and non-medicinal plants. In this paper we test several statistical methods using different ethnobotanical datasets in order to 1) define to which extent the nature of the datasets can affect the interpretation of results; 2) determine if the selection for different plant uses is based on phylogeny, or other selection criteria. We considered three different ethnobotanical datasets: two datasets of medicinal plants and a dataset of non-medicinal plants (handicraft production, domestic and agro-pastoral practices) and two floras of the Amalfi Coast. We performed residual analysis from linear regression, the binomial test and the Bayesian approach for calculating under-used and over-used plant families within ethnobotanical datasets. Percentages of agreement were calculated to compare the results of the analyses. We also analyzed the relationship between plant selection and phylogeny, chorology, life form and habitat using the chi-square test. Pearson's residuals for each of the significant chi-square analyses were examined for investigating alternative hypotheses of plant selection criteria. The three statistical analysis methods differed within the same dataset, and between different datasets and floras, but with some similarities. In the two medicinal datasets, only Lamiaceae was identified in both floras as an over-used family by all three statistical methods. All statistical methods in one flora agreed that Malvaceae was over-used and Poaceae under-used, but this was not found to be consistent with results of the second flora in which one statistical result was non-significant. All other families had some discrepancy in significance across methods, or floras. Significant over- or under-use was observed in only a minority of cases. The chi-square analyses were significant for phylogeny, life form and habitat. Pearson's residuals indicated a non-random selection of woody species for non-medicinal uses and an under-use of plants of temperate forests for medicinal uses. Our study showed that selection criteria for plant uses (including medicinal) are not always based on phylogeny. The comparison of different statistical methods (regression, binomial and Bayesian) under different conditions led to the conclusion that the most conservative results are obtained using regression analysis.

Atomoxetine-Related Change in Sluggish Cognitive Tempo Is Partially Independent of Change in Attention-Deficit/Hyperactivity Disorder Inattentive Symptoms.

PubMed

McBurnett, Keith; Clemow, David; Williams, David; Villodas, Miguel; Wietecha, Linda; Barkley, Russell

2017-02-01

To evaluate effects of atomoxetine versus placebo on sluggish cognitive tempo (SCT) and determine factors affecting improvement of SCT in children with attention-deficit/hyperactivity disorder (ADHD) with dyslexia (ADHD+D) or dyslexia only. This is a post hoc analysis of a 16-week placebo-controlled, double-blind randomized phase of a previously reported atomoxetine study in children aged 10-16 years with ADHD+D, Dyslexia-only, or ADHD-only (no placebo arm). Least squares mean changes from baseline to endpoint for atomoxetine versus placebo on the Kiddie-Sluggish Cognitive Tempo Interview (K-SCT) (Parent, Teacher, and Youth) were analyzed using analysis of covariance and multiple regression (partial R 2 ) analyses to test contributions of ADHD and dyslexia to improvements in K-SCT scores. Results were examined for the three informants within the three diagnostic groups (nine outcomes). Atomoxetine treatment was associated with significant reductions from baseline in seven of the nine outcomes using the p = 0.05 significance level, appropriate for exploratory analysis. When change in ADHD symptom severity was controlled, all of the seven SCT outcomes remained significant; changes in effect sizes were minimal. Regression analyses using SCT change as the criterion found a significant contribution by inattention change only for parent report, whereas, baseline SCT severity was a significant predictor in the randomized groups with the exception of teacher report in the Dyslexia-only group. Given that controlling for change in ADHD symptoms had little effect on change in SCT scores, findings suggest that change in SCT is substantially independent of change in ADHD. By inference, SCT and its response to treatment is a partially distinct phenomenon from ADHD response. Regression analyses did not reveal global effects of inattention change on SCT change; instead, baseline SCT severity was the strongest predictor of placebo-controlled treatment effect on SCT. Atomoxetine effects on SCT appear to be best predicted by how much room for improvement exists for SCT rather than by severity or improvement in inattention. NCT00607919, www.clinicaltrials.gov.

HIV/AIDS information by African companies: an empirical analysis.

PubMed

Barako, Dulacha G; Taplin, Ross H; Brown, Alistair M

2010-01-01

This article investigates the extent of Human Immunodeficiency Virus/Acquired Immune Deficiency Syndrome Disclosures (HIV/AIDSD) in online annual reports by 200 listed companies from 10 African countries for the year ending 2006. Descriptive statistics reveal a very low level of overall HIV/AIDSD practices with a mean of 6 per cent disclosure, with half (100 out of 200) of the African companies making no disclosures at all. Logistic regression analysis reveals that company size and country are highly significant predictors of any disclosure of HIV/AIDS in annual reports. Profitability is also statistically significantly associated with the extent of disclosure.

Relationships between locus of control and paranormal beliefs.

PubMed

Newby, Robert W; Davis, Jessica Boyette

2004-06-01

The present study investigated the associations between scores on paranormal beliefs, locus of control, and certain psychological processes such as affect and cognitions as measured by the Linguistic Inquiry and Word Count. Analysis yielded significant correlations between scores on Locus of Control and two subscales of Tobacyk's (1988) Revised Paranormal Beliefs Scale, New Age Philosophy and Traditional Paranormal Beliefs. A step-wise multiple regression analysis indicated that Locus of Control was significantly related to New Age Philosophy. Other correlations were found between Tobacyk's subscales, Locus of Control, and three processes measured by the Linguistic Inquiry and Word Count.

Learning effect and test-retest variability of pulsar perimetry.

PubMed

Salvetat, Maria Letizia; Zeppieri, Marco; Parisi, Lucia; Johnson, Chris A; Sampaolesi, Roberto; Brusini, Paolo

2013-03-01

To assess Pulsar Perimetry learning effect and test-retest variability (TRV) in normal (NORM), ocular hypertension (OHT), glaucomatous optic neuropathy (GON), and primary open-angle glaucoma (POAG) eyes. This multicenter prospective study included 43 NORM, 38 OHT, 33 GON, and 36 POAG patients. All patients underwent standard automated perimetry and Pulsar Contrast Perimetry using white stimuli modulated in phase and counterphase at 30 Hz (CP-T30W test). The learning effect and TRV for Pulsar Perimetry were assessed for 3 consecutive visual fields (VFs). The learning effect were evaluated by comparing results from the first session with the other 2. TRV was assessed by calculating the mean of the differences (in absolute value) between retests for each combination of single tests. TRV was calculated for Mean Sensitivity, Mean Defect, and single Mean Sensitivity for each 66 test locations. Influence of age, VF eccentricity, and loss severity on TRV were assessed using linear regression analysis and analysis of variance. The learning effect was not significant in any group (analysis of variance, P>0.05). TRV for Mean Sensitivity and Mean Defect was significantly lower in NORM and OHT (0.6 ± 0.5 spatial resolution contrast units) than in GON and POAG (0.9 ± 0.5 and 1.0 ± 0.8 spatial resolution contrast units, respectively) (Kruskal-Wallis test, P=0.04); however, the differences in NORM among age groups was not significant (Kruskal-Wallis test, P>0.05). Slight significant differences were found for the single Mean Sensitivity TRV among single locations (Duncan test, P<0.05). For POAG, TRV significantly increased with decreasing Mean Sensitivity and increasing Mean Defect (linear regression analysis, P<0.01). The Pulsar Perimetry CP-T30W test did not show significant learning effect in patients with standard automated perimetry experience. TRV for global indices was generally low, and was not related to patient age; it was only slightly affected by VF defect eccentricity, and significantly influenced by VF loss severity.

Combining synthetic controls and interrupted time series analysis to improve causal inference in program evaluation.

PubMed

Linden, Ariel

2018-04-01

Interrupted time series analysis (ITSA) is an evaluation methodology in which a single treatment unit's outcome is studied over time and the intervention is expected to "interrupt" the level and/or trend of the outcome. The internal validity is strengthened considerably when the treated unit is contrasted with a comparable control group. In this paper, we introduce a robust evaluation framework that combines the synthetic controls method (SYNTH) to generate a comparable control group and ITSA regression to assess covariate balance and estimate treatment effects. We evaluate the effect of California's Proposition 99 for reducing cigarette sales, by comparing California to other states not exposed to smoking reduction initiatives. SYNTH is used to reweight nontreated units to make them comparable to the treated unit. These weights are then used in ITSA regression models to assess covariate balance and estimate treatment effects. Covariate balance was achieved for all but one covariate. While California experienced a significant decrease in the annual trend of cigarette sales after Proposition 99, there was no statistically significant treatment effect when compared to synthetic controls. The advantage of using this framework over regression alone is that it ensures that a comparable control group is generated. Additionally, it offers a common set of statistical measures familiar to investigators, the capability for assessing covariate balance, and enhancement of the evaluation with a comprehensive set of postestimation measures. Therefore, this robust framework should be considered as a primary approach for evaluating treatment effects in multiple group time series analysis. © 2018 John Wiley & Sons, Ltd.

Assessment of triglyceride and cholesterol in overweight people based on multiple linear regression and artificial intelligence model.

PubMed

Ma, Jing; Yu, Jiong; Hao, Guangshu; Wang, Dan; Sun, Yanni; Lu, Jianxin; Cao, Hongcui; Lin, Feiyan

2017-02-20

The prevalence of high hyperlipemia is increasing around the world. Our aims are to analyze the relationship of triglyceride (TG) and cholesterol (TC) with indexes of liver function and kidney function, and to develop a prediction model of TG, TC in overweight people. A total of 302 adult healthy subjects and 273 overweight subjects were enrolled in this study. The levels of fasting indexes of TG (fs-TG), TC (fs-TC), blood glucose, liver function, and kidney function were measured and analyzed by correlation analysis and multiple linear regression (MRL). The back propagation artificial neural network (BP-ANN) was applied to develop prediction models of fs-TG and fs-TC. The results showed there was significant difference in biochemical indexes between healthy people and overweight people. The correlation analysis showed fs-TG was related to weight, height, blood glucose, and indexes of liver and kidney function; while fs-TC was correlated with age, indexes of liver function (P < 0.01). The MRL analysis indicated regression equations of fs-TG and fs-TC both had statistic significant (P < 0.01) when included independent indexes. The BP-ANN model of fs-TG reached training goal at 59 epoch, while fs-TC model achieved high prediction accuracy after training 1000 epoch. In conclusions, there was high relationship of fs-TG and fs-TC with weight, height, age, blood glucose, indexes of liver function and kidney function. Based on related variables, the indexes of fs-TG and fs-TC can be predicted by BP-ANN models in overweight people.

Geographical, temporal and racial disparities in late-stage prostate cancer incidence across Florida: A multiscale joinpoint regression analysis

PubMed Central

2011-01-01

Background Although prostate cancer-related incidence and mortality have declined recently, striking racial/ethnic differences persist in the United States. Visualizing and modelling temporal trends of prostate cancer late-stage incidence, and how they vary according to geographic locations and race, should help explaining such disparities. Joinpoint regression is increasingly used to identify the timing and extent of changes in time series of health outcomes. Yet, most analyses of temporal trends are aspatial and conducted at the national level or for a single cancer registry. Methods Time series (1981-2007) of annual proportions of prostate cancer late-stage cases were analyzed for non-Hispanic Whites and non-Hispanic Blacks in each county of Florida. Noise in the data was first filtered by binomial kriging and results were modelled using joinpoint regression. A similar analysis was also conducted at the state level and for groups of metropolitan and non-metropolitan counties. Significant racial differences were detected using tests of parallelism and coincidence of time trends. A new disparity statistic was introduced to measure spatial and temporal changes in the frequency of racial disparities. Results State-level percentage of late-stage diagnosis decreased 50% since 1981; a decline that accelerated in the 90's when Prostate Specific Antigen (PSA) screening was introduced. Analysis at the metropolitan and non-metropolitan levels revealed that the frequency of late-stage diagnosis increased recently in urban areas, and this trend was significant for white males. The annual rate of decrease in late-stage diagnosis and the onset years for significant declines varied greatly among counties and racial groups. Most counties with non-significant average annual percent change (AAPC) were located in the Florida Panhandle for white males, whereas they clustered in South-eastern Florida for black males. The new disparity statistic indicated that the spatial extent of racial disparities reached a peak in 1990 because of an early decline in frequency of late-stage diagnosis observed for black males. Conclusions Analyzing temporal trends in cancer incidence and mortality rates outside a spatial framework is unsatisfactory, since it leads one to overlook significant geographical variation which can potentially generate new insights about the impact of various interventions. Differences observed among nested geographies in Florida show how the modifiable areal unit problem (MAUP) also impacts the analysis of temporal changes. PMID:22142274

Geographical, temporal and racial disparities in late-stage prostate cancer incidence across Florida: a multiscale joinpoint regression analysis.

PubMed

Goovaerts, Pierre; Xiao, Hong

2011-12-05

Although prostate cancer-related incidence and mortality have declined recently, striking racial/ethnic differences persist in the United States. Visualizing and modelling temporal trends of prostate cancer late-stage incidence, and how they vary according to geographic locations and race, should help explaining such disparities. Joinpoint regression is increasingly used to identify the timing and extent of changes in time series of health outcomes. Yet, most analyses of temporal trends are aspatial and conducted at the national level or for a single cancer registry. Time series (1981-2007) of annual proportions of prostate cancer late-stage cases were analyzed for non-Hispanic Whites and non-Hispanic Blacks in each county of Florida. Noise in the data was first filtered by binomial kriging and results were modelled using joinpoint regression. A similar analysis was also conducted at the state level and for groups of metropolitan and non-metropolitan counties. Significant racial differences were detected using tests of parallelism and coincidence of time trends. A new disparity statistic was introduced to measure spatial and temporal changes in the frequency of racial disparities. State-level percentage of late-stage diagnosis decreased 50% since 1981; a decline that accelerated in the 90's when Prostate Specific Antigen (PSA) screening was introduced. Analysis at the metropolitan and non-metropolitan levels revealed that the frequency of late-stage diagnosis increased recently in urban areas, and this trend was significant for white males. The annual rate of decrease in late-stage diagnosis and the onset years for significant declines varied greatly among counties and racial groups. Most counties with non-significant average annual percent change (AAPC) were located in the Florida Panhandle for white males, whereas they clustered in South-eastern Florida for black males. The new disparity statistic indicated that the spatial extent of racial disparities reached a peak in 1990 because of an early decline in frequency of late-stage diagnosis observed for black males. Analyzing temporal trends in cancer incidence and mortality rates outside a spatial framework is unsatisfactory, since it leads one to overlook significant geographical variation which can potentially generate new insights about the impact of various interventions. Differences observed among nested geographies in Florida show how the modifiable areal unit problem (MAUP) also impacts the analysis of temporal changes.

Changes of visual-field global indices after cataract surgery in primary open-angle glaucoma patients.

PubMed

Seol, Bo Ram; Jeoung, Jin Wook; Park, Ki Ho

2016-11-01

To determine changes of visual-field (VF) global indices after cataract surgery and the factors associated with the effect of cataracts on those indices in primary open-angle glaucoma (POAG) patients. A retrospective chart review of 60 POAG patients who had undergone phacoemulsification and intraocular lens insertion was conducted. All of the patients were evaluated with standard automated perimetry (SAP; 30-2 Swedish interactive threshold algorithm; Carl Zeiss Meditec Inc.) before and after surgery. VF global indices before surgery were compared with those after surgery. The best-corrected visual acuity, intraocular pressure (IOP), number of glaucoma medications before surgery, mean total deviation (TD) values, mean pattern deviation (PD) value, and mean TD-PD value were also compared with the corresponding postoperative values. Additionally, postoperative peak IOP and mean IOP were evaluated. Univariate and multivariate logistic regression analyses were performed to identify the factors associated with the effect of cataract on global indices. Mean deviation (MD) after cataract surgery was significantly improved compared with the preoperative MD. Pattern standard deviation (PSD) and visual-field index (VFI) after surgery were similar to those before surgery. Also, mean TD and mean TD-PD were significantly improved after surgery. The posterior subcapsular cataract (PSC) type showed greater MD changes than did the non-PSC type in both the univariate and multivariate logistic regression analyses. In the univariate logistic regression analysis, the preoperative TD-PD value and type of cataract were associated with MD change. However, in the multivariate logistic regression analysis, type of cataract was the only associated factor. None of the other factors was associated with MD change. MD was significantly affected by cataracts, whereas PSD and VFI were not. Most notably, the PSC type showed better MD improvement compared with the non-PSC type after cataract surgery. Clinicians therefore should carefully analyze VF examination results for POAG patients with the PSC type.

Prevalence of vitamin D deficiency and associated factors in women and newborns in the immediate postpartum period

PubMed Central

do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2015-01-01

Abstract Objective: To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. Methods: This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95%, was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α <5%. Results: From 226 women included, 200 (88.5%) were 20-44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. Conclusions: This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. PMID:26100593

Risk factors for pedicled flap necrosis in hand soft tissue reconstruction: a multivariate logistic regression analysis.

PubMed

Gong, Xu; Cui, Jianli; Jiang, Ziping; Lu, Laijin; Li, Xiucun

2018-03-01

Few clinical retrospective studies have reported the risk factors of pedicled flap necrosis in hand soft tissue reconstruction. The aim of this study was to identify non-technical risk factors associated with pedicled flap perioperative necrosis in hand soft tissue reconstruction via a multivariate logistic regression analysis. For patients with hand soft tissue reconstruction, we carefully reviewed hospital records and identified 163 patients who met the inclusion criteria. The characteristics of these patients, flap transfer procedures and postoperative complications were recorded. Eleven predictors were identified. The correlations between pedicled flap necrosis and risk factors were analysed using a logistic regression model. Of 163 skin flaps, 125 flaps survived completely without any complications. The pedicled flap necrosis rate in hands was 11.04%, which included partial flap necrosis (7.36%) and total flap necrosis (3.68%). Soft tissue defects in fingers were noted in 68.10% of all cases. The logistic regression analysis indicated that the soft tissue defect site (P = 0.046, odds ratio (OR) = 0.079, confidence interval (CI) (0.006, 0.959)), flap size (P = 0.020, OR = 1.024, CI (1.004, 1.045)) and postoperative wound infection (P < 0.001, OR = 17.407, CI (3.821, 79.303)) were statistically significant risk factors for pedicled flap necrosis of the hand. Soft tissue defect site, flap size and postoperative wound infection were risk factors associated with pedicled flap necrosis in hand soft tissue defect reconstruction. © 2017 Royal Australasian College of Surgeons.

Bidirectional relationship between renal function and periodontal disease in older Japanese women.

PubMed

Yoshihara, Akihiro; Iwasaki, Masanori; Miyazaki, Hideo; Nakamura, Kazutoshi

2016-09-01

The purpose of this study was to evaluate the reciprocal effects of chronic kidney disease (CKD) and periodontal disease. A total of 332 postmenopausal never smoking women were enrolled, and their serum high-sensitivity C-reactive protein, serum osteocalcin and serum cystatin C levels were measured. Poor renal function was defined as serum cystatin C > 0.91 mg/l. Periodontal disease markers, including clinical attachment level and the periodontal inflamed surface area (PISA), were also evaluated. Logistic regression analysis was conducted to evaluate the relationships between renal function and periodontal disease markers, serum osteocalcin level and hsCRP level. The prevalence-rate ratios (PRRs) on multiple Poisson regression analyses were determined to evaluate the relationships between periodontal disease markers and serum osteocalcin, serum cystatin C and serum hsCRP levels. On logistic regression analysis, PISA was significantly associated with serum cystatin C level. The odds ratio for serum cystatin C level was 2.44 (p = 0.011). The PRR between serum cystatin C level and periodontal disease markers such as number of sites with clinical attachment level ≥6 mm was significantly positive (3.12, p < 0.001). Similar tendencies were shown for serum osteocalcin level. This study suggests that CKD and periodontal disease can have reciprocal effects. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Data Mining CMMSs: How to Convert Data into Knowledge.

PubMed

Fennigkoh, Larry; Nanney, D Courtney

2018-01-01

Although the healthcare technology management (HTM) community has decades of accumulated medical device-related maintenance data, little knowledge has been gleaned from these data. Finding and extracting such knowledge requires the use of the well-established, but admittedly somewhat foreign to HTM, application of inferential statistics. This article sought to provide a basic background on inferential statistics and describe a case study of their application, limitations, and proper interpretation. The research question associated with this case study involved examining the effects of ventilator preventive maintenance (PM) labor hours, age, and manufacturer on needed unscheduled corrective maintenance (CM) labor hours. The study sample included more than 21,000 combined PM inspections and CM work orders on 2,045 ventilators from 26 manufacturers during a five-year period (2012-16). A multiple regression analysis revealed that device age, manufacturer, and accumulated PM inspection labor hours all influenced the amount of CM labor significantly (P < 0.001). In essence, CM labor hours increased with increasing PM labor. However, and despite the statistical significance of these predictors, the regression analysis also indicated that ventilator age, manufacturer, and PM labor hours only explained approximately 16% of all variability in CM labor, with the remainder (84%) caused by other factors that were not included in the study. As such, the regression model obtained here is not suitable for predicting ventilator CM labor hours.

Magnitude and Determinants of the Ratio between Prevalence of Low Vision and Blindness in Rapid Assessment of Avoidable Blindness Surveys.

PubMed

Kaphle, Dinesh; Lewallen, Susan

2017-10-01

To determine the magnitude and determinants of the ratio between prevalence of low vision and prevalence of blindness in rapid assessment of avoidable blindness (RAAB) surveys globally. Standard RAAB reports were downloaded from the repository or requested from principal investigators. Potential predictor variables included prevalence of uncorrected refractive error (URE) as well as gross domestic product (GDP) per capita, health expenditure per capita of the country across World Bank regions. Univariate and multivariate linear regression were used to investigate the correlation between potential predictor variables and the ratio. The results of 94 surveys from 43 countries showed that the ratio ranged from 1.35 in Mozambique to 11.03 in India with a median value of 3.90 (Interquartile range 3.06;5.38). Univariate regression analysis showed that prevalence of URE (p = 0.04), logarithm of GDP per capita (p = 0.01) and logarithm of health expenditure per capita (p = 0.03) were significantly associated with the higher ratio. However, only prevalence of URE was found to be significant in multivariate regression analysis (p = 0.03). There is a wide variation in the ratio of the prevalence of low vision to the prevalence of blindness. Eye care service utilization indicators such as the prevalence of URE may explain some of the variation across the regions.

Impact of Pacemaker Lead Characteristics on Pacemaker Related Infection and Heart Perforation: A Nationwide Population-Based Cohort Study.

PubMed

Lin, Yu-Sheng; Chen, Tien-Hsing; Hung, Sheng-Ping; Chen, Dong Yi; Mao, Chun-Tai; Tsai, Ming-Lung; Chang, Shih-Tai; Wang, Chun-Chieh; Wen, Ming-Shien; Chen, Mien-Cheng

2015-01-01

Several risk factors for pacemaker (PM) related complications have been reported. However, no study has investigated the impact of lead characteristics on pacemaker-related complications. Patients who received a new pacemaker implant from January 1997 to December 2011 were selected from the Taiwan National Health Insurance Database. This population was grouped according to the pacemaker lead characteristics in terms of fixation and insulation. The impact of the characteristics of leads on early heart perforation was analyzed by multivariable logistic regression analysis, while the impact of the lead characteristics on early and late infection and late heart perforation over a three-year period were analyzed using Cox regression. This study included 36,104 patients with a mean age of 73.4±12.5 years. In terms of both early and late heart perforations, there were no significant differences between groups across the different types of fixation and insulations. In the multivariable Cox regression analysis, the pacemaker-related infection rate was significantly lower in the active fixation only group compared to either the both fixation (OR, 0.23; 95% CI, 0.07-0.80; P = 0.020) or the passive fixation group (OR, 0.26; 95% CI, 0.08-0.83; P = 0.023). There was no difference in heart perforation between active and passive fixation leads. Active fixation leads were associated with reduced risk of pacemaker-related infection.

Changes in aerobic power of men, ages 25-70 yr

NASA Technical Reports Server (NTRS)

Jackson, A. S.; Beard, E. F.; Wier, L. T.; Ross, R. M.; Stuteville, J. E.; Blair, S. N.

1995-01-01

This study quantified and compared the cross-sectional and longitudinal influence of age, self-report physical activity (SR-PA), and body composition (%fat) on the decline of maximal aerobic power (VO2peak). The cross-sectional sample consisted of 1,499 healthy men ages 25-70 yr. The 156 men of the longitudinal sample were from the same population and examined twice, the mean time between tests was 4.1 (+/- 1.2) yr. Peak oxygen uptake was determined by indirect calorimetry during a maximal treadmill exercise test. The zero-order correlations between VO2peak and %fat (r = -0.62) and SR-PA (r = 0.58) were significantly (P < 0.05) higher that the age correlation (r = -0.45). Linear regression defined the cross-sectional age-related decline in VO2peak at 0.46 ml.kg-1.min-1.yr-1. Multiple regression analysis (R = 0.79) showed that nearly 50% of this cross-sectional decline was due to %fat and SR-PA, adding these lifestyle variables to the multiple regression model reduced the age regression weight to -0.26 ml.kg-1.min-1.yr-1. Statistically controlling for time differences between tests, general linear models analysis showed that longitudinal changes in aerobic power were due to independent changes in %fat and SR-PA, confirming the cross-sectional results.

Wheat flour dough Alveograph characteristics predicted by Mixolab regression models.

PubMed

Codină, Georgiana Gabriela; Mironeasa, Silvia; Mironeasa, Costel; Popa, Ciprian N; Tamba-Berehoiu, Radiana

2012-02-01

In Romania, the Alveograph is the most used device to evaluate the rheological properties of wheat flour dough, but lately the Mixolab device has begun to play an important role in the breadmaking industry. These two instruments are based on different principles but there are some correlations that can be found between the parameters determined by the Mixolab and the rheological properties of wheat dough measured with the Alveograph. Statistical analysis on 80 wheat flour samples using the backward stepwise multiple regression method showed that Mixolab values using the ‘Chopin S’ protocol (40 samples) and ‘Chopin + ’ protocol (40 samples) can be used to elaborate predictive models for estimating the value of the rheological properties of wheat dough: baking strength (W), dough tenacity (P) and extensibility (L). The correlation analysis confirmed significant findings (P < 0.05 and P < 0.01) between the parameters of wheat dough studied by the Mixolab and its rheological properties measured with the Alveograph. A number of six predictive linear equations were obtained. Linear regression models gave multiple regression coefficients with R²(adjusted) > 0.70 for P, R²(adjusted) > 0.70 for W and R²(adjusted) > 0.38 for L, at a 95% confidence interval. Copyright © 2011 Society of Chemical Industry.

Fall-related self-efficacy, not balance and mobility performance, is related to accidental falls in chronic stroke survivors with low bone mineral density

PubMed Central

Pang, Marco Y.C.; Eng, Janice J.

2011-01-01

Introduction Chronic stroke survivors with low bone mineral density (BMD) are particularly prone to fragility fractures. The purpose of this study was to identify the determinants of balance, mobility and falls in this sub-group of stroke patients. Methods Thirty nine chronic stroke survivors with low hip BMD (T-score <-1.0) were studied. Each subject was evaluated for: balance, mobility, leg muscle strength, spasticity, and falls-related self-efficacy. Any falls in the past 12 months were also recorded. Multiple regression analysis was used to identify the determinants of balance and mobility performance whereas logistic regression was used to identify the determinants of falls. Results Multiple regression analysis revealed that after adjusting for basic demographics, falls-related self-efficacy remained independently associated with balance/mobility performance (R2=0.494, P<0.001). Logistic regression showed that falls-related self-efficacy, but not balance and mobility performance, was a significant determinant of falls (odds ratio: 0.18, P=0.04). Conclusions Falls-related self-efficacy, but not mobility and balance performance, was the most important determinant of accidental falls. This psychological factor should not be overlooked in the prevention of fragility fractures among chronic stroke survivors with low hip BMD. PMID:18097709

Determinants of spirometric abnormalities among silicotic patients in Hong Kong.

PubMed

Leung, Chi C; Chang, Kwok C; Law, Wing S; Yew, Wing W; Tam, Cheuk M; Chan, Chi K; Wong, Man Y

2005-09-01

Silicosis is the second commonest notified occupational disease in Hong Kong. To characterize the determinants of spirometric abnormalities in silicosis. The spirometric patterns of consecutive silicotic patients on confirmation by the Pneumoconiosis Medical Board from 1991 to 2002 were correlated with demographic characteristics, occupational history, smoking history, tuberculosis (TB) history and radiographic features by univariate and multiple regression analyses. Of 1576 silicotic patients included, 55.6% showed normal spirometry, 28.5% normal forced vital capacity (FVC>or=80% predicted) but reduced forced expiratory ratio (FER<70%), 7.6% reduced FVC but normal FER, and 8.4% reduced both FVC and FER. Age, ever-smoking, cigarette pack-years, industry, job type, history of TB, size of lung nodules and progressive massive fibrosis (PMF) were all significantly associated with airflow limitation on univariate analysis (all P<0.05), while sex and profusion of nodules were not. Only age, cigarette pack-years, history of TB, size of lung nodules and PMF remained as significant independent predictors of airflow obstruction in multiple logistic regression analysis. After controlling for airflow obstruction, only shorter exposure duration, history of TB and profusion of nodules were significant independent predictors of reduced FVC. As well as age, history of TB, cigarette pack-years, PMF and nodule size contributed comparable effects to airflow obstruction in multiple linear regression analyses, while profusion of nodules was the strongest factor for reduced vital capacity. In an occupational compensation setting, disease indices and history of tuberculosis are independent predictors of both airflow obstruction and reduced vital capacity for silicotic patients.

Factors predictive of the onset and duration of action of local anesthesia in mandibular third-molar surgery: a prospective study.

PubMed

Al-Shayyab, Mohammad H; Baqain, Zaid H

2018-04-01

The aim of this study was to assess the influence of patients' and surgical variables on the onset and duration of action of local anesthesia (LA) in mandibular third-molar (M3) surgery. Patients scheduled for mandibular M3 surgery were considered for inclusion in this prospective cohort study. Patients' and surgical variables were recorded. Two per cent (2%) lidocaine with 1:100,000 epinephrine was used to block the nerves for extraction of mandibular M3. Then, the onset of action and duration of LA were monitored. Univariate analysis and multivariate regression analysis were used to analyze the data. The final cohort included 88 subjects (32 men and 56 women; mean age ± SD = 29.3 ± 12.3 yr). With univariate analysis, age, gender, body mass index (BMI), smoking quantity and duration, operation time, and 'volume of local anesthetic needed' significantly influenced the onset of action and duration of LA. Multivariate regression revealed that age and smoking quantity were the only statistically significant predictors of the onset of action of LA, whereas age, smoking quantity, and 'volume of local anesthetic needed' were the only statistically significant predictors of duration of LA. Further studies are recommended to uncover other predictors of the onset of action and duration of LA. © 2018 Eur J Oral Sci.

A Review of the Study Designs and Statistical Methods Used in the Determination of Predictors of All-Cause Mortality in HIV-Infected Cohorts: 2002–2011

PubMed Central

Otwombe, Kennedy N.; Petzold, Max; Martinson, Neil; Chirwa, Tobias

2014-01-01

Background Research in the predictors of all-cause mortality in HIV-infected people has widely been reported in literature. Making an informed decision requires understanding the methods used. Objectives We present a review on study designs, statistical methods and their appropriateness in original articles reporting on predictors of all-cause mortality in HIV-infected people between January 2002 and December 2011. Statistical methods were compared between 2002–2006 and 2007–2011. Time-to-event analysis techniques were considered appropriate. Data Sources Pubmed/Medline. Study Eligibility Criteria Original English-language articles were abstracted. Letters to the editor, editorials, reviews, systematic reviews, meta-analysis, case reports and any other ineligible articles were excluded. Results A total of 189 studies were identified (n = 91 in 2002–2006 and n = 98 in 2007–2011) out of which 130 (69%) were prospective and 56 (30%) were retrospective. One hundred and eighty-two (96%) studies described their sample using descriptive statistics while 32 (17%) made comparisons using t-tests. Kaplan-Meier methods for time-to-event analysis were commonly used in the earlier period (n = 69, 76% vs. n = 53, 54%, p = 0.002). Predictors of mortality in the two periods were commonly determined using Cox regression analysis (n = 67, 75% vs. n = 63, 64%, p = 0.12). Only 7 (4%) used advanced survival analysis methods of Cox regression analysis with frailty in which 6 (3%) were used in the later period. Thirty-two (17%) used logistic regression while 8 (4%) used other methods. There were significantly more articles from the first period using appropriate methods compared to the second (n = 80, 88% vs. n = 69, 70%, p-value = 0.003). Conclusion Descriptive statistics and survival analysis techniques remain the most common methods of analysis in publications on predictors of all-cause mortality in HIV-infected cohorts while prospective research designs are favoured. Sophisticated techniques of time-dependent Cox regression and Cox regression with frailty are scarce. This motivates for more training in the use of advanced time-to-event methods. PMID:24498313

Development of a User Interface for a Regression Analysis Software Tool

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred; Volden, Thomas R.

2010-01-01

An easy-to -use user interface was implemented in a highly automated regression analysis tool. The user interface was developed from the start to run on computers that use the Windows, Macintosh, Linux, or UNIX operating system. Many user interface features were specifically designed such that a novice or inexperienced user can apply the regression analysis tool with confidence. Therefore, the user interface s design minimizes interactive input from the user. In addition, reasonable default combinations are assigned to those analysis settings that influence the outcome of the regression analysis. These default combinations will lead to a successful regression analysis result for most experimental data sets. The user interface comes in two versions. The text user interface version is used for the ongoing development of the regression analysis tool. The official release of the regression analysis tool, on the other hand, has a graphical user interface that is more efficient to use. This graphical user interface displays all input file names, output file names, and analysis settings for a specific software application mode on a single screen which makes it easier to generate reliable analysis results and to perform input parameter studies. An object-oriented approach was used for the development of the graphical user interface. This choice keeps future software maintenance costs to a reasonable limit. Examples of both the text user interface and graphical user interface are discussed in order to illustrate the user interface s overall design approach.

Regression Analysis and the Sociological Imagination

ERIC Educational Resources Information Center

De Maio, Fernando

2014-01-01

Regression analysis is an important aspect of most introductory statistics courses in sociology but is often presented in contexts divorced from the central concerns that bring students into the discipline. Consequently, we present five lesson ideas that emerge from a regression analysis of income inequality and mortality in the USA and Canada.

Sperm Retrieval in Patients with Klinefelter Syndrome: A Skewed Regression Model Analysis.

PubMed

Chehrazi, Mohammad; Rahimiforoushani, Abbas; Sabbaghian, Marjan; Nourijelyani, Keramat; Sadighi Gilani, Mohammad Ali; Hoseini, Mostafa; Vesali, Samira; Yaseri, Mehdi; Alizadeh, Ahad; Mohammad, Kazem; Samani, Reza Omani

2017-01-01

The most common chromosomal abnormality due to non-obstructive azoospermia (NOA) is Klinefelter syndrome (KS) which occurs in 1-1.72 out of 500-1000 male infants. The probability of retrieving sperm as the outcome could be asymmetrically different between patients with and without KS, therefore logistic regression analysis is not a well-qualified test for this type of data. This study has been designed to evaluate skewed regression model analysis for data collected from microsurgical testicular sperm extraction (micro-TESE) among azoospermic patients with and without non-mosaic KS syndrome. This cohort study compared the micro-TESE outcome between 134 men with classic KS and 537 men with NOA and normal karyotype who were referred to Royan Institute between 2009 and 2011. In addition to our main outcome, which was sperm retrieval, we also used logistic and skewed regression analyses to compare the following demographic and hormonal factors: age, level of follicle stimulating hormone (FSH), luteinizing hormone (LH), and testosterone between the two groups. A comparison of the micro-TESE between the KS and control groups showed a success rate of 28.4% (38/134) for the KS group and 22.2% (119/537) for the control group. In the KS group, a significantly difference (P<0.001) existed between testosterone levels for the successful sperm retrieval group (3.4 ± 0.48 mg/mL) compared to the unsuccessful sperm retrieval group (2.33 ± 0.23 mg/mL). The index for quasi Akaike information criterion (QAIC) had a goodness of fit of 74 for the skewed model which was lower than logistic regression (QAIC=85). According to the results, skewed regression is more efficient in estimating sperm retrieval success when the data from patients with KS are analyzed. This finding should be investigated by conducting additional studies with different data structures.

A meta-analysis of association between glutathione S-transferase M1 gene polymorphism and Parkinson's disease susceptibility.

PubMed

Weikang, Chen; Jie, Li; Likang, Lan; Weiwen, Qiu; Liping, Lu

2016-01-01

The aim of this meta-analysis was to evaluate whether there was an association between glutathione S-transferase M1(GSTM1)gene polymorphism and Parkinson's disease (PD) susceptibility by pooling published data. We performed comprehensive electronic database search for articles published between February12,2015 and April30 2016. The published case-control or cohort studies related to GSTM1 gene polymorphism and Parkinson's disease susceptibility were screened, reviewed, and included in this meta-analysis. The correlation between GSTM1 gene polymorphism and PD susceptibility was expressed by odds ratio (OR) and its corresponding 95% confidence interval (95%CI). Publication bias was evaluated by Begg's funnel plot and Egger's line regression test. All analysis was done by stata11.0 software. After searching the PubMed, EMBASE, and CNKI databases, seventeen case-control studies with 3,538 PD and 5,180 controls were included in the final meta-analysis. The data was pooled by a fixed-effect model for lack of statistical heterogeneity across the studies; the results showed GSTM1 null expression can significant increase the susceptibility of PD (OR=1.11, 95% CI:1.01-1.21, P<0.05). Subgroup analysis indicated GSTM1 gene polymorphism was associated with PD susceptibility in the Caucasian ethnic group (OR=1.15, 95% CI:1.05-1.27, P<0.05) but not in the Asian ethnic group (OR=0.89, 95% CI:0.70-1.12, P>0.05). Begg's funnel plot and Egger's line regression test showed no significant publication bias. Based on the present evidence, GSTM1 null expression can significant increase the susceptibility of PD in persons of Caucasian ethnicity.

Simultaneous determination of estrogens (ethinylestradiol and norgestimate) concentrations in human and bovine serum albumin by use of fluorescence spectroscopy and multivariate regression analysis.

PubMed

Hordge, LaQuana N; McDaniel, Kiara L; Jones, Derick D; Fakayode, Sayo O

2016-05-15

The endocrine disruption property of estrogens necessitates the immediate need for effective monitoring and development of analytical protocols for their analyses in biological and human specimens. This study explores the first combined utility of a steady-state fluorescence spectroscopy and multivariate partial-least-square (PLS) regression analysis for the simultaneous determination of two estrogens (17α-ethinylestradiol (EE) and norgestimate (NOR)) concentrations in bovine serum albumin (BSA) and human serum albumin (HSA) samples. The influence of EE and NOR concentrations and temperature on the emission spectra of EE-HSA EE-BSA, NOR-HSA, and NOR-BSA complexes was also investigated. The binding of EE with HSA and BSA resulted in increase in emission characteristics of HSA and BSA and a significant blue spectra shift. In contrast, the interaction of NOR with HSA and BSA quenched the emission characteristics of HSA and BSA. The observed emission spectral shifts preclude the effective use of traditional univariate regression analysis of fluorescent data for the determination of EE and NOR concentrations in HSA and BSA samples. Multivariate partial-least-squares (PLS) regression analysis was utilized to correlate the changes in emission spectra with EE and NOR concentrations in HSA and BSA samples. The figures-of-merit of the developed PLS regression models were excellent, with limits of detection as low as 1.6×10(-8) M for EE and 2.4×10(-7) M for NOR and good linearity (R(2)>0.994985). The PLS models correctly predicted EE and NOR concentrations in independent validation HSA and BSA samples with a root-mean-square-percent-relative-error (RMS%RE) of less than 6.0% at physiological condition. On the contrary, the use of univariate regression resulted in poor predictions of EE and NOR in HSA and BSA samples, with RMS%RE larger than 40% at physiological conditions. High accuracy, low sensitivity, simplicity, low-cost with no prior analyte extraction or separation required makes this method promising, compelling, and attractive alternative for the rapid determination of estrogen concentrations in biomedical and biological specimens, pharmaceuticals, or environmental samples. Published by Elsevier B.V.

Perception of self and significant others by alcoholics and nonalcoholics.

PubMed

Quereshi, M Y; Soat, D M

1976-01-01

Ratings of self and 15 significant others on four personality factors by 47 alcoholic and 90 nonalcoholic males were analyzed by means of step-wise regression analysis and multivariate analysis of covariance. Alcoholics rated themselves less positively on extraversion and self-assertiveness (lower mean on extraversion and higher on self-assertiveness) and also judged intimate others (father, mother, and spouse) less positively on unhappiness, extraversion, and productive persistence (higher mean on unhappiness and lower means on extraversion and productive persistence). There were no significant differences between the two groups in judging persons as a whole or in the degree of differentiation that was exhibited in rating all 16 persons including self.

Utility of an Abbreviated Dizziness Questionnaire to Differentiate between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study

PubMed Central

Roland, Lauren T.; Kallogjeri, Dorina; Sinks, Belinda C.; Rauch, Steven D.; Shepard, Neil T.; White, Judith A.; Goebel, Joel A.

2015-01-01

Objective Test performance of a focused dizziness questionnaire’s ability to discriminate between peripheral and non-peripheral causes of vertigo. Study Design Prospective multi-center Setting Four academic centers with experienced balance specialists Patients New dizzy patients Interventions A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Main outcomes Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and non-peripheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. Results 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and non-peripheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central and other causes were considered good as measured by c-indices of 0.75, 0.7 and 0.78, respectively. Conclusions This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from non-peripheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed. PMID:26485598

Utility of an Abbreviated Dizziness Questionnaire to Differentiate Between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study.

PubMed

Roland, Lauren T; Kallogjeri, Dorina; Sinks, Belinda C; Rauch, Steven D; Shepard, Neil T; White, Judith A; Goebel, Joel A

2015-12-01

Test performance of a focused dizziness questionnaire's ability to discriminate between peripheral and nonperipheral causes of vertigo. Prospective multicenter. Four academic centers with experienced balance specialists. New dizzy patients. A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and nonperipheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. In total, 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and nonperipheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central, and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central, and other causes was considered good as measured by c-indices of 0.75, 0.7, and 0.78, respectively. This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from nonperipheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed.

The impact of pneumatic tube system on routine laboratory parameters: a systematic review and meta-analysis.

PubMed

Kapoula, Georgia V; Kontou, Panagiota I; Bagos, Pantelis G

2017-10-26

Pneumatic tube system (PTS) is a widely used method of transporting blood samples in hospitals. The aim of this study was to evaluate the effects of the PTS transport in certain routine laboratory parameters as it has been implicated with hemolysis. A systematic review and a meta-analysis were conducted. PubMed and Scopus databases were searched (up until November 2016) to identify prospective studies evaluating the impact of PTS transport in hematological, biochemical and coagulation measurements. The random-effects model was used in the meta-analysis utilizing the mean difference (MD). Heterogeneity was quantitatively assessed using the Cohran's Q and the I2 index. Subgroup analysis, meta-regression analysis, sensitivity analysis, cumulative meta-analysis and assessment of publication bias were performed for all outcomes. From a total of 282 studies identified by the searching procedure, 24 were finally included in the meta-analysis. The meta-analysis yielded statistically significant results for potassium (K) [MD=0.04 mmol/L; 95% confidence interval (CI)=0.015-0.065; p=0.002], lactate dehydrogenase (LDH) (MD=10.343 U/L; 95% CI=6.132-14.554; p<10-4) and aspartate aminotransferase (AST) (MD=1.023 IU/L; 95% CI=0.344-1.702; p=0.003). Subgroup analysis and random-effects meta-regression analysis according to the speed and distance of the samples traveled via the PTS revealed that there is relation between the rate and the distance of PTS with the measurements of K, LDH, white blood cells and red blood cells. This meta-analysis suggests that PTS may be associated with alterations in K, LDH and AST measurements. Although these findings may not have any significant clinical effect on laboratory results, it is wise that each hospital validates their PTS.

Features of natural and gonadotropin-releasing hormone antagonist-induced corpus luteum regression and effects of in vivo human chorionic gonadotropin.

PubMed

Del Canto, Felipe; Sierralta, Walter; Kohen, Paulina; Muñoz, Alex; Strauss, Jerome F; Devoto, Luigi

2007-11-01

The natural process of luteolysis and luteal regression is induced by withdrawal of gonadotropin support. The objectives of this study were: 1) to compare the functional changes and apoptotic features of natural human luteal regression and induced luteal regression; 2) to define the ultrastructural characteristics of the corpus luteum at the time of natural luteal regression and induced luteal regression; and 3) to examine the effect of human chorionic gonadotropin (hCG) on the steroidogenic response and apoptotic markers within the regressing corpus luteum. Twenty-three women with normal menstrual cycles undergoing tubal ligation donated corpus luteum at specific stages in the luteal phase. Some women received a GnRH antagonist prior to collection of corpus luteum, others received an injection of hCG with or without prior treatment with a GnRH antagonist. Main outcome measures were plasma hormone levels and analysis of excised luteal tissue for markers of apoptosis, histology, and ultrastructure. The progesterone and estradiol levels, corpus luteum DNA, and protein contents in induced luteal regression resembled those of natural luteal regression. hCG treatment raised progesterone and estradiol in both natural luteal regression and induced luteal regression. The increase in apoptosis detected in induced luteal regression by cytochrome c in the cytosol, activated caspase-3, and nuclear DNA fragmentation, was similar to that observed in natural luteal regression. The antiapoptotic protein Bcl-2 was significantly lower during natural luteal regression. The proapoptotic proteins Bax and Bak were at a constant level. Apoptotic and nonapoptotic death of luteal cells was observed in natural luteal regression and induced luteal regression at the ultrastructural level. hCG prevented apoptotic cell death, but not autophagy. The low number of apoptotic cells disclosed and the frequent autophagocytic suggest that multiple mechanisms are involved in cell death at luteal regression. hCG restores steroidogenic function and restrains the apoptotic process, but not autophagy.

Examination of Parameters Affecting the House Prices by Multiple Regression Analysis and its Contributions to Earthquake-Based Urban Transformation

NASA Astrophysics Data System (ADS)

Denli, H. H.; Durmus, B.

2016-12-01

The purpose of this study is to examine the factors which may affect the apartment prices with multiple linear regression analysis models and visualize the results by value maps. The study is focused on a county of Istanbul - Turkey. Totally 390 apartments around the county Umraniye are evaluated due to their physical and locational conditions. The identification of factors affecting the price of apartments in the county with a population of approximately 600k is expected to provide a significant contribution to the apartment market.Physical factors are selected as the age, number of rooms, size, floor numbers of the building and the floor that the apartment is positioned in. Positional factors are selected as the distances to the nearest hospital, school, park and police station. Totally ten physical and locational parameters are examined by regression analysis.After the regression analysis has been performed, value maps are composed from the parameters age, price and price per square meters. The most significant of the composed maps is the price per square meters map. Results show that the location of the apartment has the most influence to the square meter price information of the apartment. A different practice is developed from the composed maps by searching the ability of using price per square meters map in urban transformation practices. By marking the buildings older than 15 years in the price per square meters map, a different and new interpretation has been made to determine the buildings, to which should be given priority during an urban transformation in the county.This county is very close to the North Anatolian Fault zone and is under the threat of earthquakes. By marking the apartments older than 15 years on the price per square meters map, both older and expensive square meters apartments list can be gathered. By the help of this list, the priority could be given to the selected higher valued old apartments to support the economy of the country during an earthquake loss. We may call this urban transformation as earthquake-based urban transformation.

Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

PubMed Central

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

Multi Objective Optimization of Multi Wall Carbon Nanotube Based Nanogrinding Wheel Using Grey Relational and Regression Analysis

NASA Astrophysics Data System (ADS)

Sethuramalingam, Prabhu; Vinayagam, Babu Kupusamy

2016-07-01

Carbon nanotube mixed grinding wheel is used in the grinding process to analyze the surface characteristics of AISI D2 tool steel material. Till now no work has been carried out using carbon nanotube based grinding wheel. Carbon nanotube based grinding wheel has excellent thermal conductivity and good mechanical properties which are used to improve the surface finish of the workpiece. In the present study, the multi response optimization of process parameters like surface roughness and metal removal rate of grinding process of single wall carbon nanotube (CNT) in mixed cutting fluids is undertaken using orthogonal array with grey relational analysis. Experiments are performed with designated grinding conditions obtained using the L9 orthogonal array. Based on the results of the grey relational analysis, a set of optimum grinding parameters is obtained. Using the analysis of variance approach the significant machining parameters are found. Empirical model for the prediction of output parameters has been developed using regression analysis and the results are compared empirically, for conditions of with and without CNT grinding wheel in grinding process.

Cognitive, emotive, and cognitive-behavioral correlates of suicidal ideation among Chinese adolescents in Hong Kong.

PubMed

Kwok, Sylvia Lai Yuk Ching; Shek, Daniel Tan Lei

2010-03-05

Utilizing Daniel Goleman's theory of emotional competence, Beck's cognitive theory, and Rudd's cognitive-behavioral theory of suicidality, the relationships between hopelessness (cognitive component), social problem solving (cognitive-behavioral component), emotional competence (emotive component), and adolescent suicidal ideation were examined. Based on the responses of 5,557 Secondary 1 to Secondary 4 students from 42 secondary schools in Hong Kong, results showed that suicidal ideation was positively related to adolescent hopelessness, but negatively related to emotional competence and social problem solving. While standard regression analyses showed that all the above variables were significant predictors of suicidal ideation, hierarchical regression analyses showed that hopelessness was the most important predictor of suicidal ideation, followed by social problem solving and emotional competence. Further regression analyses found that all four subscales of emotional competence, i.e., empathy, social skills, self-management of emotions, and utilization of emotions, were important predictors of male adolescent suicidal ideation. However, the subscale of social skills was not a significant predictor of female adolescent suicidal ideation. Standard regression analysis also revealed that all three subscales of social problem solving, i.e., negative problem orientation, rational problem solving, and impulsiveness/carelessness style, were important predictors of suicidal ideation. Theoretical and practice implications of the findings are discussed.

Multiple correlates of cigarette use among high school students.

PubMed

McDermott, R J; Sarvela, P D; Hoalt, P N; Bajracharya, S M; Marty, P J; Emery, E M

1992-04-01

A cross-sectional survey research design measured factors related to cigarette use among 2,212 senior high school students. Results showed 14.3% of the sample smoked cigarettes at least occasionally, with 5.3% reporting they were daily smokers. About 12.8% indicated they were ex-smokers. Males and females smoked at almost equal rates, and the percentage of 10th grade student smokers was slightly higher (16.4%) than the percentage of juniors and seniors who smoked. Approximately 22% of Hispanic students, 15% of Caucasian students, and 4.5% of African-American students reported smoking cigarettes at least occasionally. An initial regression analysis used 21 variables to predict cigarette smoking. A more parsimonious regression model (R2 = .28), using variables from the initial regression analysis with significance levels of .01 or less, indicated the most important predictors of cigarette use were ethnic group, attitude toward females who smoke, close friends' use of cigarettes, personal use of marijuana, best friend's use of cigarettes, personal use of alcohol, and school self-esteem. Implications for school health programs are addressed.

Expression profiling reveals distinct sets of genes altered during induction and regression of cardiac hypertrophy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Friddle, Carl J; Koga, Teiichiro; Rubin, Edward M.

2000-03-15

While cardiac hypertrophy has been the subject of intensive investigation, regression of hypertrophy has been significantly less studied, precluding large-scale analysis of the relationship between these processes. In the present study, using pharmacological models of hypertrophy in mice, expression profiling was performed with fragments of more than 3,000 genes to characterize and contrast expression changes during induction and regression of hypertrophy. Administration of angiotensin II and isoproterenol by osmotic minipump produced increases in heart weight (15% and 40% respectively) that returned to pre-induction size following drug withdrawal. From multiple expression analyses of left ventricular RNA isolated at daily time-points duringmore » cardiac hypertrophy and regression, we identified sets of genes whose expression was altered at specific stages of this process. While confirming the participation of 25 genes or pathways previously known to be altered by hypertrophy, a larger set of 30 genes was identified whose expression had not previously been associated with cardiac hypertrophy or regression. Of the 55 genes that showed reproducible changes during the time course of induction and regression, 32 genes were altered only during induction and 8 were altered only during regression. This study identified both known and novel genes whose expression is affected at different stages of cardiac hypertrophy and regression and demonstrates that cardiac remodeling during regression utilizes a set of genes that are distinct from those used during induction of hypertrophy.« less

Multivariate Regression Analysis and Slaughter Livestock,

DTIC Science & Technology

AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY

Segmented regression analysis of interrupted time series data to assess outcomes of a South American road traffic alcohol policy change.

PubMed

Nistal-Nuño, Beatriz

2017-09-01

In Chile, a new law introduced in March 2012 decreased the legal blood alcohol concentration (BAC) limit for driving while impaired from 1 to 0.8 g/l and the legal BAC limit for driving under the influence of alcohol from 0.5 to 0.3 g/l. The goal is to assess the impact of this new law on mortality and morbidity outcomes in Chile. A review of national databases in Chile was conducted from January 2003 to December 2014. Segmented regression analysis of interrupted time series was used for analyzing the data. In a series of multivariable linear regression models, the change in intercept and slope in the monthly incidence rate of traffic deaths and injuries and association with alcohol per 100,000 inhabitants was estimated from pre-intervention to postintervention, while controlling for secular changes. In nested regression models, potential confounding seasonal effects were accounted for. All analyses were performed at a two-sided significance level of 0.05. Immediate level drops in all the monthly rates were observed after the law from the end of the prelaw period in the majority of models and in all the de-seasonalized models, although statistical significance was reached only in the model for injures related to alcohol. After the law, the estimated monthly rate dropped abruptly by -0.869 for injuries related to alcohol and by -0.859 adjusting for seasonality (P < 0.001). Regarding the postlaw long-term trends, it was evidenced a steeper decreasing trend after the law in the models for deaths related to alcohol, although these differences were not statistically significant. A strong evidence of a reduction in traffic injuries related to alcohol was found following the law in Chile. Although insufficient evidence was found of a statistically significant effect for the beneficial effects seen on deaths and overall injuries, potential clinically important effects cannot be ruled out. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Sexual possibility situations and sexual behaviors among young adolescents: the moderating role of protective factors.

PubMed

DiLorio, Colleen; Dudley, William N; Soet, Johanna E; McCarty, Frances

2004-12-01

To examine sexual possibility situations (SPS) and protective practices associated with involvement in intimate sexual behaviors and the initiation of sexual intercourse among young adolescents and to determine if protective factors moderate the relationship between SPS and sexual behaviors. Data for these analyses were obtained from the baseline assessment for adolescents conducted as part of an HIV prevention study called "Keepin' it R.E.A.L.!" The study was conducted with a community-based organization (CBO) in an urban area serving a predominantly African-American population. In addition to items assessing SPS, intimate sexual behaviors, and initiation of sexual intercourse, adolescents provided information on the following protective factors: educational goals, self-concept, future time perspective, orientation to health, self-efficacy, outcome expectations, parenting, communication, values, and prosocial activities. Background personal information, including age and gender, was also collected. The analyses were conducted on data from 491 predominantly African-American adolescents, 61% of whom were boys. Variables were combined to form SPS and protective indices that were used in the first set of regression analyses. In a second set of analyses, the indices were unbundled and individual variables were entered into regression analyses. Both SPS and protective indices explained significant portions of variance in intimate sexual behaviors, and the SPS index explained a significant portion of variance in the initiation of sexual intercourse. The regression analysis using the unbundled SPS and protective factors revealed the following statistically significant predictors for intimate sexual behaviors: age, gender, time alone with groups of peers, time alone with a member of the opposite sex, behavior self-concept, popularity self-concept, self-efficacy for abstinence, outcome expectations for abstinence, parental control, personal values, and parental values. A similar regression analysis revealed that age, time alone with a member of the opposite sex, and personal values were significant predictors of initiation of sexual intercourse. These results provide evidence for the important role of protective factors in explaining early involvement in sexual behaviors and show that protective factors extend beyond personal characteristics to include both familial and peer factors.

Epistasis analysis for quantitative traits by functional regression model.

PubMed

Zhang, Futao; Boerwinkle, Eric; Xiong, Momiao

2014-06-01

The critical barrier in interaction analysis for rare variants is that most traditional statistical methods for testing interactions were originally designed for testing the interaction between common variants and are difficult to apply to rare variants because of their prohibitive computational time and poor ability. The great challenges for successful detection of interactions with next-generation sequencing (NGS) data are (1) lack of methods for interaction analysis with rare variants, (2) severe multiple testing, and (3) time-consuming computations. To meet these challenges, we shift the paradigm of interaction analysis between two loci to interaction analysis between two sets of loci or genomic regions and collectively test interactions between all possible pairs of SNPs within two genomic regions. In other words, we take a genome region as a basic unit of interaction analysis and use high-dimensional data reduction and functional data analysis techniques to develop a novel functional regression model to collectively test interactions between all possible pairs of single nucleotide polymorphisms (SNPs) within two genome regions. By intensive simulations, we demonstrate that the functional regression models for interaction analysis of the quantitative trait have the correct type 1 error rates and a much better ability to detect interactions than the current pairwise interaction analysis. The proposed method was applied to exome sequence data from the NHLBI's Exome Sequencing Project (ESP) and CHARGE-S study. We discovered 27 pairs of genes showing significant interactions after applying the Bonferroni correction (P-values < 4.58 × 10(-10)) in the ESP, and 11 were replicated in the CHARGE-S study. © 2014 Zhang et al.; Published by Cold Spring Harbor Laboratory Press.

Protein-coding genes combined with long noncoding RNA as a novel transcriptome molecular staging model to predict the survival of patients with esophageal squamous cell carcinoma.

PubMed

Guo, Jin-Cheng; Wu, Yang; Chen, Yang; Pan, Feng; Wu, Zhi-Yong; Zhang, Jia-Sheng; Wu, Jian-Yi; Xu, Xiu-E; Zhao, Jian-Mei; Li, En-Min; Zhao, Yi; Xu, Li-Yan

2018-04-09

Esophageal squamous cell carcinoma (ESCC) is the predominant subtype of esophageal carcinoma in China. This study was to develop a staging model to predict outcomes of patients with ESCC. Using Cox regression analysis, principal component analysis (PCA), partitioning clustering, Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, and classification and regression tree (CART) analysis, we mined the Gene Expression Omnibus database to determine the expression profiles of genes in 179 patients with ESCC from GSE63624 and GSE63622 dataset. Univariate cox regression analysis of the GSE63624 dataset revealed that 2404 protein-coding genes (PCGs) and 635 long non-coding RNAs (lncRNAs) were associated with the survival of patients with ESCC. PCA categorized these PCGs and lncRNAs into three principal components (PCs), which were used to cluster the patients into three groups. ROC analysis demonstrated that the predictive ability of PCG-lncRNA PCs when applied to new patients was better than that of the tumor-node-metastasis staging (area under ROC curve [AUC]: 0.69 vs. 0.65, P < 0.05). Accordingly, we constructed a molecular disaggregated model comprising one lncRNA and two PCGs, which we designated as the LSB staging model using CART analysis in the GSE63624 dataset. This LSB staging model classified the GSE63622 dataset of patients into three different groups, and its effectiveness was validated by analysis of another cohort of 105 patients. The LSB staging model has clinical significance for the prognosis prediction of patients with ESCC and may serve as a three-gene staging microarray.

Does vitamin D supplementation alter plasma adipokines concentrations? A systematic review and meta-analysis of randomized controlled trials.

PubMed

Dinca, Madalina; Serban, Maria-Corina; Sahebkar, Amirhossein; Mikhailidis, Dimitri P; Toth, Peter P; Martin, Seth S; Blaha, Michael J; Blüher, Matthias; Gurban, Camelia; Penson, Peter; Michos, Erin D; Hernandez, Adrian V; Jones, Steven R; Banach, Maciej

2016-05-01

We aimed to elucidate the role of vitamin D supplementation on adipokines through a systematic review and a meta-analysis of randomized placebo-controlled trials (RCTs). The search included PUBMED, Scopus, Web of Science and Google Scholar through July 1st, 2015. Finally we identified 9 RCTs and 484 participants. Meta-analysis of data from 7 studies did not find a significant change in plasma adiponectin concentrations following vitamin D supplementation (mean difference [MD]: 4.45%, 95%CI: -3.04, 11.93, p=0.244; Q=2.18, I(2)=0%). In meta-regression, changes in plasma adiponectin concentrations following vitamin D supplementation were found to be independent of treatment duration (slope: 0.25; 95%CI: -0.69, 1.19; p=0.603) and changes in serum 25-hydroxy vitamin D [25(OH)D] levels (slope: -0.02; 95%CI: -0.15, 0.12; p=0.780). Meta-analysis of data from 6 studies did not find a significant change in plasma leptin concentrations following vitamin D supplementation (MD: -4.51%, 95%CI: -25.13, 16.11, p=0.668; Q=6.41, I(2)=21.97%). Sensitivity analysis showed that this effect size is sensitive to one of the studies; removing it resulted in a significant reduction in plasma leptin levels (MD: -12.81%, 95%CI: -24.33, -1.30, p=0.029). In meta-regression, changes in plasma leptin concentrations following vitamin D supplementation were found to be independent of treatment duration (slope: -1.93; 95%CI: -4.08, 0.23; p=0.080). However, changes in serum 25(OH)D were found to be significantly associated with changes in plasma leptin levels following vitamin D supplementation (slope: 1.05; 95%CI: 0.08, 2.02; p=0.033). In conclusion, current data did not indicate a significant effect of vitamin D supplementation on adiponectin and leptin levels. Copyright © 2016 Elsevier Ltd. All rights reserved.

Radiation Dose-Response Model for Locally Advanced Rectal Cancer After Preoperative Chemoradiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Appelt, Ane L., E-mail: ane.lindegaard.appelt@slb.regionsyddanmark.dk; University of Southern Denmark, Odense; Ploen, John

2013-01-01

Purpose: Preoperative chemoradiation therapy (CRT) is part of the standard treatment of locally advanced rectal cancers. Tumor regression at the time of operation is desirable, but not much is known about the relationship between radiation dose and tumor regression. In the present study we estimated radiation dose-response curves for various grades of tumor regression after preoperative CRT. Methods and Materials: A total of 222 patients, treated with consistent chemotherapy and radiation therapy techniques, were considered for the analysis. Radiation therapy consisted of a combination of external-beam radiation therapy and brachytherapy. Response at the time of operation was evaluated from themore » histopathologic specimen and graded on a 5-point scale (TRG1-5). The probability of achieving complete, major, and partial response was analyzed by ordinal logistic regression, and the effect of including clinical parameters in the model was examined. The radiation dose-response relationship for a specific grade of histopathologic tumor regression was parameterized in terms of the dose required for 50% response, D{sub 50,i}, and the normalized dose-response gradient, {gamma}{sub 50,i}. Results: A highly significant dose-response relationship was found (P=.002). For complete response (TRG1), the dose-response parameters were D{sub 50,TRG1} = 92.0 Gy (95% confidence interval [CI] 79.3-144.9 Gy), {gamma}{sub 50,TRG1} = 0.982 (CI 0.533-1.429), and for major response (TRG1-2) D{sub 50,TRG1} and {sub 2} = 72.1 Gy (CI 65.3-94.0 Gy), {gamma}{sub 50,TRG1} and {sub 2} = 0.770 (CI 0.338-1.201). Tumor size and N category both had a significant effect on the dose-response relationships. Conclusions: This study demonstrated a significant dose-response relationship for tumor regression after preoperative CRT for locally advanced rectal cancer for tumor dose levels in the range of 50.4-70 Gy, which is higher than the dose range usually considered.« less

Mortality and nursing care dependency one year after first ischemic stroke: an analysis of German statutory health insurance data.

PubMed

Kemper, Claudia; Koller, Daniela; Glaeske, Gerd; van den Bussche, Hendrik

2011-01-01

Aphasia, dementia, and depression are important and common neurological and neuropsychological disorders after ischemic stroke. We estimated the frequency of these comorbidities and their impact on mortality and nursing care dependency. Data of a German statutory health insurance were analyzed for people aged 50 years and older with first ischemic stroke. Aphasia, dementia, and depression were defined on the basis of outpatient medical diagnoses within 1 year after stroke. Logistic regression models for mortality and nursing care dependency were calculated and were adjusted for age, sex, and other relevant comorbidity. Of 977 individuals with a first ischemic stroke, 14.8% suffered from aphasia, 12.5% became demented, and 22.4% became depressed. The regression model for mortality showed a significant influence of age, aphasia, and other relevant comorbidity. In the regression model for nursing care dependency, the factors age, aphasia, dementia, depression, and other relevant comorbidity were significant. Aphasia has a high impact on mortality and nursing care dependency after ischemic stroke, while dementia and depression are strongly associated with increasing nursing care dependency.

Predictors of effects of lifestyle intervention on diabetes mellitus type 2 patients.

PubMed

Jacobsen, Ramune; Vadstrup, Eva; Røder, Michael; Frølich, Anne

2012-01-01

The main aim of the study was to identify predictors of the effects of lifestyle intervention on diabetes mellitus type 2 patients by means of multivariate analysis. Data from a previously published randomised clinical trial, which compared the effects of a rehabilitation programme including standardised education and physical training sessions in the municipality's health care centre with the same duration of individual counseling in the diabetes outpatient clinic, were used. Data from 143 diabetes patients were analysed. The merged lifestyle intervention resulted in statistically significant improvements in patients' systolic blood pressure, waist circumference, exercise capacity, glycaemic control, and some aspects of general health-related quality of life. The linear multivariate regression models explained 45% to 80% of the variance in these improvements. The baseline outcomes in accordance to the logic of the regression to the mean phenomenon were the only statistically significant and robust predictors in all regression models. These results are important from a clinical point of view as they highlight the more urgent need for and better outcomes following lifestyle intervention for those patients who have worse general and disease-specific health.

Effects of Sleep Quality on the Association between Problematic Mobile Phone Use and Mental Health Symptoms in Chinese College Students.

PubMed

Tao, Shuman; Wu, Xiaoyan; Zhang, Yukun; Zhang, Shichen; Tong, Shilu; Tao, Fangbiao

2017-02-14

Problematic mobile phone use (PMPU) is a risk factor for both adolescents' sleep quality and mental health. It is important to examine the potential negative health effects of PMPU exposure. This study aims to evaluate PMPU and its association with mental health in Chinese college students. Furthermore, we investigated how sleep quality influences this association. In 2013, we collected data regarding participants' PMPU, sleep quality, and mental health (psychopathological symptoms, anxiety, and depressive symptoms) by standardized questionnaires in 4747 college students. Multivariate logistic regression analysis was applied to assess independent effects and interactions of PMPU and sleep quality with mental health. PMPU and poor sleep quality were observed in 28.2% and 9.8% of participants, respectively. Adjusted logistic regression models suggested independent associations of PMPU and sleep quality with mental health ( p < 0.001). Further regression analyses suggested a significant interaction between these measures ( p < 0.001). The study highlights that poor sleep quality may play a more significant role in increasing the risk of mental health problems in students with PMPU than in those without PMPU.

Early Warning Signals of Financial Crises with Multi-Scale Quantile Regressions of Log-Periodic Power Law Singularities.

PubMed

Zhang, Qun; Zhang, Qunzhi; Sornette, Didier

2016-01-01

We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle (at least partially) the genuine LPPLS signal and the a priori unknown complicated residuals. Second, we propose to combine the many quantile regressions with a multi-scale analysis, which aggregates and consolidates the obtained ensembles of scenarios. Third, we define and implement the so-called DS LPPLS Confidence™ and Trust™ indicators that enrich considerably the diagnostic of bubbles. Using a detailed study of the "S&P 500 1987" bubble and presenting analyses of 16 historical bubbles, we show that the quantile regression of LPPLS signals contributes useful early warning signals. The comparison between the constructed signals and the price development in these 16 historical bubbles demonstrates their significant predictive ability around the real critical time when the burst/rally occurs.

Height and Weight Estimation From Anthropometric Measurements Using Machine Learning Regressions

PubMed Central

Fernandes, Bruno J. T.; Roque, Alexandre

2018-01-01

Height and weight are measurements explored to tracking nutritional diseases, energy expenditure, clinical conditions, drug dosages, and infusion rates. Many patients are not ambulant or may be unable to communicate, and a sequence of these factors may not allow accurate estimation or measurements; in those cases, it can be estimated approximately by anthropometric means. Different groups have proposed different linear or non-linear equations which coefficients are obtained by using single or multiple linear regressions. In this paper, we present a complete study of the application of different learning models to estimate height and weight from anthropometric measurements: support vector regression, Gaussian process, and artificial neural networks. The predicted values are significantly more accurate than that obtained with conventional linear regressions. In all the cases, the predictions are non-sensitive to ethnicity, and to gender, if more than two anthropometric parameters are analyzed. The learning model analysis creates new opportunities for anthropometric applications in industry, textile technology, security, and health care. PMID:29651366

Ridge regression for predicting elastic moduli and hardness of calcium aluminosilicate glasses

NASA Astrophysics Data System (ADS)

Deng, Yifan; Zeng, Huidan; Jiang, Yejia; Chen, Guorong; Chen, Jianding; Sun, Luyi

2018-03-01

It is of great significance to design glasses with satisfactory mechanical properties predictively through modeling. Among various modeling methods, data-driven modeling is such a reliable approach that can dramatically shorten research duration, cut research cost and accelerate the development of glass materials. In this work, the ridge regression (RR) analysis was used to construct regression models for predicting the compositional dependence of CaO-Al2O3-SiO2 glass elastic moduli (Shear, Bulk, and Young’s moduli) and hardness based on the ternary diagram of the compositions. The property prediction over a large glass composition space was accomplished with known experimental data of various compositions in the literature, and the simulated results are in good agreement with the measured ones. This regression model can serve as a facile and effective tool for studying the relationship between the compositions and the property, enabling high-efficient design of glasses to meet the requirements for specific elasticity and hardness.

Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea.

PubMed

Lee, Soo Yee; Mediani, Ahmed; Maulidiani, Maulidiani; Khatib, Alfi; Ismail, Intan Safinar; Zawawi, Norhasnida; Abas, Faridah

2018-01-01

Neptunia oleracea is a plant consumed as a vegetable and which has been used as a folk remedy for several diseases. Herein, two regression models (partial least squares, PLS; and random forest, RF) in a metabolomics approach were compared and applied to the evaluation of the relationship between phenolics and bioactivities of N. oleracea. In addition, the effects of different extraction conditions on the phenolic constituents were assessed by pattern recognition analysis. Comparison of the PLS and RF showed that RF exhibited poorer generalization and hence poorer predictive performance. Both the regression coefficient of PLS and the variable importance of RF revealed that quercetin and kaempferol derivatives, caffeic acid and vitexin-2-O-rhamnoside were significant towards the tested bioactivities. Furthermore, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results showed that sonication and absolute ethanol are the preferable extraction method and ethanol ratio, respectively, to produce N. oleracea extracts with high phenolic levels and therefore high DPPH scavenging and α-glucosidase inhibitory activities. Both PLS and RF are useful regression models in metabolomics studies. This work provides insight into the performance of different multivariate data analysis tools and the effects of different extraction conditions on the extraction of desired phenolics from plants. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

ACTN3 genotype and physical function and frailty in an elderly Chinese population: the Rugao Longevity and Ageing Study.

PubMed

Ma, Teng; Lu, Deyi; Zhu, Yin-Sheng; Chu, Xue-Feng; Wang, Yong; Shi, Guo-Ping; Wang, Zheng-Dong; Yu, Li; Jiang, Xiao-Yan; Wang, Xiao-Feng

2018-05-01

To examine the associations of the actinin alpha 3 gene (ACTN3) R577X polymorphism with physical performance and frailty in an older Chinese population. Data from 1,463 individuals (57.8% female) aged 70-87 years from the Rugao Longevity and Ageing Study were used. The associations between R577X and timed 5-m walk, grip strength, timed Up and Go test, and frailty index (FI) based on deficits of 23 laboratory tests (FI-Lab) were examined. Analysis of variance and linear regression models were used to evaluate the genetic effects of ACTN3 R577X on physical performance and FI-Lab. The XX and RX genotypes of the ACTN3 R557X polymorphism accounted for 17.1 and 46.9%, respectively. Multivariate regression analysis revealed that in men aged 70-79 years, the ACTN3 577X allele was significantly associated with physical performance (5-m walk time, regression coefficient (β) = 0.258, P = 0.006; grip strength, β = -1.062, P = 0.012; Up and Go test time β = 0.368, P = 0.019). In women aged 70-79 years, a significant association between the ACTN3 577X allele and the FI-Lab score was observed, with a regression coefficient of β = 0.019 (P = 0.003). These findings suggest an age- and gender-specific X-additive model of R577X for 5-m walk time, grip strength, Up and Go Test time, and FI-Lab score. The ACTN3 577X allele is associated with an age- and sex-specific decrease in physical performance and an increase in frailty in an older population.

Plant leaf chlorophyll content retrieval based on a field imaging spectroscopy system.

PubMed

Liu, Bo; Yue, Yue-Min; Li, Ru; Shen, Wen-Jing; Wang, Ke-Lin

2014-10-23

A field imaging spectrometer system (FISS; 380-870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%-35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector.

Plant Leaf Chlorophyll Content Retrieval Based on a Field Imaging Spectroscopy System

PubMed Central

Liu, Bo; Yue, Yue-Min; Li, Ru; Shen, Wen-Jing; Wang, Ke-Lin

2014-01-01

A field imaging spectrometer system (FISS; 380–870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%–35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector. PMID:25341439