Abnormal dynamics of language in schizophrenia.

PubMed

Stephane, Massoud; Kuskowski, Michael; Gundel, Jeanette

2014-05-30

Language could be conceptualized as a dynamic system that includes multiple interactive levels (sub-lexical, lexical, sentence, and discourse) and components (phonology, semantics, and syntax). In schizophrenia, abnormalities are observed at all language elements (levels and components) but the dynamic between these elements remains unclear. We hypothesize that the dynamics between language elements in schizophrenia is abnormal and explore how this dynamic is altered. We, first, investigated language elements with comparable procedures in patients and healthy controls. Second, using measures of reaction time, we performed multiple linear regression analyses to evaluate the inter-relationships among language elements and the effect of group on these relationships. Patients significantly differed from controls with respect to sub-lexical/lexical, lexical/sentence, and sentence/discourse regression coefficients. The intercepts of the regression slopes increased in the same order above (from lower to higher levels) in patients but not in controls. Regression coefficients between syntax and both sentence level and discourse level semantics did not differentiate patients from controls. This study indicates that the dynamics between language elements is abnormal in schizophrenia. In patients, top-down flow of linguistic information might be reduced, and the relationship between phonology and semantics but not between syntax and semantics appears to be altered. Published by Elsevier Ireland Ltd.

Determination of osteoporosis risk factors using a multiple logistic regression model in postmenopausal Turkish women.

PubMed

Akkus, Zeki; Camdeviren, Handan; Celik, Fatma; Gur, Ali; Nas, Kemal

2005-09-01

To determine the risk factors of osteoporosis using a multiple binary logistic regression method and to assess the risk variables for osteoporosis, which is a major and growing health problem in many countries. We presented a case-control study, consisting of 126 postmenopausal healthy women as control group and 225 postmenopausal osteoporotic women as the case group. The study was carried out in the Department of Physical Medicine and Rehabilitation, Dicle University, Diyarbakir, Turkey between 1999-2002. The data from the 351 participants were collected using a standard questionnaire that contains 43 variables. A multiple logistic regression model was then used to evaluate the data and to find the best regression model. We classified 80.1% (281/351) of the participants using the regression model. Furthermore, the specificity value of the model was 67% (84/126) of the control group while the sensitivity value was 88% (197/225) of the case group. We found the distribution of residual values standardized for final model to be exponential using the Kolmogorow-Smirnow test (p=0.193). The receiver operating characteristic curve was found successful to predict patients with risk for osteoporosis. This study suggests that low levels of dietary calcium intake, physical activity, education, and longer duration of menopause are independent predictors of the risk of low bone density in our population. Adequate dietary calcium intake in combination with maintaining a daily physical activity, increasing educational level, decreasing birth rate, and duration of breast-feeding may contribute to healthy bones and play a role in practical prevention of osteoporosis in Southeast Anatolia. In addition, the findings of the present study indicate that the use of multivariate statistical method as a multiple logistic regression in osteoporosis, which maybe influenced by many variables, is better than univariate statistical evaluation.

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.

Regression Analysis with Dummy Variables: Use and Interpretation.

ERIC Educational Resources Information Center

Hinkle, Dennis E.; Oliver, J. Dale

1986-01-01

Multiple regression analysis (MRA) may be used when both continuous and categorical variables are included as independent research variables. The use of MRA with categorical variables involves dummy coding, that is, assigning zeros and ones to levels of categorical variables. Caution is urged in results interpretation. (Author/CH)

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.

A cross-sectional study for estimation of associations between education level and osteoporosis in a Chinese men sample.

PubMed

Yu, Cai-Xia; Zhang, Xiu-Zhen; Zhang, Keqin; Tang, Zihui

2015-12-09

The main aim of this study was to evaluate the association between education level and osteoporosis (OP) in general Chinese Men. We conducted a large-scale, community-based, cross-sectional study to investigate the association by using self-report questionnaire to assess education levels. The data of 1092 men were available for analysis in this study. Multiple regression models controlling for confounding factors to include education level were performed to explore the relationship between education level and OP. Positive correlations between education level and T-score of quantitative bone ultrasound (QUS-T score) were reported (β = 0.108, P value < 0.001). Multiple regression analysis indicated that the education level was independently and significantly associated with OP (P < 0.1 for all models). The men with lower education level had a higher prevalence of OP. The education level was independently and significantly associated with OP. The prevalence of OP was more frequent in Chinese men with lower education level. ClinicalTrials.gov Identifier: NCT02451397 ; date of registration: 05/28/2015).

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.

When Law Students Read Multiple Documents about Global Warming: Examining the Role of Topic-Specific Beliefs about the Nature of Knowledge and Knowing

ERIC Educational Resources Information Center

Braten, Ivar; Stromso, Helge I.

2010-01-01

In this study, law students (n = 49) read multiple authentic documents presenting conflicting information on the topic of climate change and responded to verification tasks assessing their superficial as well as their deeper-level within- and across-documents comprehension. Hierarchical multiple regression analyses showed that even after variance…

Comparison of two-concentration with multi-concentration linear regressions: Retrospective data analysis of multiple regulated LC-MS bioanalytical projects.

PubMed

Musuku, Adrien; Tan, Aimin; Awaiye, Kayode; Trabelsi, Fethi

2013-09-01

Linear calibration is usually performed using eight to ten calibration concentration levels in regulated LC-MS bioanalysis because a minimum of six are specified in regulatory guidelines. However, we have previously reported that two-concentration linear calibration is as reliable as or even better than using multiple concentrations. The purpose of this research is to compare two-concentration with multiple-concentration linear calibration through retrospective data analysis of multiple bioanalytical projects that were conducted in an independent regulated bioanalytical laboratory. A total of 12 bioanalytical projects were randomly selected: two validations and two studies for each of the three most commonly used types of sample extraction methods (protein precipitation, liquid-liquid extraction, solid-phase extraction). When the existing data were retrospectively linearly regressed using only the lowest and the highest concentration levels, no extra batch failure/QC rejection was observed and the differences in accuracy and precision between the original multi-concentration regression and the new two-concentration linear regression are negligible. Specifically, the differences in overall mean apparent bias (square root of mean individual bias squares) are within the ranges of -0.3% to 0.7% and 0.1-0.7% for the validations and studies, respectively. The differences in mean QC concentrations are within the ranges of -0.6% to 1.8% and -0.8% to 2.5% for the validations and studies, respectively. The differences in %CV are within the ranges of -0.7% to 0.9% and -0.3% to 0.6% for the validations and studies, respectively. The average differences in study sample concentrations are within the range of -0.8% to 2.3%. With two-concentration linear regression, an average of 13% of time and cost could have been saved for each batch together with 53% of saving in the lead-in for each project (the preparation of working standard solutions, spiking, and aliquoting). Furthermore, examples are given as how to evaluate the linearity over the entire concentration range when only two concentration levels are used for linear regression. To conclude, two-concentration linear regression is accurate and robust enough for routine use in regulated LC-MS bioanalysis and it significantly saves time and cost as well. Copyright © 2013 Elsevier B.V. All rights reserved.

Regression and multivariate models for predicting particulate matter concentration level.

PubMed

Nazif, Amina; Mohammed, Nurul Izma; Malakahmad, Amirhossein; Abualqumboz, Motasem S

2018-01-01

The devastating health effects of particulate matter (PM 10 ) exposure by susceptible populace has made it necessary to evaluate PM 10 pollution. Meteorological parameters and seasonal variation increases PM 10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM 10 concentration levels. The analyses were carried out using daily average PM 10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM 10 concentration levels having coefficient of determination (R 2 ) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R 2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R 2 result from 0.50 to 0.60. While, PCR models had R 2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.

GLOBALLY ADAPTIVE QUANTILE REGRESSION WITH ULTRA-HIGH DIMENSIONAL DATA

PubMed Central

Zheng, Qi; Peng, Limin; He, Xuming

2015-01-01

Quantile regression has become a valuable tool to analyze heterogeneous covaraite-response associations that are often encountered in practice. The development of quantile regression methodology for high dimensional covariates primarily focuses on examination of model sparsity at a single or multiple quantile levels, which are typically prespecified ad hoc by the users. The resulting models may be sensitive to the specific choices of the quantile levels, leading to difficulties in interpretation and erosion of confidence in the results. In this article, we propose a new penalization framework for quantile regression in the high dimensional setting. We employ adaptive L1 penalties, and more importantly, propose a uniform selector of the tuning parameter for a set of quantile levels to avoid some of the potential problems with model selection at individual quantile levels. Our proposed approach achieves consistent shrinkage of regression quantile estimates across a continuous range of quantiles levels, enhancing the flexibility and robustness of the existing penalized quantile regression methods. Our theoretical results include the oracle rate of uniform convergence and weak convergence of the parameter estimators. We also use numerical studies to confirm our theoretical findings and illustrate the practical utility of our proposal. PMID:26604424

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.

Multiple Regression with Varying Levels of Correlation among Predictors: Monte Carlo Sampling from Normal and Non-Normal Populations.

ERIC Educational Resources Information Center

Vasu, Ellen Storey

1978-01-01

The effects of the violation of the assumption of normality in the conditional distributions of the dependent variable, coupled with the condition of multicollinearity upon the outcome of testing the hypothesis that the regression coefficient equals zero, are investigated via a Monte Carlo study. (Author/JKS)

Serum 25-hydroxyvitamin D level is associated with myopia in the Korea national health and nutrition examination survey.

PubMed

Kwon, Jin-Woo; Choi, Jin A; La, Tae Yoon

2016-11-01

The aim of this article was to assess the associations of serum 25-hydroxyvitamin D [25(OH)D] and daily sun exposure time with myopia in Korean adults.This study is based on the Korea National Health and Nutrition Examination Survey (KNHANES) of Korean adults in 2010-2012; multiple logistic regression analyses were performed to examine the associations of serum 25(OH)D levels and daily sun exposure time with myopia, defined as spherical equivalent ≤-0.5D, after adjustment for age, sex, household income, body mass index (BMI), exercise, intraocular pressure (IOP), and education level. Also, multiple linear regression analyses were performed to examine the relationship between serum 25(OH)D levels with spherical equivalent after adjustment for daily sun exposure time in addition to the confounding factors above.Between the nonmyopic and myopic groups, spherical equivalent, age, IOP, BMI, waist circumference, education level, household income, and area of residence differed significantly (all P < 0.05). Compared with subjects with daily sun exposure time <2 hour, subjects with sun exposure time ≥2 to <5 hour, and those with sun exposure time ≥5 hour had significantly less myopia (P < 0.001). In addition, compared with subjects were categorized into quartiles of serum 25(OH)D, the higher quartiles had gradually lower prevalences of myopia after adjustment for confounding factors (P < 0.001). In multiple linear regression analyses, spherical equivalent was significantly associated with serum 25(OH)D concentration after adjustment for confounding factors (P = 0.002).Low serum 25(OH)D levels and shorter daily sun exposure time may be independently associated with a high prevalence of myopia in Korean adults. These data suggest a direct role for vitamin D in the development of myopia.

Sport Commitment among Competitive Female Gymnasts: A Developmental Perspective

ERIC Educational Resources Information Center

Weiss, Windee M.; Weiss, Maureen R.

2007-01-01

The purpose of this study was to examine age and competitive level differences in the relationship between determinants and level of sport commitment. Gymnasts (N = 304) comprised three age groups (8-11, 11-14.5, and 14.5-18 years) and two competitive levels (Levels 5-6 and 8-10). Multiple regression analyses revealed: (a) perceived costs and…

A Quantile Regression Approach to Understanding the Relations among Morphological Awareness, Vocabulary, and Reading Comprehension in Adult Basic Education Students

ERIC Educational Resources Information Center

Tighe, Elizabeth L.; Schatschneider, Christopher

2016-01-01

The purpose of this study was to investigate the joint and unique contributions of morphological awareness and vocabulary knowledge at five reading comprehension levels in adult basic education (ABE) students. We introduce the statistical technique of multiple quantile regression, which enabled us to assess the predictive utility of morphological…

The relationship between hemoglobin level and the type 1 diabetic nephropathy in Anhui Han's patients.

PubMed

Jiang, Jun; Lei, Lan; Zhou, Xiaowan; Li, Peng; Wei, Ren

2018-02-20

Recent studies have shown that low hemoglobin (Hb) level promote the progression of chronic kidney disease. This study assessed the relationship between Hb level and type 1 diabetic nephropathy (DN) in Anhui Han's patients. There were a total of 236 patients diagnosed with type 1 diabetes mellitus and (T1DM) seen between January 2014 and December 2016 in our centre. Hemoglobin levels in patients with DN were compared with those without DN. The relationship between Hb level and the urinary albumin-creatinine ratio (ACR) was examined by Spearman's correlational analysis and multiple stepwise regression analysis. The binary logistic multivariate regression analysis was performed to analyze the correlated factors for type 1 DN, calculate the Odds Ratio (OR) and 95%confidence interval (CI). The predicting value of Hb level for DN was evaluated by area under receiver operation characteristic curve (AUROC) for discrimination and Hosmer-Lemeshow goodness-of-fit test for calibration. The average Hb levels in the DN group (116.1 ± 20.8 g/L) were significantly lower than the non-DN group (131.9 ± 14.4 g/L) , P < 0.001. Hb levels were independently correlated with the urinary ACR in multiple stepwise regression analysis. The logistic multivariate regression analysis showed that the Hb level (OR: 0.936, 95% CI: 0.910 to 0.963, P < 0.001) was inversely correlated with DN in patients with T1DM. In sub-analysis, low Hb level (Hb < 120g/L in female, Hb < 130g/L in male) was still negatively associated with DN in patients with T1DM. The AUROC was 0.721 (95% CI: 0.655 to 0.787) in assessing the discrimination of the Hb level for DN. The value of P was 0.593 in Hosmer-Lemeshow goodness-of-fit test. In Anhui Han's patients with T1DM, the Hb level is inversely correlated with urinary ACR and DN. This article is protected by copyright. All rights reserved.

The prediction of intelligence in preschool children using alternative models to regression.

PubMed

Finch, W Holmes; Chang, Mei; Davis, Andrew S; Holden, Jocelyn E; Rothlisberg, Barbara A; McIntosh, David E

2011-12-01

Statistical prediction of an outcome variable using multiple independent variables is a common practice in the social and behavioral sciences. For example, neuropsychologists are sometimes called upon to provide predictions of preinjury cognitive functioning for individuals who have suffered a traumatic brain injury. Typically, these predictions are made using standard multiple linear regression models with several demographic variables (e.g., gender, ethnicity, education level) as predictors. Prior research has shown conflicting evidence regarding the ability of such models to provide accurate predictions of outcome variables such as full-scale intelligence (FSIQ) test scores. The present study had two goals: (1) to demonstrate the utility of a set of alternative prediction methods that have been applied extensively in the natural sciences and business but have not been frequently explored in the social sciences and (2) to develop models that can be used to predict premorbid cognitive functioning in preschool children. Predictions of Stanford-Binet 5 FSIQ scores for preschool-aged children is used to compare the performance of a multiple regression model with several of these alternative methods. Results demonstrate that classification and regression trees provided more accurate predictions of FSIQ scores than does the more traditional regression approach. Implications of these results are discussed.

Characterizing Individual Differences in Functional Connectivity Using Dual-Regression and Seed-Based Approaches

PubMed Central

Smith, David V.; Utevsky, Amanda V.; Bland, Amy R.; Clement, Nathan; Clithero, John A.; Harsch, Anne E. W.; Carter, R. McKell; Huettel, Scott A.

2014-01-01

A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two separate resting-state datasets comprising a total of 188 human participants. Both datasets were decomposed into resting-state networks (RSNs) using a probabilistic spatial independent components analysis (ICA). We estimated voxelwise functional connectivity with these networks using a dual-regression analysis, which characterizes the participant-level spatiotemporal dynamics of each network while controlling for (via multiple regression) the influence of other networks and sources of variability. We found that males and females exhibit distinct patterns of connectivity with multiple RSNs, including both visual and auditory networks and the right frontal-parietal network. These results replicated across both datasets and were not explained by differences in head motion, data quality, brain volume, cortisol levels, or testosterone levels. Importantly, we also demonstrate that dual-regression functional connectivity is better at detecting inter-individual variability than traditional seed-based functional connectivity approaches. Our findings characterize robust—yet frequently ignored—neural differences between males and females, pointing to the necessity of controlling for sex in neuroscience studies of individual differences. Moreover, our results highlight the importance of employing network-based models to study variability in functional connectivity. PMID:24662574

Effects of a westernized lifestyle on the association between fasting serum nonesterified fatty acids and insulin secretion in Japanese men.

PubMed

Kamei, Nozomu; Yamane, Kiminori; Nakanishi, Shuhei; Ishida, Kazufumi; Ohtaki, Megu; Okubo, Masamichi; Kohno, Nobuoki

2005-06-01

The effects of the prolonged elevation of nonesterified fatty acid (NEFA) levels on insulin secretion have been controversial and thought to be sex-specific. To investigate the association between a westernized lifestyle and the effects of NEFA on insulin secretion in Japanese men, we examined 67 nondiabetic Japanese-American men and 220 nondiabetic native Japanese men who underwent a 75-g oral glucose tolerance test (OGTT). Most Japanese Americans we surveyed are genetically identical to Japanese living in Japan, but their lifestyle is more westernized. Sets of multiple regression analyses were performed to evaluate the relationship between the sum of the immunoreactive insulin (IRI) levels during the OGTT ((Sigma)IRI) and clinical parameters. Japanese Americans had higher levels of fasting IRI, (Sigma)IRI, and a higher insulin resistance index (homeostasis model assessment for insulin resistance [HOMA-IR]) than native Japanese, whereas there were no significant differences in fasting NEFA and triglyceride levels. A multiple regression analysis adjusted for age, fasting triglycerides, and body mass index (BMI) demonstrated that the fasting NEFA level was an independent determinant of the (Sigma)IRI only in Japanese-American men ( P = .001), but not in native Japanese men ( P = .054). Even when HOMA-IR was included in models instead of BMI, the NEFA level was a significant variable of (Sigma)IRI only in Japanese Americans ( P < .001), and not in native Japanese ( P = .098). In addition, a multiple regression analysis adjusted for age, fasting triglycerides, and BMI demonstrated that the fasting NEFA level was the only independent determinant of (Sigma)C-peptide in Japanese-American men ( P = .041). In conclusion, NEFA seems to be associated with insulin secretion independent of obesity or HOMA-IR. A westernized lifestyle may increase the effects of serum fasting NEFA levels on total insulin secretion after a glucose load in Japanese men.

Small-Sample Adjustments for Tests of Moderators and Model Fit in Robust Variance Estimation in Meta-Regression

ERIC Educational Resources Information Center

Tipton, Elizabeth; Pustejovsky, James E.

2015-01-01

Randomized experiments are commonly used to evaluate the effectiveness of educational interventions. The goal of the present investigation is to develop small-sample corrections for multiple contrast hypothesis tests (i.e., F-tests) such as the omnibus test of meta-regression fit or a test for equality of three or more levels of a categorical…

Determining the Relationship between Drivers' Level of Education, Training, Working Conditions, and Job Performance in Kenya.

ERIC Educational Resources Information Center

Nafukho, Fredrick Muyia; Hinton, Barbara E.

2003-01-01

Multiple regression analyses of data from 143 public transportation drivers in Kenya indicated that driver experience and hours worked were significantly related to rates of traffic accidents. Educational level, training, salary, and average speed were not related. (Contains 45 references.) (SK)

Ethnic Identity as a Predictor of Problem Behaviors among Korean American Adolescents

ERIC Educational Resources Information Center

Shrake, Eunai K.; Rhee, Siyon

2004-01-01

This study examined three dimensions of ethnic identity (level of ethnic identity, attitudes toward other groups, and perceived discrimination) as predictors of adolescent problem behaviors among Korean American adolescents. Multiple regression analyses were carried out, and the results indicated that level of ethnic identity, perceived…

Perceived Foreign Accent: Extended Stays Abroad, Level of Instruction, and Motivation

ERIC Educational Resources Information Center

Martinsen, Rob A.; Alvord, Scott M.; Tanner, Joshua

2014-01-01

Studies have examined various factors that affect pronunciation including phonetic context, style variation, first language transfer, and experience abroad. A plethora of research has also linked motivation to higher levels of proficiency in the second language. The present study uses native speaker ratings and multiple regression analysis to…

Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

PubMed

Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa

2008-01-01

This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.

Impacts of education level and employment status on health-related quality of life in multiple sclerosis patients.

PubMed

Šabanagić-Hajrić, Selma; Alajbegović, Azra

2015-02-01

To evaluate the impacts of education level and employment status on health-related quality of life (HRQoL) in multiple sclerosis patients. This study included 100 multiple sclerosis patients treated at the Department of Neurology, Clinical Center of the University of Sarajevo. Inclusion criteria were the Expanded Disability Status Scale (EDSS) score between 1.0 and 6.5, age between 18 and 65 years, stable disease on enrollment. Quality of life (QoL) was evaluated by the Multiple Sclerosis Quality of Life-54 questionnaire (MSQoL-54). Mann-Whitney and Kruskal-Wallis test were used for comparisons. Linear regression analyses were performed to evaluate prediction value of educational level and employment status in predicting MSQOL-54 physical and mental composite scores. Full employment status had positive impact on physical health (54.85 vs. 37.90; p les than 0.001) and mental health (59.55 vs. 45.90; p les than 0.001) composite scores. Employment status retained its independent predictability for both physical (r(2)=0.105) and mental (r(2)=0.076) composite scores in linear regression analysis. Patients with college degree had slightly higher median value of physical (49.36 vs. 45.30) and mental health composite score (66.74 vs. 55.62) comparing to others, without statistically significant difference. Employment proved to be an important factor in predicting quality of life in multiple sclerosis patients. Higher education level may determine better QOL but without significant predictive value. Sustained employment and development of vocational rehabilitation programs for MS patients living in the country with high unemployment level is an important factor in improving both physical and mental health outcomes in MS patients.

[Breast feeding and systemic blood pressure in infants].

PubMed

Hernández-González, Martha A; Díaz-De-León, Luz V; Guízar-Mendoza, Juan M; Amador-Licona, Norma; Cipriano-González, Marisol; Díaz-Pérez, Raúl; Murillo-Ortiz, Blanca O; De-la-Roca-Chiapas, José María; Solorio-Meza, Sergio Eduardo

2012-01-01

Blood pressure levels in childhood influence these levels in adulthood, and breastfeeding has been considered such as a cardioprotective. We evaluated the association between blood pressure levels and feeding type in a group of infants. We conducted a comparative cross-sectional study in term infants with appropriate weight at birth, to compare blood pressure levels in those children with exclusively breastfeeding, mixed-feeding and formula feeding. The comparison of groups was performed using ANOVA and multiple regression analysis was used to identify variables associated with mean arterial blood pressure levels. A p value < 0.05 was considered significant. We included 20 men and 24 women per group. Infant Formula Feeding had higher current weight and weight gain compared with the other two groups (p < 0.05). Systolic, diastolic and mean blood pressure levels, as well as respiratory and heart rate were higher in the groups of exclusively formula feeding and mixed-feeding than in those with exclusively breastfeeding (p < 0.05). Multiple regression analysis identified that variables associated with mean blood pressure levels were current body mass index, weight gain and formula feeding. Infants in breastfeeding show lower blood pressure, BMI and weight gain.

Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

PubMed

Ng, Kar Yong; Awang, Norhashidah

2018-01-06

Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.

Birthweight Related Factors in Northwestern Iran: Using Quantile Regression Method.

PubMed

Fallah, Ramazan; Kazemnejad, Anoshirvan; Zayeri, Farid; Shoghli, Alireza

2015-11-18

Birthweight is one of the most important predicting indicators of the health status in adulthood. Having a balanced birthweight is one of the priorities of the health system in most of the industrial and developed countries. This indicator is used to assess the growth and health status of the infants. The aim of this study was to assess the birthweight of the neonates by using quantile regression in Zanjan province. This analytical descriptive study was carried out using pre-registered (March 2010 - March 2012) data of neonates in urban/rural health centers of Zanjan province using multiple-stage cluster sampling. Data were analyzed using multiple linear regressions andquantile regression method and SAS 9.2 statistical software. From 8456 newborn baby, 4146 (49%) were female. The mean age of the mothers was 27.1±5.4 years. The mean birthweight of the neonates was 3104 ± 431 grams. Five hundred and seventy-three patients (6.8%) of the neonates were less than 2500 grams. In all quantiles, gestational age of neonates (p<0.05), weight and educational level of the mothers (p<0.05) showed a linear significant relationship with the i of the neonates. However, sex and birth rank of the neonates, mothers age, place of residence (urban/rural) and career were not significant in all quantiles (p>0.05). This study revealed the results of multiple linear regression and quantile regression were not identical. We strictly recommend the use of quantile regression when an asymmetric response variable or data with outliers is available.

Birthweight Related Factors in Northwestern Iran: Using Quantile Regression Method

PubMed Central

Fallah, Ramazan; Kazemnejad, Anoshirvan; Zayeri, Farid; Shoghli, Alireza

2016-01-01

Introduction: Birthweight is one of the most important predicting indicators of the health status in adulthood. Having a balanced birthweight is one of the priorities of the health system in most of the industrial and developed countries. This indicator is used to assess the growth and health status of the infants. The aim of this study was to assess the birthweight of the neonates by using quantile regression in Zanjan province. Methods: This analytical descriptive study was carried out using pre-registered (March 2010 - March 2012) data of neonates in urban/rural health centers of Zanjan province using multiple-stage cluster sampling. Data were analyzed using multiple linear regressions andquantile regression method and SAS 9.2 statistical software. Results: From 8456 newborn baby, 4146 (49%) were female. The mean age of the mothers was 27.1±5.4 years. The mean birthweight of the neonates was 3104 ± 431 grams. Five hundred and seventy-three patients (6.8%) of the neonates were less than 2500 grams. In all quantiles, gestational age of neonates (p<0.05), weight and educational level of the mothers (p<0.05) showed a linear significant relationship with the i of the neonates. However, sex and birth rank of the neonates, mothers age, place of residence (urban/rural) and career were not significant in all quantiles (p>0.05). Conclusion: This study revealed the results of multiple linear regression and quantile regression were not identical. We strictly recommend the use of quantile regression when an asymmetric response variable or data with outliers is available. PMID:26925889

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.

Groundwater-level prediction using multiple linear regression and artificial neural network techniques: a comparative assessment

NASA Astrophysics Data System (ADS)

Sahoo, Sasmita; Jha, Madan K.

2013-12-01

The potential of multiple linear regression (MLR) and artificial neural network (ANN) techniques in predicting transient water levels over a groundwater basin were compared. MLR and ANN modeling was carried out at 17 sites in Japan, considering all significant inputs: rainfall, ambient temperature, river stage, 11 seasonal dummy variables, and influential lags of rainfall, ambient temperature, river stage and groundwater level. Seventeen site-specific ANN models were developed, using multi-layer feed-forward neural networks trained with Levenberg-Marquardt backpropagation algorithms. The performance of the models was evaluated using statistical and graphical indicators. Comparison of the goodness-of-fit statistics of the MLR models with those of the ANN models indicated that there is better agreement between the ANN-predicted groundwater levels and the observed groundwater levels at all the sites, compared to the MLR. This finding was supported by the graphical indicators and the residual analysis. Thus, it is concluded that the ANN technique is superior to the MLR technique in predicting spatio-temporal distribution of groundwater levels in a basin. However, considering the practical advantages of the MLR technique, it is recommended as an alternative and cost-effective groundwater modeling tool.

Mental ability and psychological work performance in Chinese workers.

PubMed

Zhong, Fei; Yano, Eiji; Lan, Yajia; Wang, Mianzhen; Wang, Zhiming; Wang, Xiaorong

2006-10-01

This study was to explore the relationship among mental ability, occupational stress, and psychological work performance in Chinese workers, and to identify relevant modifiers of mental ability and psychological work performance. Psychological Stress Intensity (PSI), psychological work performance, and mental ability (Mental Function Index, MFI) were determined among 485 Chinese workers (aged 33 to 62 yr, 65% of men) with varied work occupations. Occupational Stress Questionnaire (OSQ) and mental ability with 3 tests (including immediate memory, digit span, and cipher decoding) were used. The relationship between mental ability and psychological work performance was analyzed with multiple linear regression approach. PSI, MFI, or psychological work performance were significantly different among different work types and educational level groups (p<0.01). Multiple linear regression analysis showed that MFI was significantly related to gender, age, educational level, and work type. Higher MFI and lower PSI predicted a better psychological work performance, even after adjusted for gender, age, educational level, and work type. The study suggests that occupational stress and low mental ability are important predictors for poor psychological work performance, which is modified by both gender and educational level.

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

Serum levels of the immune activation marker neopterin change with age and gender and are modified by race, BMI, and percentage of body fat.

PubMed

Spencer, Monique E; Jain, Alka; Matteini, Amy; Beamer, Brock A; Wang, Nae-Yuh; Leng, Sean X; Punjabi, Naresh M; Walston, Jeremy D; Fedarko, Neal S

2010-08-01

Neopterin, a GTP metabolite expressed by macrophages, is a marker of immune activation. We hypothesize that levels of this serum marker alter with donor age, reflecting increased chronic immune activation in normal aging. In addition to age, we assessed gender, race, body mass index (BMI), and percentage of body fat (%fat) as potential covariates. Serum was obtained from 426 healthy participants whose age ranged from 18 to 87 years. Anthropometric measures included %fat and BMI. Neopterin concentrations were measured by competitive ELISA. The paired associations between neopterin and age, BMI, or %fat were analyzed by Spearman's correlation or by linear regression of log-transformed neopterin, whereas overall associations were modeled by multiple regression of log-transformed neopterin as a function of age, gender, race, BMI, %fat, and interaction terms. Across all participants, neopterin exhibited a positive association with age, BMI, and %fat. Multiple regression modeling of neopterin in women and men as a function of age, BMI, and race revealed that each covariate contributed significantly to neopterin values and that optimal modeling required an interaction term between race and BMI. The covariate %fat was highly correlated with BMI and could be substituted for BMI to yield similar regression coefficients. The association of age and gender with neopterin levels and their modification by race, BMI, or %fat reflect the biology underlying chronic immune activation and perhaps gender differences in disease incidence, morbidity, and mortality.

Characterizing individual differences in functional connectivity using dual-regression and seed-based approaches.

PubMed

Smith, David V; Utevsky, Amanda V; Bland, Amy R; Clement, Nathan; Clithero, John A; Harsch, Anne E W; McKell Carter, R; Huettel, Scott A

2014-07-15

A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two separate resting-state datasets comprising a total of 188 human participants. Both datasets were decomposed into resting-state networks (RSNs) using a probabilistic spatial independent component analysis (ICA). We estimated voxel-wise functional connectivity with these networks using a dual-regression analysis, which characterizes the participant-level spatiotemporal dynamics of each network while controlling for (via multiple regression) the influence of other networks and sources of variability. We found that males and females exhibit distinct patterns of connectivity with multiple RSNs, including both visual and auditory networks and the right frontal-parietal network. These results replicated across both datasets and were not explained by differences in head motion, data quality, brain volume, cortisol levels, or testosterone levels. Importantly, we also demonstrate that dual-regression functional connectivity is better at detecting inter-individual variability than traditional seed-based functional connectivity approaches. Our findings characterize robust-yet frequently ignored-neural differences between males and females, pointing to the necessity of controlling for sex in neuroscience studies of individual differences. Moreover, our results highlight the importance of employing network-based models to study variability in functional connectivity. Copyright © 2014 Elsevier Inc. All rights reserved.

High-level language ability in healthy individuals and its relationship with verbal working memory.

PubMed

Antonsson, Malin; Longoni, Francesca; Einald, Christina; Hallberg, Lina; Kurt, Gabriella; Larsson, Kajsa; Nilsson, Tina; Hartelius, Lena

2016-01-01

The aims of the study were to investigate healthy subjects' performance on a clinical test of high-level language (HLL) and how it is related to demographic characteristics and verbal working memory (VWM). One hundred healthy subjects (20-79 years old) were assessed with the Swedish BeSS test (Laakso, Brunnegård, Hartelius, & Ahlsén, 2000) and two digit span tasks. Relationships between the demographic variables, VWM and BeSS were investigated both with bivariate correlations and multiple regression analysis. The results present the norms for BeSS. The correlations and multiple regression analysis show that demographic variables had limited influence on test performance. Measures of VWM were moderately related to total BeSS score and weakly to moderately correlated with five of the seven subtests. To conclude, education has an influence on the test as a whole but measures of VWM stood out as the most robust predictor of HLL.

A structured sparse regression method for estimating isoform expression level from multi-sample RNA-seq data.

PubMed

Zhang, L; Liu, X J

2016-06-03

With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data. SSRSeq uses a non-parameter model to capture the general tendency of non-uniformity read distribution for all genes across multiple samples. Additionally, our method adds a structured sparse regularization, which not only incorporates the sparse specificity between a gene and its corresponding isoform expression levels, but also reduces the effects of noisy reads, especially for lowly expressed genes and isoforms. Four real datasets were used to evaluate our method on isoform expression estimation. Compared with other popular methods, SSRSeq reduced the variance between multiple samples, and produced more accurate isoform expression estimations, and thus more meaningful biological interpretations.

Modeling Joint Exposures and Health Outcomes for Cumulative Risk Assessment: The Case of Radon and Smoking

PubMed Central

Chahine, Teresa; Schultz, Bradley D.; Zartarian, Valerie G.; Xue, Jianping; Subramanian, SV; Levy, Jonathan I.

2011-01-01

Community-based cumulative risk assessment requires characterization of exposures to multiple chemical and non-chemical stressors, with consideration of how the non-chemical stressors may influence risks from chemical stressors. Residential radon provides an interesting case example, given its large attributable risk, effect modification due to smoking, and significant variability in radon concentrations and smoking patterns. In spite of this fact, no study to date has estimated geographic and sociodemographic patterns of both radon and smoking in a manner that would allow for inclusion of radon in community-based cumulative risk assessment. In this study, we apply multi-level regression models to explain variability in radon based on housing characteristics and geological variables, and construct a regression model predicting housing characteristics using U.S. Census data. Multi-level regression models of smoking based on predictors common to the housing model allow us to link the exposures. We estimate county-average lifetime lung cancer risks from radon ranging from 0.15 to 1.8 in 100, with high-risk clusters in areas and for subpopulations with high predicted radon and smoking rates. Our findings demonstrate the viability of screening-level assessment to characterize patterns of lung cancer risk from radon, with an approach that can be generalized to multiple chemical and non-chemical stressors. PMID:22016710

Catching Up: Effect of the Talent Development Ninth-Grade Instructional Interventions in Reading and Mathematics in High-Poverty High Schools

ERIC Educational Resources Information Center

Balfanz, Robert; Legters, Nettie; Jordan, Will

2004-01-01

Little is known about the feasibility and rapidity with which the academic learning of students who enter high school multiple years behind grade level can be accelerated. This study uses multiple regression analyses of standardized test and survey data from high-poverty high schools in two large urban districts to evaluate initial effects of the…

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.

Interquantile Shrinkage in Regression Models

PubMed Central

Jiang, Liewen; Wang, Huixia Judy; Bondell, Howard D.

2012-01-01

Conventional analysis using quantile regression typically focuses on fitting the regression model at different quantiles separately. However, in situations where the quantile coefficients share some common feature, joint modeling of multiple quantiles to accommodate the commonality often leads to more efficient estimation. One example of common features is that a predictor may have a constant effect over one region of quantile levels but varying effects in other regions. To automatically perform estimation and detection of the interquantile commonality, we develop two penalization methods. When the quantile slope coefficients indeed do not change across quantile levels, the proposed methods will shrink the slopes towards constant and thus improve the estimation efficiency. We establish the oracle properties of the two proposed penalization methods. Through numerical investigations, we demonstrate that the proposed methods lead to estimations with competitive or higher efficiency than the standard quantile regression estimation in finite samples. Supplemental materials for the article are available online. PMID:24363546

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

NASA Astrophysics Data System (ADS)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

Two studies on participation in decision-making and equity among FAA personnel.

DOT National Transportation Integrated Search

1991-07-01

Study 1 Moderated multiple regression analyses on data collected from 2,177 FAA air traffic controller specialists indicated that equity perceptions moderated the relationship between participation in decision-making and level of job satisfaction. Sp...

The Association of Free Testosterone Levels in Men and Lifestyle Factors and Chronic Disease Status: A North Texas Healthy Heart Study.

PubMed

Cardarelli, Roberto; Singh, Meharvan; Meyer, Jason; Balyakina, Elizabeth; Perez, Oscar; King, Michael

2014-07-01

Hypogonadism is highly prevalent in men older than 45 years and is associated with an increased risk of chronic diseases, including obesity, metabolic syndrome, diabetes, and cardiovascular disease. The objective of this study was to determine whether lifestyle factors such as smoking, diet, and exercise are associated with reduced testosterone levels. In this cross-sectional study, 147 men older than 44 years were recruited from a collaborative network of primary care clinics in the Dallas/Fort Worth, Texas, metropolitan area. Free testosterone levels were measured in plasma samples via an enzyme-linked immunosorbent assay-based method, and analyzed by simple and multiple linear regression in relationship to age, race/ethnicity, smoking, diet, exercise, obesity, diabetes, hypertension, and dyslipidemia. The participants had a mean free testosterone level of 3.1 ng/mL (standard deviation [SD] = 1.5) and mean age of 56.8 years (SD = 7.9). In simple regression analysis, free testosterone levels were associated with increased age (β = -0.04; P = .02), diet (β = -0.49; P = .05), diabetes (β = -0.9; P = .003), and hypertension (β = -0.55; P = .03) but not with race/ethnicity, smoking, exercise, obesity, or dyslipidemia. In multiple regression analysis, free testosterone values were significantly associated only with age (β = -0.05; P = .01) and diet (β = -0.72; P = .01). This study implicates diet, in addition to advanced age as a possible risk factor in the development of reduced testosterone levels. © The Author(s) 2014.

Using an innovative multiple regression procedure in a cancer population (Part 1): detecting and probing relationships of common interacting symptoms (pain, fatigue/weakness, sleep problems) as a strategy to discover influential symptom pairs and clusters

PubMed Central

Francoeur, Richard B

2015-01-01

Background The majority of patients with advanced cancer experience symptom pairs or clusters among pain, fatigue, and insomnia. Improved methods are needed to detect and interpret interactions among symptoms or diesease markers to reveal influential pairs or clusters. In prior work, I developed and validated sequential residual centering (SRC), a method that improves the sensitivity of multiple regression to detect interactions among predictors, by conditioning for multicollinearity (shared variation) among interactions and component predictors. Materials and methods Using a hypothetical three-way interaction among pain, fatigue, and sleep to predict depressive affect, I derive and explain SRC multiple regression. Subsequently, I estimate raw and SRC multiple regressions using real data for these symptoms from 268 palliative radiation outpatients. Results Unlike raw regression, SRC reveals that the three-way interaction (pain × fatigue/weakness × sleep problems) is statistically significant. In follow-up analyses, the relationship between pain and depressive affect is aggravated (magnified) within two partial ranges: 1) complete-to-some control over fatigue/weakness when there is complete control over sleep problems (ie, a subset of the pain–fatigue/weakness symptom pair), and 2) no control over fatigue/weakness when there is some-to-no control over sleep problems (ie, a subset of the pain–fatigue/weakness–sleep problems symptom cluster). Otherwise, the relationship weakens (buffering) as control over fatigue/weakness or sleep problems diminishes. Conclusion By reducing the standard error, SRC unmasks a three-way interaction comprising a symptom pair and cluster. Low-to-moderate levels of the moderator variable for fatigue/weakness magnify the relationship between pain and depressive affect. However, when the comoderator variable for sleep problems accompanies fatigue/weakness, only frequent or unrelenting levels of both symptoms magnify the relationship. These findings suggest that a countervailing mechanism involving depressive affect could account for the effectiveness of a cognitive behavioral intervention to reduce the severity of a pain, fatigue, and sleep disturbance cluster in a previous randomized trial. PMID:25565865

Using an innovative multiple regression procedure in a cancer population (Part 1): detecting and probing relationships of common interacting symptoms (pain, fatigue/weakness, sleep problems) as a strategy to discover influential symptom pairs and clusters.

PubMed

Francoeur, Richard B

2015-01-01

The majority of patients with advanced cancer experience symptom pairs or clusters among pain, fatigue, and insomnia. Improved methods are needed to detect and interpret interactions among symptoms or diesease markers to reveal influential pairs or clusters. In prior work, I developed and validated sequential residual centering (SRC), a method that improves the sensitivity of multiple regression to detect interactions among predictors, by conditioning for multicollinearity (shared variation) among interactions and component predictors. Using a hypothetical three-way interaction among pain, fatigue, and sleep to predict depressive affect, I derive and explain SRC multiple regression. Subsequently, I estimate raw and SRC multiple regressions using real data for these symptoms from 268 palliative radiation outpatients. Unlike raw regression, SRC reveals that the three-way interaction (pain × fatigue/weakness × sleep problems) is statistically significant. In follow-up analyses, the relationship between pain and depressive affect is aggravated (magnified) within two partial ranges: 1) complete-to-some control over fatigue/weakness when there is complete control over sleep problems (ie, a subset of the pain-fatigue/weakness symptom pair), and 2) no control over fatigue/weakness when there is some-to-no control over sleep problems (ie, a subset of the pain-fatigue/weakness-sleep problems symptom cluster). Otherwise, the relationship weakens (buffering) as control over fatigue/weakness or sleep problems diminishes. By reducing the standard error, SRC unmasks a three-way interaction comprising a symptom pair and cluster. Low-to-moderate levels of the moderator variable for fatigue/weakness magnify the relationship between pain and depressive affect. However, when the comoderator variable for sleep problems accompanies fatigue/weakness, only frequent or unrelenting levels of both symptoms magnify the relationship. These findings suggest that a countervailing mechanism involving depressive affect could account for the effectiveness of a cognitive behavioral intervention to reduce the severity of a pain, fatigue, and sleep disturbance cluster in a previous randomized trial.

The Effects of Social Capital Elements on Job Satisfaction and Motivation Levels of Teachers

ERIC Educational Resources Information Center

Boydak Özan, Mukadder; Yavuz Özdemir, Tuncay; Yaras, Zübeyde

2017-01-01

The purpose of this study is to examine the effects of social capital elements' on job satisfaction and motivation levels of teachers. The mixed method was used in the study. The quantitative data were analyzed through Correlation and Multiple Regression analyses. An interview form developed by the researchers was used for analyzing the…

Alpha-synuclein levels in patients with multiple system atrophy: a meta-analysis.

PubMed

Yang, Fei; Li, Wan-Jun; Huang, Xu-Sheng

2018-05-01

This study evaluates the relationship between multiple system atrophy and α-synuclein levels in the cerebrospinal fluid, plasma and neural tissue. Literature search for relevant research articles was undertaken in electronic databases and study selection was based on a priori eligibility criteria. Random-effects meta-analyses of standardized mean differences in α-synuclein levels between multiple system atrophy patients and normal controls were conducted to obtain the overall and subgroup effect sizes. Meta-regression analyses were performed to evaluate the effect of age, gender and disease severity on standardized mean differences. Data were obtained from 11 studies involving 378 multiple system atrophy patients and 637 healthy controls (age: multiple system atrophy patients 64.14 [95% confidence interval 62.05, 66.23] years; controls 64.16 [60.06, 68.25] years; disease duration: 44.41 [26.44, 62.38] months). Cerebrospinal fluid α-synuclein levels were significantly lower in multiple system atrophy patients than in controls but in plasma and neural tissue, α-synuclein levels were significantly higher in multiple system atrophy patients (standardized mean difference: -0.99 [-1.65, -0.32]; p = 0.001). Percentage of male multiple system atrophy patients was significantly positively associated with the standardized mean differences of cerebrospinal fluid α-synuclein levels (p = 0.029) whereas the percentage of healthy males was not associated with the standardized mean differences of cerebrospinal fluid α-synuclein levels (p = 0.920). In multiple system atrophy patients, α-synuclein levels were significantly lower in the cerebrospinal fluid and were positively associated with the male gender.

[Correlation of retinol binding protein 4 with 
metabolic indexes of glucose and 
lipid, bile cholesterol saturation index].

PubMed

Wang, Wen; Li, Nianfeng

2015-06-01

To measure retinol binding protein 4 (RBP4) levels in serum and bile and to analyze their relationship with insulin resistance, dyslipidemia or cholesterol saturation index (CSI).
 A total of 60 patients with gallstone were divided into a diabetes group (n=30) and a control group (n=30). The concentrations of RBP4 in serum and bile were detected by enzyme-linked immunosorbent assay (ELISA). Enzyme colorimetric method was used to measure the concentration of biliary cholesterol, bile acid and phospholipid. Biliary CSI was calculated by Carey table. Partial correlation and multiple linear regression analysis were used to evaluate the correlation between the RBP4 levels in serum or bile and the above indexes.
 The RBP4 concentrations in serum and bile in the diabetes group were significantly elevated compared with those in the control group (both P<0.01). There was no significant difference in the serum total bile acid (TBA), serum triglyceride (TG), serum high-density lipoprotein (HDL), bile TBA, bile total cholesterol (TC) , bile phospholipids and bile CSI between the 2 groups (all P>0.05); but the serum TC, low density lipoprotein (LDL), fasting blood glucose (FBG), fasting insulin (FINS), and homeostasis model assessment for insulin resistance (HOMA-IR) in the diabetes group were significantly increased compared to those in the control group (all P<0.05). The partial correlation analysis, which was adjusted by age, showed that the bile RBP4 was positively correlated with body mass index (BMI), waist circumference (WC), FINS, FBG, TC, LDL and HOMA-IR (r=0.283, 0.405, 0.685, 0.667, 0.553, 0.424 and 0.735, respectively), and the serum RBP4 was also positively correlated with the WC, FINS, FBG, TC, LDL and HOMA-IR (r=0.317, 0.734, 0.609, 0.528, 0.386 and 0.751, respectively). Stepwise multivariate linear regression analysis suggested that the HOMA-IR, BMI and WC were independently correlated with the level of bile RBP4 (multiple regression equation: Ybile RBP4=2.372XHOMA-IR+0.420XBMI+0.178XWC-26.813), and the serum RBP4 level was correlated with the HOMA-IR and WC independently (multiple regression equation: Yserum RBP4=2.832XHOMA-IR +0.235XWC-20.128). Multiple regression equations showed that HOMA-IR was the strongest correlation factor with RBP4.
 RBP4 concentrations in serum and bile in the diabetes group are significantly higher than those in the control group. HOMA-IR, BMI and WC are independently correlated with the level of bile RBP4. HOMA-IR and WC are independently correlated with the serum RBP4 level. HOMA-IR is the strongest correlation factor with RBP4. RBP4 might play an important role in the course of gallstone formation in Type 2 diabetes mellitus.

Ten years of helicopter emergency medical services in Germany: do we still need the helicopter rescue in multiple traumatised patients?

PubMed

Andruszkow, Hagen; Hildebrand, Frank; Lefering, Rolf; Pape, Hans-Christoph; Hoffmann, Reinhard; Schweigkofler, Uwe

2014-10-01

Helicopter emergency medical service (HEMS) has been established in the preclinical treatment of multiple traumatised patients despite an ongoing controversy towards the potential benefit. Celebrating the 20th anniversary of TraumaRegister DGU(®) of the German Trauma Society (DGU) the presented study intended to provide an overview of HEMS rescue in Germany over the last 10 years analysing the potential beneficial impact of a nationwide helicopter rescue in multiple traumatised patients. We analysed TraumaRegister DGU(®) including multiple traumatised patients (ISS ≥ 16) between 2002 and 2012. In-hospital mortality was defined as main outcome. An adjusted, multivariate regression with 13 confounders was performed to evaluate the potential survival benefit. 42,788 patients were included in the present study. 14,275 (33.4%) patients were rescued by HEMS and 28,513 (66.6%) by GEMS. Overall, 66.8% (n=28,569) patients were transported to a level I trauma centre and 28.2% (n=12,052) to a level II trauma centre. Patients rescued by HEMS sustained a higher injury severity compared to GEMS (ISS HEMS: 29.5 ± 12.6 vs. 27.5 ± 11.8). Helicopter rescue teams performed more on-scene interventions, and mission times were increased in HEMS rescue (HEMS: 77.2 ± 28.7 min. vs. GEMS: 60.9 ± 26.9 min.). Linear regression analysis revealed that the frequency of HEMS rescue has decreased significantly between 2002 and 2012. In case of transportation to level I trauma centres a decrease of 1.7% per year was noted (p<0.001) while a decline of 1.6% per year (p<0.001) was measured for level II trauma centre admissions. According to multivariate logistic regression HEMS was proven a positive independent survival predictor between 2002 and 2012 (OR 0.863; 95%-CI 0.800-0.930; Nagelkerkes-R(2) 0.539) with only little differences between each year. This study was able to prove an independent survival benefit of HEMS in multiple traumatised patients during the last 10 years. Despite this fact, a constant decline of HEMS rescue missions was found in multiple trauma patients due to unknown reasons. We concluded that HEMS should be used more often in case of trauma in order to guarantee the proven benefit for multiple traumatised patients. Copyright © 2014 Elsevier Ltd. All rights reserved.

The impact of attachment and depression symptoms on multiple risk behaviors in post-war adolescents in northern Uganda.

PubMed

Okello, J; Nakimuli-Mpungu, E; Klasen, F; Voss, C; Musisi, S; Broekaert, E; Derluyn, I

2015-07-15

We have previously shown that depression symptoms are associated with multiple risk behaviors and that parental attachments are protective against depression symptoms in post-war adolescents. Accumulating literature indicates that low levels of attachment may sensitize individuals to increased multiple risk behaviors when depression symptoms exist. This investigation examined the interactive effects of attachment and depression symptoms on multiple risk behavior. We conducted hierarchical logistic regression analyses to examine the impact of attachment and depression symptoms on multiple risk behavior in our post-war sample of 551 adolescents in Gulu district. Analyses revealed interactive effects for only maternal attachment-by-depression interaction. Interestingly, high levels of maternal attachment exacerbated the relationship between depression symptoms and multiple risk behaviors while low levels of maternal attachment attenuated this relationship. It is possible that this analysis could be biased by a common underlying factor that influences self-reporting and therefore is correlated with each of self-reported attachment security, depressive symptoms, and multiple risk behaviors. These findings suggest that maternal attachment serves as a protective factor at low levels while serving as an additional risk factor at high levels. Findings support and expand current knowledge about the roles that attachment and depression symptoms play in the development of multiple risk behaviors and suggest a more complex etiology for post-war adolescents. Copyright © 2015 Elsevier B.V. All rights reserved.

Age, Body Mass Index, and Frequency of Sexual Activity are Independent Predictors of Testosterone Deficiency in Men With Erectile Dysfunction.

PubMed

Pagano, Matthew J; De Fazio, Adam; Levy, Alison; RoyChoudhury, Arindam; Stahl, Peter J

2016-04-01

To identify clinical predictors of testosterone deficiency (TD) in men with erectile dysfunction (ED), thereby identifying subgroups that are most likely to benefit from targeted testosterone screening. Retrospective review was conducted on 498 men evaluated for ED between January 2013 and July 2014. Testing for TD by early morning serum measurement was offered to all eligible men. Patients with history of prostate cancer or testosterone replacement were excluded. Univariable linear regression was conducted to analyze 19 clinical variables for associations with serum total testosterone (TT), calculated free testosterone (cFT), and TD (T <300 ng/dL or cFT <6.5 ng/dL). Variables significant on univariable analysis were included in multiple regression models. A total of 225 men met inclusion criteria. Lower TT levels were associated with greater body mass index (BMI), less frequent sexual activity, and absence of clinical depression on multiple regression analysis. TT decreased by 49.5 ng/dL for each 5-point increase in BMI. BMI and age were the only independent predictors of cFT levels on multivariable analysis. Overall, 62 subjects (27.6%) met criteria for TD. Older age, greater BMI, and less frequent sexual activity were the only independent predictors of TD on multiple regression. We observed a 2.2-fold increase in the odds of TD for every 5-point increase in BMI, and a 1.8-fold increase for every 10 year increase in age. Men with ED and elevated BMI, advanced age, or infrequent sexual activity appear to be at high risk of TD, and such patients represent excellent potential candidates for targeted testosterone screening. Copyright © 2016 Elsevier Inc. All rights reserved.

Serum Folate Shows an Inverse Association with Blood Pressure in a Cohort of Chinese Women of Childbearing Age: A Cross-Sectional Study

PubMed Central

Shen, Minxue; Tan, Hongzhuan; Zhou, Shujin; Retnakaran, Ravi; Smith, Graeme N.; Davidge, Sandra T.; Trasler, Jacquetta; Walker, Mark C.; Wen, Shi Wu

2016-01-01

Background It has been reported that higher folate intake from food and supplementation is associated with decreased blood pressure (BP). The association between serum folate concentration and BP has been examined in few studies. We aim to examine the association between serum folate and BP levels in a cohort of young Chinese women. Methods We used the baseline data from a pre-conception cohort of women of childbearing age in Liuyang, China, for this study. Demographic data were collected by structured interview. Serum folate concentration was measured by immunoassay, and homocysteine, blood glucose, triglyceride and total cholesterol were measured through standardized clinical procedures. Multiple linear regression and principal component regression model were applied in the analysis. Results A total of 1,532 healthy normotensive non-pregnant women were included in the final analysis. The mean concentration of serum folate was 7.5 ± 5.4 nmol/L and 55% of the women presented with folate deficiency (< 6.8 nmol/L). Multiple linear regression and principal component regression showed that serum folate levels were inversely associated with systolic and diastolic BP, after adjusting for demographic, anthropometric, and biochemical factors. Conclusions Serum folate is inversely associated with BP in non-pregnant women of childbearing age with high prevalence of folate deficiency. PMID:27182603

[Associations between dormitory environment/other factors and sleep quality of medical students].

PubMed

Zheng, Bang; Wang, Kailu; Pan, Ziqi; Li, Man; Pan, Yuting; Liu, Ting; Xu, Dan; Lyu, Jun

2016-03-01

To investigate the sleep quality and related factors among medical students in China, understand the association between dormitory environment and sleep quality, and provide evidence and recommendations for sleep hygiene intervention. A total of 555 undergraduate students were selected from a medical school of an university in Beijing through stratified-cluster random-sampling to conduct a questionnaire survey by using Chinese version of Pittsburgh Sleep Quality Index (PSQI) and self-designed questionnaire. Analyses were performed by using multiple logistic regression model as well as multilevel linear regression model. The prevalence of sleep disorder was 29.1%(149/512), and 39.1%(200/512) of the students reported that the sleep quality was influenced by dormitory environment. PSQI score was negatively correlated with self-reported rating of dormitory environment (γs=-0.310, P<0.001). Logistic regression analysis showed the related factors of sleep disorder included grade, sleep regularity, self-rated health status, pressures of school work and employment, as well as dormitory environment. RESULTS of multilevel regression analysis also indicated that perception on dormitory environment (individual level) was associated with sleep quality with the dormitory level random effects under control (b=-0.619, P<0.001). The prevalence of sleep disorder was high in medical students, which was associated with multiple factors. Dormitory environment should be taken into consideration when the interventions are taken to improve the sleep quality of students.

Female married illiteracy as the most important continual determinant of total fertility rate among districts of Empowered Action Group States of India: Evidence from Annual Health Survey 2011-12.

PubMed

Kumar, Rajesh; Dogra, Vishal; Rani, Khushbu; Sahu, Kanti

2017-01-01

District level determinants of total fertility rate in Empowered Action Group states of India can help in ongoing population stabilization programs in India. Present study intends to assess the role of district level determinants in predicting total fertility rate among districts of the Empowered Action Group states of India. Data from Annual Health Survey (2011-12) was analysed using STATA and R software packages. Multiple linear regression models were built and evaluated using Akaike Information Criterion. For further understanding, recursive partitioning was used to prepare a regression tree. Female married illiteracy positively associated with total fertility rate and explained more than half (53%) of variance. Under multiple linear regression model, married illiteracy, infant mortality rate, Ante natal care registration, household size, median age of live birth and sex ratio explained 70% of total variance in total fertility rate. In regression tree, female married illiteracy was the root node and splits at 42% determined TFR <= 2.7. The next left side branch was again married illiteracy with splits at 23% to determine TFR <= 2.1. We conclude that female married illiteracy is one of the most important determinants explaining total fertility rate among the districts of an Empowered Action Group states. Focus on female literacy is required to stabilize the population growth in long run.

Testing a single regression coefficient in high dimensional linear models

PubMed Central

Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2017-01-01

In linear regression models with high dimensional data, the classical z-test (or t-test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z-test to assess the significance of each covariate. Based on the p-value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively. PMID:28663668

Testing a single regression coefficient in high dimensional linear models.

PubMed

Lan, Wei; Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2016-11-01

In linear regression models with high dimensional data, the classical z -test (or t -test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z -test to assess the significance of each covariate. Based on the p -value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively.

[Prevalence of vitamin D deficiency and associated factors in women and newborns in the immediate postpartum period].

PubMed

do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado Junior, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2015-01-01

To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. 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%. From 226 women included, 200 (88.5%) were 20 to 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. 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. Copyright © 2015 Sociedade de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.

Comparing methods of analysing datasets with small clusters: case studies using four paediatric datasets.

PubMed

Marston, Louise; Peacock, Janet L; Yu, Keming; Brocklehurst, Peter; Calvert, Sandra A; Greenough, Anne; Marlow, Neil

2009-07-01

Studies of prematurely born infants contain a relatively large percentage of multiple births, so the resulting data have a hierarchical structure with small clusters of size 1, 2 or 3. Ignoring the clustering may lead to incorrect inferences. The aim of this study was to compare statistical methods which can be used to analyse such data: generalised estimating equations, multilevel models, multiple linear regression and logistic regression. Four datasets which differed in total size and in percentage of multiple births (n = 254, multiple 18%; n = 176, multiple 9%; n = 10 098, multiple 3%; n = 1585, multiple 8%) were analysed. With the continuous outcome, two-level models produced similar results in the larger dataset, while generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) produced divergent estimates using the smaller dataset. For the dichotomous outcome, most methods, except generalised least squares multilevel modelling (ML GH 'xtlogit' in Stata) gave similar odds ratios and 95% confidence intervals within datasets. For the continuous outcome, our results suggest using multilevel modelling. We conclude that generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) should be used with caution when the dataset is small. Where the outcome is dichotomous and there is a relatively large percentage of non-independent data, it is recommended that these are accounted for in analyses using logistic regression with adjusted standard errors or multilevel modelling. If, however, the dataset has a small percentage of clusters greater than size 1 (e.g. a population dataset of children where there are few multiples) there appears to be less need to adjust for clustering.

Exposure to Pre- and Perinatal Risk Factors Partially Explains Mean Differences in Self-Regulation between Races.

PubMed

Barnes, J C; Boutwell, Brian B; Miller, J Mitchell; DeShay, Rashaan A; Beaver, Kevin M; White, Norman

2016-01-01

To examine whether differential exposure to pre- and perinatal risk factors explained differences in levels of self-regulation between children of different races (White, Black, Hispanic, Asian, and Other). Multiple regression models based on data from the Early Childhood Longitudinal Study, Birth Cohort (n ≈ 9,850) were used to analyze the impact of pre- and perinatal risk factors on the development of self-regulation at age 2 years. Racial differences in levels of self-regulation were observed. Racial differences were also observed for 9 of the 12 pre-/perinatal risk factors. Multiple regression analyses revealed that a portion of the racial differences in self-regulation was explained by differential exposure to several of the pre-/perinatal risk factors. Specifically, maternal age at childbirth, gestational timing, and the family's socioeconomic status were significantly related to the child's level of self-regulation. These factors accounted for a statistically significant portion of the racial differences observed in self-regulation. The findings indicate racial differences in self-regulation may be, at least partially, explained by racial differences in exposure to pre- and perinatal risk factors.

Vitamin D levels and their associations with survival and major disease outcomes in a large cohort of patients with chronic graft-vs-host disease

PubMed Central

Katić, Mašenjka; Pirsl, Filip; Steinberg, Seth M.; Dobbin, Marnie; Curtis, Lauren M.; Pulanić, Dražen; Desnica, Lana; Titarenko, Irina; Pavletic, Steven Z.

2016-01-01

Aim To identify the factors associated with vitamin D status in patients with chronic graft-vs-host disease (cGVHD) and evaluate the association between serum vitamin D (25(OH)D) levels and cGVHD characteristics and clinical outcomes defined by the National Institutes of Health (NIH) criteria. Methods 310 cGVHD patients enrolled in the NIH cGVHD natural history study (clinicaltrials.gov: NCT00092235) were analyzed. Univariate analysis and multiple logistic regression were used to determine the associations between various parameters and 25(OH)D levels, dichotomized into categorical variables: ≤20 and >20 ng/mL, and as a continuous parameter. Multiple logistic regression was used to develop a predictive model for low vitamin D. Survival analysis and association between cGVHD outcomes and 25(OH)D as a continuous as well as categorical variable: ≤20 and >20 ng/mL; <50 and ≥50 ng/mL, and among three ordered categories: ≤20, 20-50, and ≥50 ng/mL, was performed. PMID:27374829

Ca analysis: An Excel based program for the analysis of intracellular calcium transients including multiple, simultaneous regression analysis☆

PubMed Central

Greensmith, David J.

2014-01-01

Here I present an Excel based program for the analysis of intracellular Ca transients recorded using fluorescent indicators. The program can perform all the necessary steps which convert recorded raw voltage changes into meaningful physiological information. The program performs two fundamental processes. (1) It can prepare the raw signal by several methods. (2) It can then be used to analyze the prepared data to provide information such as absolute intracellular Ca levels. Also, the rates of change of Ca can be measured using multiple, simultaneous regression analysis. I demonstrate that this program performs equally well as commercially available software, but has numerous advantages, namely creating a simplified, self-contained analysis workflow. PMID:24125908

Wage differentials among Appalachian sawmills

Treesearch

Charles H. Wolf

1977-01-01

Wage differences among Appalachian sawmills were investigated, using multiple-regression analysis. Wages and fringe benefits were found to vary with type of product sawed, education of the work force, distance to urban areas, general wage levels, and use of collective-bargaining agreements between management and labor.

Empirical Modeling of Microbial Indicators at a South Carolina Beach

EPA Science Inventory

Public concerns about water quality at beaches have prompted the development of multiple linear regression and other models that can be used to "nowcast" levels of bacterial indicators. Hydrometeorological and biogeochemical data from summer, 2009 were used to develop empirical m...

An Exploratory Study of Religion and Trust in Ghana

ERIC Educational Resources Information Center

Addai, Isaac; Opoku-Agyeman, Chris; Ghartey, Helen Tekyiwa

2013-01-01

Based on individual-level data from 2008 Afro-barometer survey, this study explores the relationship between religion (religious affiliation and religious importance) and trust (interpersonal and institutional) among Ghanaians. Employing hierarchical multiple regression technique, our analyses reveal a positive relationship between religious…

Mathematics Readiness of First-Year University Students

ERIC Educational Resources Information Center

Atuahene, Francis; Russell, Tammy A.

2016-01-01

The majority of high school students, particularly underrepresented minorities (URMs) from low socioeconomic backgrounds are graduating from high school less prepared academically for advanced-level college mathematics. Using 2009 and 2010 course enrollment data, several statistical analyses (multiple linear regression, Cochran Mantel Haenszel…

Perceived Parenting Styles on College Students' Optimism

ERIC Educational Resources Information Center

Baldwin, Debora R.; McIntyre, Anne; Hardaway, Elizabeth

2007-01-01

The purpose of this study was to examine the relationship between perceived parenting styles and levels of optimism in undergraduate college students. Sixty-three participants were administered surveys measuring dispositional optimism and perceived parental Authoritative and Authoritarian styles. Multiple regression analysis revealed that both…

Multiple Correlation versus Multiple Regression.

ERIC Educational Resources Information Center

Huberty, Carl J.

2003-01-01

Describes differences between multiple correlation analysis (MCA) and multiple regression analysis (MRA), showing how these approaches involve different research questions and study designs, different inferential approaches, different analysis strategies, and different reported information. (SLD)

Factors Associated with Level of Living in Washington County, Mississippi. Technical Bulletin No. 1501.

ERIC Educational Resources Information Center

McCoy, John L.

Step-wise multiple regression and typological analysis were used to analyze the extent to which selected factors influence vertical mobility and achieved level of living. A sample of 418 male household heads who were 18 to 45 years old in Washington County, Mississippi were interviewed during 1971. A prescreening using census and local housing…

Academic Procrastination and the Performance of Graduate-Level Cooperative Groups in Research Methods Courses

ERIC Educational Resources Information Center

Jiao, Qun G.; DaRos-Voseles, Denise A.; Collins, Kathleen M. T.; Onwuegbuzie, Anthony J.

2011-01-01

This study examined the extent to which academic procrastination predicted the performance of cooperative groups in graduate-level research methods courses. A total of 28 groups was examined (n = 83 students), ranging in size from 2 to 5 (M = 2.96, SD = 1.10). Multiple regression analyses revealed that neither within-group mean nor within-group…

The Detection and Interpretation of Interaction Effects between Continuous Variables in Multiple Regression.

ERIC Educational Resources Information Center

Jaccard, James; And Others

1990-01-01

Issues in the detection and interpretation of interaction effects between quantitative variables in multiple regression analysis are discussed. Recent discussions associated with problems of multicollinearity are reviewed in the context of the conditional nature of multiple regression with product terms. (TJH)

Estimating Time to Event From Longitudinal Categorical Data: An Analysis of Multiple Sclerosis Progression.

PubMed

Mandel, Micha; Gauthier, Susan A; Guttmann, Charles R G; Weiner, Howard L; Betensky, Rebecca A

2007-12-01

The expanded disability status scale (EDSS) is an ordinal score that measures progression in multiple sclerosis (MS). Progression is defined as reaching EDSS of a certain level (absolute progression) or increasing of one point of EDSS (relative progression). Survival methods for time to progression are not adequate for such data since they do not exploit the EDSS level at the end of follow-up. Instead, we suggest a Markov transitional model applicable for repeated categorical or ordinal data. This approach enables derivation of covariate-specific survival curves, obtained after estimation of the regression coefficients and manipulations of the resulting transition matrix. Large sample theory and resampling methods are employed to derive pointwise confidence intervals, which perform well in simulation. Methods for generating survival curves for time to EDSS of a certain level, time to increase of EDSS of at least one point, and time to two consecutive visits with EDSS greater than three are described explicitly. The regression models described are easily implemented using standard software packages. Survival curves are obtained from the regression results using packages that support simple matrix calculation. We present and demonstrate our method on data collected at the Partners MS center in Boston, MA. We apply our approach to progression defined by time to two consecutive visits with EDSS greater than three, and calculate crude (without covariates) and covariate-specific curves.

Associations of blood lead, cadmium, and mercury with estimated glomerular filtration rate in the Korean general population: Analysis of 2008-2010 Korean National Health and Nutrition Examination Survey data

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

Kim, Yangho; Lee, Byung-Kook, E-mail: bklee@sch.ac.kr

Introduction: The objective of this study was to evaluate associations between blood lead, cadmium, and mercury levels with estimated glomerular filtration rate in a general population of South Korean adults. Methods: This was a cross-sectional study based on data obtained in the Korean National Health and Nutrition Examination Survey (KNHANES) (2008-2010). The final analytical sample consisted of 5924 participants. Estimated glomerular filtration rate (eGFR) was calculated using the MDRD Study equation as an indicator of glomerular function. Results: In multiple linear regression analysis of log2-transformed blood lead as a continuous variable on eGFR, after adjusting for covariates including cadmium andmore » mercury, the difference in eGFR levels associated with doubling of blood lead were -2.624 mL/min per 1.73 m Superscript-Two (95% CI: -3.803 to -1.445). In multiple linear regression analysis using quartiles of blood lead as the independent variable, the difference in eGFR levels comparing participants in the highest versus the lowest quartiles of blood lead was -3.835 mL/min per 1.73 m Superscript-Two (95% CI: -5.730 to -1.939). In a multiple linear regression analysis using blood cadmium and mercury, as continuous or categorical variables, as independent variables, neither metal was a significant predictor of eGFR. Odds ratios (ORs) and 95% CI values for reduced eGFR calculated for log2-transformed blood metals and quartiles of the three metals showed similar trends after adjustment for covariates. Discussion: In this large, representative sample of South Korean adults, elevated blood lead level was consistently associated with lower eGFR levels and with the prevalence of reduced eGFR even in blood lead levels below 10 {mu}g/dL. In conclusion, elevated blood lead level was associated with lower eGFR in a Korean general population, supporting the role of lead as a risk factor for chronic kidney disease.« less

Deaf college students' mathematical skills relative to morphological knowledge, reading level, and language proficiency.

PubMed

Kelly, Ronald R; Gaustad, Martha G

2007-01-01

This study of deaf college students examined specific relationships between their mathematics performance and their assessed skills in reading, language, and English morphology. Simple regression analyses showed that deaf college students' language proficiency scores, reading grade level, and morphological knowledge regarding word segmentation and meaning were all significantly correlated with both the ACT Mathematics Subtest and National Technical Institute for the Deaf (NTID) Mathematics Placement Test scores. Multiple regression analyses identified the best combination from among these potential independent predictors of students' performance on both the ACT and NTID mathematics tests. Additionally, the participating deaf students' grades in their college mathematics courses were significantly and positively associated with their reading grade level and their knowledge of morphological components of words.

Retention in Differentiated Care: Multiple Measures Analysis for a Decentralized HIV Care and Treatment Program in North Central Nigeria

PubMed Central

Agaba, Patricia A; Genberg, Becky L; Sagay, Atiene S; Agbaji, Oche O; Meloni, Seema T; Dadem, Nancin Y; Kolawole, Grace O; Okonkwo, Prosper; Kanki, Phyllis J; Ware, Norma C

2018-01-01

Objective Differentiated care refers collectively to flexible service models designed to meet the differing needs of HIV-infected persons in resource-scarce settings. Decentralization is one such service model. Retention is a key indicator for monitoring the success of HIV treatment and care programs. We used multiple measures to compare retention in a cohort of patients receiving HIV care at “hub” (central) and “spoke” (decentralized) sites in a large public HIV treatment program in north central Nigeria. Methods This retrospective cohort study utilized longitudinal program data representing central and decentralized levels of care in the Plateau State Decentralization Initiative, north central Nigeria. We examined retention with patient- level (retention at fixed times, loss-to-follow-up [LTFU]) and visit-level (gaps-in-care, visit constancy) measures. Regression models with generalized estimating equations (GEE) were used to estimate the effect of decentralization on visit-level measures. Patient-level measures were examined using survival methods with Cox regression models, controlling for baseline variables. Results Of 15,650 patients, 43% were enrolled at the hub. Median time in care was 3.1 years. Hub patients were less likely to be LTFU (adjusted hazard ratio (AHR)=0.91, 95% CI: 0.85-0.97), compared to spoke patients. Visit constancy was lower at the hub (−4.5%, 95% CI: −3.5, −5.5), where gaps in care were also more likely to occur (adjusted odds ratio=1.95, 95% CI: 1.83-2.08). Conclusion Decentralized sites demonstrated better retention outcomes using visit-level measures, while the hub achieved better retention outcomes using patient-level measures. Retention estimates produced by incorporating multiple measures showed substantial variation, confirming the influence of measurement strategies on the results of retention research. Future studies of retention in HIV care in sub-Saharan Africa will be well-served by including multiple measures. PMID:29682399

Retention in Differentiated Care: Multiple Measures Analysis for a Decentralized HIV Care and Treatment Program in North Central Nigeria.

PubMed

Agaba, Patricia A; Genberg, Becky L; Sagay, Atiene S; Agbaji, Oche O; Meloni, Seema T; Dadem, Nancin Y; Kolawole, Grace O; Okonkwo, Prosper; Kanki, Phyllis J; Ware, Norma C

2018-01-01

Differentiated care refers collectively to flexible service models designed to meet the differing needs of HIV-infected persons in resource-scarce settings. Decentralization is one such service model. Retention is a key indicator for monitoring the success of HIV treatment and care programs. We used multiple measures to compare retention in a cohort of patients receiving HIV care at "hub" (central) and "spoke" (decentralized) sites in a large public HIV treatment program in north central Nigeria. This retrospective cohort study utilized longitudinal program data representing central and decentralized levels of care in the Plateau State Decentralization Initiative, north central Nigeria. We examined retention with patient- level (retention at fixed times, loss-to-follow-up [LTFU]) and visit-level (gaps-in-care, visit constancy) measures. Regression models with generalized estimating equations (GEE) were used to estimate the effect of decentralization on visit-level measures. Patient-level measures were examined using survival methods with Cox regression models, controlling for baseline variables. Of 15,650 patients, 43% were enrolled at the hub. Median time in care was 3.1 years. Hub patients were less likely to be LTFU (adjusted hazard ratio (AHR)=0.91, 95% CI: 0.85-0.97), compared to spoke patients. Visit constancy was lower at the hub (-4.5%, 95% CI: -3.5, -5.5), where gaps in care were also more likely to occur (adjusted odds ratio=1.95, 95% CI: 1.83-2.08). Decentralized sites demonstrated better retention outcomes using visit-level measures, while the hub achieved better retention outcomes using patient-level measures. Retention estimates produced by incorporating multiple measures showed substantial variation, confirming the influence of measurement strategies on the results of retention research. Future studies of retention in HIV care in sub-Saharan Africa will be well-served by including multiple measures.

Beyond Multiple Regression: Using Commonality Analysis to Better Understand R[superscript 2] Results

ERIC Educational Resources Information Center

Warne, Russell T.

2011-01-01

Multiple regression is one of the most common statistical methods used in quantitative educational research. Despite the versatility and easy interpretability of multiple regression, it has some shortcomings in the detection of suppressor variables and for somewhat arbitrarily assigning values to the structure coefficients of correlated…

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Parts-Per-Billion Mass Measurement Accuracy Achieved through the Combination of Multiple Linear Regression and Automatic Gain Control in a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer

PubMed Central

Williams, D. Keith; Muddiman, David C.

2008-01-01

Fourier transform ion cyclotron resonance mass spectrometry has the ability to achieve unprecedented mass measurement accuracy (MMA); MMA is one of the most significant attributes of mass spectrometric measurements as it affords extraordinary molecular specificity. However, due to space-charge effects, the achievable MMA significantly depends on the total number of ions trapped in the ICR cell for a particular measurement. Even through the use of automatic gain control (AGC), the total ion population is not constant between spectra. Multiple linear regression calibration in conjunction with AGC is utilized in these experiments to formally account for the differences in total ion population in the ICR cell between the external calibration spectra and experimental spectra. This ability allows for the extension of dynamic range of the instrument while allowing mean MMA values to remain less than 1 ppm. In addition, multiple linear regression calibration is used to account for both differences in total ion population in the ICR cell as well as relative ion abundance of a given species, which also affords mean MMA values at the parts-per-billion level. PMID:17539605

The effects of sleep quality, physical activity, and environmental quality on the risk of falls in dementia.

PubMed

Eshkoor, Sima Ataollahi; Hamid, Tengku Aizan; Nudin, Siti Sa'adiah Hassan; Mun, Chan Yoke

2013-06-01

This study aimed to identify the effects of sleep quality, physical activity, environmental quality, age, ethnicity, sex differences, marital status, and educational level on the risk of falls in the elderly individuals with dementia. Data were derived from a group of 1210 Malaysian elderly individuals who were noninstitutionalized and demented. The multiple logistic regression model was applied to estimate the risk of falls in respondents. Approximately the prevalence of falls was 17% among the individuals. The results of multiple logistic regression analysis revealed that age (odds ratio [OR] = 1.03), ethnicity (OR = 1.76), sleep quality (OR = 1.46), and environmental quality (OR = 0.62) significantly affected the risk of falls in individuals (P < .05). Furthermore, sex differences, marital status, educational level, and physical activity were not significant predictors of falls in samples (P > .05). It was found that age, ethnic non-Malay, and sleep disruption increased the risk of falls in respondents, but high environmental quality reduced the risk of falls.

Reactive oxygen metabolites (ROMs) are associated with cardiovascular disease in chronic hemodialysis patients.

PubMed

Bossola, Maurizio; Vulpio, Carlo; Colacicco, Luigi; Scribano, Donata; Zuppi, Cecilia; Tazza, Luigi

2012-02-11

The aim of our study was to measure reactive oxygen metabolites (ROMs) in chronic hemodialysis (HD) patients and evaluate the possible association with cardiovascular disease (CVD) and mortality. We measured ROMs in 76 HD patients and correlated with CVD, cardiovascular (CV) events in the follow-up and all-cause and CVD-related mortality. The levels of ROMs presented a median value of 270 (238.2-303.2) CARR U (interquartile range). We created a ROC curve (ROMs levels vs. CVD) and we identified a cut-off point of 273 CARR U. Patients with ROMs levels ≥273 CARR U were significantly older, had higher C-reactive protein levels and lower creatinine concentrations. The prevalence of CVD was higher in patients with ROMs levels ≥273 (87.1%) than in those with ROMs levels <273 CARR U (17.7%; p<0.0001). ROMs levels were significantly higher in patients with CVD (317±63.8) than in those without (242.7±49.1; p<0.0001). At multiple regression analysis, age, creatinine and C-reactive protein were independent factors associated with ROMs. At multiple logistic regression analysis the association between ROMs and CVD was independent (OR: 1.02, 95% CI: 1.00-1.05; p=0.03). Twenty six patients developed cardiovascular (CV) events during the follow-up. Of these, seven were in the group with ROMs levels <273 CARR U and 19 in the group with ROMs levels ≥273 CARR U. The logistic regression analysis showed that both age (OR: 1.06, 95% CI: 1.01-1.12; p=0.013) and ROMs levels (OR: 1.10, 95% CI: 1.00-1.02; p=0.045) were independently associated with CV events in the follow-up. ROMs are independently associated with CVD and predict CV events in chronic HD patients.

Oral health literacy and information sources among adults in Tehran, Iran.

PubMed

Sistani, M M Naghibi; Yazdani, R; Virtanen, J; Pakdaman, A; Murtomaa, H

2013-09-01

To assess oral health literacy level and oral health information of Iranian adults in Tehran, and to determine the factors related to oral health literacy. A cross-sectional population study. A random sample of 1,031 adults in Tehran, Iran. Oral health literacy was measured using an oral health adult literacy questionnaire (OHL-AQ). Variation in use of information sources by socio-economic and demographic background was estimated by odds ratios. A multiple linear regression model served to determine predictor factors of OHL-AQ scores controlling for characteristics of the subjects and number of information sources. The mean OHL-AQ score was 10.5 (sd 3.0). Women (p < 0.001), younger (p < 0.001), and better educated participants (p < 0.001) had higher OHL-AQ scores. The most common sources of oral health information were dentists (52.6%), and TV/Radio (49.5%). According to the regression model, females (p = 0.001), high educational level (p < 0.001), and use of multiple information sources (two sources p = 0.01, three sources or more p = 0.002) were the main predictor factors of OHL-AQ scores. The average oral health literacy level of Iranian adults was low. Disseminating evidence-based oral health care information from multiple sources including TV/radio, dentists, and other health professionals in different settings should improve public oral health literacy.

MERGANSER- Predicting Mercury Levels in Fish and Loons in New England Lakes

EPA Science Inventory

MERGANSER (MERcury Geo-spatial AssesmentS for the New England Region) is an empirical least squares multiple regression model using atmospheric deposition of mercury (Hg) and readily obtainable lake and watershed features to predict fish and common loon Hg (as methyl mercury) in ...

Mindfulness-Based Awareness and Compassion: Predictors of Counselor Empathy and Anxiety

ERIC Educational Resources Information Center

Fulton, Cheryl L.; Cashwell, Craig S.

2015-01-01

Mindfulness-based awareness and compassion were examined as predictors of empathy and anxiety among 152 master's-level counseling interns. Results of hierarchical multiple regression analysis supported that awareness and compassion differentially contributed to explaining the variance in counselor empathy and anxiety. Implications for counselor…

Using Multilevel Modeling in Language Assessment Research: A Conceptual Introduction

ERIC Educational Resources Information Center

Barkaoui, Khaled

2013-01-01

This article critiques traditional single-level statistical approaches (e.g., multiple regression analysis) to examining relationships between language test scores and variables in the assessment setting. It highlights the conceptual, methodological, and statistical problems associated with these techniques in dealing with multilevel or nested…

[Factors of psychiatric treatment satisfaction in inpatients with neurotic and depressive disorders].

PubMed

Tsygankov, B D; Malygin, Ya V; Gatin, F F

2015-01-01

Factors of patients' satisfaction with medical care vary depending on the level of care and medical specialty. Patient's satisfaction with psychiatric care is understudied. An aim of the present study is to find out the factors of satisfaction with psychiatric care in inpatients with neurotic and depressive disorders. The sample included 356 inpatients suffering from neurotic or depressive disorders. The patients were questioned using PAPI questionnaire designed for this study. Statistical analysis was performed using multiple regression. Key factors of satisfaction with medical care included quality of work of nurses and psychiatrists, hospital ward comfort, the number and quality of psychotherapeutic sessions, psychiatrists' empathy and aptitude to provide the patient with information about the disease and treatment. Multiple regression equation explained 81% of the variance of patients' satisfaction.

Ca analysis: an Excel based program for the analysis of intracellular calcium transients including multiple, simultaneous regression analysis.

PubMed

Greensmith, David J

2014-01-01

Here I present an Excel based program for the analysis of intracellular Ca transients recorded using fluorescent indicators. The program can perform all the necessary steps which convert recorded raw voltage changes into meaningful physiological information. The program performs two fundamental processes. (1) It can prepare the raw signal by several methods. (2) It can then be used to analyze the prepared data to provide information such as absolute intracellular Ca levels. Also, the rates of change of Ca can be measured using multiple, simultaneous regression analysis. I demonstrate that this program performs equally well as commercially available software, but has numerous advantages, namely creating a simplified, self-contained analysis workflow. Copyright © 2013 The Author. Published by Elsevier Ireland Ltd.. All rights reserved.

False Positives in Multiple Regression: Unanticipated Consequences of Measurement Error in the Predictor Variables

ERIC Educational Resources Information Center

Shear, Benjamin R.; Zumbo, Bruno D.

2013-01-01

Type I error rates in multiple regression, and hence the chance for false positive research findings, can be drastically inflated when multiple regression models are used to analyze data that contain random measurement error. This article shows the potential for inflated Type I error rates in commonly encountered scenarios and provides new…

Using Robust Standard Errors to Combine Multiple Regression Estimates with Meta-Analysis

ERIC Educational Resources Information Center

Williams, Ryan T.

2012-01-01

Combining multiple regression estimates with meta-analysis has continued to be a difficult task. A variety of methods have been proposed and used to combine multiple regression slope estimates with meta-analysis, however, most of these methods have serious methodological and practical limitations. The purpose of this study was to explore the use…

Use of Multiple Regression and Use-Availability Analyses in Determining Habitat Selection by Gray Squirrels (Sciurus Carolinensis)

Treesearch

John W. Edwards; Susan C. Loeb; David C. Guynn

1994-01-01

Multiple regression and use-availability analyses are two methods for examining habitat selection. Use-availability analysis is commonly used to evaluate macrohabitat selection whereas multiple regression analysis can be used to determine microhabitat selection. We compared these techniques using behavioral observations (n = 5534) and telemetry locations (n = 2089) of...

The isoform A of reticulon-4 (Nogo-A) in cerebrospinal fluid of primary brain tumor patients: influencing factors.

PubMed

Koper, Olga Martyna; Kamińska, Joanna; Milewska, Anna; Sawicki, Karol; Mariak, Zenon; Kemona, Halina; Matowicka-Karna, Joanna

2018-05-18

The influence of isoform A of reticulon-4 (Nogo-A), also known as neurite outgrowth inhibitor, on primary brain tumor development was reported. Therefore the aim was the evaluation of Nogo-A concentrations in cerebrospinal fluid (CSF) and serum of brain tumor patients compared with non-tumoral individuals. All serum results, except for two cases, obtained both in brain tumors and non-tumoral individuals, were below the lower limit of ELISA detection. Cerebrospinal fluid Nogo-A concentrations were significantly lower in primary brain tumor patients compared to non-tumoral individuals. The univariate linear regression analysis found that if white blood cell count increases by 1 × 10 3 /μL, the mean cerebrospinal fluid Nogo-A concentration value decreases 1.12 times. In the model of multiple linear regression analysis predictor variables influencing cerebrospinal fluid Nogo-A concentrations included: diagnosis, sex, and sodium level. The mean cerebrospinal fluid Nogo-A concentration value was 1.9 times higher for women in comparison to men. In the astrocytic brain tumor group higher sodium level occurs with lower cerebrospinal fluid Nogo-A concentrations. We found the opposite situation in non-tumoral individuals. Univariate linear regression analysis revealed, that cerebrospinal fluid Nogo-A concentrations change in relation to white blood cell count. In the created model of multiple linear regression analysis we found, that within predictor variables influencing CSF Nogo-A concentrations were diagnosis, sex, and sodium level. Results may be relevant to the search for cerebrospinal fluid biomarkers and potential therapeutic targets in primary brain tumor patients. Nogo-A concentrations were tested by means of enzyme-linked immunosorbent assay (ELISA).

Female married illiteracy as the most important continual determinant of total fertility rate among districts of Empowered Action Group States of India: Evidence from Annual Health Survey 2011–12

PubMed Central

Kumar, Rajesh; Dogra, Vishal; Rani, Khushbu; Sahu, Kanti

2017-01-01

Background: District level determinants of total fertility rate in Empowered Action Group states of India can help in ongoing population stabilization programs in India. Objective: Present study intends to assess the role of district level determinants in predicting total fertility rate among districts of the Empowered Action Group states of India. Material and Methods: Data from Annual Health Survey (2011-12) was analysed using STATA and R software packages. Multiple linear regression models were built and evaluated using Akaike Information Criterion. For further understanding, recursive partitioning was used to prepare a regression tree. Results: Female married illiteracy positively associated with total fertility rate and explained more than half (53%) of variance. Under multiple linear regression model, married illiteracy, infant mortality rate, Ante natal care registration, household size, median age of live birth and sex ratio explained 70% of total variance in total fertility rate. In regression tree, female married illiteracy was the root node and splits at 42% determined TFR <= 2.7. The next left side branch was again married illiteracy with splits at 23% to determine TFR <= 2.1. Conclusion: We conclude that female married illiteracy is one of the most important determinants explaining total fertility rate among the districts of an Empowered Action Group states. Focus on female literacy is required to stabilize the population growth in long run. PMID:29416999

Building Regression Models: The Importance of Graphics.

ERIC Educational Resources Information Center

Dunn, Richard

1989-01-01

Points out reasons for using graphical methods to teach simple and multiple regression analysis. Argues that a graphically oriented approach has considerable pedagogic advantages in the exposition of simple and multiple regression. Shows that graphical methods may play a central role in the process of building regression models. (Author/LS)

Testing Different Model Building Procedures Using Multiple Regression.

ERIC Educational Resources Information Center

Thayer, Jerome D.

The stepwise regression method of selecting predictors for computer assisted multiple regression analysis was compared with forward, backward, and best subsets regression, using 16 data sets. The results indicated the stepwise method was preferred because of its practical nature, when the models chosen by different selection methods were similar…

Decreasing Multicollinearity: A Method for Models with Multiplicative Functions.

ERIC Educational Resources Information Center

Smith, Kent W.; Sasaki, M. S.

1979-01-01

A method is proposed for overcoming the problem of multicollinearity in multiple regression equations where multiplicative independent terms are entered. The method is not a ridge regression solution. (JKS)

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.

HAPRAP: a haplotype-based iterative method for statistical fine mapping using GWAS summary statistics.

PubMed

Zheng, Jie; Rodriguez, Santiago; Laurin, Charles; Baird, Denis; Trela-Larsen, Lea; Erzurumluoglu, Mesut A; Zheng, Yi; White, Jon; Giambartolomei, Claudia; Zabaneh, Delilah; Morris, Richard; Kumari, Meena; Casas, Juan P; Hingorani, Aroon D; Evans, David M; Gaunt, Tom R; Day, Ian N M

2017-01-01

Fine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data require the pairwise correlation coefficients ([Formula: see text]) of the variants. However, haplotypes rather than pairwise [Formula: see text], are the true biological representation of linkage disequilibrium (LD) among multiple loci. In this article, we present an empirical iterative method, HAPlotype Regional Association analysis Program (HAPRAP), that enables fine mapping using summary statistics and haplotype information from an individual-level reference panel. Simulations with individual-level genotypes show that the results of HAPRAP and multiple regression are highly consistent. In simulation with summary-level data, we demonstrate that HAPRAP is less sensitive to poor LD estimates. In a parametric simulation using Genetic Investigation of ANthropometric Traits height data, HAPRAP performs well with a small training sample size (N < 2000) while other methods become suboptimal. Moreover, HAPRAP's performance is not affected substantially by single nucleotide polymorphisms (SNPs) with low minor allele frequencies. We applied the method to existing quantitative trait and binary outcome meta-analyses (human height, QTc interval and gallbladder disease); all previous reported association signals were replicated and two additional variants were independently associated with human height. Due to the growing availability of summary level data, the value of HAPRAP is likely to increase markedly for future analyses (e.g. functional prediction and identification of instruments for Mendelian randomization). The HAPRAP package and documentation are available at http://apps.biocompute.org.uk/haprap/ CONTACT: : jie.zheng@bristol.ac.uk or tom.gaunt@bristol.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Fasting insulin levels and metabolic risk factors in type 2 diabetic patients at the first visit in Japan: a 10-year, nationwide, observational study (JDDM 28).

PubMed

Matsuba, Ikuro; Saito, Kazumi; Takai, Masahiko; Hirao, Koichi; Sone, Hirohito

2012-09-01

To investigate the relationship between fasting insulin levels and metabolic risk factors (MRFs) in type 2 diabetic patients at the first clinic/hospital visit in Japan over the years 2000 to 2009. In total, 4,798 drug-naive Japanese patients with type 2 diabetes were registered on their first clinic/hospital visits. Conventional clinical factors and fasting insulin levels were observed at baseline within the Japan Diabetes Clinical Data Management (JDDM) study between consecutive 2-year groups. Multiple linear regression analysis was performed using a model in which the dependent variable was fasting insulin values using various clinical explanatory variables. Fasting insulin levels were found to be decreasing from 2000 to 2009. Multiple linear regression analysis with the fasting insulin levels as the dependent variable showed that waist circumference (WC), BMI, mean blood pressure, triglycerides, and HDL cholesterol were significant, with WC and BMI as the main factors. ANCOVA after adjustment for age and fasting plasma glucose clearly shows the decreasing trend in fasting insulin levels and the increasing trend in BMI. During the 10-year observation period, the decreasing trend in fasting insulin was related to the slight increase in WC/BMI in type 2 diabetes. Low pancreatic β-cell reserve on top of a lifestyle background might be dependent on an increase in MRFs.

Fasting Insulin Levels and Metabolic Risk Factors in Type 2 Diabetic Patients at the First Visit in Japan

PubMed Central

Matsuba, Ikuro; Saito, Kazumi; Takai, Masahiko; Hirao, Koichi; Sone, Hirohito

2012-01-01

OBJECTIVE To investigate the relationship between fasting insulin levels and metabolic risk factors (MRFs) in type 2 diabetic patients at the first clinic/hospital visit in Japan over the years 2000 to 2009. RESEARCH DESIGN AND METHODS In total, 4,798 drug-naive Japanese patients with type 2 diabetes were registered on their first clinic/hospital visits. Conventional clinical factors and fasting insulin levels were observed at baseline within the Japan Diabetes Clinical Data Management (JDDM) study between consecutive 2-year groups. Multiple linear regression analysis was performed using a model in which the dependent variable was fasting insulin values using various clinical explanatory variables. RESULTS Fasting insulin levels were found to be decreasing from 2000 to 2009. Multiple linear regression analysis with the fasting insulin levels as the dependent variable showed that waist circumference (WC), BMI, mean blood pressure, triglycerides, and HDL cholesterol were significant, with WC and BMI as the main factors. ANCOVA after adjustment for age and fasting plasma glucose clearly shows the decreasing trend in fasting insulin levels and the increasing trend in BMI. CONCLUSIONS During the 10-year observation period, the decreasing trend in fasting insulin was related to the slight increase in WC/BMI in type 2 diabetes. Low pancreatic β-cell reserve on top of a lifestyle background might be dependent on an increase in MRFs. PMID:22665215

Deep ensemble learning of sparse regression models for brain disease diagnosis.

PubMed

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2017-04-01

Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effectiveness in handling high-dimensional data but with a small number of training samples, especially in medical problems. In the meantime, deep learning methods have been making great successes by outperforming the state-of-the-art performances in various applications. In this paper, we propose a novel framework that combines the two conceptually different methods of sparse regression and deep learning for Alzheimer's disease/mild cognitive impairment diagnosis and prognosis. Specifically, we first train multiple sparse regression models, each of which is trained with different values of a regularization control parameter. Thus, our multiple sparse regression models potentially select different feature subsets from the original feature set; thereby they have different powers to predict the response values, i.e., clinical label and clinical scores in our work. By regarding the response values from our sparse regression models as target-level representations, we then build a deep convolutional neural network for clinical decision making, which thus we call 'Deep Ensemble Sparse Regression Network.' To our best knowledge, this is the first work that combines sparse regression models with deep neural network. In our experiments with the ADNI cohort, we validated the effectiveness of the proposed method by achieving the highest diagnostic accuracies in three classification tasks. We also rigorously analyzed our results and compared with the previous studies on the ADNI cohort in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep ensemble learning of sparse regression models for brain disease diagnosis

PubMed Central

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2018-01-01

Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effectiveness in handling high-dimensional data but with a small number of training samples, especially in medical problems. In the meantime, deep learning methods have been making great successes by outperforming the state-of-the-art performances in various applications. In this paper, we propose a novel framework that combines the two conceptually different methods of sparse regression and deep learning for Alzheimer’s disease/mild cognitive impairment diagnosis and prognosis. Specifically, we first train multiple sparse regression models, each of which is trained with different values of a regularization control parameter. Thus, our multiple sparse regression models potentially select different feature subsets from the original feature set; thereby they have different powers to predict the response values, i.e., clinical label and clinical scores in our work. By regarding the response values from our sparse regression models as target-level representations, we then build a deep convolutional neural network for clinical decision making, which thus we call ‘ Deep Ensemble Sparse Regression Network.’ To our best knowledge, this is the first work that combines sparse regression models with deep neural network. In our experiments with the ADNI cohort, we validated the effectiveness of the proposed method by achieving the highest diagnostic accuracies in three classification tasks. We also rigorously analyzed our results and compared with the previous studies on the ADNI cohort in the literature. PMID:28167394

The impact of depression on fatigue in patients with haemodialysis: a correlational study.

PubMed

Bai, Yu-Ling; Lai, Liu-Yuan; Lee, Bih-O; Chang, Yong-Yuan; Chiou, Chou-Ping

2015-07-01

To investigate the fatigue levels and important fatigue predictors for patients undergoing haemodialysis. Fatigue is a common symptom for haemodialysis patients. With its debilitating and distressing effects, it impacts patients in terms of their quality of life while also increasing their mortality rate. A descriptive correlational study. Convenience sampling was conducted at six chosen haemodialysis centres in Southern Taiwan. Data were collected via a structured questionnaire from 193 haemodialysis patients. The scales involved in this study were socio-demographic details, the Center for Epidemiologic Studies Depression Scale, and the Fatigue Scale for haemodialysis patients. Data analysis included percentages, means, standard deviations and hierarchical multiple regression analysis. The fatigue level for haemodialysis patients was in the moderate range. Results from the hierarchical multiple regression analysis indicated that age, employment status, types of medications, physical activity and depression were significant. Of those variables, depression had the greatest impact on the patients' fatigue level, accounting for up to 30·6% of the explanatory power. The total explanatory power of the regression model was 64·2%. This study determined that for haemodialysis patients, unemployment, increased age, taking more medications or lower exercise frequencies resulted in more severe depression, which translated in turn to higher levels of fatigue. Among all these factors, depression had the greatest impact on the patients' fatigue levels. Not only is this finding beneficial to future studies on fatigue as a source of reference, it is also helpful in our understanding of important predictors relating to fatigue in the everyday lives of haemodialysis patients. It is recommended that when caring for fatigued patients, more care should be dedicated to their psychological states, and assistance should be provided in a timely way so as to reduce the amount of fatigue suffered. © 2015 John Wiley & Sons Ltd.

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

Sociodemographic and social contextual predictors of multiple health behavior change: data from the Healthy Directions-Small Business study.

PubMed

Harley, Amy E; Sapp, Amy L; Li, Yi; Marino, Miguel; Quintiliani, Lisa M; Sorensen, Glorian

2013-03-01

Multiple modifiable health behaviors contribute to the chronic diseases that are the leading causes of death in the USA. Disparities for meeting recommended health behavior guidelines exist across occupational classes and socioeconomic levels. The purpose of this paper was to investigate sociodemographic and social contextual predictors of multiple health behavior change in a worksite intervention. We analyzed data on four diet and exercise variables from an intervention trial with worksite-level randomization. Eight hundred forty-one employees had complete data from baseline (response rate = 84 %) and follow-up surveys (response rate = 77 %). Multilevel logistic regression estimated associations between least absolute shrinkage and selection operator-selected sociodemographic and social contextual predictor variables and the multiple health behavior change outcome (changing 2+ versus 0 behaviors). Gender, being married/partnered, and perceived discrimination were significantly associated with multiple health behavior change. Sociodemographic and social contextual factors predict multiple health behavior change and could inform the design and delivery of worksite interventions targeting multiple health behaviors.

The Impact of Prior Programming Knowledge on Lecture Attendance and Final Exam

ERIC Educational Resources Information Center

Veerasamy, Ashok Kumar; D'Souza, Daryl; Lindén, Rolf; Laakso, Mikko-Jussi

2018-01-01

In this article, we report the results of the impact of prior programming knowledge (PPK) on lecture attendance (LA) and on subsequent final programming exam performance in a university level introductory programming course. This study used Spearman's rank correlation coefficient, multiple regression, Kruskal-Wallis, and Bonferroni correction…

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…

Multiple-Instance Regression with Structured Data

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Lane, Terran; Roper, Alex

2008-01-01

We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) operates on a set of bags with real-valued labels, each containing a set of unlabeled items, in which the relevance of each item to its bag label is unknown. The goal is to predict the labels of new bags from their contents. Unlike previous MIR methods, MI-ClusterRegress can operate on bags that are structured in that they contain items drawn from a number of distinct (but unknown) distributions. MI-ClusterRegress simultaneously learns a model of the bag's internal structure, the relevance of each item, and a regression model that accurately predicts labels for new bags. We evaluated this approach on the challenging MIR problem of crop yield prediction from remote sensing data. MI-ClusterRegress provided predictions that were more accurate than those obtained with non-multiple-instance approaches or MIR methods that do not model the bag structure.

High stress, lack of sleep, low school performance, and suicide attempts are associated with high energy drink intake in adolescents.

PubMed

Kim, So Young; Sim, Songyong; Choi, Hyo Geun

2017-01-01

Although an association between energy drinks and suicide has been suggested, few prior studies have considered the role of emotional factors including stress, sleep, and school performance in adolescents. This study aimed to evaluate the association of energy drinks with suicide, independent of possible confounders including stress, sleep, and school performance. In total, 121,106 adolescents with 13-18 years olds from the 2014 and 2015 Korea Youth Risk Behavior Web-based Survey were surveyed for age, sex, region of residence, economic level, paternal and maternal education level, sleep time, stress level, school performance, frequency of energy drink intake, and suicide attempts. Subjective stress levels were classified into severe, moderate, mild, a little, and no stress. Sleep time was divided into 6 groups: < 6 h; 6 ≤ h < 7; 7 ≤ h < 8; 8 ≤ h < 9; and ≥ 9 h. School performance was classified into 5 levels: A (highest), B (middle, high), C (middle), D (middle, low), and E (lowest). Frequency of energy drink consumption was divided into 3 groups: ≥ 3, 1-2, and 0 times a week. The associations of sleep time, stress level, and school performance with suicide attempts and the frequency of energy drink intake were analyzed using multiple and ordinal logistic regression analysis, respectively, with complex sampling. The relationship between frequency of energy drink intake and suicide attempts was analyzed using multiple logistic regression analysis with complex sampling. Higher stress levels, lack of sleep, and low school performance were significantly associated with suicide attempts (each P < 0.001). These variables of high stress level, abnormal sleep time, and low school performance were also proportionally related with higher energy drink intake (P < 0.001). Frequent energy drink intake was significantly associated with suicide attempts in multiple logistic regression analyses (AOR for frequency of energy intake ≥ 3 times a week = 3.03, 95% CI = 2.64-3.49, P < 0.001). Severe stress, inadequate sleep, and low school performance were related with more energy drink intake and suicide attempts in Korean adolescents. Frequent energy drink intake was positively related with suicide attempts, even after adjusting for stress, sleep time, and school performance.

High stress, lack of sleep, low school performance, and suicide attempts are associated with high energy drink intake in adolescents

PubMed Central

Kim, So Young; Sim, Songyong

2017-01-01

Objective Although an association between energy drinks and suicide has been suggested, few prior studies have considered the role of emotional factors including stress, sleep, and school performance in adolescents. This study aimed to evaluate the association of energy drinks with suicide, independent of possible confounders including stress, sleep, and school performance. Methods In total, 121,106 adolescents with 13–18 years olds from the 2014 and 2015 Korea Youth Risk Behavior Web-based Survey were surveyed for age, sex, region of residence, economic level, paternal and maternal education level, sleep time, stress level, school performance, frequency of energy drink intake, and suicide attempts. Subjective stress levels were classified into severe, moderate, mild, a little, and no stress. Sleep time was divided into 6 groups: < 6 h; 6 ≤ h < 7; 7 ≤ h < 8; 8 ≤ h < 9; and ≥ 9 h. School performance was classified into 5 levels: A (highest), B (middle, high), C (middle), D (middle, low), and E (lowest). Frequency of energy drink consumption was divided into 3 groups: ≥ 3, 1–2, and 0 times a week. The associations of sleep time, stress level, and school performance with suicide attempts and the frequency of energy drink intake were analyzed using multiple and ordinal logistic regression analysis, respectively, with complex sampling. The relationship between frequency of energy drink intake and suicide attempts was analyzed using multiple logistic regression analysis with complex sampling. Results Higher stress levels, lack of sleep, and low school performance were significantly associated with suicide attempts (each P < 0.001). These variables of high stress level, abnormal sleep time, and low school performance were also proportionally related with higher energy drink intake (P < 0.001). Frequent energy drink intake was significantly associated with suicide attempts in multiple logistic regression analyses (AOR for frequency of energy intake ≥ 3 times a week = 3.03, 95% CI = 2.64–3.49, P < 0.001). Conclusion Severe stress, inadequate sleep, and low school performance were related with more energy drink intake and suicide attempts in Korean adolescents. Frequent energy drink intake was positively related with suicide attempts, even after adjusting for stress, sleep time, and school performance. PMID:29135989

Consumption of non-cow's milk beverages and serum vitamin D levels in early childhood.

PubMed

Lee, Grace J; Birken, Catherine S; Parkin, Patricia C; Lebovic, Gerald; Chen, Yang; L'Abbé, Mary R; Maguire, Jonathon L

2014-11-18

Vitamin D fortification of non-cow's milk beverages is voluntary in North America. The effect of consuming non-cow's milk beverages on serum 25-hydroxyvitamin D levels in children is unclear. We studied the association between non-cow's milk consumption and 25-hydroxyvitamin D levels in healthy preschool-aged children. We also explored whether cow's milk consumption modified this association and analyzed the association between daily non-cow's milk and cow's milk consumption. In this cross-sectional study, we recruited children 1-6 years of age attending routinely scheduled well-child visits. Survey responses, and anthropometric and laboratory measurements were collected. The association between non-cow's milk consumption and 25-hydroxyvitamin D levels was tested using multiple linear regression and logistic regression. Cow's milk consumption was explored as an effect modifier using an interaction term. The association between daily intake of non-cow's milk and cow's milk was explored using multiple linear regression. A total of 2831 children were included. The interaction between non-cow's milk and cow's milk consumption was statistically significant (p = 0.03). Drinking non-cow's milk beverages was associated with a 4.2-nmol/L decrease in 25-hydroxyvitamin D level per 250-mL cup consumed among children who also drank cow's milk (p = 0.008). Children who drank only non-cow's milk were at higher risk of having a 25-hydroxyvitamin D level below 50 nmol/L than children who drank only cow's milk (odds ratio 2.7, 95% confidence interval 1.6 to 4.7). Consumption of non-cow's milk beverages was associated with decreased serum 25-hydroxyvitamin D levels in early childhood. This association was modified by cow's milk consumption, which suggests a trade-off between consumption of cow's milk fortified with higher levels of vitamin D and non-cow's milk with lower vitamin D content. © 2014 Canadian Medical Association or its licensors.

Relationship of cariogenic bacteria levels with periodontal status and root surface caries in elderly Japanese.

PubMed

Saotome, Yasuhiko; Tada, Akio; Hanada, Nobuhiro; Yoshihara, Akihiro; Uematsu, Hiroshi; Miyazaki, Hideo; Senpuku, Hidenobu

2006-12-01

The relationship of the levels of cariogenic bacterial species with periodontal status and decayed root surfaces was investigated in elderly Japanese subjects. Three hundred and sixty-eight individuals (each 75 years old) were examined for periodontal status (pocket depth, attachment loss), root surface caries and salivary levels of mutans streptococci (MS) and lactobacilli (LB). Values >4 mm of attachment loss (rAL4) and for average attachment loss (aAL) of sites measured were significantly higher in subjects with LB than those without. Multiple regression analysis also showed a correlation between aAL and rAL4 values with the presence of LB (aAL p = 0.003; rAL4 p = 0.002). Further, multiple regression analysis of interacting factors regarding decayed root surfaces showed that LB carriers had a greater incidence of decayed root surface caries (p = 0.003), while MS and LB levels were correlated to the number of decayed root surfaces (LB p = 0.010; MS p = 0.026). Our results indicate that considerable attachment loss elevates the possibility of having LB, thus increasing the risk of root surface caries. It was also found that LB and MS measurements may be useful indicators of decayed root surfaces in elderly individuals with attachment loss.

Higher direct bilirubin levels during mid-pregnancy are associated with lower risk of gestational diabetes mellitus.

PubMed

Liu, Chaoqun; Zhong, Chunrong; Zhou, Xuezhen; Chen, Renjuan; Wu, Jiangyue; Wang, Weiye; Li, Xiating; Ding, Huisi; Guo, Yanfang; Gao, Qin; Hu, Xingwen; Xiong, Guoping; Yang, Xuefeng; Hao, Liping; Xiao, Mei; Yang, Nianhong

2017-01-01

Bilirubin concentrations have been recently reported to be negatively associated with type 2 diabetes mellitus. We examined the association between bilirubin concentrations and gestational diabetes mellitus. In a prospective cohort study, 2969 pregnant women were recruited prior to 16 weeks of gestation and were followed up until delivery. The value of bilirubin was tested and oral glucose tolerance test was conducted to screen gestational diabetes mellitus. The relationship between serum bilirubin concentration and gestational weeks was studied by two-piecewise linear regression. A subsample of 1135 participants with serum bilirubin test during 16-18 weeks gestation was conducted to research the association between serum bilirubin levels and risk of gestational diabetes mellitus by logistic regression. Gestational diabetes mellitus developed in 8.5 % of the participants (223 of 2969). Two-piecewise linear regression analyses demonstrated that the levels of bilirubin decreased with gestational week up to the turning point 23 and after that point, levels of bilirubin were increased slightly. In multiple logistic regression analysis, the relative risk of developing gestational diabetes mellitus was lower in the highest tertile of direct bilirubin than that in the lowest tertile (RR 0.60; 95 % CI, 0.35-0.89). The results suggested that women with higher serum direct bilirubin levels during the second trimester of pregnancy have lower risk for development of gestational diabetes mellitus.

Construction of multiple linear regression models using blood biomarkers for selecting against abdominal fat traits in broilers.

PubMed

Dong, J Q; Zhang, X Y; Wang, S Z; Jiang, X F; Zhang, K; Ma, G W; Wu, M Q; Li, H; Zhang, H

2018-01-01

Plasma very low-density lipoprotein (VLDL) can be used to select for low body fat or abdominal fat (AF) in broilers, but its correlation with AF is limited. We investigated whether any other biochemical indicator can be used in combination with VLDL for a better selective effect. Nineteen plasma biochemical indicators were measured in male chickens from the Northeast Agricultural University broiler lines divergently selected for AF content (NEAUHLF) in the fed state at 46 and 48 d of age. The average concentration of every parameter for the 2 d was used for statistical analysis. Levels of these 19 plasma biochemical parameters were compared between the lean and fat lines. The phenotypic correlations between these plasma biochemical indicators and AF traits were analyzed. Then, multiple linear regression models were constructed to select the best model used for selecting against AF content. and the heritabilities of plasma indicators contained in the best models were estimated. The results showed that 11 plasma biochemical indicators (triglycerides, total bile acid, total protein, globulin, albumin/globulin, aspartate transaminase, alanine transaminase, gamma-glutamyl transpeptidase, uric acid, creatinine, and VLDL) differed significantly between the lean and fat lines (P < 0.01), and correlated significantly with AF traits (P < 0.05). The best multiple linear regression models based on albumin/globulin, VLDL, triglycerides, globulin, total bile acid, and uric acid, had higher R2 (0.73) than the model based only on VLDL (0.21). The plasma parameters included in the best models had moderate heritability estimates (0.21 ≤ h2 ≤ 0.43). These results indicate that these multiple linear regression models can be used to select for lean broiler chickens. © 2017 Poultry Science Association Inc.

Plasma D-dimer levels and ischaemic lesions in multiple vascular regions can predict occult cancer in patients with cryptogenic stroke.

PubMed

Gon, Y; Sakaguchi, M; Takasugi, J; Kawano, T; Kanki, H; Watanabe, A; Oyama, N; Terasaki, Y; Sasaki, T; Mochizuki, H

2017-03-01

Cancer patients with cryptogenic stroke often have high plasma D-dimer levels and lesions in multiple vascular regions. Hence, if patients with cryptogenic stroke display such characteristics, occult cancer could be predicted. This study aimed to investigate the clinical characteristics of cryptogenic stroke as the first manifestation of occult cancer and to determine whether plasma D-dimer levels and lesions in multiple vascular regions can predict occult cancer in patients with cryptogenic stroke. Between January 2006 and October 2015, data on 1225 patients with acute ischaemic stroke were extracted from the stroke database of Osaka University Hospital. Among them, 184 patients were classified as having cryptogenic stroke, and 120 patients without a diagnosis of cancer at stroke onset were identified. Clinical variables were analyzed between cryptogenic stroke patients with and without occult cancer. Among 120 cryptogenic stroke patients without a diagnosis of cancer, 12 patients had occult cancer. The body mass index, hemoglobin levels and albumin levels were lower; plasma D-dimer and high-sensitivity C-reactive protein levels were higher; and lesions in multiple vascular regions were more common in patients with than in those without occult cancer. Multiple logistic regression analysis revealed that plasma D-dimer levels (odds ratio, 3.48; 95% confidence interval, 1.68-8.33; P = 0.002) and lesions in multiple vascular regions (odds ratio, 7.40; 95% confidence interval, 1.70-39.45; P = 0.01) independently predicted occult cancer. High plasma D-dimer levels and lesions in multiple vascular regions can be used to predict occult cancer in patients with cryptogenic stroke. © 2016 EAN.

Personality and attention: Levels of neuroticism and extraversion can predict attentional performance during a change detection task.

PubMed

Hahn, Sowon; Buttaccio, Daniel R; Hahn, Jungwon; Lee, Taehun

2015-01-01

The present study demonstrates that levels of extraversion and neuroticism can predict attentional performance during a change detection task. After completing a change detection task built on the flicker paradigm, participants were assessed for personality traits using the Revised Eysenck Personality Questionnaire (EPQ-R). Multiple regression analyses revealed that higher levels of extraversion predict increased change detection accuracies, while higher levels of neuroticism predict decreased change detection accuracies. In addition, neurotic individuals exhibited decreased sensitivity A' and increased fixation dwell times. Hierarchical regression analyses further revealed that eye movement measures mediate the relationship between neuroticism and change detection accuracies. Based on the current results, we propose that neuroticism is associated with decreased attentional control over the visual field, presumably due to decreased attentional disengagement. Extraversion can predict increased attentional performance, but the effect is smaller than the relationship between neuroticism and attention.

Effects of Barometric Fluctuations on Well Water-Level Measurements and Aquifer Test Data

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

Spane, Frank A.

1999-12-16

This report examines the effects of barometric fluctuations on well water-level measurements and evaluates adjustment and removal methods for determining areal aquifer head conditions and aquifer test analysis. Two examples of Hanford Site unconfined aquifer tests are examined that demonstrate baro-metric response analysis and illustrate the predictive/removal capabilities of various methods for well water-level and aquifer total head values. Good predictive/removal characteristics were demonstrated with best corrective results provided by multiple-regression deconvolution methods.

Cancer Patients Enrolled in a Smoking Cessation Clinical Trial: Characteristics and Correlates of Smoking Rate and Nicotine Dependence.

PubMed

Miele, Andrew; Thompson, Morgan; Jao, Nancy C; Kalhan, Ravi; Leone, Frank; Hogarth, Lee; Hitsman, Brian; Schnoll, Robert

2018-01-01

A substantial proportion of cancer patients continue to smoke after their diagnosis but few studies have evaluated correlates of nicotine dependence and smoking rate in this population, which could help guide smoking cessation interventions. This study evaluated correlates of smoking rate and nicotine dependence among 207 cancer patients. A cross-sectional analysis using multiple linear regression evaluated disease, demographic, affective, and tobacco-seeking correlates of smoking rate and nicotine dependence. Smoking rate was assessed using a timeline follow-back method. The Fagerström Test for Nicotine Dependence measured levels of nicotine dependence. A multiple linear regression predicting nicotine dependence showed an association with smoking to alleviate a sense of addiction from the Reasons for Smoking scale and tobacco-seeking behavior from the concurrent choice task ( p < .05), but not with affect measured by the HADS and PANAS ( p > .05). Multiple linear regression predicting prequit showed an association with smoking to alleviate addiction ( p < .05). ANOVA showed that Caucasian participants reported greater rates of smoking compared to other races. The results suggest that behavioral smoking cessation interventions that focus on helping patients to manage tobacco-seeking behavior, rather than mood management interventions, could help cancer patients quit smoking.

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.

Universal Algorithms for Plant Phenotyping: Are we there yet?

NASA Astrophysics Data System (ADS)

Kakani, V. G.; Kambham, R. R.; Zhao, D.; Foster, A. J.; Gowda, P. H.

2017-12-01

Hyperspectral remote sensing offers ability to capture spectral signatures of plant morpho-physio-biochemical traits at multiple scales (leaf to canopy to aerial). Experimental results on plant phenotype from pot, growth chamber and field studies at multiple location were used in this study. Pigment, leaf/plant water status, plant nutrient status, plant height, leaf area, fresh and dry weights of biomass and its components are correlated with hyperspectral reflectance signatures. Leaf reflectance was collected with spectroradiometer having a light source. Canopy hyperspectral reflectance was collected from 1.5 m above the canopy using a spectroradiometer, while multispectral images were acquired from aerial platforms ( 400m). Several statistical methods including simple ratios, principal component analysis, and partial least squares regression were used to identify hyperspectral reflectance bands that were tightly associated with plant phenotypic traits. Leaf level spectra best described the morpho-physio-biochemical traits (R2 = 0.6-0.9), while canopy reflectance best described plant height (R2 = 0.65), leaf area index (R2 = 0.67-0.74) and biomass (R2 = 0.69-0.78), while aerial spectra improved canopy level regression coefficients for plant height (R2 = 0.93) and leaf area index (R2 = 0.89). The comparison of multi-level spectra and resolution, clearly showed the advantage of hyperspectral reflectance data over the multispectral reflectance data, particularly for understanding the basis for spectral reflectance differences among species and traits. In conclusion, high resolution (1-2 cm) spectral imagery can help to bridge the gap across multiple levels of phenotype measurement.

Composite marginal quantile regression analysis for longitudinal adolescent body mass index data.

PubMed

Yang, Chi-Chuan; Chen, Yi-Hau; Chang, Hsing-Yi

2017-09-20

Childhood and adolescenthood overweight or obesity, which may be quantified through the body mass index (BMI), is strongly associated with adult obesity and other health problems. Motivated by the child and adolescent behaviors in long-term evolution (CABLE) study, we are interested in individual, family, and school factors associated with marginal quantiles of longitudinal adolescent BMI values. We propose a new method for composite marginal quantile regression analysis for longitudinal outcome data, which performs marginal quantile regressions at multiple quantile levels simultaneously. The proposed method extends the quantile regression coefficient modeling method introduced by Frumento and Bottai (Biometrics 2016; 72:74-84) to longitudinal data accounting suitably for the correlation structure in longitudinal observations. A goodness-of-fit test for the proposed modeling is also developed. Simulation results show that the proposed method can be much more efficient than the analysis without taking correlation into account and the analysis performing separate quantile regressions at different quantile levels. The application to the longitudinal adolescent BMI data from the CABLE study demonstrates the practical utility of our proposal. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Investigating bias in squared regression structure coefficients

PubMed Central

Nimon, Kim F.; Zientek, Linda R.; Thompson, Bruce

2015-01-01

The importance of structure coefficients and analogs of regression weights for analysis within the general linear model (GLM) has been well-documented. The purpose of this study was to investigate bias in squared structure coefficients in the context of multiple regression and to determine if a formula that had been shown to correct for bias in squared Pearson correlation coefficients and coefficients of determination could be used to correct for bias in squared regression structure coefficients. Using data from a Monte Carlo simulation, this study found that squared regression structure coefficients corrected with Pratt's formula produced less biased estimates and might be more accurate and stable estimates of population squared regression structure coefficients than estimates with no such corrections. While our findings are in line with prior literature that identified multicollinearity as a predictor of bias in squared regression structure coefficients but not coefficients of determination, the findings from this study are unique in that the level of predictive power, number of predictors, and sample size were also observed to contribute bias in squared regression structure coefficients. PMID:26217273

ℓ(p)-Norm multikernel learning approach for stock market price forecasting.

PubMed

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ(p)-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ(1)-norm multiple support vector regression model.

Association of Emotional Labor and Occupational Stressors with Depressive Symptoms among Women Sales Workers at a Clothing Shopping Mall in the Republic of Korea: A Cross-Sectional Study

PubMed Central

Chung, Yuh-Jin; Jung, Woo-Chul

2017-01-01

In the distribution service industry, sales people often experience multiple occupational stressors such as excessive emotional labor, workplace mistreatment, and job insecurity. The present study aimed to explore the associations of these stressors with depressive symptoms among women sales workers at a clothing shopping mall in Korea. A cross sectional study was conducted on 583 women who consist of clothing sales workers and manual workers using a structured questionnaire to assess demographic factors, occupational stressors, and depressive symptoms. Multiple regression analyses were performed to explore the association of these stressors with depressive symptoms. Scores for job stress subscales such as job demand, job control, and job insecurity were higher among sales workers than among manual workers (p < 0.01). The multiple regression analysis revealed the association between occupation and depressive symptoms after controlling for age, educational level, cohabiting status, and occupational stressors (sβ = 0.08, p = 0.04). A significant interaction effect between occupation and social support was also observed in this model (sβ = −0.09, p = 0.02). The multiple regression analysis stratified by occupation showed that job demand, job insecurity, and workplace mistreatment were significantly associated with depressive symptoms in both occupations (p < 0.05), although the strength of statistical associations were slightly different. We found negative associations of social support (sβ = −0.22, p < 0.01) and emotional effort (sβ = −0.17, p < 0.01) with depressive symptoms in another multiple regression model for sales workers. Emotional dissonance (sβ = 0.23, p < 0.01) showed positive association with depressive symptoms in this model. The result of this study indicated that reducing occupational stressors would be effective for women sales workers to prevent depressive symptoms. In particular, promoting social support could be the most effective way to promote women sales workers’ mental health. PMID:29168777

Association of Emotional Labor and Occupational Stressors with Depressive Symptoms among Women Sales Workers at a Clothing Shopping Mall in the Republic of Korea: A Cross-Sectional Study.

PubMed

Chung, Yuh-Jin; Jung, Woo-Chul; Kim, Hyunjoo; Cho, Seong-Sik

2017-11-23

In the distribution service industry, sales people often experience multiple occupational stressors such as excessive emotional labor, workplace mistreatment, and job insecurity. The present study aimed to explore the associations of these stressors with depressive symptoms among women sales workers at a clothing shopping mall in Korea. A cross sectional study was conducted on 583 women who consist of clothing sales workers and manual workers using a structured questionnaire to assess demographic factors, occupational stressors, and depressive symptoms. Multiple regression analyses were performed to explore the association of these stressors with depressive symptoms. Scores for job stress subscales such as job demand, job control, and job insecurity were higher among sales workers than among manual workers ( p < 0.01). The multiple regression analysis revealed the association between occupation and depressive symptoms after controlling for age, educational level, cohabiting status, and occupational stressors (sβ = 0.08, p = 0.04). A significant interaction effect between occupation and social support was also observed in this model (sβ = -0.09, p = 0.02). The multiple regression analysis stratified by occupation showed that job demand, job insecurity, and workplace mistreatment were significantly associated with depressive symptoms in both occupations ( p < 0.05), although the strength of statistical associations were slightly different. We found negative associations of social support (sβ = -0.22, p < 0.01) and emotional effort (sβ = -0.17, p < 0.01) with depressive symptoms in another multiple regression model for sales workers. Emotional dissonance (sβ = 0.23, p < 0.01) showed positive association with depressive symptoms in this model. The result of this study indicated that reducing occupational stressors would be effective for women sales workers to prevent depressive symptoms. In particular, promoting social support could be the most effective way to promote women sales workers' mental health.

On using summary statistics from an external calibration sample to correct for covariate measurement error.

PubMed

Guo, Ying; Little, Roderick J; McConnell, Daniel S

2012-01-01

Covariate measurement error is common in epidemiologic studies. Current methods for correcting measurement error with information from external calibration samples are insufficient to provide valid adjusted inferences. We consider the problem of estimating the regression of an outcome Y on covariates X and Z, where Y and Z are observed, X is unobserved, but a variable W that measures X with error is observed. Information about measurement error is provided in an external calibration sample where data on X and W (but not Y and Z) are recorded. We describe a method that uses summary statistics from the calibration sample to create multiple imputations of the missing values of X in the regression sample, so that the regression coefficients of Y on X and Z and associated standard errors can be estimated using simple multiple imputation combining rules, yielding valid statistical inferences under the assumption of a multivariate normal distribution. The proposed method is shown by simulation to provide better inferences than existing methods, namely the naive method, classical calibration, and regression calibration, particularly for correction for bias and achieving nominal confidence levels. We also illustrate our method with an example using linear regression to examine the relation between serum reproductive hormone concentrations and bone mineral density loss in midlife women in the Michigan Bone Health and Metabolism Study. Existing methods fail to adjust appropriately for bias due to measurement error in the regression setting, particularly when measurement error is substantial. The proposed method corrects this deficiency.

Advanced statistics: linear regression, part II: multiple linear regression.

PubMed

Marill, Keith A

2004-01-01

The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

Potentially Modifiable Factors Associated With Physical Activity in Individuals With Multiple Sclerosis.

PubMed

Reider, Nadia; Salter, Amber R; Cutter, Gary R; Tyry, Tuula; Marrie, Ruth Ann

2017-04-01

Physical activity levels among persons with multiple sclerosis (MS) are worryingly low. We aimed to identify the factors associated with physical activity for people with MS, with an emphasis on factors that have not been studied previously (bladder and hand dysfunction) and are potentially modifiable. This study was a secondary analysis of data collected in the spring of 2012 during the North American Research Committee on Multiple Sclerosis (NARCOMS) Registry. NARCOMS participants were surveyed regarding smoking using questions from the Behavioral Risk Factor Surveillance Survey; disability using the Patient Determined Disease Steps; fatigue, cognition, spasticity, sensory, bladder, vision and hand function using self-reported Performance Scales; health literacy using the Medical Term Recognition Test; and physical activity using questions from the Health Information National Trends Survey. We used a forward binary logistic regression to develop a predictive model in which physical activity was the outcome variable. Of 8,755 respondents, 1,707 (19.5%) were classified as active and 7,068 (80.5%) as inactive. In logistic regression, being a current smoker, moderate or severe level of disability, depression, fatigue, hand, or bladder dysfunction and minimal to mild spasticity were associated with lower odds of meeting physical activity guidelines. MS type was not linked to activity level. Several modifiable clinical and lifestyle factors influenced physical activity in MS. Prospective studies are needed to evaluate whether modification of these factors can increase physical activity participation in persons with MS. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Some Factors Effected Student's Calculus Learning Outcome

ERIC Educational Resources Information Center

Rajagukguk, Wamington

2016-01-01

The purpose of this study is to determine the factors effected calculus learning outcome of the student. This study was conducted with 176 respondents, which were selected randomly. The data were obtained by questionnaire, and then analyzed by using multiple regressions, and correlation, at level of a = 0.05. The findings showed there is the…

Lichen-based critical loads for atmospheric nitrogen deposition in Western Oregon and Washington forests, USA

Treesearch

Linda H. Geiser; Sarah E. Jovan; Doug A. Glavich; Matthew K. Porter

2010-01-01

Critical loads (CLs) define maximum atmospheric deposition levels apparently preventative of ecosystem harm. We present first nitrogen CLs for northwestern North America's maritime forests. Using multiple linear regression, we related epiphytic-macrolichen community composition to: 1) wet deposition from the National Atmospheric Deposition Program, 2) wet, dry,...

Determinants of Student Attitudes toward Team Exams

ERIC Educational Resources Information Center

Reinig, Bruce A.; Horowitz, Ira; Whittenburg, Gene

2014-01-01

We examine how student attitudes toward their group, learning method, and perceived development of professional skills are initially shaped and subsequently evolve through multiple uses of team exams. Using a Tobit regression model to analyse a sequence of 10 team quizzes given in a graduate-level tax accounting course, we show that there is an…

Ethnicity and Economic Well-Being: The Case of Ghana

ERIC Educational Resources Information Center

Addai, Isaac; Pokimica, Jelena

2010-01-01

In the context of decades of successful economic reforms in Ghana, this study investigates whether ethnicity influences economic well-being (perceived and actual) among Ghanaians at the micro-level. Drawing on Afro-barometer 2008 data, the authors employs logistic and multiple regression techniques to explore the relative effect of ethnicity on…

Too Latino and Not Latino Enough: The Role of Ethnicity-Related Stressors on Latino College Students' Life Satisfaction

ERIC Educational Resources Information Center

Ojeda, Lizette; Navarro, Rachel L.; Meza, Rocio Rosales; Arbona, Consuelo

2012-01-01

The relationship between demographics (generation status, age, gender, education level) and ethnicity-related stressors, namely, perceived discrimination, stereotype confirmation concern, and own-group conformity pressure, and the life satisfaction of 115 Latino college students was examined. A hierarchical multiple regression analysis indicated…

A Multiple Logistic Regression Model for Predicting the Development of Phytophthora ramorum symptoms in Tanoak (Lithocarpus densiflorus)

Treesearch

Mark Spencer; Kevin O' Hara

2007-01-01

Phytophthora ramorum attacks tanoak (Lithocarpus densiflorus) in California and Oregon. We present a stand-level study examining the presence of disease symptoms in individual stems. Working with data from four plots in redwood (Sequoia sempervirens)/tanoak forests in Marin County, and three plots in Mendocino...

Predictors of Parenting and Infant Outcomes for Impoverished Adolescent Parents

ERIC Educational Resources Information Center

Whitson, Melissa L.; Martinez, Andrew; Ayala, Carmen; Kaufman, Joy S.

2011-01-01

Adolescent mothers and their children are at risk for a myriad of negative outcomes. This study examined risk and protective factors and their impact on a sample (N = 172) of impoverished adolescent mothers. Multiple regression analyses revealed that depressed adolescent mothers report higher levels of parenting stress and that their children are…

A Course Specific Perspective in the Prediction of Academic Success.

ERIC Educational Resources Information Center

Beaulieu, R. P.

1990-01-01

Students (N=94) enrolled in a senior-level management course over six semesters were used to investigate the ability of four measures from two industrial tests to predict course performance. The resulting multiple regression equation with four predictors could accurately predict achievement of males, but not of females. (Author/TE)

[The effect of self-foot reflexology on the relief of premenstrual syndrome and dysmenorrhea in high school girls].

PubMed

Kim, Yi-Soon; Kim, Min-Za; Jeong, Ihn-Sook

2004-08-01

This study was aimed to identify the effect of self-foot reflexology on the relief of premenstrual syndrome and dysmenorrhea in high school girls. Study subjects was 236 women residing in the community, teachers and nurses who were older than 45 were recruited. Data was collected with self administered questionnaires from July 1st to August 31st, 2003 and analysed using SPSS/WIN 10.0 with Xtest, t-test, and stepwise multiple logistic regression at a significant level of =.05. The breast cancer screening rate was 57.2%, and repeat screening rate was 15.3%. With the multiple logistic regression analysis, factors associated with mammography screening were age and perceived barriers of action, and factors related to the repeat mammography screening were education level and other cancer screening experience. Based on the results, we recommend the development of an intervention program to decrease the perceived barrier of action, to regard mammography as an essential test in regular check-up, and to give active advertisement and education to the public to improve the rates of breast cancer screening and repeat screening.

Vocational identity, positive affect, and career thoughts in a group of young adult central nervous system cancer survivors.

PubMed

Lange, Dustin D; Wong, Alex W K; Strauser, David R; Wagner, Stacia

2014-12-01

The aims of this study were as follows: (a) to compare levels of career thoughts and vocational identity between young adult childhood central nervous system (CNS) cancer survivors and noncancer peers and (b) to investigate the contribution of vocational identity and affect on career thoughts among cancer survivors. Participants included 45 young adult CNS cancer survivors and a comparison sample of 60 college students. Participants completed Career Thoughts Inventory, My Vocational Situation, and the Positive and Negative Affect Schedule. Multivariate analysis of variance and multiple regression analysis were used to analyze the data in this study. CNS cancer survivors had a higher level of decision-making confusion than the college students. Multiple regression analysis indicated that vocational identity and positive affect significantly predicted the career thoughts of CNS survivors. The differences in decision-making confusion suggest that young adult CNS survivors would benefit from interventions that focus on providing knowledge of how to make decisions, while increasing vocational identity and positive affect for this specific population could also be beneficial.

Is This Kid a Likely Experimenter or a Likely Persister? An Analysis of Individual-Level and Family-Level Risk Factors Predicting Multiple Offending Among a Group of Adjudicated Youth.

PubMed

Buker, Hasan; Erbay, Ayhan

2018-02-01

To implement effective diversion programs and determine for a well-suited intervention strategy, ascertaining who, among the adjudicated youth, is more likely to involve in multiple offending, rather than desisting after an initial delinquent behavior, is of great significance. The overall objective of this study, therefore, is to contribute to the existing knowledge on assessing the risks for multiple offending during juvenile adjudication processes. In this regard, this study examined the predicting powers of several individual-level and family-level risk factors on multiple offending during adolescence, based on a data set derived from court-ordered social examination reports (SERs) on 400 adjudicated youth in Turkey. Two binomial regression models were implemented to test the predictor values of various risk factors from these two domains. Results indicated the following as significant predictors of multiple offending among the subjects: younger age of onset in delinquency, dropping out of school, having delinquent/drug abusing (risky) friends, being not able to share problems with the family, increased number of siblings, and having a domestically migrated family. Conclusively, these findings were compared with the existing literature, and the policy implications and recommendations for future research were discussed.

Hydrology and trout populations of cold-water rivers of Michigan and Wisconsin

USGS Publications Warehouse

Hendrickson, G.E.; Knutilla, R.L.

1974-01-01

Statistical multiple-regression analyses showed significant relationships between trout populations and hydrologic parameters. Parameters showing the higher levels of significance were temperature, hardness of water, percentage of gravel bottom, percentage of bottom vegetation, variability of streamflow, and discharge per unit drainage area. Trout populations increase with lower levels of annual maximum water temperatures, with increase in water hardness, and with increase in percentage of gravel and bottom vegetation. Trout populations also increase with decrease in variability of streamflow, and with increase in discharge per unit drainage area. Most hydrologic parameters were significant when evaluated collectively, but no parameter, by itself, showed a high degree of correlation with trout populations in regression analyses that included all the streams sampled. Regression analyses of stream segments that were restricted to certain limits of hardness, temperature, or percentage of gravel bottom showed improvements in correlation. Analyses of trout populations, in pounds per acre and pounds per mile and hydrologic parameters resulted in regression equations from which trout populations could be estimated with standard errors of 89 and 84 per cent, respectively.

Modeling Polytomous Item Responses Using Simultaneously Estimated Multinomial Logistic Regression Models

ERIC Educational Resources Information Center

Anderson, Carolyn J.; Verkuilen, Jay; Peyton, Buddy L.

2010-01-01

Survey items with multiple response categories and multiple-choice test questions are ubiquitous in psychological and educational research. We illustrate the use of log-multiplicative association (LMA) models that are extensions of the well-known multinomial logistic regression model for multiple dependent outcome variables to reanalyze a set of…

Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression.

PubMed

Zhang, Xinyan; Li, Bingzong; Han, Huiying; Song, Sha; Xu, Hongxia; Hong, Yating; Yi, Nengjun; Zhuang, Wenzhuo

2018-05-10

Multiple myeloma (MM), like other cancers, is caused by the accumulation of genetic abnormalities. Heterogeneity exists in the patients' response to treatments, for example, bortezomib. This urges efforts to identify biomarkers from numerous molecular features and build predictive models for identifying patients that can benefit from a certain treatment scheme. However, previous studies treated the multi-level ordinal drug response as a binary response where only responsive and non-responsive groups are considered. It is desirable to directly analyze the multi-level drug response, rather than combining the response to two groups. In this study, we present a novel method to identify significantly associated biomarkers and then develop ordinal genomic classifier using the hierarchical ordinal logistic model. The proposed hierarchical ordinal logistic model employs the heavy-tailed Cauchy prior on the coefficients and is fitted by an efficient quasi-Newton algorithm. We apply our hierarchical ordinal regression approach to analyze two publicly available datasets for MM with five-level drug response and numerous gene expression measures. Our results show that our method is able to identify genes associated with the multi-level drug response and to generate powerful predictive models for predicting the multi-level response. The proposed method allows us to jointly fit numerous correlated predictors and thus build efficient models for predicting the multi-level drug response. The predictive model for the multi-level drug response can be more informative than the previous approaches. Thus, the proposed approach provides a powerful tool for predicting multi-level drug response and has important impact on cancer studies.

Multiple pregnancy, short cervix, part-time worker, steroid use, low educational level and male fetus are risk factors for preterm birth in Japan: a multicenter, prospective study.

PubMed

Shiozaki, Arihiro; Yoneda, Satoshi; Nakabayashi, Masao; Takeda, Yoshiharu; Takeda, Satoru; Sugimura, Motoi; Yoshida, Koyo; Tajima, Atsushi; Manabe, Mami; Akagi, Kozo; Nakagawa, Shoko; Tada, Katsuhiko; Imafuku, Noriaki; Ogawa, Masanobu; Mizunoe, Tomoya; Kanayama, Naohiro; Itoh, Hiroaki; Minoura, Shigeki; Ogino, Mitsuharu; Saito, Shigeru

2014-01-01

To examine the relationship between preterm birth and socioeconomic factors, past history, cervical length, cervical interleukin-8, bacterial vaginosis, underlying diseases, use of medication, employment status, sex of the fetus and multiple pregnancy. In a multicenter, prospective, observational study, 1810 Japanese women registering their future delivery were enrolled at 8⁺⁰ to 12⁺⁶ weeks of gestation. Data on cervical length and delivery were obtained from 1365 pregnant women. Multivariate logistic regression analysis was performed. Short cervical length, steroid use, multiple pregnancy and male fetus were risk factors for preterm birth before 34 weeks of gestation. Multiple pregnancy, low educational level, short cervical length and part-timer were risk factors for preterm birth before 37 weeks of gestation. Multiple pregnancy and cervical shortening at 20-24 weeks of gestation was a stronger risk factor for preterm birth. Any pregnant woman being part-time employee or low educational level, having a male fetus and requiring steroid treatment should be watched for the development of preterm birth. © 2013 The Authors. Journal of Obstetrics and Gynaecology Research © 2013 Japan Society of Obstetrics and Gynecology.

Serum 25-hydroxyvitamin D3 and body composition in an elderly cohort from Germany: a cross-sectional study

PubMed Central

2012-01-01

Background Emerging evidence indicates that there is an association between vitamin D and obesity. The aim of this study was to investigate whether the level of serum 25-hydroxyvitamin D3 [25(OH)D3] in the elderly is influenced by parameters of anthropometry and body composition independent of potential confounding lifestyle factors and the level of serum intact parathyroid hormone (iPTH). Methods Cross-sectional data of 131 independently living participants (90 women, 41 men; aged 66–96 years) of the longitudinal study on nutrition and health status in senior citizens of Giessen, Germany were analysed. Concentrations of 25(OH)D3 and iPTH were ascertained by an electrochemiluminescence immunoassay. Body composition was measured by a bioelectrical impedance analysis. We performed univariate and multiple regression analyses to examine the influence of body composition on 25(OH)D3 with adjustments for age, iPTH and lifestyle factors. Results In univariate regression analyses, 25(OH)D3 was associated with body mass index (BMI), hip circumference and total body fat (TBF) in women, but not in men. Using multiple regression analyses, TBF was shown to be a negative predictor of 25(OH)D3 levels in women even after controlling for age, lifestyle and iPTH (ß = −0.247; P = 0.016), whereas the associations between BMI, hip circumference and 25(OH)D3 lost statistical significance after adjusting for iPTH. In men, 25(OH)D3 was not affected by anthropometric or body composition variables. Conclusions The results indicate that 25(OH)D3 levels are affected by TBF, especially in elderly women, independent of lifestyle factors and iPTH. PMID:22607088

An 8-year study of people with multiple sclerosis in Isfahan, Iran: Association between environmental air pollutants and severity of disease.

PubMed

Ashtari, Fereshte; Esmaeil, Nafiseh; Mansourian, Marjan; Poursafa, Parinaz; Mirmosayyeb, Omid; Barzegar, Mahdi; Pourgheisari, Hajar

2018-06-15

The evidence for an impact of ambient air pollution on the incidence and severity of multiple sclerosis (MS) is still limited. In the present study, we assessed the association between daily air pollution levels and MS prevalence and severity in Isfahan city, Iran. Data related to MS patients has been collected from 2008 to 2016 in a referral university clinic. The air quality index (AQI) data, were collected from 6 monitoring stations of Isfahan department of environment. The distribution map presenting the sites of air pollution monitoring stations as well as the residential address of MS patients was plotted on geographical information system (GIS). An increase in AQI level in four areas of the city (north, west, east and south) was associated with higher expanded disability status scale (EDSS) of MS patients[logistic regression odds ratio = 1.01 (95% CI = 1.008,1.012)]. Moreover, significant inverse association between the complete remission after the first attack with AQI level in total areas [logistic regression odds ratio = 0.987 (95% CI = 0.977, 0.997)] was found in crude model. However, after adjustment for confounding variables through multivariate logistic regression, AQI level was associated with degree of complete remission after first attack 1.005 (95% CI = 1.004, 1.006). The results of our study suggest that air pollution could play a role in the severity and remission of MS disease. However, more detailed studies with considering the complex involvement of different environmental factors including sunlight exposure, diet, depression and vitamin D are needed to determine the outcome of MS. Copyright © 2018 Elsevier B.V. All rights reserved.

Epidemiology of multiple childhood traumatic events: child abuse, parental psychopathology, and other family-level stressors.

PubMed

Menard, C B; Bandeen-Roche, K J; Chilcoat, H D

2004-11-01

Multiple family-level childhood stressors are common and are correlated. It is unknown if clusters of commonly co-occurring stressors are identifiable. The study was designed to explore family-level stressor clustering in the general population, to estimate the prevalence of exposure classes, and to examine the correlation of sociodemographic characteristics with class prevalence. Data were collected from an epidemiological sample and analyzed using latent class regression. A six-class solution was identified. Classes were characterized by low risk (prevalence=23%), universal high risk (7 %), family conflict (11 %), household substance problems (22 %), non-nuclear family structure (24 %), parent's mental illness (13 %). Class prevalence varied with race and welfare status, not gender. Interventions for childhood stressors are person-focused; the analytic approach may uniquely inform resource allocation.

Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression

ERIC Educational Resources Information Center

Beckstead, Jason W.

2012-01-01

The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic…

General Nature of Multicollinearity in Multiple Regression Analysis.

ERIC Educational Resources Information Center

Liu, Richard

1981-01-01

Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)

Association between memory impairment and brain metabolite concentrations in North Korean refugees with posttraumatic stress disorder.

PubMed

Shin, Jung Eun; Choi, Chi-Hoon; Lee, Jong Min; Kwon, Jun Soo; Lee, So Hee; Kim, Hyun-Chung; Han, Na Young; Choi, Soo-Hee; Yoo, So Young

2017-01-01

Individuals with posttraumatic stress disorder (PTSD) had experiences of enormous psychological stress that can result in neurocognitive and neurochemical changes. To date, the causal relationship between them remains unclear. The present study is to investigate the association between neurocognitive characteristics and neural metabolite concentrations in North Korean refugees with PTSD. A total of 53 North Korean refugees with or without PTSD underwent neurocognitive function tests. For neural metabolite scanning, magnetic resonance spectroscopy of the hippocampus and anterior cingulate cortex (ACC) has been conducted. We assessed between-group differences in neurocognitive test scores and metabolite levels. Additionally, a multiple regression analysis was carried out to evaluate the association between neurocognitive function and metabolite levels in patients with PTSD. Memory function, but not other neurocognitive functions, was significantly lower in the PTSD group compared with the non-PTSD group. Hippocampal N-acetylaspartate (NAA) levels were not different between groups; however, NAA levels were significantly lower in the ACC of the PTSD group than the non-PTSD group (t = 2.424, p = 0.019). The multiple regression analysis showed a negative association between hippocampal NAA levels and delayed recall score on the auditory verbal learning test (β = -1.744, p = 0.011) in the non-PTSD group, but not in the PTSD group. We identified specific memory impairment and the role of NAA levels in PTSD. Our findings suggest that hippocampal NAA has a protective role in memory impairment and development of PTSD after exposure to traumatic events.

Determinants of child maltreatment in Nepal: Results from the 2014 Nepal multiple indicator cluster survey (the 2014 NMICS).

PubMed

Atteraya, Madhu Sudhan; Ebrahim, Nasser B; Gnawali, Shreejana

2018-02-01

We examined the prevalence of child maltreatment as measured by the level of physical (moderate to severe) and emotional abuse and child labor, and the associated household level determinants of child maltreatment in Nepal. We used a nationally representative data set from the fifth round of the Nepal Multiple Indicator Cluster Survey (the 2014 NMICS). The main independent variables were household level characteristics. Dependent variables included child experience of moderate to severe physical abuse, emotional abuse, and child labor (domestic work and economic activities). Bivariate analyses and logistic regressions were used to examine the associations between independent and dependent variables. The results showed that nearly half of the children (49.8%) had experienced moderate physical abuse, 21.5% experienced severe physical abuse, and 77.3% experienced emotional abuse. About 27% of the children had engaged in domestic work and 46.7% in various economic activities. At bivariate level, educational level of household's head and household wealth status had shown significant statistical association with child maltreatment (p<0.001). Results from multivariate logistic regressions showed that higher education levels and higher household wealth status protected children from moderate to severe physical abuse, emotional abuse and child labor. In general, child maltreatment is a neglected social issue in Nepal and the high rates of child maltreatment calls for mass awareness programs focusing on parents, and involving all stakeholders including governments, local, and international organizations. Copyright © 2017 Elsevier Ltd. All rights reserved.

ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting

PubMed Central

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ 1-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ p-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ 1-norm multiple support vector regression model. PMID:23365561

Sample size determination for logistic regression on a logit-normal distribution.

PubMed

Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance

2017-06-01

Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution. Using this property of logistic regression, we propose new methods of determining the sample size for simple and multiple logistic regressions using a normal transformation of outcome measures. Simulation studies and a motivating example show several advantages of the proposed methods over the existing methods: (i) no need for [Formula: see text] for multiple logistic regression, (ii) available interim or group-sequential designs, and (iii) much smaller required sample size.

Dysglycemia, Glycemic Variability, and Outcome After Cardiac Arrest and Temperature Management at 33°C and 36°C.

PubMed

Borgquist, Ola; Wise, Matt P; Nielsen, Niklas; Al-Subaie, Nawaf; Cranshaw, Julius; Cronberg, Tobias; Glover, Guy; Hassager, Christian; Kjaergaard, Jesper; Kuiper, Michael; Smid, Ondrej; Walden, Andrew; Friberg, Hans

2017-08-01

Dysglycemia and glycemic variability are associated with poor outcomes in critically ill patients. Targeted temperature management alters blood glucose homeostasis. We investigated the association between blood glucose concentrations and glycemic variability and the neurologic outcomes of patients randomized to targeted temperature management at 33°C or 36°C after cardiac arrest. Post hoc analysis of the multicenter TTM-trial. Primary outcome of this analysis was neurologic outcome after 6 months, referred to as "Cerebral Performance Category." Thirty-six sites in Europe and Australia. All 939 patients with out-of-hospital cardiac arrest of presumed cardiac cause that had been included in the TTM-trial. Targeted temperature management at 33°C or 36°C. Nonparametric tests as well as multiple logistic regression and mixed effects logistic regression models were used. Median glucose concentrations on hospital admission differed significantly between Cerebral Performance Category outcomes (p < 0.0001). Hyper- and hypoglycemia were associated with poor neurologic outcome (p = 0.001 and p = 0.054). In the multiple logistic regression models, the median glycemic level was an independent predictor of poor Cerebral Performance Category (Cerebral Performance Category, 3-5) with an odds ratio (OR) of 1.13 in the adjusted model (p = 0.008; 95% CI, 1.03-1.24). It was also a predictor in the mixed model, which served as a sensitivity analysis to adjust for the multiple time points. The proportion of hyperglycemia was higher in the 33°C group compared with the 36°C group. Higher blood glucose levels at admission and during the first 36 hours, and higher glycemic variability, were associated with poor neurologic outcome and death. More patients in the 33°C treatment arm had hyperglycemia.

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

Relationship between prostate-specific antigen and obesity in prostate cancer screening: analysis of a large cohort in Japan.

PubMed

Kubota, Yasuaki; Seike, Kensaku; Maeda, Shinichi; Shinohara, Yuka; Iwata, Masamitsu; Sugimoto, Norio

2011-01-01

Previous studies have shown that lower prostate-specific antigen (PSA) levels in obese men might decrease the sensitivity of prostate cancer screening, leading to delayed diagnosis and unfavorable prognosis. We examined whether the effect of obesity is important in prostate cancer screening of Japanese men, who have a low prevalence of obesity. We analyzed 19,294 male subjects from a large cohort of Toyota Motor Corporation (TMC) employees (aged > 50 years, serum PSA level ≤ 4.0 ng/mL) who underwent physical examinations from August 2006 to December 2009. The relationship between PSA level and obesity-related factors was analyzed by simple and multiple regression analysis. The relationships between six body mass index (BMI) categories, and PSA level and PSA mass (PSA concentration × plasma volume) were analyzed. PSA level decreased significantly with increasing BMI, but the coefficient of determination was very low. Mean PSA values decreased from 1.02 to 0.85 ng/mL as BMI increased from underweight (BMI <18.5) to morbidly obese (BMI >35). However, PSA mass peaked in the overweight category and was slightly reduced with increasing BMI. On multiple regression analysis, PSA level was influenced by age, diastolic blood pressure and high-density lipoprotein as well as BMI. We found an inverse but weak relationship between PSA level and BMI. Obesity seems to have very limited influence on prostate cancer screening in this population. Nonetheless, when considering indications for prostatic biopsy in obese men, we should be aware that the hemodilution effect might reduce PSA levels. © 2010 The Japanese Urological Association.

Stepwise versus Hierarchical Regression: Pros and Cons

ERIC Educational Resources Information Center

Lewis, Mitzi

2007-01-01

Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…

Parsimonious model for blood glucose level monitoring in type 2 diabetes patients.

PubMed

Zhao, Fang; Ma, Yan Fen; Wen, Jing Xiao; DU, Yan Fang; Li, Chun Lin; Li, Guang Wei

2014-07-01

To establish the parsimonious model for blood glucose monitoring in patients with type 2 diabetes receiving oral hypoglycemic agent treatment. One hundred and fifty-nine adult Chinese type 2 diabetes patients were randomized to receive rapid-acting or sustained-release gliclazide therapy for 12 weeks. Their blood glucose levels were measured at 10 time points in a 24 h period before and after treatment, and the 24 h mean blood glucose levels were measured. Contribution of blood glucose levels to the mean blood glucose level and HbA1c was assessed by multiple regression analysis. The correlation coefficients of blood glucose level measured at 10 time points to the daily MBG were 0.58-0.74 and 0.59-0.79, respectively, before and after treatment (P<0.0001). The multiple stepwise regression analysis showed that the blood glucose levels measured at 6 of the 10 time points could explain 95% and 97% of the changes in MBG before and after treatment. The three blood glucose levels, which were measured at fasting, 2 h after breakfast and before dinner, of the 10 time points could explain 84% and 86% of the changes in MBG before and after treatment, but could only explain 36% and 26% of the changes in HbA1c before and after treatment, and they had a poorer correlation with the HbA1c than with the 24 h MBG. The blood glucose levels measured at fasting, 2 h after breakfast and before dinner truly reflected the change 24 h blood glucose level, suggesting that they are appropriate for the self-monitoring of blood glucose levels in diabetes patients receiving oral anti-diabetes therapy. Copyright © 2014 The Editorial Board of Biomedical and Environmental Sciences. Published by China CDC. All rights reserved.

A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy.

PubMed

Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru

2017-09-01

Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Teacher consultation and coaching within mental health practice: classroom and child effects in urban elementary schools.

PubMed

Cappella, Elise; Hamre, Bridget K; Kim, Ha Yeon; Henry, David B; Frazier, Stacy L; Atkins, Marc S; Schoenwald, Sonja K

2012-08-01

To examine effects of a teacher consultation and coaching program delivered by school and community mental health professionals on change in observed classroom interactions and child functioning across one school year. Thirty-six classrooms within 5 urban elementary schools (87% Latino, 11% Black) were randomly assigned to intervention (training + consultation/coaching) and control (training only) conditions. Classroom and child outcomes (n = 364; 43% girls) were assessed in the fall and spring. Random effects regression models showed main effects of intervention on teacher-student relationship closeness, academic self-concept, and peer victimization. Results of multiple regression models showed levels of observed teacher emotional support in the fall moderated intervention impact on emotional support at the end of the school year. Results suggest teacher consultation and coaching can be integrated within existing mental health activities in urban schools and impact classroom effectiveness and child adaptation across multiple domains. © 2012 American Psychological Association

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.

Use of Empirical Estimates of Shrinkage in Multiple Regression: A Caution.

ERIC Educational Resources Information Center

Kromrey, Jeffrey D.; Hines, Constance V.

1995-01-01

The accuracy of four empirical techniques to estimate shrinkage in multiple regression was studied through Monte Carlo simulation. None of the techniques provided unbiased estimates of the population squared multiple correlation coefficient, but the normalized jackknife and bootstrap techniques demonstrated marginally acceptable performance with…

Enhance-Synergism and Suppression Effects in Multiple Regression

ERIC Educational Resources Information Center

Lipovetsky, Stan; Conklin, W. Michael

2004-01-01

Relations between pairwise correlations and the coefficient of multiple determination in regression analysis are considered. The conditions for the occurrence of enhance-synergism and suppression effects when multiple determination becomes bigger than the total of squared correlations of the dependent variable with the regressors are discussed. It…

Gross motor development in full-term Greek infants assessed by the Alberta Infant Motor Scale: reference values and socioeconomic impact.

PubMed

Syrengelas, Dimitrios; Kalampoki, Vassiliki; Kleisiouni, Paraskevi; Konstantinou, Dimitrios; Siahanidou, Tania

2014-07-01

The aims of this study were to investigate gross motor development in Greek infants and establish AIMS percentile curves and to examine possible association of AIMS scores with socioeconomic parameters. Mean AIMS scores of 1068 healthy Greek full-term infants were compared at monthly age level with the respective mean scores of the Canadian normative sample. In a subgroup of 345 study participants, parents provided, via interview, information about family socioeconomic status. Multiple linear regression analysis was performed to evaluate the relationship of infant motor development with socioeconomic parameters. Mean AIMS scores did not differ significantly between Greek and Canadian infants in any of the 19 monthly levels of age. In multiple linear regression analysis, the educational level of the mother and also whether the infant was being raised by grandparents/babysitter were significantly associated with gross motor development (p=0.02 and p<0.001, respectively), whereas there was no significant correlation of mean AIMS scores with gender, birth order, maternal age, paternal educational level and family monthly income. Gross motor development of healthy Greek full-term infants, assessed by AIMS during the first 19months of age, follows a similar course to that of the original Canadian sample. Specific socioeconomic factors are associated with the infants' motor development. Copyright © 2014 Elsevier Ltd. All rights reserved.

An investigation of the effect of seasonal activity levels on avian censusing

Treesearch

C. John Ralph

1981-01-01

Intensive variable distance circular-plot censuses and timed activity budget data were used to compare the effects of conspicuousness upon census results. In six of ten species no correlation was found, suggesting that all birds within the "Effective Detection Distance" (EDD) were seen. In four species there were significant correlations. Multiple regression...

Using the Graded Response Model to Control Spurious Interactions in Moderated Multiple Regression

ERIC Educational Resources Information Center

Morse, Brendan J.; Johanson, George A.; Griffeth, Rodger W.

2012-01-01

Recent simulation research has demonstrated that using simple raw score to operationalize a latent construct can result in inflated Type I error rates for the interaction term of a moderated statistical model when the interaction (or lack thereof) is proposed at the latent variable level. Rescaling the scores using an appropriate item response…

Dissociating Conflict Adaptation from Feature Integration: A Multiple Regression Approach

ERIC Educational Resources Information Center

Notebaert, Wim; Verguts, Tom

2007-01-01

Congruency effects are typically smaller after incongruent than after congruent trials. One explanation is in terms of higher levels of cognitive control after detection of conflict (conflict adaptation; e.g., M. M. Botvinick, T. S. Braver, D. M. Barch, C. S. Carter, & J. D. Cohen, 2001). An alternative explanation for these results is based on…

High- and Low-Achieving Fraternity Environments at a Selective Institution: Their Influence on Members' Binge Drinking and GPA

ERIC Educational Resources Information Center

Maholchic-Nelson, Suzy

2010-01-01

This correlational study tested the efficacy of the social-ecological theory (Moos, 1979) by employing the University Residential Environmental Scale and multiple regression analysis to examine the influences of personal attributes (SAT, parents' level of education, race/ethnicity, and high school drinking) and environmental factors (high/low…

Curriculum-Based Measurement of Oral Reading: Quality of Progress Monitoring Outcomes

ERIC Educational Resources Information Center

Christ, Theodore J.; Zopluoglu, Cengiz; Long, Jeffery D.; Monaghen, Barbara D.

2012-01-01

Curriculum-based measurement of oral reading (CBM-R) is frequently used to set student goals and monitor student progress. This study examined the quality of growth estimates derived from CBM-R progress monitoring data. The authors used a linear mixed effects regression (LMER) model to simulate progress monitoring data for multiple levels of…

Using Regression Analysis To Determine If Faculty Salaries Are Overly Compressed. AIR 1997 Annual Forum Paper.

ERIC Educational Resources Information Center

Toutkoushian, Robert K.

This paper proposes a five-step process by which to analyze whether the salary ratio between junior and senior college faculty exhibits salary compression, a term used to describe an unusually small differential between faculty with different levels of experience. The procedure utilizes commonly used statistical techniques (multiple regression…

Pressure Points in Reading Comprehension: A Quantile Multiple Regression Analysis

ERIC Educational Resources Information Center

Logan, Jessica

2017-01-01

The goal of this study was to examine how selected pressure points or areas of vulnerability are related to individual differences in reading comprehension and whether the importance of these pressure points varies as a function of the level of children's reading comprehension. A sample of 245 third-grade children were given an assessment battery…

Lightning Strikes the Press: The Impact of the Telegraph on Wisconsin Newspapers.

ERIC Educational Resources Information Center

Scharlott, Bradford W.

The increase in the number of newspapers in Wisconsin's largest cities from 1840 to 1860 was analyzed to determine whether the coming of the telegraph (1848-1850) spurred newspaper growth significantly. Multiple regression analysis was used to control for the effects of population growth and price-level fluctuations. Even after accounting for the…

Prenatal Exposure to Alcohol, Caffeine, Tobacco, and Aspirin: Effects on Fine and Gross Motor Preformance in 4-Year-Old Children.

ERIC Educational Resources Information Center

Barr, Helen M.; And Others

1990-01-01

Multiple regression analyses of data from 449 children indicated statistically significant relationships between moderate levels of prenatal alcohol exposure and increased errors, increased latency, and increased total time on the Wisconsin Fine Motor Steadiness Battery and poorer balance on the Gross Motor Scale. (RH)

Sex differences and HIV risk behaviors: the interaction between the experience of multiple types of abuse and self-restraint on HIV risk behaviors.

PubMed

Conrad, Selby M; Swenson, Rebecca R; Hancock, Evan; Brown, Larry K

2014-01-01

Adolescents with abuse histories have been shown to be at increased risk to acquire human immunodeficiency virus and sexually transmitted infections. In addition, teens with lower levels of self-restraint or higher levels of distress, such as those with psychiatric concerns, have also demonstrated increased sexual risk behaviors. This study explored sex differences in sexual risk behaviors among a sample of adolescents in a therapeutic/alternative high school setting. Moderated regression analysis showed that a lower level of self-restraint was associated with sexual risk behaviors in boys but not in girls. Rather, the interaction of self-restraint and multiple types of abuse was associated with greater sex risk within girls in this sample. Results suggest that girls and boys with abuse histories and low levels of self-restraint may have different intervention needs related to sexual risk behaviors.

Model selection with multiple regression on distance matrices leads to incorrect inferences.

PubMed

Franckowiak, Ryan P; Panasci, Michael; Jarvis, Karl J; Acuña-Rodriguez, Ian S; Landguth, Erin L; Fortin, Marie-Josée; Wagner, Helene H

2017-01-01

In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM) to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC), its small-sample correction (AICc), and the Bayesian information criterion (BIC) to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.

Statistical analysis of water-quality data containing multiple detection limits: S-language software for regression on order statistics

USGS Publications Warehouse

Lee, L.; Helsel, D.

2005-01-01

Trace contaminants in water, including metals and organics, often are measured at sufficiently low concentrations to be reported only as values below the instrument detection limit. Interpretation of these "less thans" is complicated when multiple detection limits occur. Statistical methods for multiply censored, or multiple-detection limit, datasets have been developed for medical and industrial statistics, and can be employed to estimate summary statistics or model the distributions of trace-level environmental data. We describe S-language-based software tools that perform robust linear regression on order statistics (ROS). The ROS method has been evaluated as one of the most reliable procedures for developing summary statistics of multiply censored data. It is applicable to any dataset that has 0 to 80% of its values censored. These tools are a part of a software library, or add-on package, for the R environment for statistical computing. This library can be used to generate ROS models and associated summary statistics, plot modeled distributions, and predict exceedance probabilities of water-quality standards. ?? 2005 Elsevier Ltd. All rights reserved.

Estimating annual suspended-sediment loads in the northern and central Appalachian Coal region

USGS Publications Warehouse

Koltun, G.F.

1985-01-01

Multiple-regression equations were developed for estimating the annual suspended-sediment load, for a given year, from small to medium-sized basins in the northern and central parts of the Appalachian coal region. The regression analysis was performed with data for land use, basin characteristics, streamflow, rainfall, and suspended-sediment load for 15 sites in the region. Two variables, the maximum mean-daily discharge occurring within the year and the annual peak discharge, explained much of the variation in the annual suspended-sediment load. Separate equations were developed employing each of these discharge variables. Standard errors for both equations are relatively large, which suggests that future predictions will probably have a low level of precision. This level of precision, however, may be acceptable for certain purposes. It is therefore left to the user to asses whether the level of precision provided by these equations is acceptable for the intended application.

An Effect Size for Regression Predictors in Meta-Analysis

ERIC Educational Resources Information Center

Aloe, Ariel M.; Becker, Betsy Jane

2012-01-01

A new effect size representing the predictive power of an independent variable from a multiple regression model is presented. The index, denoted as r[subscript sp], is the semipartial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model…

Regression Analysis: Legal Applications in Institutional Research

ERIC Educational Resources Information Center

Frizell, Julie A.; Shippen, Benjamin S., Jr.; Luna, Andrew L.

2008-01-01

This article reviews multiple regression analysis, describes how its results should be interpreted, and instructs institutional researchers on how to conduct such analyses using an example focused on faculty pay equity between men and women. The use of multiple regression analysis will be presented as a method with which to compare salaries of…

RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,

DTIC Science & Technology

This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program...of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)

Incremental Net Effects in Multiple Regression

ERIC Educational Resources Information Center

Lipovetsky, Stan; Conklin, Michael

2005-01-01

A regular problem in regression analysis is estimating the comparative importance of the predictors in the model. This work considers the 'net effects', or shares of the predictors in the coefficient of the multiple determination, which is a widely used characteristic of the quality of a regression model. Estimation of the net effects can be a…

Floating Data and the Problem with Illustrating Multiple Regression.

ERIC Educational Resources Information Center

Sachau, Daniel A.

2000-01-01

Discusses how to introduce basic concepts of multiple regression by creating a large-scale, three-dimensional regression model using the classroom walls and floor. Addresses teaching points that should be covered and reveals student reaction to the model. Finds that the greatest benefit of the model is the low fear, walk-through, nonmathematical…

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

Using Multiple and Logistic Regression to Estimate the Median WillCost and Probability of Cost and Schedule Overrun for Program Managers

DTIC Science & Technology

2017-03-23

PUBLIC RELEASE; DISTRIBUTION UNLIMITED Using Multiple and Logistic Regression to Estimate the Median Will- Cost and Probability of Cost and... Cost and Probability of Cost and Schedule Overrun for Program Managers Ryan C. Trudelle Follow this and additional works at: https://scholar.afit.edu...afit.edu. Recommended Citation Trudelle, Ryan C., "Using Multiple and Logistic Regression to Estimate the Median Will- Cost and Probability of Cost and

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages.

PubMed

Kim, Yoonsang; Choi, Young-Ku; Emery, Sherry

2013-08-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods' performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages-SAS GLIMMIX Laplace and SuperMix Gaussian quadrature-perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes.

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages

PubMed Central

Kim, Yoonsang; Emery, Sherry

2013-01-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods’ performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages—SAS GLIMMIX Laplace and SuperMix Gaussian quadrature—perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes. PMID:24288415

Polycystic Ovary Syndrome and Increased Soluble Tumor Necrosis Factor Like Weak Inducer of Apoptosis Levels Are Independent Predictors of Dyslipidemia in Youth.

PubMed

Erkenekli, Kudret; Oztas, Efser; Kuscu, Elif; Keskin, Uğur; Kurt, Yasemin Gulcan; Tas, Ahmet; Yilmaz, Nafiye

2017-01-01

Dyslipidemia is common in women with polycystic ovary syndrome (PCOS) irrespective of age. Our aim was to investigate soluble tumor necrosis factor like weak inducer of apoptosis (sTWEAK), a cardiovascular risk marker in PCOS, and to determine if it is associated with dyslipidemia in youth. A prospective-observational study was carried out including 35 PCOS patients and 35 healthy controls. Serum sTWEAK levels were measured using commercially available kits. Multiple logistic regression analysis was then performed to verify the statistically significant differences in the possible predictors of dyslipidemia. Serum sTWEAK levels and the percentage of women with dyslipidemia were significantly higher in the PCOS group (p = 0.024 and p < 0.001, respectively). Participants were further divided into 2 subgroups based on the presence of dyslipidemia. The percentage of women with PCOS was significantly higher in the dyslipidemic group when compared with controls; 70.7 vs. 20.7%, respectively (p < 0.001). Multiple logistic regression analysis revealed that both the presence of PCOS (OR 7.924, 95% CI 2.117-29.657, p = 0.002) and increased levels of sTWEAK (>693 pg/ml; OR 3.810, 95% CI 1.075-13.501, p = 0.038) were independently associated with dyslipidemia. Increased levels of both sTWEAK and PCOS were found to be independently associated with dyslipidemia in youth. © 2016 S. Karger AG, Basel.

Leukocyte telomere length correlates with glucose control in adults with recently diagnosed type 2 diabetes.

PubMed

Rosa, Erica Carine Campos Caldas; Dos Santos, Renan Renato Cruz; Fernandes, Luis Fernando Amarante; Neves, Francisco de Assis Rocha; Coelho, Michella Soares; Amato, Angelica Amorim

2018-01-01

We investigated leukocyte relative telomere length (TL) in patients with type 2 diabetes (T2D) diagnosed for no longer than five years and its association with clinical and biochemical variables. Peripheral blood leukocyte relative TL was investigated in 108 patients with T2D (87 women, 21 men) and 125 (37 women, 88 men) age-matched control subjects with normal glucose tolerance, by quantitative polymerase chain reaction. Multiple linear regression analysis was used to examine the association between relative TL and demographic, anthropometric and biochemical indicators of metabolic control among patients with T2D. Patients with T2D had a median time since diagnosis of 1 year and most were on metformin monotherapy, with satisfactory glucose control determined by HbA1c levels. Median relative TL was not different between patients with T2D and control subjects. However, multiple linear regression analyses showed that relative TL was inversely associated with time since T2D diagnosis, fasting plasma glucose levels and HbA1c levels, but not with HbA1c levels assessed in the preceding 5-12 months, after adjustment for age, sex and body mass index. This study suggests that relative TL is not shorter in patients with recently diagnosed T2D, but is inversely correlated with glucose levels, even among patients with overall satisfactory glucose control. Copyright © 2017 Elsevier B.V. All rights reserved.

[Factors associated with activities of daily living (ADL) in independently living elderly persons in a community: a baseline examination of a large scale cohort study, Fujiwara-kyo study].

PubMed

Komatsu, Masayo; Nezu, Satoko; Tomioka, Kimiko; Hazaki, Kan; Harano, Akihiro; Morikawa, Masayuki; Takagi, Masahiro; Yamada, Masahiro; Matsumoto, Yoshitaka; Iwamoto, Junko; Ishizuka, Rika; Saeki, Keigo; Okamoto, Nozomi; Kurumatani, Norio

2013-01-01

To investigate factors associated with activities of daily living in independently living elderly persons in a community. The potential subjects were 4,472 individuals aged 65 years and older who voluntarily participated in a large cohort study, the Fujiwara-kyo study. We used self-administered questionnaires consisting of an activities of daily living (ADL) questionnaire with the Physical Fitness Test established by the Ministry of Education, Culture, Sports, Science and Technology (12 ADL items) to determine the index of higher-level physical independence, demographics, Geriatric Depression Scale, and so on. Mini-mental state examination, measurement of physical fitness, and blood tests were also carried out. A lower ADL level was defined as having a total score of the 12 ADL items (range, 12-36 points) that was below the first quartile of a total score for all the subjects. Factors associated with a low ADL level were examined by multiple logistic regression. A total of 4,198 remained as subjects for analysis. The male, female and 5-year-old groups showed significant differences in the median score of 12 ADL items between any two groups. The highest odds ratio among factors associated with lower ADL level by multiple logistic regression with mutually adjusted independent variables was 4.49 (95%CI: 2.82-7.17) in the groups of "very sharp pain" or "strong pain" during the last month. Low physical ability, self-awareness of limb weakness, a BMI of over 25, low physical activity, cerebrovascular disorder, depression, low cognitive function, unable "to see normally", unable "to hear someone", "muscle, bone and joint pain" were independently associated with lower ADL level. Multiple factors are associated with lower ADL level assessed on the basis of the 12 ADL items.

Anxiety Levels Are Independently Associated With Cognitive Performance in an Australian Multiple Sclerosis Patient Cohort.

PubMed

Ribbons, Karen; Lea, Rodney; Schofield, Peter W; Lechner-Scott, Jeannette

2017-01-01

Neurological and psychological symptoms in multiple sclerosis can affect cognitive function. The objective of this study was to explore the relationship between psychological measures and cognitive performance in a patient cohort. In 322 multiple sclerosis patients, psychological symptoms were measured using the Depression Anxiety and Stress Scale, and cognitive function was evaluated using Audio Recorded Cognitive Screen. Multifactor linear regression analysis, accounting for all clinical covariates, found that anxiety was the only psychological measure to remain a significant predictor of cognitive performance (p<0.001), particularly memory function (p<0.001). Further prospective studies are required to determine whether treatment of anxiety improves cognitive impairment.

Ghrelin level negatively predicts quality of life in obese women.

PubMed

Lu, P H; Song, Y L; Hsu, C H

2017-02-01

A cross-sectional cohort study was conducted to investigate whether ghrelin level in obese women predicts the quality of life (QOL). A total of 307 subjects fulfilled the criteria: (1) age between 20 and 65 years old, (2) body mass index ≥27 kg/m 2 (3) waist circumference ≥80 cm were enrolled in the study. All subjects were assigned to one of the plasma ghrelin level categories according to the quartiles. The median of age and BMI of the 307 obese women were 45 ± 18 years and 29.9 ± 4.1 kg/m 2 , respectively. The main outcome evaluated is the associations of plasma ghrelin level and QOL, which were evaluated using multiple linear regression analysis. Results of linear trend test show significant statistical difference in plasma lipoproteins (triglyceride, cholesterol, HDL-cholestero and LDL-cholesterol = and levels of obesity-related hormone peptides, including leptin, adiponectin, insulin among quartiles of ghrelin. Multiple liner regression analysis of serum obesity-related hormone peptide level and QOL using stepwise method shows ghrelin concentration was the only predictor of QOL, including PCS-12 level (β = -0.18, p = 0.001), MCS-12 level (β = -0.14, p = 0.009), WHOQOL-BREF scores: physical (β = -0.13, p = 0.03), psychological (β = -0.16, p = 0.007), social (β = -0.21, p =  < 0.001), and environmental (β = -0.22, p =  <0.001), after adjusting other factors for obese female subjects. This study demonstrated that ghrelin concentration is strongly associated with QOL level among obese women. Hence, ghrelin concentration might be a valuable marker to be monitored in obese women.

Serum Albumin and Disease Severity of Non-Cystic Fibrosis Bronchiectasis.

PubMed

Lee, Seung Jun; Kim, Hyo-Jung; Kim, Ju-Young; Ju, Sunmi; Lim, Sujin; Yoo, Jung Wan; Nam, Sung-Jin; Lee, Gi Dong; Cho, Hyun Seop; Kim, Rock Bum; Cho, Yu Ji; Jeong, Yi Yeong; Kim, Ho Cheol; Lee, Jong Deog

2017-08-01

A clinical classification system has been developed to define the severity and predict the prognosis of subjects with non-cystic fibrosis (CF) bronchiectasis. We aimed to identify laboratory parameters that are correlated with the bronchiectasis severity index (BSI) and FACED score. The medical records of 107 subjects with non-CF bronchiectasis for whom BSI and FACED scores could be calculated were retrospectively reviewed. The correlations between the laboratory parameters and BSI or FACED score were assessed, and multiple-linear regression analysis was performed to identify variables independently associated with BSI and FACED score. An additional subgroup analysis was performed according to sex. Among all of the enrolled subjects, 49 (45.8%) were male and 58 (54.2%) were female. The mean BSI and FACED scores were 9.43 ± 3.81 and 1.92 ± 1.59, respectively. The serum albumin level (r = -0.49), bilirubin level (r = -0.31), C-reactive protein level (r = 0.22), hemoglobin level (r = -0.2), and platelet/lymphocyte ratio (r = 0.31) were significantly correlated with BSI. Meanwhile, serum albumin (r = -0.37) and bilirubin level (r = -0.25) showed a significant correlation with the FACED score. Multiple-linear regression analysis showed that the serum bilirubin level was independently associated with BSI, and the serum albumin level was independently associated with both scoring systems. Subgroup analysis revealed that the level of uric acid was also a significant variable independently associated with the BSI in male bronchiectasis subjects. Several laboratory variables were identified as possible prognostic factors for non-CF bronchiectasis. Among them, the serum albumin level exhibited the strongest correlation and was identified as an independent variable associated with the BSI and FACED scores. Copyright © 2017 by Daedalus Enterprises.

Tools to Support Interpreting Multiple Regression in the Face of Multicollinearity

PubMed Central

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K.

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses. PMID:22457655

Tools to support interpreting multiple regression in the face of multicollinearity.

PubMed

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses.

Variables Associated with Communicative Participation in People with Multiple Sclerosis: A Regression Analysis

ERIC Educational Resources Information Center

Baylor, Carolyn; Yorkston, Kathryn; Bamer, Alyssa; Britton, Deanna; Amtmann, Dagmar

2010-01-01

Purpose: To explore variables associated with self-reported communicative participation in a sample (n = 498) of community-dwelling adults with multiple sclerosis (MS). Method: A battery of questionnaires was administered online or on paper per participant preference. Data were analyzed using multiple linear backward stepwise regression. The…

Estimating Procurement Cost Growth Using Logistic and Multiple Regression

DTIC Science & Technology

2003-03-01

Figure 4). The plots fail to pass the visual inspection for constant variance as well as the Breusch - Pagan test (Neter, 1996: 112) at an alpha level...plots fail to pass the visual inspection for constant variance as well as the Breusch - Pagan test at an alpha level of 0.05. Based on these findings...amount of cost growth a program will have 13 once model A deems that the program will incur cost growth. Sipple conducts validation testing on

A simulation study on Bayesian Ridge regression models for several collinearity levels

NASA Astrophysics Data System (ADS)

Efendi, Achmad; Effrihan

2017-12-01

When analyzing data with multiple regression model if there are collinearities, then one or several predictor variables are usually omitted from the model. However, there sometimes some reasons, for instance medical or economic reasons, the predictors are all important and should be included in the model. Ridge regression model is not uncommon in some researches to use to cope with collinearity. Through this modeling, weights for predictor variables are used for estimating parameters. The next estimation process could follow the concept of likelihood. Furthermore, for the estimation nowadays the Bayesian version could be an alternative. This estimation method does not match likelihood one in terms of popularity due to some difficulties; computation and so forth. Nevertheless, with the growing improvement of computational methodology recently, this caveat should not at the moment become a problem. This paper discusses about simulation process for evaluating the characteristic of Bayesian Ridge regression parameter estimates. There are several simulation settings based on variety of collinearity levels and sample sizes. The results show that Bayesian method gives better performance for relatively small sample sizes, and for other settings the method does perform relatively similar to the likelihood method.

Evidencing the association between swimming capacities and performance indicators in water polo: a multiple regression study.

PubMed

Kontic, Dean; Zenic, Natasa; Uljevic, Ognjen; Sekulic, Damir; Lesnik, Blaz

2017-06-01

Swimming capacities are hypothesized to be important determinants of water polo performance but there is an evident lack of studies examining different swimming capacities in relation to specific offensive and defensive performance variables in this sport. The aim of this study was to determine the relationship between five swimming capacities and six performance determinants in water polo. The sample comprised 79 high-level youth water polo players (all males, 17-18 years of age). The variables included six performance-related variables (agility in offence and defense, efficacy in offence and defense, polyvalence in offence and defense), and five swimming-capacity tests (water polo sprint test [15 m], swimming sprint test [25 m], short-distance [100 m], aerobic endurance [400 m] and an anaerobic lactate endurance test [4× 50 m]). First, multiple regressions were calculated for one-half of the sample of subjects which were then validated with the remaining half of the sample. The 25-m swim was not included in the regression analyses due to the multicollinearity with other predictors. The originally calculated regression models were validated for defensive agility (R=0.67 and R=0.55 for the original regression calculation and validation subsample, respectively) offensive agility (R=0.59 and R=0.61), and offensive efficacy (R=0.64 and R=0.58). Anaerobic lactate endurance is a significant predictor of offensive and defensive agility, while 15 m sprint significantly contributes to offensive efficacy. Swimming capacities are not found to be related to the polyvalence of the players. The most superior offensive performance can be expected from those players with a high level of anaerobic lactate endurance and advanced sprinting capacity, while anaerobic lactate endurance is recognized as most important quality in defensive duties. Future studies should observe players' polyvalence in relation to (theoretical) knowledge of technical and tactical tasks. Results reinforce the need for the cross-validation of the prediction-models in sport and exercise sciences.

A cross-sectional study to estimate associations between education level and osteoporosis in a Chinese postmenopausal women sample.

PubMed

Piao, Hui-Hong; He, Jiajia; Zhang, Keqin; Tang, Zihui

2015-01-01

Our research aims to investigate the associations between education level and osteoporosis (OP) in Chinese postmenopausal women. A large-scale, community-based, cross-sectional study was conducted to examine the associations between education level and OP. A self-reported questionnaire was used to access the demographical information and medical history of the participants. A total of 1905 postmenopausal women were available for data analysis in this study. Multiple regression models controlling for confounding factors to include education level were performed to investigate the relationship with OP. The prevalence of OP was 28.29% in our study sample. Multivariate linear regression analyses adjusted for relevant potential confounding factors detected significant associations between education level and T-score (β = 0.025, P-value = 0.095, 95% CI: -0.004-0.055 for model 1; and β = 0.092, P-value = 0.032, 95% CI: 0.008-0.175 for model 2). Multivariate logistic regression analyses detected significant associations between education level and OP in model 1 (P-value = 0.070 for model 1, Table 5), while no significant associations was reported in model 2 (P value = 0.131). In participants with high education levels, the OR for OP was 0.914 (95% CI: 0.830-1.007). The findings indicated that education level was independently and significantly associated with OP. The prevalence of OP was more frequent in Chinese postmenopausal women with low educational status.

Serum osteocalcin is significantly related to indices of obesity and lipid profile in Malaysian men.

PubMed

Chin, Kok-Yong; Ima-Nirwana, Soelaiman; Mohamed, Isa Naina; Ahmad, Fairus; Ramli, Elvy Suhana Mohd; Aminuddin, Amilia; Ngah, Wan Zurinah Wan

2014-01-01

Recent studies revealed a possible reciprocal relationship between the skeletal system and obesity and lipid metabolism, mediated by osteocalcin, an osteoblast-specific protein. This study aimed to validate the relationship between serum osteocalcin and indices of obesity and lipid parameters in a group of Malaysian men. A total of 373 men from the Malaysian Aging Male Study were included in the analysis. Data on subjects' demography, body mass index (BMI), body fat (BF) mass, waist circumference (WC), serum osteocalcin and fasting lipid levels were collected. Bioelectrical impendence (BIA) method was used to estimate BF. Multiple linear and binary logistic regression analyses were performed to analyze the association between serum osteocalcin and the aforementioned variables, with adjustment for age, ethnicity and BMI. Multiple regression results indicated that weight, BMI, BF mass, BF %, WC were significantly and negatively associated with serum osteocalcin (p < 0.001). There was a significant positive association between serum osteocalcin and high density lipoprotein (HDL) cholesterol (p = 0.032). Binary logistic results indicated that subjects with low serum osteocalcin level were more likely to be associated with high BMI (obese and overweight), high BF%, high WC and low HDL cholesterol (p < 0.05). Subjects with high osteocalcin level also demonstrated high total cholesterol level (p < 0.05) but this association was probably driven by high HDL level. These variables were not associated with serum C-terminal of telopeptide crosslinks in the subjects (p > 0.05). Serum osteocalcin is associated with indices of obesity and HDL level in men. These relationships should be validated by a longitudinal study, with comprehensive hormone profile testing.

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.

Impact of pine tip moth attack on loblolly pine

Treesearch

Roy Hedden

1999-01-01

Data on the impact of Nantucket pine tip moth, Rhyacionia frustrana, attack on the height of loblolly pine, Pinus taeda, in the first three growing seasons after planting from three locations in eastern North Carolina (U.S.A.) was used to develop multiple linear regression models relating tree height to tip moth infestation level in each growing season. These models...

The Role of Perceived Learning and Communities of Inquiry in Predicting International Students' Course Grades in Computer-Mediated Graduate Courses

ERIC Educational Resources Information Center

Wendt, Jillian L.; Nisbet, Deanna L.

2017-01-01

This study examined the predictive relationship among international students' sense of community, perceived learning, and end-of-course grades in computer-mediated, U.S. graduate-level courses. The community of inquiry (CoI) framework served as the theoretical foundation for the study. Step-wise hierarchical multiple regression showed no…

The impact of green stormwater infrastructure installation on surrounding health and safety.

PubMed

Kondo, Michelle C; Low, Sarah C; Henning, Jason; Branas, Charles C

2015-03-01

We investigated the health and safety effects of urban green stormwater infrastructure (GSI) installments. We conducted a difference-in-differences analysis of the effects of GSI installments on health (e.g., blood pressure, cholesterol and stress levels) and safety (e.g., felonies, nuisance and property crimes, narcotics crimes) outcomes from 2000 to 2012 in Philadelphia, Pennsylvania. We used mixed-effects regression models to compare differences in pre- and posttreatment measures of outcomes for treatment sites (n=52) and randomly chosen, matched control sites (n=186) within multiple geographic extents surrounding GSI sites. Regression-adjusted models showed consistent and statistically significant reductions in narcotics possession (18%-27% less) within 16th-mile, quarter-mile, half-mile (P<.001), and eighth-mile (P<.01) distances from treatment sites and at the census tract level (P<.01). Narcotics manufacture and burglaries were also significantly reduced at multiple scales. Nonsignificant reductions in homicides, assaults, thefts, public drunkenness, and narcotics sales were associated with GSI installation in at least 1 geographic extent. Health and safety considerations should be included in future assessments of GSI programs. Subsequent studies should assess mechanisms of this association.

The Impact of Green Stormwater Infrastructure Installation on Surrounding Health and Safety

PubMed Central

Low, Sarah C.; Henning, Jason; Branas, Charles C.

2015-01-01

Objectives. We investigated the health and safety effects of urban green stormwater infrastructure (GSI) installments. Methods. We conducted a difference-in-differences analysis of the effects of GSI installments on health (e.g., blood pressure, cholesterol and stress levels) and safety (e.g., felonies, nuisance and property crimes, narcotics crimes) outcomes from 2000 to 2012 in Philadelphia, Pennsylvania. We used mixed-effects regression models to compare differences in pre- and posttreatment measures of outcomes for treatment sites (n = 52) and randomly chosen, matched control sites (n = 186) within multiple geographic extents surrounding GSI sites. Results. Regression-adjusted models showed consistent and statistically significant reductions in narcotics possession (18%–27% less) within 16th-mile, quarter-mile, half-mile (P < .001), and eighth-mile (P < .01) distances from treatment sites and at the census tract level (P < .01). Narcotics manufacture and burglaries were also significantly reduced at multiple scales. Nonsignificant reductions in homicides, assaults, thefts, public drunkenness, and narcotics sales were associated with GSI installation in at least 1 geographic extent. Conclusions. Health and safety considerations should be included in future assessments of GSI programs. Subsequent studies should assess mechanisms of this association. PMID:25602887

[Factors associated with physical activity among Chinese immigrant women].

PubMed

Cho, Sung-Hye; Lee, Hyeonkyeong

2013-12-01

This study was done to assess the level of physical activity among Chinese immigrant women and to determine the relationships of physical activity with individual characteristics and behavior-specific cognition. A cross-sectional descriptive study was conducted with 161 Chinese immigrant women living in Busan. A health promotion model of physical activity adapted from Pender's Health Promotion Model was used. Self-administered questionnaires were used to collect data during the period from September 25 to November 20, 2012. Using SPSS 18.0 program, descriptive statistics, t-test, analysis of variance, correlation analysis, and multiple regression analysis were done. The average level of physical activity of the Chinese immigrant women was 1,050.06 ± 686.47 MET-min/week and the minimum activity among types of physical activity was most dominant (59.6%). As a result of multiple regression analysis, it was confirmed that self-efficacy and acculturation were statistically significant variables in the model (p<.001), with an explanatory power of 23.7%. The results indicate that the development and application of intervention strategies to increase acculturation and self-efficacy for immigrant women will aid in increasing the physical activity in Chinese immigrant women.

Maternal overprotection score of the Parental Bonding Instrument predicts the outcome of cognitive behavior therapy by trainees for depression.

PubMed

Asano, Motoshi; Esaki, Kosei; Wakamatsu, Aya; Kitajima, Tomoko; Narita, Tomohiro; Naitoh, Hiroshi; Ozaki, Norio; Iwata, Nakao

2013-07-01

The purpose of this study was to predict the outcome of cognitive behavior therapy (CBT) by trainees for major depressive disorder (MDD) based on the Parental Bonding Instrument (PBI). The hypothesis was that the higher level of care and/or lower level of overprotection score would predict a favorable outcome of CBT by trainees. The subjects were all outpatients with MDD treated with CBT as a training case. All the subjects were asked to fill out the Japanese version of the PBI before commencing the course of psychotherapy. The difference between the first and the last Beck Depression Inventory (BDI) score was used to represent the improvement of the intensity of depression by CBT. In order to predict improvement (the difference of the BDI scores) as the objective variable, multiple regression analysis was performed using maternal overprotection score and baseline BDI score as the explanatory variables. The multiple regression model was significant (P = 0.0026) and partial regression coefficient for the maternal overprotection score and the baseline BDI was -0.73 (P = 0.0046) and 0.88 (P = 0.0092), respectively. Therefore, when a patient's maternal overprotection score of the PBI was lower, a better outcome of CBT was expected. The hypothesis was partially supported. This result would be useful in determining indications for CBT by trainees for patients with MDD. © 2013 The Authors. Psychiatry and Clinical Neurosciences © 2013 Japanese Society of Psychiatry and Neurology.

How does the use of multiple needles/syringes per injecting episode impact on the measurement of individual level needle and syringe program coverage?

PubMed

O'Keefe, Daniel; McCormack, Angus; Cogger, Shelley; Aitken, Campbell; Burns, Lucinda; Bruno, Raimondo; Stafford, Jenny; Butler, Kerryn; Breen, Courtney; Dietze, Paul

2017-08-01

Recent work by McCormack et al. (2016) showed that the inclusion of syringe stockpiling improves the measurement of individual-level syringe coverage. We explored whether including the use of a new parameter, multiple sterile syringes per injecting episode, further improves coverage measures. Data comes from 838 people who inject drugs, interviewed as part of the 2015 Illicit Drug Reporting System. Along with syringe coverage questions, the survey recorded the number of sterile syringes used on average per injecting episode. We constructed three measures of coverage: one adapted from Bluthenthal et al. (2007), the McCormack et al. measure, and a new coverage measure that included use of multiple syringes. Predictors of multiple syringe use and insufficient coverage (<100% of injecting episodes using a sterile syringe) using the new measure, were tested in logistic regression and the ability of the measures to discriminate key risk behaviours was compared using ROC curve analysis. 134 (16%) participants reported needing multiple syringes per injecting episode. Women showed significantly increased odds of multiple syringe use, as did those reporting injection related injuries/diseases and injecting of opioid substitution drugs or pharmaceutical opioids. Levels of insufficient coverage across the three measures were substantial (20%-28%). ROC curve analysis suggested that our new measure was no better at discriminating injecting risk behaviours than the existing measures. Based on our findings, there appears to be little need for adding a multiple syringe use parameter to existing coverage formulae. Hence, we recommend that multiple syringe use is not included in the measurement of individual-level syringe coverage. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Deriving the Intrahepatic Arteriovenous Shunt Rate from CT Images and Biochemical Data Instead of from Arterial Perfusion Scintigraphy in Hepatic Arterial Infusion Chemotherapy

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

Ozaki, Toshiro, E-mail: ganronbun@amail.plala.or.jp; Seki, Hiroshi; Shiina, Makoto

2009-09-15

The purpose of the present study was to elucidate a method for predicting the intrahepatic arteriovenous shunt rate from computed tomography (CT) images and biochemical data, instead of from arterial perfusion scintigraphy, because adverse exacerbated systemic effects may be induced in cases where a high shunt rate exists. CT and arterial perfusion scintigraphy were performed in patients with liver metastases from gastric or colorectal cancer. Biochemical data and tumor marker levels of 33 enrolled patients were measured. The results were statistically verified by multiple regression analysis. The total metastatic hepatic tumor volume (V{sub metastasized}), residual hepatic parenchyma volume (V{sub residual};more » calculated from CT images), and biochemical data were treated as independent variables; the intrahepatic arteriovenous (IHAV) shunt rate (calculated from scintigraphy) was treated as a dependent variable. The IHAV shunt rate was 15.1 {+-} 11.9%. Based on the correlation matrixes, the best correlation coefficient of 0.84 was established between the IHAV shunt rate and V{sub metastasized} (p < 0.01). In the multiple regression analysis with the IHAV shunt rate as the dependent variable, the coefficient of determination (R{sup 2}) was 0.75, which was significant at the 0.1% level with two significant independent variables (V{sub metastasized} and V{sub residual}). The standardized regression coefficients ({beta}) of V{sub metastasized} and V{sub residual} were significant at the 0.1 and 5% levels, respectively. Based on this result, we can obtain a predicted value of IHAV shunt rate (p < 0.001) using CT images. When a high shunt rate was predicted, beneficial and consistent clinical monitoring can be initiated in, for example, hepatic arterial infusion chemotherapy.« less

The Geometry of Enhancement in Multiple Regression

ERIC Educational Resources Information Center

Waller, Niels G.

2011-01-01

In linear multiple regression, "enhancement" is said to occur when R[superscript 2] = b[prime]r greater than r[prime]r, where b is a p x 1 vector of standardized regression coefficients and r is a p x 1 vector of correlations between a criterion y and a set of standardized regressors, x. When p = 1 then b [is congruent to] r and…

Body burden levels of dioxin, furans, and PCBs among frequent consumers of Great Lakes sport fish

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

Falk, C.; Hanrahan, L.; Anderson, H.A.

1999-02-01

Dioxins, furans, and polychlorinated biphenyls (PCBs) are toxic, persist in the environment, and bioaccumulate to concentrations that can be harmful to humans. The Health Departments of five GL states, Wisconsin, Michigan, Ohio, Illinois, and Indiana, formed a consortium to study body burden levels of chemical residues in fish consumers of Lakes Michigan, Huron, and Erie. In Fall 1993, a telephone survey was administered to sport angler households to obtain fish consumption habits and demographics. A blood sample was obtained from a portion of the study subjects. One hundred serum samples were analyzed for 8 dioxin, 10 furan, and 4 coplanarmore » PCB congeners. Multiple linear regression was conducted to assess the predictability of the following covariates: GL sport fish species, age, BMI, gender, years sport fish consumed, and lake. Median total dioxin toxic equivalents (TEq), total furan TEq, and total coplanar PCB TEq were higher among all men than all women (P = 0.0001). Lake trout, salmon, age, BMI, and gender were significant regression predictors of log (total coplanar PCBs). Lake trout, age, gender, and lake were significant regression predictors of log (total furans). Age was the only significant predictor of total dioxin levels.« less

Trends in Mortality After Primary Cytoreductive Surgery for Ovarian Cancer: A Systematic Review and Metaregression of Randomized Clinical Trials and Observational Studies.

PubMed

Di Donato, Violante; Kontopantelis, Evangelos; Aletti, Giovanni; Casorelli, Assunta; Piacenti, Ilaria; Bogani, Giorgio; Lecce, Francesca; Benedetti Panici, Pierluigi

2017-06-01

Primary cytoreductive surgery (PDS) followed by platinum-based chemotherapy is the cornerstone of treatment and the absence of residual tumor after PDS is universally considered the most important prognostic factor. The aim of the present analysis was to evaluate trend and predictors of 30-day mortality in patients undergoing primary cytoreduction for ovarian cancer. Literature was searched for records reporting 30-day mortality after PDS. All cohorts were rated for quality. Simple and multiple Poisson regression models were used to quantify the association between 30-day mortality and the following: overall or severe complications, proportion of patients with stage IV disease, median age, year of publication, and weighted surgical complexity index. Using the multiple regression model, we calculated the risk of perioperative mortality at different levels for statistically significant covariates of interest. Simple regression identified median age and proportion of patients with stage IV disease as statistically significant predictors of 30-day mortality. When included in the multiple Poisson regression model, both remained statistically significant, with an incidence rate ratio of 1.087 for median age and 1.017 for stage IV disease. Disease stage was a strong predictor, with the risk estimated to increase from 2.8% (95% confidence interval 2.02-3.66) for stage III to 16.1% (95% confidence interval 6.18-25.93) for stage IV, for a cohort with a median age of 65 years. Metaregression demonstrated that increased age and advanced clinical stage were independently associated with an increased risk of mortality, and the combined effects of both factors greatly increased the risk.

Spirituality and Resilience Among Mexican American IPV Survivors.

PubMed

de la Rosa, Iván A; Barnett-Queen, Timothy; Messick, Madeline; Gurrola, Maria

2016-12-01

Women with abusive partners use a variety of coping strategies. This study examined the correlation between spirituality, resilience, and intimate partner violence using a cross-sectional survey of 54 Mexican American women living along the U.S.-Mexico border. The meaning-making coping model provides the conceptual framework to explore how spirituality is used as a copying strategy. Multiple ordinary least squares (OLS) regression results indicate women who score higher on spirituality also report greater resilient characteristics. Poisson regression analyses revealed that an increase in level of spirituality is associated with lower number of types of abuse experienced. Clinical, programmatic, and research implications are discussed. © The Author(s) 2015.

Modeling daily soil temperature over diverse climate conditions in Iran—a comparison of multiple linear regression and support vector regression techniques

NASA Astrophysics Data System (ADS)

Delbari, Masoomeh; Sharifazari, Salman; Mohammadi, Ehsan

2018-02-01

The knowledge of soil temperature at different depths is important for agricultural industry and for understanding climate change. The aim of this study is to evaluate the performance of a support vector regression (SVR)-based model in estimating daily soil temperature at 10, 30 and 100 cm depth at different climate conditions over Iran. The obtained results were compared to those obtained from a more classical multiple linear regression (MLR) model. The correlation sensitivity for the input combinations and periodicity effect were also investigated. Climatic data used as inputs to the models were minimum and maximum air temperature, solar radiation, relative humidity, dew point, and the atmospheric pressure (reduced to see level), collected from five synoptic stations Kerman, Ahvaz, Tabriz, Saghez, and Rasht located respectively in the hyper-arid, arid, semi-arid, Mediterranean, and hyper-humid climate conditions. According to the results, the performance of both MLR and SVR models was quite well at surface layer, i.e., 10-cm depth. However, SVR performed better than MLR in estimating soil temperature at deeper layers especially 100 cm depth. Moreover, both models performed better in humid climate condition than arid and hyper-arid areas. Further, adding a periodicity component into the modeling process considerably improved the models' performance especially in the case of SVR.

Advanced statistics: linear regression, part I: simple linear regression.

PubMed

Marill, Keith A

2004-01-01

Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

Multivariate research in areas of phosphorus cast-iron brake shoes manufacturing using the statistical analysis and the multiple regression equations

NASA Astrophysics Data System (ADS)

Kiss, I.; Cioată, V. G.; Alexa, V.; Raţiu, S. A.

2017-05-01

The braking system is one of the most important and complex subsystems of railway vehicles, especially when it comes for safety. Therefore, installing efficient safe brakes on the modern railway vehicles is essential. Nowadays is devoted attention to solving problems connected with using high performance brake materials and its impact on thermal and mechanical loading of railway wheels. The main factor that influences the selection of a friction material for railway applications is the performance criterion, due to the interaction between the brake block and the wheel produce complex thermos-mechanical phenomena. In this work, the investigated subjects are the cast-iron brake shoes, which are still widely used on freight wagons. Therefore, the cast-iron brake shoes - with lamellar graphite and with a high content of phosphorus (0.8-1.1%) - need a special investigation. In order to establish the optimal condition for the cast-iron brake shoes we proposed a mathematical modelling study by using the statistical analysis and multiple regression equations. Multivariate research is important in areas of cast-iron brake shoes manufacturing, because many variables interact with each other simultaneously. Multivariate visualization comes to the fore when researchers have difficulties in comprehending many dimensions at one time. Technological data (hardness and chemical composition) obtained from cast-iron brake shoes were used for this purpose. In order to settle the multiple correlation between the hardness of the cast-iron brake shoes, and the chemical compositions elements several model of regression equation types has been proposed. Because a three-dimensional surface with variables on three axes is a common way to illustrate multivariate data, in which the maximum and minimum values are easily highlighted, we plotted graphical representation of the regression equations in order to explain interaction of the variables and locate the optimal level of each variable for maximal response. For the calculation of the regression coefficients, dispersion and correlation coefficients, the software Matlab was used.

Association between depression and work stress in nursing professionals with technical education level 1

PubMed Central

Gherardi-Donato, Edilaine Cristina da Silva; Cardoso, Lucilene; Teixeira, Carla Araújo Bastos; Pereira, Sandra de Souza; Reisdorfer, Emilene

2015-01-01

Abstract Objective: to analize the relationship between depression and work stress in nursing professionals with technical education level of a teaching hospital in a city of the state of São Paulo. Methods: a cross-sectional study was carried out with 310 nursing technicians and nursing assistants, randomly selected. The outcome analyzed was the report of depression and its relationship with high levels of work stress, measured using the Job Stress Scale. Descriptive statistics and logistic regression were performed. Results: the prevalence of depression in this study was 20%, and it was more expressive in females, aged over 40 years, living without a partner and in smokers. The chance of depression was twice as high among professionals showing high levels of work stress, even after multiple regression adjusting. Conclusion: depressive symptoms were strongly associated with high stress levels among nursing assistants and nursing technicians, evidencing a problem to be considered along with the planning of specific intervention programs for this population, as well as the need for better cases management by the supervisors. PMID:26444177

Periodontitis in coronary heart disease patients: strong association between bleeding on probing and systemic biomarkers.

PubMed

Bokhari, Syed Akhtar H; Khan, Ayyaz A; Butt, Arshad K; Hanif, Mohammad; Izhar, Mateen; Tatakis, Dimitris N; Ashfaq, Mohammad

2014-11-01

Few studies have examined the relationship of individual periodontal parameters with individual systemic biomarkers. This study assessed the possible association between specific clinical parameters of periodontitis and systemic biomarkers of coronary heart disease risk in coronary heart disease patients with periodontitis. Angiographically proven coronary heart disease patients with periodontitis (n = 317), aged >30 years and without other systemic illness were examined. Periodontal clinical parameters of bleeding on probing (BOP), probing depth (PD), and clinical attachment level (CAL) and systemic levels of high-sensitivity C-reactive protein (CRP), fibrinogen (FIB) and white blood cells (WBC) were noted and analyzed to identify associations through linear and stepwise multiple regression analyses. Unadjusted linear regression showed significant associations between periodontal and systemic parameters; the strongest association (r = 0.629; p < 0.001) was found between BOP and CRP levels, the periodontal and systemic inflammation marker, respectively. Stepwise regression analysis models revealed that BOP was a predictor of systemic CRP levels (p < 0.0001). BOP was the only periodontal parameter significantly associated with each systemic parameter (CRP, FIB, and WBC). In coronary heart disease patients with periodontitis, BOP is strongly associated with systemic CRP levels; this association possibly reflects the potential significance of the local periodontal inflammatory burden for systemic inflammation. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Signaling mechanisms underlying the robustness and tunability of the plant immune network

PubMed Central

Kim, Yungil; Tsuda, Kenichi; Igarashi, Daisuke; Hillmer, Rachel A.; Sakakibara, Hitoshi; Myers, Chad L.; Katagiri, Fumiaki

2014-01-01

Summary How does robust and tunable behavior emerge in a complex biological network? We sought to understand this for the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, PAD4, and salicylate sectors, which together explain up to 80% of the PTI level, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, was central to the network robustness via its inhibition of the jasmonate sector. The model's multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability. PMID:24439900

Noninvasive spectral imaging of skin chromophores based on multiple regression analysis aided by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Wiswadarma, Aditya; Hase, Yota; Tanaka, Noriyuki; Maeda, Takaaki; Niizeki, Kyuichi; Aizu, Yoshihisa

2011-08-01

In order to visualize melanin and blood concentrations and oxygen saturation in human skin tissue, a simple imaging technique based on multispectral diffuse reflectance images acquired at six wavelengths (500, 520, 540, 560, 580 and 600nm) was developed. The technique utilizes multiple regression analysis aided by Monte Carlo simulation for diffuse reflectance spectra. Using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are deduced numerically in advance, while oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments with human skin of the human hand during upper limb occlusion and of the inner forearm exposed to UV irradiation demonstrated the ability of the method to evaluate physiological reactions of human skin tissue.

Work related stress and blood glucose levels.

PubMed

Sancini, A; Ricci, S; Tomei, F; Sacco, C; Pacchiarotti, A; Nardone, N; Ricci, P; Suppi, A; De Cesare, D P; Anzelmo, V; Giubilati, R; Pimpinella, B; Rosati, M V; Tomei, G

2017-01-01

The aim of the study is to evaluate work-related subjective stress in a group of workers on a major Italian company in the field of healthcare through the administration of a valid "questionnaire-tool indicator" (HSE Indicator Tool), and to analyze any correlation between stress levels taken from questionnaire scores and blood glucose values. We studied a final sample consisting of 241 subjects with different tasks. The HSE questionnaire - made up of 35 items (divided into 7 organizational dimensions) with 5 possible answers - has been distributed to all the subjects in occasion of the health surveillance examinations provided by law. The questionnaire was then analyzed using its specific software to process the results related to the 7 dimensions. These results were compared using the Pearson correlation and multiple linear regression with the blood glucose values obtained from each subject. From the analysis of the data the following areas resulted critical, in other words linked to an intermediate (yellow area) or high (red area) condition of stress: sustain from managers, sustain from colleagues, quality of relationships and professional changes. A significant positive correlation (p <0.05) between the mean values of all critical areas and the concentrations of glucose values have been highlighted with the correlation index of Pearson. Multiple linear regression confirmed these findings, showing that the critical dimensions resulting from the questionnaire were the significant variables that can increase the levels of blood glucose. The preliminary results indicate that perceived work stress can be statistically associated with increased levels of blood glucose.

Step-rate cut-points for physical activity intensity in patients with multiple sclerosis: The effect of disability status.

PubMed

Agiovlasitis, Stamatis; Sandroff, Brian M; Motl, Robert W

2016-02-15

Evaluating the relationship between step-rate and rate of oxygen uptake (VO2) may allow for practical physical activity assessment in patients with multiple sclerosis (MS) of differing disability levels. To examine whether the VO2 to step-rate relationship during over-ground walking differs across varying disability levels among patients with MS and to develop step-rate thresholds for moderate- and vigorous-intensity physical activity. Adults with MS (N=58; age: 51 ± 9 years; 48 women) completed one over-ground walking trial at comfortable speed, one at 0.22 m · s(-1) slower, and one at 0.22 m · s(-1) faster. Each trial lasted 6 min. VO2 was measured with portable spirometry and steps with hand-tally. Disability status was classified as mild, moderate, or severe based on Expanded Disability Status Scale scores. Multi-level regression indicated that step-rate, disability status, and height significantly predicted VO2 (p<0.05). Based on this model, we developed step-rate thresholds for activity intensity that vary by disability status and height. A separate regression without height allowed for development of step-rate thresholds that vary only by disability status. The VO2 during over-ground walking differs among ambulatory patients with MS based on disability level and height, yielding different step-rate thresholds for physical activity intensity. Copyright © 2015 Elsevier B.V. All rights reserved.

Using the Coefficient of Determination "R"[superscript 2] to Test the Significance of Multiple Linear Regression

ERIC Educational Resources Information Center

Quinino, Roberto C.; Reis, Edna A.; Bessegato, Lupercio F.

2013-01-01

This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. (Contains 3 figures.)

Predictors of life satisfaction among caregivers of individuals with multiple sclerosis.

PubMed

Waldron-Perrine, Brigid; Rapport, Lisa J; Ryan, Kelly A; Harper, Kaja Telmet

2009-04-01

Research on life satisfaction among caregivers of persons with multiple sclerosis (MS) is sparse. This study examined the extent to which MS-specific disease and psychosocial characteristics predict caregiver life satisfaction. Participants were 64 caregivers of patients with MS and the patients for whom they care. Multiple regression analysis indicated that caregiver perception of illness uncertainty and patients' unawareness of deficits have unique value in predicting caregiver life satisfaction, even after accounting for general financial status. Gender and level of social support were also important contributing factors to caregiver life satisfaction. The findings suggest that duration and severity of the patients' illness take a greater toll on life satisfaction of caregivers with low versus high social support, particularly among women caregivers.

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.

Quality of life among people with multiple sclerosis: Replication of a three-factor prediction model.

PubMed

Bishop, Malachy; Rumrill, Phillip D; Roessler, Richard T

2015-01-01

This article presents a replication of Rumrill, Roessler, and Fitzgerald's 2004 analysis of a three-factor model of the impact of multiple sclerosis (MS) on quality of life (QOL). The three factors in the original model included illness-related, employment-related, and psychosocial adjustment factors. To test hypothesized relationships between QOL and illness-related, employment-related, and psychosocial variables using data from a survey of the employment concerns of Americans with MS (N = 1,839). An ex post facto, multiple correlational design was employed incorporating correlational and multiple regression analyses. QOL was positively related to educational level, employment status, job satisfaction, and job-match, and negatively related to number of symptoms, severity of symptoms, and perceived stress level. The three-factor model explained approximately 37 percent of the variance in QOL scores. The results of this replication confirm the continuing value of the three-factor model for predicting the QOL of adults with MS, and demonstrate the importance of medical, mental health, and vocational rehabilitation interventions and services in promoting QOL.

Reduction of interferences in graphite furnace atomic absorption spectrometry by multiple linear regression modelling

NASA Astrophysics Data System (ADS)

Grotti, Marco; Abelmoschi, Maria Luisa; Soggia, Francesco; Tiberiade, Christian; Frache, Roberto

2000-12-01

The multivariate effects of Na, K, Mg and Ca as nitrates on the electrothermal atomisation of manganese, cadmium and iron were studied by multiple linear regression modelling. Since the models proved to efficiently predict the effects of the considered matrix elements in a wide range of concentrations, they were applied to correct the interferences occurring in the determination of trace elements in seawater after pre-concentration of the analytes. In order to obtain a statistically significant number of samples, a large volume of the certified seawater reference materials CASS-3 and NASS-3 was treated with Chelex-100 resin; then, the chelating resin was separated from the solution, divided into several sub-samples, each of them was eluted with nitric acid and analysed by electrothermal atomic absorption spectrometry (for trace element determinations) and inductively coupled plasma optical emission spectrometry (for matrix element determinations). To minimise any other systematic error besides that due to matrix effects, accuracy of the pre-concentration step and contamination levels of the procedure were checked by inductively coupled plasma mass spectrometric measurements. Analytical results obtained by applying the multiple linear regression models were compared with those obtained with other calibration methods, such as external calibration using acid-based standards, external calibration using matrix-matched standards and the analyte addition technique. Empirical models proved to efficiently reduce interferences occurring in the analysis of real samples, allowing an improvement of accuracy better than for other calibration methods.

Systematic genomic identification of colorectal cancer genes delineating advanced from early clinical stage and metastasis

PubMed Central

2013-01-01

Background Colorectal cancer is the third leading cause of cancer deaths in the United States. The initial assessment of colorectal cancer involves clinical staging that takes into account the extent of primary tumor invasion, determining the number of lymph nodes with metastatic cancer and the identification of metastatic sites in other organs. Advanced clinical stage indicates metastatic cancer, either in regional lymph nodes or in distant organs. While the genomic and genetic basis of colorectal cancer has been elucidated to some degree, less is known about the identity of specific cancer genes that are associated with advanced clinical stage and metastasis. Methods We compiled multiple genomic data types (mutations, copy number alterations, gene expression and methylation status) as well as clinical meta-data from The Cancer Genome Atlas (TCGA). We used an elastic-net regularized regression method on the combined genomic data to identify genetic aberrations and their associated cancer genes that are indicators of clinical stage. We ranked candidate genes by their regression coefficient and level of support from multiple assay modalities. Results A fit of the elastic-net regularized regression to 197 samples and integrated analysis of four genomic platforms identified the set of top gene predictors of advanced clinical stage, including: WRN, SYK, DDX5 and ADRA2C. These genetic features were identified robustly in bootstrap resampling analysis. Conclusions We conducted an analysis integrating multiple genomic features including mutations, copy number alterations, gene expression and methylation. This integrated approach in which one considers all of these genomic features performs better than any individual genomic assay. We identified multiple genes that robustly delineate advanced clinical stage, suggesting their possible role in colorectal cancer metastatic progression. PMID:24308539

Results of the 2005 AORN salary survey--trends for perioperative nursing.

PubMed

Bacon, Donald

2005-12-01

AORN conducted its annual compensation survey for perioperative nurses in August 2005. A multiple regression model was used to examine how a variety of variables, including job title, education level, certification, experience, and geographic region, affect nursing compensation. This survey also examines the effect of other forms of compensation (eg, on-call compensation, overtime, bonuses, shift differential) on average base compensation rates.

Results of the 2006 AORN salary survey: trends for perioperative nursing.

PubMed

Bacon, Donald

2006-12-01

AORN CONDUCTED ITS ANNUAL compensation survey for perioperative nurses in August 2006. MULTIPLE REGRESSION MODEL was used to examine how a variety of variables, including job title, education level, certification, experience, and geographic region, affect nursing compensation. THIS SURVEY ALSO EXAMINES the effect of other forms of compensation (eg, on-call compensation, overtime, bonuses, shift differential) on average base compensation rates.

The Relationship of Item-Level Response Times with Test-Taker and Item Variables in an Operational CAT Environment. LSAC Research Report Series.

ERIC Educational Resources Information Center

Swygert, Kimberly A.

In this study, data from an operational computerized adaptive test (CAT) were examined in order to gather information concerning item response times in a CAT environment. The CAT under study included multiple-choice items measuring verbal, quantitative, and analytical reasoning. The analyses included the fitting of regression models describing the…

Rape Myth Acceptance, Hypermasculinity, and SAT Scores as Correlates of Moral Development: Understanding Sexually Aggressive Attitudes in First-Year College Men

ERIC Educational Resources Information Center

Tatum, Jerry L.; Foubert, John D.

2009-01-01

Male perpetrated sexual aggression has long been recognized as a serious problem on college campuses. The purpose of this multiple regression correlation study was to assess the relationship between levels of moral development (measured by the Defining Issues Test) and the degree to which first-year college men (N = 161) ascribed to rape…

The M Word: Multicollinearity in Multiple Regression.

ERIC Educational Resources Information Center

Morrow-Howell, Nancy

1994-01-01

Notes that existence of substantial correlation between two or more independent variables creates problems of multicollinearity in multiple regression. Discusses multicollinearity problem in social work research in which independent variables are usually intercorrelated. Clarifies problems created by multicollinearity, explains detection of…

[Prediction model of health workforce and beds in county hospitals of Hunan by multiple linear regression].

PubMed

Ling, Ru; Liu, Jiawang

2011-12-01

To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

PubMed

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.

Species Composition at the Sub-Meter Level in Discontinuous Permafrost in Subarctic Sweden

NASA Astrophysics Data System (ADS)

Anderson, S. M.; Palace, M. W.; Layne, M.; Varner, R. K.; Crill, P. M.

2013-12-01

Northern latitudes are experiencing rapid warming. Wetlands underlain by permafrost are particularly vulnerable to warming which results in changes in vegetative cover. Specific species have been associated with greenhouse gas emissions therefore knowledge of species compositional shift allows for the systematic change and quantification of emissions and changes in such emissions. Species composition varies on the sub-meter scale based on topography and other microsite environmental parameters. This complexity and the need to scale vegetation to the landscape level proves vital in our estimation of carbon dioxide (CO2) and methane (CH4) emissions and dynamics. Stordalen Mire (68°21'N, 18°49'E) in Abisko and is located at the edge of discontinuous permafrost zone. This provides a unique opportunity to analyze multiple vegetation communities in a close proximity. To do this, we randomly selected 25 1x1 meter plots that were representative of five major cover types: Semi-wet, wet, hummock, tall graminoid, and tall shrub. We used a quadrat with 64 sub plots and measured areal percent cover for 24 species. We collected ground based remote sensing (RS) at each plot to determine species composition using an ADC-lite (near infrared, red, green) and GoPro (red, blue, green). We normalized each image based on a Teflon white chip placed in each image. Textural analysis was conducted on each image for entropy, angular second momentum, and lacunarity. A logistic regression was developed to examine vegetation cover types and remote sensing parameters. We used a multiple linear regression using forwards stepwise variable selection. We found statistical difference in species composition and diversity indices between vegetation cover types. In addition, we were able to build regression model to significantly estimate vegetation cover type as well as percent cover for specific key vegetative species. This ground-based remote sensing allows for quick quantification of vegetation cover and species and also provides the framework for scaling to satellite image data to estimate species composition and shift on the landscape level. To determine diversity within our plots we calculated species richness and Shannon Index. We found that there were statistically different species composition within each vegetation cover type and also determined which species were indicative for cover type. Our logistical regression was able to significantly classify vegetation cover types based on RS parameters. Our multiple regression analysis indicated Betunla nana (Dwarf Birch) (r2= .48, p=<0.0001) and Sphagnum (r2=0.59, p=<0.0001) were statistically significant with respect to RS parameters. We suggest that ground based remote sensing methods may provide a unique and efficient method to quantify vegetation across the landscape in northern latitude wetlands.

Teacher Consultation and Coaching within Mental Health Practice: Classroom and Child Effects in Urban Elementary Schools

PubMed Central

Cappella, Elise; Hamre, Bridget K.; Kim, Ha Yeon; Henry, David B.; Frazier, Stacy L.; Atkins, Marc S.; Schoenwald, Sonja K.

2012-01-01

Objective To examine effects of a teacher consultation and coaching program delivered by school and community mental health professionals on change in observed classroom interactions and child functioning across one school year. Method Thirty-six classrooms within five urban elementary schools (87% Latino, 11% Black) were randomly assigned to intervention (training + consultation/coaching) and control (training only) conditions. Classroom and child outcomes (n = 364; 43% girls) were assessed in the fall and spring. Results Random effects regression models showed main effects of intervention on teacher-student relationship closeness, academic self-concept, and peer victimization. Results of multiple regression models showed levels of observed teacher emotional support in the fall moderated intervention impact on emotional support at the end of the school year. Conclusions Results suggest teacher consultation and coaching can be integrated within existing mental health activities in urban schools and impact classroom effectiveness and child adaptation across multiple domains. PMID:22428941

Improvement of the air quality in student health centers with chlorine dioxide.

PubMed

Hsu, Ching-Shan; Huang, Da-Ji; Lu, Ming-Chun

2010-04-01

This study aims to monitor bioaerosol levels of a local campus of a student health center in Taiwan and then to perform disinfection by applying chlorine dioxide. First, air samples were taken and evaluated in the six areas of the center. The average background bioaerosol levels were 714 +/- 1706 CFU/m(3) for bacterium and 802 +/- 633 CFU/m(3) for fungi. Then, chlorine dioxide was applied through three different procedures: single, multiple and regular disinfections. The results indicated that both multiple and regular disinfections can achieve efficiency levels higher than 59.0%. The regression analysis on bioaerosol levels showed that the number of people present correlating to the number of persons entering the room per door-opening, had a correlation of p < 0.05. Utilizing this analysis result, an empirical model was developed to predict indoor bioaerosol concentrations. It can be inferred that for indoor human activity of health centers, regular disinfection is a very effective process.

Missing data treatments matter: an analysis of multiple imputation for anterior cervical discectomy and fusion procedures.

PubMed

Ondeck, Nathaniel T; Fu, Michael C; Skrip, Laura A; McLynn, Ryan P; Cui, Jonathan J; Basques, Bryce A; Albert, Todd J; Grauer, Jonathan N

2018-04-09

The presence of missing data is a limitation of large datasets, including the National Surgical Quality Improvement Program (NSQIP). In addressing this issue, most studies use complete case analysis, which excludes cases with missing data, thus potentially introducing selection bias. Multiple imputation, a statistically rigorous approach that approximates missing data and preserves sample size, may be an improvement over complete case analysis. The present study aims to evaluate the impact of using multiple imputation in comparison with complete case analysis for assessing the associations between preoperative laboratory values and adverse outcomes following anterior cervical discectomy and fusion (ACDF) procedures. This is a retrospective review of prospectively collected data. Patients undergoing one-level ACDF were identified in NSQIP 2012-2015. Perioperative adverse outcome variables assessed included the occurrence of any adverse event, severe adverse events, and hospital readmission. Missing preoperative albumin and hematocrit values were handled using complete case analysis and multiple imputation. These preoperative laboratory levels were then tested for associations with 30-day postoperative outcomes using logistic regression. A total of 11,999 patients were included. Of this cohort, 63.5% of patients had missing preoperative albumin and 9.9% had missing preoperative hematocrit. When using complete case analysis, only 4,311 patients were studied. The removed patients were significantly younger, healthier, of a common body mass index, and male. Logistic regression analysis failed to identify either preoperative hypoalbuminemia or preoperative anemia as significantly associated with adverse outcomes. When employing multiple imputation, all 11,999 patients were included. Preoperative hypoalbuminemia was significantly associated with the occurrence of any adverse event and severe adverse events. Preoperative anemia was significantly associated with the occurrence of any adverse event, severe adverse events, and hospital readmission. Multiple imputation is a rigorous statistical procedure that is being increasingly used to address missing values in large datasets. Using this technique for ACDF avoided the loss of cases that may have affected the representativeness and power of the study and led to different results than complete case analysis. Multiple imputation should be considered for future spine studies. Copyright © 2018 Elsevier Inc. All rights reserved.

Clinical relevance of valgus deformity of proximal femur in cerebral palsy.

PubMed

Lee, Kyoung Min; Kang, Jong Yeol; Chung, Chin Youb; Kwon, Dae Gyu; Lee, Sang Hyeong; Choi, In Ho; Cho, Tae-Joon; Yoo, Won Joon; Park, Moon Seok

2010-01-01

Proximal femoral deformity related to physis has not been studied in patients with cerebral palsy (CP). This study was performed to investigate the clinical relevance of neck shaft angle (NSA), head shaft angle (HSA), and proximal femoral epiphyseal shape in patients with CP, which represent the deformities of metaphysis, physis, and epiphysis, respectively. Three hundred eighty-four patients with CP (mean age 9.1 y, 249 males and 135 females) were included. Extent of involvement and functional states [Gross Motor Function Classification System (GMFCS) level] were obtained. Radiographic measurements including NSA, HSA, and qualitative shape of the proximal femoral epiphysis were evaluated and analyzed according to extent of involvement and GMFCS level. Reliability and correlation with each measurement were assessed. Multiple regression test was performed to examine the significant contributing factors to migration percentage (MP) that represents hip instability. NSA showed excellent interobserver reliability with intraclass correlation coefficients of 0.976. Correlation with the MP was higher in the NSA (r=0.419, P<0.001) than in the HSA (r=0.256, P<0.001). NSA, HSA, and MP tended to increase with increasing GMFCS level, and proportion of valgus deformed proximal femoral epiphysis also increased with increasing GMFCS level, which means valgus deformity and unstable hips in the less favorable functional states. Multiple regression analysis revealed NSA, GMFCS level, and shape of the proximal femoral epiphysis to be significant factors affecting MP. NSA appeared to be more clinically relevant than HSA in evaluating proximal femoral deformity in patients with CP. Shape of proximal femoral epiphysis is believed to have clinical implications in terms of hip instability. Diagnostic level II.

Interleukin-6 Level among Shift and Night Workers in Japan: Cross-Sectional Analysis of the J-HOPE Study.

PubMed

Amano, Hoichi; Fukuda, Yoshiharu; Yokoo, Takashi; Yamaoka, Kazue

2018-03-27

Shift workers have a high risk of cardiovascular disease (CVD). Systemic inflammation measured has been associated with the risk of CVD onset, in addition to classical risk factors. However, the association between work schedule and inflammatory cytokine levels remains unclear. The purpose of this study was to examine the association between work schedule and interleukin-6 (IL-6)/high-sensitivity C-reactive protein (hs-CRP) levels among Japanese workers. The present cross-sectional study was a part of the Japanese Study of Health, Occupation and Psychosocial Factors Related Equity (J-HOPE). A total of 5259 persons who measured inflammatory cytokine were analyzed in this study. One-way analysis of variance was used to test log-transformed IL-6/hs-CRP differences by work schedule. Multiple regression analysis was used to examine the difference adjusted for other possible CVD risk factors. There were 3660 participants who had a regular work schedule; the remaining schedules were shift work without night work for 181 participants, shift work with night work for 1276 participants, and only night work for 142 participants. The unadjusted model showed that only night workers were significantly related to high levels of IL-6 compared with regular workers. Even in the multiple regression analysis, the higher level of IL-6 among only night workers remained significant (β=0.058, P=0.01). On the contrary, hs-CRP was not. The present study revealed that only night shift work is significantly associated with high levels of IL-6 in Japanese workers. These observations help us understand the mechanism for the association between work schedule and CVD onset.

[Impact of air pollution in paediatric consultations in Primary Health Care: Ecological study].

PubMed

Martín Martín, Raquel; Sánchez Bayle, Marciano

2017-08-09

To study the correlation between the levels of environmental pollutants and the number of paediatric consultations related to respiratory disease in Primary Health Care. An ecological study is performed, in which the dependent variable analysed was the number of paediatric consultations in an urban Primary Health Care centre in Madrid over a 3 year period (2013-2015), and specifically the consultations related to bronchiolitis, recurrent bronchospasm, and upper respiratory diseases. The independent variables analysed were the levels of environmental pollutants. Coefficients of correlation and multiple lineal regressions were calculated. An analysis has been carried out comparing the average of paediatric consultations when the levels of nitrogen dioxide (NO 2 ) were higher and lower than 40μg/m 3. RESULTS: During the period of the study, there were a total of 52,322 paediatric consultations in the health centre, of which 6,473 (12.37%) were related to respiratory diseases. A positive correlation was found between SO 2 , CO, NOx and NO 2 and benzene levels and paediatric consultations related to respiratory diseases, and a negative correlation with temperature. The number of consultations was significantly higher when NO 2 levels exceeded 40μg/m 3 . In the multiple lineal regression (P=.0001), the correlation was only positive between consultations and NO 2 levels (3.630, 95% CI: 0.691-6.570), and negative with temperature (-5,957, 95% CI: -8.665 to -3.248). NO 2 environmental pollution is related to an increase in respiratory diseases in children. Paediatricians should contribute to promote an improvement in urban air quality as a significant preventive measure. Copyright © 2017. Publicado por Elsevier España, S.L.U.

Resilience and Associated Factors among Mainland Chinese Women Newly Diagnosed with Breast Cancer.

PubMed

Wu, Zijing; Liu, Ye; Li, Xuelian; Li, Xiaohan

2016-01-01

Resilience is the individual's ability to bounce back from trauma. It has been studied for some time in the U.S., but few studies in China have addressed this important construct. In mainland China, relatively little is known about the resilience of patients in clinical settings, especially among patients with breast cancer. In this study, we aimed to evaluate the level of resilience and identify predictors of resilience among mainland Chinese women newly diagnosed with breast cancer. A cross-sectional descriptive study was conducted with 213 mainland Chinese women newly diagnosed with breast cancer between November 2014 and June 2015. Participants were assessed with the Connor-Davidson Resilience Scale (CD-RISC), Social Support Rating Scale (SSRS), Medical Coping Modes Questionnaire (MCMQ, including 3 subscales: confrontation, avoidance, and acceptance-resignation), Herth Hope Index (HHI), and demographic and disease-related information. Descriptive statistics, bivariate analyses and multiple stepwise regression were conducted to explore predictors for resilience. The average score for CD-RISC was 60.97, ranging from 37 to 69. Resilience was positively associated with educational level, family income, time span after diagnosis, social support, confrontation, avoidance, and hope. However, resilience was negatively associated with age, body mass index (BMI), and acceptance-resignation. Multiple stepwise regression analysis indicated that hope (β = 0.343, P<0.001), educational level of junior college or above (β = 0.272, P<0.001), educational level of high school (β = 0.235, P<0.001), avoidance (β = 0.220, P<0.001), confrontation (β = 0.187, P = 0.001), and age (β = -0.108, P = 0.037) significantly affected resilience and explained 50.1% of the total variance in resilience. Women with newly diagnosed breast cancer from mainland China demonstrated particularly low resilience level, which was predicted by hope educational level, avoidance, confrontation, and age.

[High Risk Sex Behaviors and Associated Factors in Young Men in Chengdu].

PubMed

2015-11-01

To determine the prevalence of high risk sex behaviors and associated factors in 18-34 years old men in Chengdu. Methods An anonymous questionnaire survey was conducted in 18-34 years old men selected by multi-stage random sampling in Chengdu. Data of 1536 respondents who reported having sex contacts were analyzed. 23.6% of respondents had multiple sex partners in the past 12 months; 11.8% were involved commercial sex; 9.0% had group sex; 4. 7% had anal sex; 15.6% had never used a condom; 37.7% had sex under the influence of alcohol or drugs. Logistic regression analysis revealed that marital status [married, standardized partial regression coefficient (B) = -0.086, P<0.05] , level of education (bachelor or above, B= -0.063, P<0.05), frequency of exposure to pornography (B=0.058, P<0.05), childhood sexual abuse (B= 0.042, P<0.05), first sexual intercourse at an earlier age (B=0.162, P<0.05), frequency of sex under the influence of alcohol or drugs (B=0.054, P<0.05) were significant predictors of having multiple sexual partners. Sexual orientation, age, smoking, alcohol abuse, drug use, anxiety, depression, childhood physical abuse did not appear to be significant factors associated with having multiple sexual partners. Having multiple sexual partners is the main high risk sex behavior of young men in Chengdu. Childhood sexual abuse and early start of sexual intercourse are the major predictors of having multiple sexual partners.

Burnout, stress and satisfaction among Australian and New Zealand radiation oncology trainees.

PubMed

Leung, John; Rioseco, Pilar

2017-02-01

To evaluate the incidence of burnout among radiation oncology trainees in Australia and New Zealand and the stress and satisfaction factors related to burnout. A survey of trainees was conducted in mid-2015. There were 42 Likert scale questions on stress, 14 Likert scale questions on satisfaction and the Maslach Burnout Inventory-Human Services Survey assessed burnout. A principal component analysis identified specific stress and satisfaction areas. Categorical variables for the stress and satisfaction factors were computed. Associations between respondent's characteristics and stress and satisfaction subscales were examined by independent sample t-tests and analysis of variance. Effect sizes were calculated using Cohens's d when significant mean differences were observed. This was also done for respondent characteristics and the three burnout subscales. Multiple regression analyses were performed. The response rate was 81.5%. The principal component analysis for stress identified five areas: demands on time, professional development/training, delivery demands, interpersonal demands and administration/organizational issues. There were no significant differences by demographic group or area of interest after P-values were adjusted for the multiple tests conducted. The principal component analysis revealed two satisfaction areas: resources/professional activities and value/delivery of services. There were no significant differences by demographic characteristics or area of interest in the level of satisfaction after P-values were adjusted for the multiple tests conducted. The burnout results revealed 49.5% of respondents scored highly in emotional exhaustion and/or depersonalization and 13.1% had burnout in all three measures. Multiple regression analysis revealed the stress subscales 'demands on time' and 'interpersonal demands' were associated with emotional exhaustion. 'Interpersonal demands' was also associated with depersonalization and correlated negatively with personal accomplishment. The satisfaction of value/delivery of services subscale was associated with higher levels of personal accomplishment. There is a significant level of burnout among radiation oncology trainees in Australia and New Zealand. Further work addressing intervention would be appropriate to reduce levels of burnout. © 2016 The Authors. Journal of Medical Imaging and Radiation Oncology published by John Wiley & Sons Australia, Ltd on behalf of The Royal Australian and New Zealand College of Radiologists.

SOME STATISTICAL ISSUES RELATED TO MULTIPLE LINEAR REGRESSION MODELING OF BEACH BACTERIA CONCENTRATIONS

EPA Science Inventory

As a fast and effective technique, the multiple linear regression (MLR) method has been widely used in modeling and prediction of beach bacteria concentrations. Among previous works on this subject, however, several issues were insufficiently or inconsistently addressed. Those is...

MULTIPLE REGRESSION MODELS FOR HINDCASTING AND FORECASTING MIDSUMMER HYPOXIA IN THE GULF OF MEXICO

EPA Science Inventory

A new suite of multiple regression models were developed that describe the relationship between the area of bottom water hypoxia along the northern Gulf of Mexico and Mississippi-Atchafalaya River nitrate concentration, total phosphorus (TP) concentration, and discharge. Variabil...

Estimate the contribution of incubation parameters influence egg hatchability using multiple linear regression analysis

PubMed Central

Khalil, Mohamed H.; Shebl, Mostafa K.; Kosba, Mohamed A.; El-Sabrout, Karim; Zaki, Nesma

2016-01-01

Aim: This research was conducted to determine the most affecting parameters on hatchability of indigenous and improved local chickens’ eggs. Materials and Methods: Five parameters were studied (fertility, early and late embryonic mortalities, shape index, egg weight, and egg weight loss) on four strains, namely Fayoumi, Alexandria, Matrouh, and Montazah. Multiple linear regression was performed on the studied parameters to determine the most influencing one on hatchability. Results: The results showed significant differences in commercial and scientific hatchability among strains. Alexandria strain has the highest significant commercial hatchability (80.70%). Regarding the studied strains, highly significant differences in hatching chick weight among strains were observed. Using multiple linear regression analysis, fertility made the greatest percent contribution (71.31%) to hatchability, and the lowest percent contributions were made by shape index and egg weight loss. Conclusion: A prediction of hatchability using multiple regression analysis could be a good tool to improve hatchability percentage in chickens. PMID:27651666

Mean centering, multicollinearity, and moderators in multiple regression: The reconciliation redux.

PubMed

Iacobucci, Dawn; Schneider, Matthew J; Popovich, Deidre L; Bakamitsos, Georgios A

2017-02-01

In this article, we attempt to clarify our statements regarding the effects of mean centering. In a multiple regression with predictors A, B, and A × B (where A × B serves as an interaction term), mean centering A and B prior to computing the product term can clarify the regression coefficients (which is good) and the overall model fit R 2 will remain undisturbed (which is also good).

A Common Mechanism for Resistance to Oxime Reactivation of Acetylcholinesterase Inhibited by Organophosphorus Compounds

DTIC Science & Technology

2013-01-01

application of the Hammett equation with the constants rph in the chemistry of organophosphorus compounds, Russ. Chem. Rev. 38 (1969) 795–811. [13...of oximes and OP compounds and the ability of oximes to reactivate OP- inhibited AChE. Multiple linear regression equations were analyzed using...phosphonate pairs, 21 oxime/ phosphoramidate pairs and 12 oxime/phosphate pairs. The best linear regression equation resulting from multiple regression anal

Neurofilament light chain and oligoclonal bands are prognostic biomarkers in radiologically isolated syndrome.

PubMed

Matute-Blanch, Clara; Villar, Luisa M; Álvarez-Cermeño, José C; Rejdak, Konrad; Evdoshenko, Evgeniy; Makshakov, Gleb; Nazarov, Vladimir; Lapin, Sergey; Midaglia, Luciana; Vidal-Jordana, Angela; Drulovic, Jelena; García-Merino, Antonio; Sánchez-López, Antonio J; Havrdova, Eva; Saiz, Albert; Llufriu, Sara; Alvarez-Lafuente, Roberto; Schroeder, Ina; Zettl, Uwe K; Galimberti, Daniela; Ramió-Torrentà, Lluís; Robles, René; Quintana, Ester; Hegen, Harald; Deisenhammer, Florian; Río, Jordi; Tintoré, Mar; Sánchez, Alex; Montalban, Xavier; Comabella, Manuel

2018-04-01

The prognostic role of cerebrospinal fluid molecular biomarkers determined in early pathogenic stages of multiple sclerosis has yet to be defined. In the present study, we aimed to investigate the prognostic value of chitinase 3 like 1 (CHI3L1), neurofilament light chain, and oligoclonal bands for conversion to clinically isolated syndrome and to multiple sclerosis in 75 patients with radiologically isolated syndrome. Cerebrospinal fluid levels of CHI3L1 and neurofilament light chain were measured by enzyme-linked immunosorbent assay. Uni- and multivariable Cox regression models including as covariates age at diagnosis of radiologically isolated syndrome, number of brain lesions, sex and treatment were used to investigate associations between cerebrospinal fluid CHI3L1 and neurofilament light chain levels and time to conversion to clinically isolated syndrome and multiple sclerosis. Neurofilament light chain levels and oligoclonal bands were independent risk factors for the development of clinically isolated syndrome (hazard ratio = 1.02, P = 0.019, and hazard ratio = 14.7, P = 0.012, respectively) and multiple sclerosis (hazard ratio = 1.03, P = 0.003, and hazard ratio = 8.9, P = 0.046, respectively). The best cut-off to classify cerebrospinal fluid neurofilament light chain levels into high and low was 619 ng/l, and high neurofilament light chain levels were associated with a trend to shorter time to clinically isolated syndrome (P = 0.079) and significant shorter time to multiple sclerosis (P = 0.017). Similarly, patients with radiologically isolated syndrome presenting positive oligoclonal bands converted faster to clinically isolated syndrome and multiple sclerosis (P = 0.005 and P = 0.008, respectively). The effects of high neurofilament light chain levels shortening time to clinically isolated syndrome and multiple sclerosis were more pronounced in radiologically isolated syndrome patients with ≥37 years compared to younger patients. Cerebrospinal fluid CHI3L1 levels did not influence conversion to clinically isolated syndrome and multiple sclerosis in radiologically isolated syndrome patients. Overall, these findings suggest that cerebrospinal neurofilament light chain levels and oligoclonal bands are independent predictors of clinical conversion in patients with radiologically isolated syndrome. The association with a faster development of multiple sclerosis reinforces the importance of cerebrospinal fluid analysis in patients with radiologically isolated syndrome.

Psychological and biographical differences between secondary school teachers experiencing high and low levels of burnout.

PubMed

Pierce, C M; Molloy, G N

1990-02-01

A total of 750 teachers from 16 government and non-government schools from areas of contrasted socio-economic status (SES) responded to a questionnaire designed to investigate associations between selected aspects of burnout among teachers working in secondary schools in Victoria, Australia. By comparing high and low burnout groups on biographic, psychological and work pattern variables, differences between teachers experiencing high and low levels of burnout were identified. Multiple regression analyses assessed the relative importance of these variables in accounting for the variance in each of the three burnout subscales. School type was related to perceptions of stress and burnout. Higher levels of burnout were associated with poorer physical health, higher rates of absenteeism, lower self-confidence and more frequent use of regressive coping strategies. Teachers classified as experiencing high levels of burnout attributed most of the stress in their lives to teaching and reported low levels of career commitment and satisfaction. Further, teachers who recorded high levels of burnout were characterised by lower levels of the personality disposition of hardiness, lower levels of social support, higher levels of role stress and more custodial pupil control ideologies than their low-burnout counterparts. Psychological variables were found to be more significant predictors of burnout than biographical variables.

Association of serum uric acid with high-sensitivity C-reactive protein in postmenopausal women.

PubMed

Raeisi, A; Ostovar, A; Vahdat, K; Rezaei, P; Darabi, H; Moshtaghi, D; Nabipour, I

2017-02-01

To explore the independent correlation between serum uric acid and low-grade inflammation (measured by high-sensitivity C-reactive protein, hs-CRP) in postmenopausal women. A total of 378 healthy Iranian postmenopausal women were randomly selected in a population-based study. Circulating hs-CRP levels were measured by highly specific enzyme-linked immunosorbent assay method and an enzymatic calorimetric method was used to measure serum levels of uric acid. Pearson correlation coefficient, multiple linear regression and logistic regression models were used to analyze the association between uric acid and hs-CRP levels. A statistically significant correlation was seen between serum levels of uric acid and log-transformed circulating hs-CRP (r = 0.25, p < 0.001). After adjustment for age and cardiovascular risk factors (according to NCEP ATP III criteria), circulating hs-CRP levels were significantly associated with serum uric acid levels (β = 0.20, p < 0.001). After adjustment for age and cardiovascular risk factors, hs-CRP levels ≥3 mg/l were significantly associated with higher uric acid levels (odds ratio =1.52, 95% confidence interval 1.18-1.96). Higher serum uric acid levels were positively and independently associated with circulating hs-CRP in healthy postmenopausal women.

Effects of export concentration on CO2 emissions in developed countries: an empirical analysis.

PubMed

Apergis, Nicholas; Can, Muhlis; Gozgor, Giray; Lau, Chi Keung Marco

2018-03-08

This paper provides the evidence on the short- and the long-run effects of the export product concentration on the level of CO 2 emissions in 19 developed (high-income) economies, spanning the period 1962-2010. To this end, the paper makes use of the nonlinear panel unit root and cointegration tests with multiple endogenous structural breaks. It also considers the mean group estimations, the autoregressive distributed lag model, and the panel quantile regression estimations. The findings illustrate that the environmental Kuznets curve (EKC) hypothesis is valid in the panel dataset of 19 developed economies. In addition, it documents that a higher level of the product concentration of exports leads to lower CO 2 emissions. The results from the panel quantile regressions also indicate that the effect of the export product concentration upon the per capita CO 2 emissions is relatively high at the higher quantiles.

Multivariate Boosting for Integrative Analysis of High-Dimensional Cancer Genomic Data

PubMed Central

Xiong, Lie; Kuan, Pei-Fen; Tian, Jianan; Keles, Sunduz; Wang, Sijian

2015-01-01

In this paper, we propose a novel multivariate component-wise boosting method for fitting multivariate response regression models under the high-dimension, low sample size setting. Our method is motivated by modeling the association among different biological molecules based on multiple types of high-dimensional genomic data. Particularly, we are interested in two applications: studying the influence of DNA copy number alterations on RNA transcript levels and investigating the association between DNA methylation and gene expression. For this purpose, we model the dependence of the RNA expression levels on DNA copy number alterations and the dependence of gene expression on DNA methylation through multivariate regression models and utilize boosting-type method to handle the high dimensionality as well as model the possible nonlinear associations. The performance of the proposed method is demonstrated through simulation studies. Finally, our multivariate boosting method is applied to two breast cancer studies. PMID:26609213

Deficiencies of Circulating Mucosal-associated Invariant T Cells and Natural Killer T Cells in Patients with Multiple Trauma.

PubMed

Jo, Young Goun; Choi, Hyun Jung; Kim, Jung Chul; Cho, Young Nan; Kang, Jeong Hwa; Jin, Hye Mi; Kee, Seung Jung; Park, Yong Wook

2017-05-01

Mucosal-associated invariant T (MAIT) cells and natural killer T (NKT) cells are known to play important roles in autoimmunity, infectious diseases and cancers. However, little is known about the roles of these invariant T cells in multiple trauma. The purposes of this study were to examine MAIT and NKT cell levels in patients with multiple trauma and to investigate potential relationships between these cell levels and clinical parameters. The study cohort was composed of 14 patients with multiple trauma and 22 non-injured healthy controls (HCs). Circulating MAIT and NKT cell levels in the peripheral blood were measured by flow cytometry. The severity of injury was categorised according to the scoring systems, such as Acute Physiology and Chronic Health Evaluation (APACHE) II score, Simplified Acute Physiology Score (SAPS) II, and Injury Severity Score (ISS). Circulating MAIT and NKT cell numbers were significantly lower in multiple trauma patients than in HCs. Linear regression analysis showed that circulating MAIT cell numbers were significantly correlated with age, APACHE II, SAPS II, ISS category, hemoglobin, and platelet count. NKT cell numbers in the peripheral blood were found to be significantly correlated with APACHE II, SAPS II, and ISS category. This study shows numerical deficiencies of circulating MAIT cells and NKT cells in multiple trauma. In addition, these invariant T cell deficiencies were found to be associated with disease severity. These findings provide important information for predicting the prognosis of multiple trauma. © 2017 The Korean Academy of Medical Sciences.

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.

Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.

PubMed

He, Dan; Kuhn, David; Parida, Laxmi

2016-06-15

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.

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

Penna, M.L.; Duchiade, M.P.

The authors report the results of an investigation into the possible association between air pollution and infant mortality from pneumonia in the Rio de Janeiro Metropolitan Area. This investigation employed multiple linear regression analysis (stepwise method) for infant mortality from pneumonia in 1980, including the study population's areas of residence, incomes, and pollution exposure as independent variables. With the income variable included in the regression, a statistically significant association was observed between the average annual level of particulates and infant mortality from pneumonia. While this finding should be accepted with caution, it does suggest a biological association between these variables.more » The authors' conclusion is that air quality indicators should be included in studies of acute respiratory infections in developing countries.« less

Multiple imputation for cure rate quantile regression with censored data.

PubMed

Wu, Yuanshan; Yin, Guosheng

2017-03-01

The main challenge in the context of cure rate analysis is that one never knows whether censored subjects are cured or uncured, or whether they are susceptible or insusceptible to the event of interest. Considering the susceptible indicator as missing data, we propose a multiple imputation approach to cure rate quantile regression for censored data with a survival fraction. We develop an iterative algorithm to estimate the conditionally uncured probability for each subject. By utilizing this estimated probability and Bernoulli sample imputation, we can classify each subject as cured or uncured, and then employ the locally weighted method to estimate the quantile regression coefficients with only the uncured subjects. Repeating the imputation procedure multiple times and taking an average over the resultant estimators, we obtain consistent estimators for the quantile regression coefficients. Our approach relaxes the usual global linearity assumption, so that we can apply quantile regression to any particular quantile of interest. We establish asymptotic properties for the proposed estimators, including both consistency and asymptotic normality. We conduct simulation studies to assess the finite-sample performance of the proposed multiple imputation method and apply it to a lung cancer study as an illustration. © 2016, The International Biometric Society.

Plasma and serum L-selectin and clinical and subclinical the Multi-Ethnic Study of Atherosclerosis (MESA)cardiovascular disease

PubMed Central

BERARDI, CECILIA; DECKER, PAUL A.; KIRSCH, PHILLIP S.; DE ANDRADE, MARIZA; TSAI, MICHAEL Y.; PANKOW, JAMES S.; SALE, MICHELE M.; SICOTTE, HUGUES; TANG, WEIHONG; HANSON, NAOMI; POLAK, JOSEPH F.; BIELINSKI, SUZETTE J.

2014-01-01

L-selectin has been suggested to play a role in atherosclerosis. Previous studies on cardiovascular disease (CVD) and serum or plasma L-selectin are inconsistent. The association of serum L-selectin (sL-selectin) with carotid intima-media thickness, coronary artery calcium, ankle-brachial index (subclinical CVD) and incident CVD was assessed within 2403 participants in the Multi-Ethnic Study of Atherosclerosis (MESA). Regression analysis and the Tobit model were used to study subclinical disease; Cox Proportional Hazards regression for incident CVD. Mean age was 63 ± 10, 47% were males; mean sL-selectin was significantly different across ethnicities. Within each race/ethnicity, sL-selectin was associated with age and sex; among Caucasians and African Americans, it was associated with smoking status and current alcohol use. sL-selectin levels did not predict subclinical or clinical CVD after correction for multiple comparisons. Conditional logistic regression models were used to study plasma L-selectin and CVD within 154 incident CVD cases, occurred in a median follow up of 8.5 years, and 306 age-, sex-, and ethnicity-matched controls. L-selectin levels in plasma were significantly lower than in serum and the overall concordance was low. Plasma levels were not associated with CVD. In conclusion, this large multi-ethnic population, soluble L-selectin levels did not predict clinical or subclinical CVD. PMID:24631064

Peripheral arterial stiffness is associated with higher baseline plasma uric acid: A prospective cohort study.

PubMed

Ding, Xiaohan; Ye, Ping; Wang, Xiaona; Cao, Ruihua; Yang, Xu; Xiao, Wenkai; Zhang, Yun; Bai, Yongyi; Wu, Hongmei

2017-03-01

This prospective cohort study aimed at identifying association between uric acid (UA) and peripheral arterial stiffness. A prospective cohort longitudinal study was performed according to an average of 4.8 years' follow-up. The demographic data, anthropometric parameters, peripheral arterial stiffness (carotid-radial pulse-wave velocity, cr-PWV) and biomarker variables including UA were examined at both baseline and follow-up. Pearson's correlations were used to identify the associations between UA and peripheral arterial stiffness. Further logistic regressions were employed to determine the associations between UA and arterial stiffness. At the end of follow-up, 1447 subjects were included in the analyses. At baseline, cr-PWV ( r  = 0.200, p  < 0.001) was closely associated with UA. Furthermore, the follow-up cr-PWV ( r  = 0.145, p  < 0.001) was also strongly correlated to baseline UA in Pearson's correlation analysis. Multiple regressions also indicated the association between follow-up cr-PWV ( β  = 0.493, p  = 0.013) and baseline UA level. Logistic regressions revealed that higher baseline UA level was an independent predictor of arterial stiffness severity assessed by cr-PWV at follow-up cross-section. Peripheral arterial stiffness is closely associated with higher baseline UA level. Furthermore, a higher baseline UA level is an independent risk factor and predictor for peripheral arterial stiffness.

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…

MULGRES: a computer program for stepwise multiple regression analysis

Treesearch

A. Jeff Martin

1971-01-01

MULGRES is a computer program source deck that is designed for multiple regression analysis employing the technique of stepwise deletion in the search for most significant variables. The features of the program, along with inputs and outputs, are briefly described, with a note on machine compatibility.

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)

Prediction system of hydroponic plant growth and development using algorithm Fuzzy Mamdani method

NASA Astrophysics Data System (ADS)

Sudana, I. Made; Purnawirawan, Okta; Arief, Ulfa Mediaty

2017-03-01

Hydroponics is a method of farming without soil. One of the Hydroponic plants is Watercress (Nasturtium Officinale). The development and growth process of hydroponic Watercress was influenced by levels of nutrients, acidity and temperature. The independent variables can be used as input variable system to predict the value level of plants growth and development. The prediction system is using Fuzzy Algorithm Mamdani method. This system was built to implement the function of Fuzzy Inference System (Fuzzy Inference System/FIS) as a part of the Fuzzy Logic Toolbox (FLT) by using MATLAB R2007b. FIS is a computing system that works on the principle of fuzzy reasoning which is similar to humans' reasoning. Basically FIS consists of four units which are fuzzification unit, fuzzy logic reasoning unit, base knowledge unit and defuzzification unit. In addition to know the effect of independent variables on the plants growth and development that can be visualized with the function diagram of FIS output surface that is shaped three-dimensional, and statistical tests based on the data from the prediction system using multiple linear regression method, which includes multiple linear regression analysis, T test, F test, the coefficient of determination and donations predictor that are calculated using SPSS (Statistical Product and Service Solutions) software applications.

Lifestyle and Genetic Predictors of Stiffness Index in Community-dwelling Elderly Korean Men and Women.

PubMed

Park, Kyung-Ae; Park, Yeon-Hwan; Suh, Min-Hee; Choi-Kwon, Smi

2015-09-01

Differing lifestyle, nutritional, and genetic factors may lead to a differing stiffness index (SI) determined by quantitative ultrasound in elderly men and women. The purpose of this study was to determine SI and the gender-specific factors associated with low SI in a Korean elderly cohort. This was a cross-sectional descriptive study identifying the gender-specific factors related to SI in 252 men and women aged 65 years and greater from local senior centers in Seoul, Korea between January and February 2009. The mean SI of elderly men was significantly higher than that of the women's. A multiple regression analysis reveals that age, nutritional status, and physical activity were predictive factors of lower SI in men, whereas age, alcohol consumption, educational level, and genetic polymorphism were predictive factors for elderly women. Low SI was common in both elderly men and women. We found gender differences in factors linked to low SI. In multiple regression analysis, nutritional status and physical activity were more important factors in men, whereas alcohol consumption, educational level, and genetic polymorphism were significant factors predicting low SI in women. Gender-specific modifiable risk factors associated with low SI should be considered when developing osteoporosis prevention programs for the elderly. Copyright © 2015. Published by Elsevier B.V.

The effect of working in an infection isolation room on hospital nurses' job satisfaction.

PubMed

Kagan, Ilya; Fridman, Shoshana; Shalom, Esther; Melnikov, Semyon

2018-03-01

To examine how the nature of working in a carbapenemase-producing Klebsiella pneumoniae infection isolation room affects nurses' job performance and job satisfaction. Job satisfaction is under intensive research as a factor in the retention of nursing staff. In a cross-sectional design study, a convenience sample of 87 registered nurses who had worked in carbapenemase-producing Klebsiella pneumoniae isolation rooms in a tertiary medical centre in Israel answered a self-administered questionnaire. Data were analysed by descriptive statistics, Pearson correlation coefficients, t tests, one-way ANOVA and multiple regression analysis. Job satisfaction was significantly correlated with perceived knowledge of carbapenemase-producing Klebsiella pneumoniae, with personal experience of working in an isolation room and the perceived level of professional functioning. Multiple regression analysis found that the quality of the nurses' personal experience of isolation room work and their perceived level of professional functioning there explained 33% of the variance in job satisfaction. Managers need to take into account that prolonged work in isolation can negatively impinge upon both performance and job satisfaction. Managers can consider refraining from lengthy nurse assignment to the isolation room. This would also apply to other areas of nursing practice where work is performed in isolation. © 2017 John Wiley & Sons Ltd.

Depression in non-Korean women residing in South Korea following marriage to Korean men.

PubMed

Kim, Hyun-Sil; Kim, Hun-Soo

2013-06-01

The purpose of the study was to examine the roles of acculturative stress, life satisfaction, and language literacy in depression in non-Korean women residing in South Korea following marriage to Korean men. A cross-sectional study was performed, using an anonymous, self-reporting questionnaire. A total of 173 women were selected using a proportional stratified random sampling method. The relation between acculturation, depression, language literacy, life satisfaction and socio-demographic variables and the predictors of depression among participants were analyzed. The analysis included descriptive statistics and hierarchical multiple regression. Of the participants, 9.2% had depression, which was almost twice the rate of depression found in the general Korean population. In hierarchical multiple regression analysis, acculturative stress (beta=-.325, P<.001) and life satisfaction (beta=-.282, P=.003) were significantly associated with the level of depression. This final model was statistically significant and life satisfaction, acculturative stress, language literacy accounted for 31.0% (adjusted R(2)) of the variance in the depression score (P<.001). Elevated acculturative stress and less life satisfaction were significantly associated with a higher level of depression in migrant wives in Korea. Implications for practice and research are discussed. Copyright © 2013 Elsevier Inc. All rights reserved.

Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

PubMed

Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

2016-01-01

Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

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.

Advanced Statistics for Exotic Animal Practitioners.

PubMed

Hodsoll, John; Hellier, Jennifer M; Ryan, Elizabeth G

2017-09-01

Correlation and regression assess the association between 2 or more variables. This article reviews the core knowledge needed to understand these analyses, moving from visual analysis in scatter plots through correlation, simple and multiple linear regression, and logistic regression. Correlation estimates the strength and direction of a relationship between 2 variables. Regression can be considered more general and quantifies the numerical relationships between an outcome and 1 or multiple variables in terms of a best-fit line, allowing predictions to be made. Each technique is discussed with examples and the statistical assumptions underlying their correct application. Copyright © 2017 Elsevier Inc. All rights reserved.

Reduced gamma-aminobutyric acid concentration is associated with physical disability in progressive multiple sclerosis

PubMed Central

Solanky, Bhavana S.; Muhlert, Nils; Tur, Carmen; Edden, Richard A. E.; Wheeler-Kingshott, Claudia A. M.; Miller, David H.; Thompson, Alan J.; Ciccarelli, Olga

2015-01-01

Neurodegeneration is thought to be the major cause of ongoing, irreversible disability in progressive stages of multiple sclerosis. Gamma-aminobutyric acid is the principle inhibitory neurotransmitter in the brain. The aims of this study were to investigate if gamma-aminobutyric acid levels (i) are abnormal in patients with secondary progressive multiple sclerosis compared with healthy controls; and (ii) correlate with physical and cognitive performance in this patient population. Thirty patients with secondary progressive multiple sclerosis and 17 healthy control subjects underwent single-voxel MEGA-PRESS (MEscher-GArwood Point RESolved Spectroscopy) magnetic resonance spectroscopy at 3 T, to quantify gamma-aminobutyric acid levels in the prefrontal cortex, right hippocampus and left sensorimotor cortex. All subjects were assessed clinically and underwent a cognitive assessment. Multiple linear regression models were used to compare differences in gamma-aminobutyric acid concentrations between patients and controls adjusting for age, gender and tissue fractions within each spectroscopic voxel. Regression was used to examine the relationships between the cognitive function and physical disability scores specific for these regions with gamma-aminobuytric acid levels, adjusting for age, gender, and total N-acetyl-aspartate and glutamine-glutamate complex levels. When compared with controls, patients performed significantly worse on all motor and sensory tests, and were cognitively impaired in processing speed and verbal memory. Patients had significantly lower gamma-aminobutyric acid levels in the hippocampus (adjusted difference = −0.403 mM, 95% confidence intervals −0.792, −0.014, P = 0.043) and sensorimotor cortex (adjusted difference = −0.385 mM, 95% confidence intervals −0.667, −0.104, P = 0.009) compared with controls. In patients, reduced motor function in the right upper and lower limb was associated with lower gamma-aminobutyric acid concentration in the sensorimotor cortex. Specifically for each unit decrease in gamma-aminobutyric acid levels (in mM), there was a predicted −10.86 (95% confidence intervals −16.786 to −4.482) decrease in grip strength (kg force) (P < 0.001) and −8.74 (95% confidence intervals −13.943 to −3.015) decrease in muscle strength (P < 0.006). This study suggests that reduced gamma-aminobutyric acid levels reflect pathological abnormalities that may play a role in determining physical disability. These abnormalities may include decreases in the pre- and postsynaptic components of gamma-aminobutyric acid neurotransmission and in the density of inhibitory neurons. Additionally, the reduced gamma-aminobutyric acid concentration may contribute to the neurodegenerative process, resulting in increased firing of axons, with consequent increased energy demands, which may lead to neuroaxonal degeneration and loss of the compensatory mechanisms that maintain motor function. This study supports the idea that modulation of gamma-aminobutyric acid neurotransmission may be an important target for neuroprotection in multiple sclerosis. See De Stefano and Giorgio (doi:10.1093/brain/awv213) for a scientific commentary on this article. PMID:26304151

Acculturation Stress and Drinking Problems Among Urban Heavy Drinking Latinos in the Northeast

PubMed Central

Lee, Christina S.; Colby, Suzanne M.; Rohsenow, Damaris J.; López, Steven R.; Hernández, Lynn; Caetano, Raul

2014-01-01

This study investigates the relationship between level of acculturation and acculturation stress, and the extent to which each predicts problems related to drinking. Hispanics who met criteria for hazardous drinking completed measures of acculturation, acculturation stress, and drinking problems. Sequential multiple regression was used to determine whether levels of self-reported acculturation stress predicted concurrent alcohol problems after controlling for the predictive value of acculturation level. Acculturation stress accounted for significant variance in drinking problems while adjusting for acculturation, income, and education. Choosing to drink in response to acculturation stress should be an intervention target with Hispanic heavy drinkers. PMID:24215224

Acculturation stress and drinking problems among urban heavy drinking Latinos in the Northeast.

PubMed

Lee, Christina S; Colby, Suzanne M; Rohsenow, Damaris J; López, Steven R; Hernández, Lynn; Caetano, Raul

2013-01-01

This study investigates the relationship between the level of acculturation and acculturation stress and the extent to which each predicts problems related to drinking. Hispanics who met criteria for hazardous drinking completed measures of acculturation, acculturation stress, and drinking problems. Sequential multiple regression was used to determine whether the levels of self-reported acculturation stress predicted concurrent alcohol problems after controlling for the predictive value of the acculturation level. Acculturation stress accounted for a significant variance in drinking problems, while adjusting for acculturation, income, and education. Choosing to drink in response to acculturation stress should be an intervention target with Hispanic heavy drinkers.

Statistical analysis of water-level, springflow, and streamflow data for the Edwards Aquifer in south-central Texas

USGS Publications Warehouse

Puente, Celso

1976-01-01

Water-level, springflow, and streamflow data were used to develop simple and multiple linear-regression equations for use in estimating water levels in wells and the flow of three major springs in the Edwards aquifer in the eastern San Antonio area. The equations provide daily, monthly, and annual estimates that compare very favorably with observed data. Analyses of geologic and hydrologic data indicate that the water discharged by the major springs is supplied primarily by regional underflow from the west and southwest and by local recharge in the infiltration area in northern Bexar, Comal, and Hays Counties.

Use of Thematic Mapper for water quality assessment

NASA Technical Reports Server (NTRS)

Horn, E. M.; Morrissey, L. A.

1984-01-01

The evaluation of simulated TM data obtained on an ER-2 aircraft at twenty-five predesignated sample sites for mapping water quality factors such as conductivity, pH, suspended solids, turbidity, temperature, and depth, is discussed. Using a multiple regression for the seven TM bands, an equation is developed for the suspended solids. TM bands 1, 2, 3, 4, and 6 are used with logarithm conductivity in a multiple regression. The assessment of regression equations for a high coefficient of determination (R-squared) and statistical significance is considered. Confidence intervals about the mean regression point are calculated in order to assess the robustness of the regressions used for mapping conductivity, turbidity, and suspended solids, and by regressing random subsamples of sites and comparing the resultant range of R-squared, cross validation is conducted.

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.

INTRODUCTION TO A COMBINED MULTIPLE LINEAR REGRESSION AND ARMA MODELING APPROACH FOR BEACH BACTERIA PREDICTION

EPA Science Inventory

Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...

Determining the Spatial and Seasonal Variability in OM/OC Ratios across the U.S. Using Multiple Regression

EPA Science Inventory

Data from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network are used to estimate organic mass to organic carbon (OM/OC) ratios across the United States by extending previously published multiple regression techniques. Our new methodology addresses com...

Analysis and Interpretation of Findings Using Multiple Regression Techniques

ERIC Educational Resources Information Center

Hoyt, William T.; Leierer, Stephen; Millington, Michael J.

2006-01-01

Multiple regression and correlation (MRC) methods form a flexible family of statistical techniques that can address a wide variety of different types of research questions of interest to rehabilitation professionals. In this article, we review basic concepts and terms, with an emphasis on interpretation of findings relevant to research questions…

Tracking the Gender Pay Gap: A Case Study

ERIC Educational Resources Information Center

Travis, Cheryl B.; Gross, Louis J.; Johnson, Bruce A.

2009-01-01

This article provides a short introduction to standard considerations in the formal study of wages and illustrates the use of multiple regression and resampling simulation approaches in a case study of faculty salaries at one university. Multiple regression is especially beneficial where it provides information on strength of association, specific…

Estimating air drying times of lumber with multiple regression

Treesearch

William T. Simpson

2004-01-01

In this study, the applicability of a multiple regression equation for estimating air drying times of red oak, sugar maple, and ponderosa pine lumber was evaluated. The equation allows prediction of estimated air drying times from historic weather records of temperature and relative humidity at any desired location.

Using Robust Variance Estimation to Combine Multiple Regression Estimates with Meta-Analysis

ERIC Educational Resources Information Center

Williams, Ryan

2013-01-01

The purpose of this study was to explore the use of robust variance estimation for combining commonly specified multiple regression models and for combining sample-dependent focal slope estimates from diversely specified models. The proposed estimator obviates traditionally required information about the covariance structure of the dependent…

Multiple Regression: A Leisurely Primer.

ERIC Educational Resources Information Center

Daniel, Larry G.; Onwuegbuzie, Anthony J.

Multiple regression is a useful statistical technique when the researcher is considering situations in which variables of interest are theorized to be multiply caused. It may also be useful in those situations in which the researchers is interested in studies of predictability of phenomena of interest. This paper provides an introduction to…

Using Monte Carlo Techniques to Demonstrate the Meaning and Implications of Multicollinearity

ERIC Educational Resources Information Center

Vaughan, Timothy S.; Berry, Kelly E.

2005-01-01

This article presents an in-class Monte Carlo demonstration, designed to demonstrate to students the implications of multicollinearity in a multiple regression study. In the demonstration, students already familiar with multiple regression concepts are presented with a scenario in which the "true" relationship between the response and…

Assessing the Impact of Influential Observations on Multiple Regression Analysis on Human Resource Research.

ERIC Educational Resources Information Center

Bates, Reid A.; Holton, Elwood F., III; Burnett, Michael F.

1999-01-01

A case study of learning transfer demonstrates the possible effect of influential observation on linear regression analysis. A diagnostic method that tests for violation of assumptions, multicollinearity, and individual and multiple influential observations helps determine which observation to delete to eliminate bias. (SK)

Irisin and Myostatin Levels in Patients with Graves' Disease.

PubMed

Yalcin, Mehmet Muhittin; Akturk, Mujde; Tohma, Yusuf; Cerit, Ethem Turgay; Altinova, Alev Eroglu; Arslan, Emre; Yetkin, Ilhan; Toruner, Fusun Balos

2016-08-01

Skeletal muscle system, which is one of the primary targets for thyroid hormones, has an important role in energy metabolism. Some myokines such as irisin and myostatin have considerable effects on energy metabolism in addition to the musculoskeletal system. Our aim was to investigate circulating irisin and myostatin levels in patients with Graves' Disease (GD). This study included 41 patients with GD who were in overt hyperthyroid status and 44 healthy subjects. Serum irisin levels were higher in patients with hyperthyroidism than in control group (p = 0.003). However, there was no statistical difference in myostatin levels between groups (p = 0.21). Irisin levels were positively correlated with free triiodothyronine (FT3), free thyroxine (FT4), thyrotropin receptor antibody (TRAb) (p = 0.03, p = 0.02, p = 0.02, respectively) and negatively correlated with thyroid-stimulating hormone (TSH) (p = 0.006) in both groups. In multiple regression analysis, the presence of GD was the only significant factor associated with serum irisin levels (β = 0.29, p = 0.01). Myostatin levels were positively correlated with age, body mass index (BMI), FT4, HOMA-IR (p = 0.001, p = 0.04, p = 0.003, p = 0.03, respectively) and negatively correlated with TSH (p = 0.01). Multiple regression analysis also revealed that age and FT4 were the significant factors associated with circulating myostatin levels (β = 0.27, p = 0.02; β = 0.22, p = 0.04, respectively). Our results suggest that increased irisin levels might contribute to altered energy metabolism in hyperthyroidism. Further studies to determine whether myostatin is affected due to hyperthyroidism are needed. Copyright © 2016 IMSS. Published by Elsevier Inc. All rights reserved.

Higher cortisol levels at diurnal trough predict greater attentional bias towards threat in healthy young adults.

PubMed

Hakamata, Yuko; Izawa, Shuhei; Sato, Eisuke; Komi, Shotaro; Murayama, Norio; Moriguchi, Yoshiya; Hanakawa, Takashi; Inoue, Yusuke; Tagaya, Hirokuni

2013-11-01

Attentional bias (AB), selective information processing towards threat, can exacerbate anxiety and depression. Despite growing interest, physiological determinants of AB are yet to be understood. We examined whether stress hormone cortisol and its diurnal variation pattern contribute to AB. Eighty-seven healthy young adults underwent assessments for AB, anxious personality traits, depressive symptoms, and attentional function. Salivary cortisol was collected at three time points daily (at awakening, 30 min after awakening, and bedtime) for 2 consecutive days. We performed: (1) multiple regression analysis to examine the relationships between AB and the other measures and (2) analysis of variance (ANOVA) between groups with different cortisol variation patterns for the other measures. Multiple regression analysis revealed that higher cortisol levels at bedtime (p<0.001), an anxious personality trait (p=0.011), and years of education (p=0.036) were included in the optimal model to predict AB (adjusted R(2)=0.234, p<0.001). ANOVA further demonstrated significant mean differences in AB and depressive symptoms; individuals with blunted cortisol variation exhibited significantly greater AB and depression than those with moderate variation (p=0.037 and p=0.009, respectively). Neuropsychological assessment focused on attention and cortisol measurement at three time points daily. We showed that higher cortisol levels at bedtime and blunted cortisol variation are associated with greater AB. Individuals who have higher cortisol levels at diurnal trough might be at risk of clinical anxiety or depression but could also derive more benefits from the attentional-bias-modification program. © 2013 Elsevier B.V. All rights reserved.

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.

The relationship between vitronectin and hepatic insulin resistance in type 2 diabetes mellitus.

PubMed

Cao, Yan; Li, Xinyu; Lu, Chong; Zhan, Xiaorong

2018-05-18

The World Health Organization (WHO) estimates that approximately 300 million people will suffer from diabetes mellitus by 2025. Type 2 diabetes mellitus (T2DM) is much more prevalent. T2DM comprises approximately 90% of diabetes mellitus cases, and it is caused by a combination of insulin resistance and inadequate compensatory insulin secretory response. In this study, we aimed to compare the plasma vitronectin (VN) levels between patients with T2DM and insulin resistance (IR) and healthy controls. Seventy patients with IR and 70 age- and body mass index (BMI)-matched healthy controls were included in the study. The insulin, Waist-to-Hip Ratio (WHR), C-peptide (CP) and VN levels of all participants were examined. The homeostasis model of assessment for insulin resistence index (HOMA-IR (CP)) formula was used to calculate insulin resistance. The levels of BMI, fasting plasma gluose (FPG), 2-hour postprandial glucose (2hPG), glycated hemoglobins (HbA1c), and HOMA-IR (CP) were significantly elevated in case group compared with controls. VN was found to be significantly decreased in case group. (VN Mean (Std): 8.55 (2.92) versus 12.88 (1.26) ng/mL p < 0.001). Multiple linear regression analysis was performed. This model explained 43.42% of the total variability of VN. Multiple linear regression analysis showed that HOMA-IR (CP) and age independently predicted VN levels. The VN may be a candidate target for the appraisal of hepatic insulin resistance in patients with T2DM.

Ecology of Vibrio vulnificus in estuarine waters of eastern North Carolina.

PubMed

Pfeffer, Courtney S; Hite, M Frances; Oliver, James D

2003-06-01

While several studies on the ecology of Vibrio vulnificus in Gulf Coast environments have been reported, there is little information on the distribution of this pathogen in East Coast waters. Thus, we conducted a multiyear study on the ecology of V. vulnificus in estuarine waters of the eastern United States, employing extensive multiple regression analyses to reveal the major environmental factors controlling the presence of this pathogen, and of Vibrio spp., in these environments. Monthly field samplings were conducted between July 2000 and April 2002 at six different estuarine sites along the eastern coast of North Carolina. At each site, water samples were taken and nine physicochemical parameters were measured. V. vulnificus isolates, along with estuarine bacteria, Vibrio spp., Escherichia coli organisms, and total coliforms, were enumerated in samples from each site by using selective media. During the last 6 months of the study, sediment samples were also analyzed for the presence of vibrios, including V. vulnificus. Isolates were confirmed as V. vulnificus by using hemolysin gene PCR or colony hybridization. V. vulnificus was isolated only when water temperatures were between 15 and 27 degrees C, and its presence correlated with water temperature and dissolved oxygen and vibrio levels. Levels of V. vulnificus in sediments were low, and no evidence for an overwintering in this environment was found. Multiple regression analysis indicated that vibrio levels were controlled primarily by temperature, turbidity, and levels of dissolved oxygen, estuarine bacteria, and coliforms. Water temperature accounted for most of the variability in the concentrations of both V. vulnificus (47%) and Vibrio spp. (48%).

Replication analysis of genetic association of the NCAN-CILP2 region with plasma lipid levels and non-alcoholic fatty liver disease in Asian and Pacific ethnic groups.

PubMed

Boonvisut, Supichaya; Nakayama, Kazuhiro; Makishima, Saho; Watanabe, Kazuhisa; Miyashita, Hiroshi; Lkhagvasuren, Munkhtulga; Kagawa, Yasuo; Iwamoto, Sadahiko

2016-01-13

The Neurocan-cartilage intermediate layer protein 2 (NCAN-CILP2) region forms a tight linkage disequilibrium (LD) block and is associated with plasma lipid levels and non-alcoholic fatty liver disease (NAFLD) in individuals of European descent but not in the Malay and Japanese ethnic groups. Recent genome-wide resequence studies identified a missense single-nucleotide polymorphism (SNP) (rs58542926) of the transmembrane 6 superfamily member 2 (TM6SF2) gene in the NCAN-CILP2 region related to hepatic triglyceride content. This study aims to analyze the influences of SNPs in this region on NAFLD and plasma lipid levels in the Asian and Pacific ethnic groups and to reveal the reasons behind positive and negative genetic associations dependent on ethnicity. Samples and characteristic data were collected from 3,013 Japanese, 119 Palauan, 947 Mongolian, 212 Thai and 401 Chinese people. Hepatic sonography data was obtained from the Japanese individuals. Genotyping data of five SNPs, rs58542926, rs735273, rs1009136, rs1858999, and rs16996148, were used to verify the effect on serum lipid levels by multiple linear regression, and the association with NAFLD in the Japanese population was examined by logistic regression analysis. rs58542926 showed significant association with the plasma triglyceride (TG) level in Japanese (P = 0.0009, effect size = 9.5 (± 3.25) mg/dl/allele) and Thai (P = 0.0008, effect size = 31.6 (± 11.7) mg/dl/allele) study subjects. In Mongolian individuals, there was a significant association of rs58542926 with total cholesterol level (P = 0.0003, 11.7 (± 3.2) mg/dl/allele) but not with TG level. In multiple comparisons in Chinese individuals, rs58542926 was weakly (P = 0.022) associated with TG levels, although the threshold for statistical significance was not reached. In Palauan individuals, there was no significant association with the studied SNPs. rs58542926 also showed significant association with Japanese NAFLD. The minor allele (t) increased NAFLD risk (OR 1.682, 95 % CI 1.289-2.196, p value 0.00013). This study confirmed the genetic association of missense SNP of TM6SF2, rs58542926, with plasma lipid levels in multiple East Asian ethnic groups and with NAFLD in Japanese individuals.

Integrative eQTL analysis of tumor and host omics data in individuals with bladder cancer.

PubMed

Pineda, Silvia; Van Steen, Kristel; Malats, Núria

2017-09-01

Integrative analyses of several omics data are emerging. The data are usually generated from the same source material (i.e., tumor sample) representing one level of regulation. However, integrating different regulatory levels (i.e., blood) with those from tumor may also reveal important knowledge about the human genetic architecture. To model this multilevel structure, an integrative-expression quantitative trait loci (eQTL) analysis applying two-stage regression (2SR) was proposed. This approach first regressed tumor gene expression levels with tumor markers and the adjusted residuals from the previous model were then regressed with the germline genotypes measured in blood. Previously, we demonstrated that penalized regression methods in combination with a permutation-based MaxT method (Global-LASSO) is a promising tool to fix some of the challenges that high-throughput omics data analysis imposes. Here, we assessed whether Global-LASSO can also be applied when tumor and blood omics data are integrated. We further compared our strategy with two 2SR-approaches, one using multiple linear regression (2SR-MLR) and other using LASSO (2SR-LASSO). We applied the three models to integrate genomic, epigenomic, and transcriptomic data from tumor tissue with blood germline genotypes from 181 individuals with bladder cancer included in the TCGA Consortium. Global-LASSO provided a larger list of eQTLs than the 2SR methods, identified a previously reported eQTLs in prostate stem cell antigen (PSCA), and provided further clues on the complexity of APBEC3B loci, with a minimal false-positive rate not achieved by 2SR-MLR. It also represents an important contribution for omics integrative analysis because it is easy to apply and adaptable to any type of data. © 2017 WILEY PERIODICALS, INC.

Abdominal girth and vertebral column length can adjust spinal anesthesia for lower limb surgery, a prospective, observational study.

PubMed

Zhou, Qing-he; Zhu, Bo; Wei, Chang-na; Yan, Min

2016-03-24

Studies have shown that abdominal girth and vertebral column length have high predictive value for spinal spread after administering a dose of plain bupivacaine. we designed a study to identify the specific correlations between abdominal girth, vertebral column length and a 0.5% dosage of plain bupivacaine, which should provide a minimum upper block level (T12) and a suitable upper block level (T10) for lower limb surgeries. A suitable dose of 0.5% plain bupivacaine was administered intrathecally between the L3 and L4 vertebrae for lower limb surgeries. If the upper cephalad spread of the patient by loss of pinprick discrimination was T12 or T10, the patient was enrolled in this study. Five patient variables and intrathecal plain bupivacaine dose were recorded. Linear regression and multiple regression analyses were performed. Totals of 111 patients and 121 patients who lost pinprick discrimination at T12 and T10, respectively, were analyzed in this study. Linear regression analysis showed that only abdominal girth and plain bupivacaine dose were strongly correlated (r =-0.827 for T12, r = -0.806 for T10; both p < 0.0001). Multiple linear regression analysis showed that both abdominal girth and vertebral column length were the key determinants of plain bupivacaine dose (both p < 0.0001). R(2) was 0.874 and 0.860 for the loss of pinprick discrimination at T12 and T10, respectively. Our data indicated that vertebral column length and abdominal girth were strongly correlated with the dosage of intrathecal plain bupivacaine for the loss of pinprick discrimination at T12 and T10. The two regression equations were YT12 = 3.547 + 0.045X1-0.044X2 and YT10 = 3.848 + 0.047X1- 0.046X2 (Y, 0.5% plain bupivacaine volume; X1, vertebral column length;and X 2, abdominal girth), which can accurately predict the minimum and suitable intrathecal bupivacaine dose for lower limb surgery to a great extent, separately.

Examining gender salary disparities: an analysis of the 2003 multistate salary survey.

PubMed

Brown, Lawrence M; Schommer, Jon C; Mott, Dave; Gaither, Caroline A; Doucette, William R; Zgarrick, Dave P; Droege, Marcus

2006-09-01

Pharmacist salary and wage surveys have been conducted at the state and national level for more than 20 years; however, it is not known to what extent, if any, wage disparities due to gender still exist. The overall objective of this study was to determine if wage disparities exist among male and female pharmacists at the multistate and individual state level for each of 6 states studied. A secondary objective was to explore the effect of various demographic variables on the hourly wages of pharmacists. Data were collected from 1,688 pharmacists in 6 states during 2003 using a cross-sectional descriptive survey design. A multiple regression analysis on hourly wage testing the effects of state of practice, practice setting, position, terminal degree, and years in practice was conducted. Subsequent multiple regression analyses were conducted individually for each of the 6 states to test the effects of the above variables on hourly wage for both male and female pharmacists, followed by state-level analyses for male and female pharmacists, respectively. For the pooled data, all variables were found to be significant predictors of hourly wage, except for earning a PharmD degree without a residency or graduate degree. Gender was not a significant predictor of wage disparities in the state-level analyses. Position was the only significant predictor of wage disparities in all states (except Tennessee) such that pharmacists in management positions make significantly higher salaries than those in staff positions. The results of these analyses suggest that wage disparities due to gender do not exist at the state level for the 6 states surveyed, when controlling for practice setting, position, terminal degree, and years in practice. The larger number of men in management positions may explain lower wages for female pharmacists.

Association of Central Obesity with Sex Hormonebinding Globulin: A Cross-sectional Study of 1166 Chinese Men.

PubMed

Liu, Fangwei; Shen, Xubo; Wang, Ruifeng; Yu, Na; Shi, Yongjun; Xiong, Shimin; Xiong, Chengliang; Zhou, Yuanzhong

2018-01-01

Background Both sex hormone-binding globulin and central obesity have been found to be associated with metabolic and cardiovascular diseases. However, the direct relation between sex hormone-binding globulin and central obesity has not been demonstrated. Methodology We performed a cross-sectional study of 1166 male participants from Zunyi, Guizhou, western China, in 2013. Each participant completed a questionnaire and had a brief clinical exam with a fasting blood sample taken. All blood samples underwent standard laboratory testing for sex hormone-binding globulin. Level of serum sex hormone-binding globulin was compared by demographic characteristics, and multiple linear regression was used to evaluate the independent association of variables and sex hormone-binding globulin level. Results The mean serum level of sex hormone-binding globulin was increased in old-aged men (older than 40 years; mean 44.68±20.58 nmol/L), low diastolic blood pressure (<90mmHg; 43.76±20.50 nmol/L), waist-to-height ratio <0.5 (48.73±20.59 nmol/L), no education (52.36±22.91 nmol/L), farm occupation (43.58±20.60nmol/L), non-alcohol or former user (44.78±20.94 nmol/L) and long-term medication history (44.79±21.50 nmol/L). Factors independently associated with sex hormone binding globulin level on multiple regression were waist-to-height ratio (β=- 11.84 [95% confidence interval -13.96,-9.72]), age(β=12.40 [9.63,15.17]) and diastolic blood pressure (β=-5.07 [-7.44,-2.71]). Conclusions Central obesity has an independent inverse relation with serum level of sex hormone binding globulin among western Chinese men.

Factors associated with subjective well-being in cancer workers in Queensland.

PubMed

Poulsen, Michael G; Poulsen, Anne A; Khan, Asaduzzaman; Poulsen, Emma E; Khan, Shanchita R

2012-06-01

This study aims to describe factors associated with subjective well-being (SWB) in cancer workers in Queensland and compares results to normative data for the Australian population. This study was based on a cross-sectional survey of 544 cancer workers in Queensland with a response rate of 54%. SWB was measured using the Personal Wellbeing Index for Adults. Multiple regression analyses were performed to identify explanatory variables, which were independently associated with SWB. Results were compared with normative Australian data. The overall mean SWB for study participants was 74.63, which was comparable to the mean of 75.02 for the Australian population (P = 0.47). Female cancer workers had significantly lower levels of SWB compared to the normative data of female Australians (74.44 compared to 75.7, P = 0.03). Multiple regression analyses showed that higher levels of SWB were associated with having 11-30 h of direct patient care hours per week, being married, no child or elder care commitments, good physical health, low levels of both psychological distress and burnout, and high levels of work engagement. Cancer workers' overall levels of SWB were similar to the national mean scores. Amount of time in direct patient care was linked with SWB, with an optimal time between 11 and 30 h per week associated with high SWB. The majority of the factors significantly associated with SWB were of a personal nature such as marital status and physical and mental health. These data provide a valuable baseline for future research in this area, especially in the area of interventions to promote SWB of workers. © 2012 The Authors. Journal of Medical Imaging and Radiation Oncology © 2012 The Royal Australian and New Zealand College of Radiologists.

Serum Vitamin D Status in Iranian Fibromyalgia Patients: according to the Symptom Severity and Illness Invalidation

PubMed Central

Maafi, Alireza Amir; Haghdoost, Afrooz; Aarabi, Yasaman; Hajiabbasi, Asghar; Shenavar Masooleh, Irandokht; Zayeni, Habib; Ghalebaghi, Babak; Hassankhani, Amir; Bidari, Ali

2016-01-01

Background This study was designed to assess serum vitamin D status (25-OHD) in the fibromyalgia (FM) patients and to compare it with a healthy control group. It also aimed to investigate the correlation of serum vitamin D level with FM symptom severity and invalidation experiences. Methods A total of 74 consecutive patients with FM and 68 healthy control participants were enrolled. The eligible FM patients completed the Illness Invalidation Inventory (3*I), the Revised Fibromyalgia Impact Questionnaire (FIQR) and a short-form health survey (SF-12). Venous blood samples were drawn from all participants to evaluate serum 25-OHD levels. Mann-Whitney tests and multiple logistic regression analyses were performed and Spearman's correlations were calculated. Results 88.4% of FM patients had low levels of serum 25-OHD. FM patients had significantly higher level of serum 25-OHD than the control group (17.24 ± 13.50 and 9.91 ± 6.47 respectively, P = 0.0001). There were no significant correlations between serum 25-OHD levels and the clinical measures of disease impact, invalidation dimensions, and health status. Multiple logistic regression analyses revealed that an increased discounting of the disease by the patient's spouse was associated with a 4-fold increased risk for vitamin D deficiency (OR = 4.36; 95% CI, 0.95–19.87, P = 0.05). Conclusions This study showed that although high rates of vitamin D insufficiency or deficiency were seen among FM patients and healthy non-FM participants, but it seems there was no intrinsic association between FM and vitamin D deficiency. Addressing of invalidation experience especially by the patient's spouse is important in management of FM. PMID:27413482

School league tables: a new population based predictor of dental restorative treatment need.

PubMed

Crowley, Evelyn; O'Brien, Graham; Marcenes, Wagner

2003-06-01

To test whether dental restorative treatment need was related to the school league tables and level of social deprivation of the school ward. An ecological study using clinical data aggregated at school level, collected in the school dental screening examinations (1996-97), National Census (1991) and the results of the UK school league tables--Key Stage 2 SATs (1996-97). State primary schools in the Greenwich District of SE London, UK (1996-97). 12,854 pupils (6-11 years of age) in 62 schools. The percentage of 6 to 11 year old pupils per school requiring dental restorative treatment. Deprivation as measured by the overall Jarman Under Privileged Area Index (UPA) of the school ward was not associated with dental restorative treatment need (p > 0.05). Only two components of the Jarman Index, level of unemployment and the number of lone parent families in the school ward were found to be significantly associated with dental restorative treatment need (p < 0.05). Results of stepwise multiple linear regression analysis showed that the association with the school league table results in all three subjects, English, Mathematics and Science remained statistically significant after adjusting for levels of unemployment and single parents. Results of multiple linear regression analysis showed that a high level of dental restorative treatment need was significantly associated with poor school league table results in English, Mathematics and Science (p < 0.05) after adjusting for the overall Jarman score of the school ward. A separate analysis for the 11-year-old pupils aggregated by school (n = 46 schools) gave similar results. Aggregate measures of academic achievement may be a potential indicator of dental restorative treatment need.

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

Impact of divorce on the quality of life in school-age children.

PubMed

Eymann, Alfredo; Busaniche, Julio; Llera, Julián; De Cunto, Carmen; Wahren, Carlos

2009-01-01

To assess psychosocial quality of life in school-age children of divorced parents. A cross-sectional survey was conducted at the pediatric outpatient clinic of a community hospital. Children 5 to 12 years old from married families and divorced families were included. Child quality of life was assessed through maternal reports using a Child Health Questionnaire-Parent Form 50. A multiple linear regression model was constructed including clinically relevant variables significant on univariate analysis (beta coefficient and 95%CI). Three hundred and thirty families were invited to participate and 313 completed the questionnaire. Univariate analysis showed that quality of life was significantly associated with parental separation, child sex, time spent with the father, standard of living, and maternal education. In a multiple linear regression model, quality of life scores decreased in boys -4.5 (-6.8 to -2.3) and increased for time spent with the father 0.09 (0.01 to 0.2). In divorced families, multiple linear regression showed that quality of life scores increased when parents had separated by mutual agreement 6.1 (2.7 to 9.4), when the mother had university level education 5.9 (1.7 to 10.1) and for each year elapsed since separation 0.6 (0.2 to 1.1), whereas scores decreased in boys -5.4 (-9.5 to -1.3) and for each one-year increment of maternal age -0.4 (-0.7 to -0.05). Children's psychosocial quality of life was affected by divorce. The Child Health Questionnaire can be useful to detect a decline in the psychosocial quality of life.

Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels

PubMed Central

Van de Voorde, Tim; Vlaeminck, Jeroen; Canters, Frank

2008-01-01

Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city's inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP) at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing. PMID:27879914

Advantage of multiple spot urine collections for estimating daily sodium excretion: comparison with two 24-h urine collections as reference.

PubMed

Uechi, Ken; Asakura, Keiko; Ri, Yui; Masayasu, Shizuko; Sasaki, Satoshi

2016-02-01

Several estimation methods for 24-h sodium excretion using spot urine sample have been reported, but accurate estimation at the individual level remains difficult. We aimed to clarify the most accurate method of estimating 24-h sodium excretion with different numbers of available spot urine samples. A total of 370 participants from throughout Japan collected multiple 24-h urine and spot urine samples independently. Participants were allocated randomly into a development and a validation dataset. Two estimation methods were established in the development dataset using the two 24-h sodium excretion samples as reference: the 'simple mean method' estimated by multiplying the sodium-creatinine ratio by predicted 24-h creatinine excretion, whereas the 'regression method' employed linear regression analysis. The accuracy of the two methods was examined by comparing the estimated means and concordance correlation coefficients (CCC) in the validation dataset. Mean sodium excretion by the simple mean method with three spot urine samples was closest to that by 24-h collection (difference: -1.62  mmol/day). CCC with the simple mean method increased with an increased number of spot urine samples at 0.20, 0.31, and 0.42 using one, two, and three samples, respectively. This method with three spot urine samples yielded higher CCC than the regression method (0.40). When only one spot urine sample was available for each study participant, CCC was higher with the regression method (0.36). The simple mean method with three spot urine samples yielded the most accurate estimates of sodium excretion. When only one spot urine sample was available, the regression method was preferable.

White Blood Cells, Neutrophils, and Reactive Oxygen Metabolites among Asymptomatic Subjects.

PubMed

Kotani, Kazuhiko; Sakane, Naoki

2012-06-01

Chronic inflammation and oxidative stress are associated with health and the disease status. The objective of the present study was to investigate the association among white blood cell (WBC) counts, neutrophil counts as a WBC subpopulation, and diacron reactive oxygen metabolites (d-ROMs) levels in an asymptomatic population. The clinical data, including general cardiovascular risk variables and high-sensitivity C-reactive protein (hs-CRP), were collected from 100 female subjects (mean age, 62 years) in outpatient clinics. The correlation of the d-ROMs with hs-CRP, WBC, and neutrophil counts was examined. The mean/median levels were WBC counts 5.9 × 10(9)/L, neutrophil counts 3.6 × 10(9)/L, hs-CRP 0.06 mg/dL, and d-ROMs 359 CURR U. A simple correlation analysis showed a significant positive correlation of the d-ROMs with the WBC counts, neutrophil counts, or hs-CRP levels. The correlation between d-ROMs and neutrophil counts (β = 0.22, P < 0.05), as well as that between d-ROMs and hs-CRP (β = 0.28, P < 0.01), remained significant and independent in a multiple linear regression analysis adjusted for other variables. A multiple linear regression analysis showed that WBC counts had only a positive correlation tendency to the d-ROMs. Neutrophils may be slightly but more involved in the oxidative stress status, as assessed by d-ROMs, in comparison to the overall WBC. Further studies are needed to clarify the biologic mechanism(s) of the observed relationship.

Comparison of Mental Toughness and Power Test Performances in High-Level Kickboxers by Competitive Success.

PubMed

Slimani, Maamer; Miarka, Bianca; Briki, Walid; Cheour, Foued

2016-06-01

Kickboxing is a high-intensity intermittent striking combat sport, which is characterized by complex skills and tactical key actions with short duration. The present study compared and verified the relationship between mental toughness (MT), countermovement jump (CMJ) and medicine ball throw (MBT) power tests by outcomes of high-level kickboxers during National Championship. Thirty two high-level male kickboxers (winner = 16 and loser = 16: 21.2 ± 3.1 years, 1.73 ± 0.07 m, and 70.2 ± 9.4 kg) were analyzed using the CMJ, MBT tests and sports mental toughness questionnaire (SMTQ; based in confidence, constancy and control subscales), before the fights of the 2015 national championship (16 bouts). In statistical analysis, Mann-Withney test and a multiple linear regression were used to compare groups and to observe relationships, respectively, P ≤ 0.05. The present results showed significant differences between losers vs. winners, respectively, of total MT (7(7;8) vs. 11(10.2;11), confidence (3(3;3) vs. 4(4;4)), constancy (2(2;2) vs. 3(3;3)), control (2(2;3) vs. 4(4;4)) subscales and MBT (4.1(4;4.3) vs. 4.6(4.4;4.8)). The multiple linear regression showed a strong associations between MT results and outcome (r = 0.89), MBT (r = 0.84) and CMJ (r = 0.73). The findings suggest that MT will be more predictive of performance in those sports and in the outcome of competition.

Matsuda-DeFronzo insulin sensitivity index is a better predictor than HOMA-IR of hypertension in Japanese: the Tanno-Sobetsu study.

PubMed

Furugen, M; Saitoh, S; Ohnishi, H; Akasaka, H; Mitsumata, K; Chiba, M; Furukawa, T; Miyazaki, Y; Shimamoto, K; Miura, T

2012-05-01

Here we examined whether the Matsuda-DeFronzo insulin sensitivity index (ISI-M) is more efficient than the homeostasis model assessment of insulin resistance (HOMA-IR) for assessing risk of hypertension. Cross-sectional and longitudinal analyses were conducted using normotensive subjects who were selected among 1399 subjects in the Tanno-Sobetsu cohort. In the cross-sectional analysis (n=740), blood pressure (BP) level was correlated with HOMA-IR and with ISI-M, but correlation coefficients indicate a tighter correlation with ISI-M. Multiple linear regression analysis adjusted by age, sex, body mass index (BMI) and serum triglyceride level (TG) showed contribution of ISI-M and fasting plasma glucose, but not of HOMA-IR. In the longitudinal analysis (n=607), 241 subjects (39.7%) developed hypertension during a 10-year follow-up period, and multiple logistic regression indicated that age, TG, systolic BP and ISI-M, but not HOMA-IR, were associated with development of hypertension. In subjects <60 years old, odds ratio of new-onset hypertension was higher in the low ISI-M group (ISI-M, less than the median) than in the high ISI-M group for any tertile of BMI. In conclusion, ISI-M is a better predictor of hypertension than is HOMA-IR. Non-hepatic IR may be a determinant, which is independent of TG, BP level and BMI, of the development of hypertension.

Organizational resilience and enrollment trends of independent, for-profit higher education institutions.

PubMed

Frisbie, Kathryn; Converso, Judith

2016-05-24

From 2010 to 2012, the for-profit sector of higher education in the United States (otherwise known as career colleges) existed in a turbulent environment, characterized by regulatory, media, and public scrutiny. While virtually all career colleges experienced enrollment declines during this period, by 2012 some colleges were starting to see this trend stabilize or reverse, whereas others did not. The purpose of this study was to determine if the differences in career colleges' enrollment trends could be attributed to organizational resilience. A quantitative correlation study using a multiple regression analysis was conducted to determine the nature of the relationship between organizational resilience and the enrollment fluctuations of 59 career colleges located throughout the United States. The correlation between organizational resilience levels and enrollment fluctuations was fair to moderate and significant, r = 0.40, p < 0.05. A multiple-regression analysis revealed that the model significantly explained the impact of the six organizational resilience factors on enrollment fluctuations, F = 4.15, p < 0.01. The R2 for the model was 0.32, and the adjusted R2 was 0.25. In terms of individual organizational resilience factors, two tested either significantly or moderately significantly: avoidance-skepticism and critical understanding or sensemaking. Recommendations for college leaders include monitoring the level of avoidance to ensure a healthy balance of skepticism regarding new situations and incorporating strategies to help organizational members increase their levels of critical understanding or sensemaking.

Using adrenaline during neonatal resuscitation may have an impact on serum cardiac troponin-T levels.

PubMed

Helmer, Caroline; Skranes, Janne H; Liestøl, Knut; Fugelseth, Drude

2015-09-01

It has been suggested that serum cardiac troponin-T (cTnT) can predict the severity of neonatal hypoxic-ischaemic encephalopathy. We evaluated whether cTnT was better correlated with adrenaline during cardiopulmonary resuscitation (CPR) than with the severity of the insult itself, based on the Apgar scores. Serum cTnT was analysed in 47 asphyxiated newborn infants treated with hypothermia. Blood samples and resuscitation data were collected from medical records, and multiple linear regressions were used to evaluate the effect of the treatment and the Apgar scores on cTnT levels. The infants were divided into three groups: the no CPR group (n = 29) just received stimulation and ventilation, the CPR minus adrenaline group (n = 9) received cardiac compression and ventilation and the CPR plus adrenaline group (n = 9) received complete CPR, including adrenaline. In the univariate analysis, the five and ten-minute Apgar scores were significantly lower in the CPR plus adrenaline group and the cTnT was significantly higher. Multiple regression analysis showed significantly higher cTnT values in the CPR plus adrenaline group, but no significant relationship between cTnT and the Apgar scores. Although cTnT correlated with the severity of the insult in neonatal hypoxic-ischaemic encephalopathy, the levels may have been affected by adrenaline administered during CPR. ©2015 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

Nutrient intake and use of dietary supplements among US adults with disabilities.

PubMed

An, Ruopeng; Chiu, Chung-Yi; Andrade, Flavia

2015-04-01

Physical, mental, social, and financial hurdles in adults with disabilities may limit their access to adequate nutrition. To examine the impact of dietary supplement use on daily total nutrient intake levels among US adults 20 years and older with disabilities. Study sample came from 2007-2008 and 2009-2010 waves of the National Health and Nutrition Examination Survey, a nationally representative repeated cross-sectional survey. Disability was classified into 5 categories using standardized indices. Nutrient intakes from foods and dietary supplements were calculated from 2 nonconsecutive 24-hour dietary recalls. Two-sample proportion tests and multiple logistic regressions were used to examine the adherence rates to the recommended daily nutrient intake levels between dietary supplement users and nonusers in each disability category. The association between sociodemographic characteristics and dietary supplement use was assessed using multiple logistic regressions, accounting for complex survey design. A substantial proportion of the US adult population with disabilities failed to meet dietary guidelines, with insufficient intakes of multiple nutrients. Over half of the US adults with disabilities used dietary supplements. Dietary supplement use was associated with higher adherence rates for vitamin A, vitamin B1, vitamin B2, vitamin B6, vitamin B12, vitamin C, vitamin D, vitamin E, calcium, copper, iron, magnesium, and zinc intake among adults with disabilities. Women, non-Hispanic Whites, older age, higher education, and higher household income were found to predict dietary supplement use. Proper use of dietary supplements under the guidance of health care providers may improve the nutritional status among adults with disabilities. Copyright © 2015 Elsevier Inc. All rights reserved.

The impact of professional identity on role stress in nursing students: A cross-sectional study.

PubMed

Sun, Li; Gao, Ying; Yang, Juan; Zang, Xiao-Ying; Wang, Yao-Gang

2016-11-01

As newcomers to the clinical workplace, nursing students will encounter a high degree of role stress, which is an important predictor of burnout and engagement. Professional identity is theorised to be a key factor in providing high-quality care to improve patient outcomes and is thought to mediate the negative effects of a high-stress workplace and improve clinical performance and job retention. To investigate the level of nursing students' professional identity and role stress at the end of the first sub-internship, and to explore the impact of the nursing students' professional identity and other characteristics on role stress. A cross-sectional study. Three nursing schools in China. Nursing students after a 6-month sub-internship in a general hospital (n=474). The Role Stress Scale (score range: 12-60) and the Professional Identity Questionnaire for Nursing students (score range: 17-85) were used to investigate the levels of nursing students' role stress and professional identity. Higher scores indicated higher levels of role stress and professional identity. Basic demographic information about the nursing students was collected. The Pearson correlation, point-biserial correlation and multiple linear regression analysis were used to analyse the data. The mean total scores of the Role Stress Scale and Professional Identity Questionnaire for Nursing Students were 34.04 (SD=6.57) and 57.63 (SD=9.63), respectively. In the bivariate analyses, the following independent variables were found to be significantly associated with the total score of the Role Stress Scale: the total score of the Professional Identity Questionnaire for Nursing Students (r=-0.295, p<0.01), age (r=0.145, p<0.01), whether student was an only child or not (r=-0.114, p<0.05), education level (r=0.295, p<0.01) and whether student had experience in community organisations or not (r=0.151, p<0.01). In the multiple linear regression analysis, the total score of the Professional Identity Questionnaire for Nursing Students (standardised coefficient Beta: -0.260, p<0.001), education level (standardised coefficient Beta: 0.212, p<0.001) and whether or not student had experience in community organisations (standardised coefficient Beta: 0.107, p<0.016) were the factors significantly associated with the total score of the Role Stress Scale. The multiple linear regression model explained 18.2% (adjusted R 2 scores 16.5%) of the Role Stress Scale scores variance. The nursing students' level of role stress at the end of the first sub-internship was high. The students with higher professional identity values had lower role stress levels. Compared with other personal characteristics, professional identity and education level had the strongest impact on the nursing students' level of role stress. This is a new perspective that shows that developing and improving professional identity may prove helpful for nursing students in managing role stress. Copyright © 2016 Elsevier Ltd. All rights reserved.

Intimate relationship quality, self-concept and illness acceptance in those with multiple sclerosis.

PubMed

Wright, Thomas M; Kiropoulos, Litza A

2017-02-01

Lower levels of Intimate Relationship Quality (IRQ) have been found in those with Multiple Sclerosis (MS) compared to the general population. This study examined an MS sample to see whether IRQ was positively associated with self-concept, whether IRQ was positively associated with MS illness acceptance and whether IRQ was predicted by self-concept and illness acceptance. In this cross-sectional study, 115 participants with MS who were in an intimate relationship completed an online survey advertised on MS related websites. The survey assessed demographic variables, MS illness variables and levels of IRQ, self-concept and illness acceptance. Results revealed that IRQ was significantly positively associated with self-concept and with illness acceptance. Multiple hierarchical linear regression analysis revealed that, after controlling for illness duration and level of disability, self-concept significantly predicted IRQ but illness acceptance did not significantly predict IRQ. This study addressed several gaps and methodological flaws in the literature and was the first known to assess predictors of IRQ in those with MS. The results suggest that self-concept could be a potential target for individual and couple psychological interventions to improve IRQ and contribute to improved outcomes for those with MS.

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.

Effect of plasma homocysteine level and urinary monomethylarsonic acid on the risk of arsenic-associated carotid atherosclerosis

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

Wu, M.-M.; Graduate Institute of Medicine, College of Medicine, Fu-Jen Catholic University, Taipei, Taiwan; Chiou, H.-Y.

2006-10-01

Arsenic-contaminated well water has been shown to increase the risk of atherosclerosis. Because of involving S-adenosylmethionine, homocysteine may modify the risk by interfering with the biomethylation of ingested arsenic. In this study, we assessed the effect of plasma homocysteine level and urinary monomethylarsonic acid (MMA{sup V}) on the risk of atherosclerosis associated with arsenic. In total, 163 patients with carotid atherosclerosis and 163 controls were studied. Lifetime cumulative arsenic exposure from well water for study subjects was measured as index of arsenic exposure. Homocysteine level was determined by high-performance liquid chromatography (HPLC). Proportion of MMA{sup V} (MMA%) was calculated bymore » dividing with total arsenic species in urine, including arsenite, arsenate, MMA{sup V}, and dimethylarsinic acid (DMA{sup V}). Results of multiple linear regression analysis show a positive correlation of plasma homocysteine levels to the cumulative arsenic exposure after controlling for atherosclerosis status and nutritional factors (P < 0.05). This correlation, however, did not change substantially the effect of arsenic exposure on the risk of atherosclerosis as analyzed in a subsequent logistic regression model. Logistic regression analyses also show that elevated plasma homocysteine levels did not confer an independent risk for developing atherosclerosis in the study population. However, the risk of having atherosclerosis was increased to 5.4-fold (95% CI, 2.0-15.0) for the study subjects with high MMA% ({>=}16.5%) and high homocysteine levels ({>=}12.7 {mu}mol/l) as compared to those with low MMA% (<9.9%) and low homocysteine levels (<12.7 {mu}mol/l). Elevated homocysteinemia may exacerbate the formation of atherosclerosis related to arsenic exposure in individuals with high levels of MMA% in urine.« less

Serum bilirubin levels are positively associated with glycemic variability in women with type 2 diabetes.

PubMed

Kim, Lee Kyung; Roh, Eun; Kim, Min Joo; Kim, Min Kyeong; Park, Kyeong Seon; Kwak, Soo Heon; Cho, Young Min; Park, Kyong Soo; Jang, Hak Chul; Jung, Hye Seung

2016-11-01

Glycemic variability is known to induce oxidative stress. We investigated the relationships between glycemic variability and serum bilirubin levels, an endogenous anti-oxidant, in patients with diabetes. A cross-sectional study was carried out with 77 patients with type 2 diabetes who had been recruited to two clinical studies from 2008 to 2014. There were no participants with diseases of the pancreas, liver, biliary tract and chronic renal insufficiency. Glycemic variation was calculated by a continuous glucose monitoring system, and correlation analyses were carried out to evaluate their association with bilirubin levels. Multiple linear regression was carried out to identify independent factors influencing bilirubin levels and glycemic variation. Among the participants, 42.3% were men. The mean (standard deviation) age was 61.5 years (10.4 years), body mass index was 24.2 kg/m 2 (2.8 kg/m 2 ), diabetes duration was 17.7 years (9.5 years), hemoglobin A 1c was 60.7 mmol/mol (7.1 mmol/mol; 7.7 [0.7]%) and bilirubin was 11.8 μmol/L (4.10 μmol/L). Serum bilirubin levels were not different according to age, body mass index and hemoglobin A 1c . However, the mean amplitude of glucose excursion was positively associated with bilirubin levels in women (r = 0.588, P < 0.001). After adjustment with duration of diabetes, serum albumin, liver enzymes, and mean glucose, the correlation between bilirubin and mean amplitude of glucose excursion remained significant (r = 0.566, P < 0.001). Multiple linear regression analyses showed that bilirubin was an independent determinant for the mean amplitude of glucose excursion in women. 1,5-Anhydroglucitol was also associated with bilirubin levels in women. Bilirubin level within the physiological range might be an independent predictor for glycemic variability in women with type 2 diabetes. © 2016 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.

Burnout, working conditions and gender - results from the northern Sweden MONICA Study

PubMed Central

2010-01-01

Background Sick-leave because of mental and behavioural disorders has increased considerably in Sweden since the late nineties, and especially in women. The aim of this study was to assess the level of burnout in the general working population in northern Sweden and analyse it's relation to working conditions and gender. Methods In this cross-sectional study the survey from the MONICA-study (Monitoring of Trends and Determinants in Cardiovascular Disease) in northern Sweden 2004 was used. A burnout instrument, the Shirom Melamed Burnout Questionnaire (SMBQ), was incorporated in the original survey which was sent to a random sample of 2500 individuals with a response rate of 76%. After including only actively working people, aged 25-64 years, our study population consisted of 1000 participants (497 women and 503 men). ANOVA and multiple linear regression models were used. Results The prevalence of a high level of burnout (SMBQ >4.0) was 13%. Women had a higher level of burnout than men with the most pronounced difference in the age group 35-44 years. In both sexes the level of burnout decreased with age. Demand and control at work, and job insecurity were related to burnout. In women the level of education, socioeconomic position, work object, and working varying hours were of importance. Interaction effects were found between sex and work object, and sex and working hours. In a multiple regression analysis almost half of the gender difference could be explained by work related and life situational factors. Conclusions Working life conditions contributed to the level of burnout in this actively working sample from the general population in northern Sweden. Especially in women, socioeconomic position was associated with burnout. The high level of burnout in women compared to men was partly explained by more unfavourable working conditions and life situational factors. Efforts to level out gender differences in burnout should probably focus on improving both working and socioeconomic conditions for women. PMID:20534136

Higher ambulatory systolic blood pressure independently associated with enlarged perivascular spaces in basal ganglia.

PubMed

Yang, Shuna; Yuan, Junliang; Zhang, Xiaoyu; Fan, Huimin; Li, Yue; Yin, Jiangmei; Hu, Wenli

2017-09-01

Enlarged perivascular spaces (EPVS) have been identified as a marker of cerebral small vessel diseases (CSVD). Ambulatory blood pressure (ABP) is the strongest predictor of hypertension-related brain damage. However, the relationship between ABP levels and EPVS is unclear. This study aimed to investigate the association between ABP levels and EPVS by 24-hour ambulatory blood pressure monitoring (ABPM). We prospectively recruited inpatients for physical examinations in our hospital from May 2013 to Jun 2016. 24-hour ABPM data and cranial magnetic resonance imaging information were collected. EPVS in basal ganglia (BG) and centrum semiovale (CSO) were identified and classified into three categories by the severity. White matter hyperintensities were scored by Fazekas scale. Spearman correlation analysis and multiple logistic regression analysis were used to determine the relationship between ABP levels and EPVS. A total of 573 subjects were enrolled in this study. 24-hour, day and night systolic blood pressure (SBP) levels were positively related to higher numbers of EPVS in BG (24-hour SBP: r = 0.23, p < 0.01; day SBP: r = 0.25, p < 0.01; night SBP: r = 0.30, p < 0.01). The association was unchanged after controlling for confounders by multiple logistic regression analysis. 24-hour and day diastolic blood pressure (DBP) levels increased with an increasing degree of EPVS in CSO (p = 0.04 and 0.049, respectively). But the association disappeared after adjusting for confounders. Spearman correlation analysis indicated that ABP levels were not associated with higher numbers of EPVS in CSO (p > 0.05). DBP levels were not independently associated with the severity of EPVS in BG and CSO. Higher SBP levels were independently associated with EPVS in BG, but not in CSO, which supported EPVS in BG to be a marker of CSVD. Pathogenesis of EPVS in BG and CSO might be different.

An analysis of collegiate band directors' exposure to sound pressure levels

NASA Astrophysics Data System (ADS)

Roebuck, Nikole Moore

Noise-induced hearing loss (NIHL) is a significant but unfortunate common occupational hazard. The purpose of the current study was to measure the magnitude of sound pressure levels generated within a collegiate band room and determine if those sound pressure levels are of a magnitude that exceeds the policy standards and recommendations of the Occupational Safety and Health Administration (OSHA), and the National Institute of Occupational Safety and Health (NIOSH). In addition, reverberation times were measured and analyzed in order to determine the appropriateness of acoustical conditions for the band rehearsal environment. Sound pressure measurements were taken from the rehearsal of seven collegiate marching bands. Single sample t test were conducted to compare the sound pressure levels of all bands to the noise exposure standards of OSHA and NIOSH. Multiple regression analysis were conducted and analyzed in order to determine the effect of the band room's conditions on the sound pressure levels and reverberation times. Time weighted averages (TWA), noise percentage doses, and peak levels were also collected. The mean Leq for all band directors was 90.5 dBA. The total accumulated noise percentage dose for all band directors was 77.6% of the maximum allowable daily noise dose under the OSHA standard. The total calculated TWA for all band directors was 88.2% of the maximum allowable daily noise dose under the OSHA standard. The total accumulated noise percentage dose for all band directors was 152.1% of the maximum allowable daily noise dose under the NIOSH standards, and the total calculated TWA for all band directors was 93dBA of the maximum allowable daily noise dose under the NIOSH standard. Multiple regression analysis revealed that the room volume, the level of acoustical treatment and the mean room reverberation time predicted 80% of the variance in sound pressure levels in this study.

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Wavelet regression model in forecasting crude oil price

NASA Astrophysics Data System (ADS)

Hamid, Mohd Helmie; Shabri, Ani

2017-05-01

This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

Multiple regression for physiological data analysis: the problem of multicollinearity.

PubMed

Slinker, B K; Glantz, S A

1985-07-01

Multiple linear regression, in which several predictor variables are related to a response variable, is a powerful statistical tool for gaining quantitative insight into complex in vivo physiological systems. For these insights to be correct, all predictor variables must be uncorrelated. However, in many physiological experiments the predictor variables cannot be precisely controlled and thus change in parallel (i.e., they are highly correlated). There is a redundancy of information about the response, a situation called multicollinearity, that leads to numerical problems in estimating the parameters in regression equations; the parameters are often of incorrect magnitude or sign or have large standard errors. Although multicollinearity can be avoided with good experimental design, not all interesting physiological questions can be studied without encountering multicollinearity. In these cases various ad hoc procedures have been proposed to mitigate multicollinearity. Although many of these procedures are controversial, they can be helpful in applying multiple linear regression to some physiological problems.

Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

ERIC Educational Resources Information Center

Li, Spencer D.

2011-01-01

Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…

A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants

ERIC Educational Resources Information Center

Cooper, Paul D.

2010-01-01

A new procedure using a student-friendly least-squares multiple linear-regression technique utilizing a function within Microsoft Excel is described that enables students to calculate molecular constants from the vibronic spectrum of iodine. This method is advantageous pedagogically as it calculates molecular constants for ground and excited…

Conjoint Analysis: A Study of the Effects of Using Person Variables.

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

Three statistical techniques--conjoint analysis, a multiple linear regression model, and a multiple linear regression model with a surrogate person variable--were used to estimate the relative importance of five university attributes for students in the process of selecting a college. The five attributes include: availability and variety of…

An Exploratory Study of Face-to-Face and Cyberbullying in Sixth Grade Students

ERIC Educational Resources Information Center

Accordino, Denise B.; Accordino, Michael P.

2011-01-01

In a pilot study, sixth grade students (N = 124) completed a questionnaire assessing students' experience with bullying and cyberbullying, demographic information, quality of parent-child relationship, and ways they have dealt with bullying/cyberbullying in the past. Two multiple regression analyses were conducted. The multiple regression analysis…

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…

The Use of Multiple Regression Models to Determine if Conjoint Analysis Should Be Conducted on Aggregate Data.

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

1996-01-01

In a conjoint-analysis consumer-preference study, researchers must determine whether the product factor estimates, which measure consumer preferences, should be calculated and interpreted for each respondent or collectively. Multiple regression models can determine whether to aggregate data by examining factor-respondent interaction effects. This…

Double Cross-Validation in Multiple Regression: A Method of Estimating the Stability of Results.

ERIC Educational Resources Information Center

Rowell, R. Kevin

In multiple regression analysis, where resulting predictive equation effectiveness is subject to shrinkage, it is especially important to evaluate result replicability. Double cross-validation is an empirical method by which an estimate of invariance or stability can be obtained from research data. A procedure for double cross-validation is…

Stress and the multiple-role woman: taking a closer look at the "superwoman".

PubMed

Sumra, Monika K; Schillaci, Michael A

2015-01-01

In the academic literature there is debate as to whether women who engage in multiple social roles experience more or less stress than women in fewer roles. For the present research we examined the relationship between levels of engagement in seven distinct roles and perceived stress and life satisfaction in a small non-random sample of women in North America (N = 308). We did not find a significant correlation between role engagement and perceived stress, though we did find a small but significant positive correlation between role engagement and life satisfaction. Similarly, in a subset of the participants (N = 31), there was not a significant relationship between the level of role engagement and physiological stress as measured by hair or urinary cortisol levels. We found a significant negative correlation between perceived stress and life satisfaction, and role satisfaction. The results from multiple regression models did not identify the level of role engagement as a significant predictor of either perceived stress or life satisfaction. Role satisfaction in addition to several life style variables such as the frequency of sex and exercise were identified as significant predictors of both outcome variables. We also examined the popularized notion of the "superwoman", which we defined as women who fell within the 4th quartile of role engagement, or those engaged in the wife/mother/worker/homemaker role combination. Based on popular discourses surrounding the superwoman we expected that superwomen would exhibit higher levels of perceived stress. Our results revealed that superwomen do not experience a significantly higher level of perceived stress than non-superwomen. The results of our study therefore suggest that multiple role engagement in women, even at a relatively high level as experienced by "superwomen", is not associated with significantly higher stress, or reduced life satisfaction.

Results of the 2008 AORN Salary Survey.

PubMed

Bacon, Donald

2008-12-01

AORN conducted its sixth annual compensation survey for perioperative nurses in August of 2008. A multiple regression model was used to examine how a variety of variables including job title, education level, certification, experience, and geographic region affect nursing compensation. Comparisons between the 2008 and previous years' data are presented. The effects of other forms of compensation, such as on-call compensation, overtime, bonuses, and shift differentials on average base compensation rates also are examined.

Neurocognitive correlates of helplessness, hopelessness, and well-being in schizophrenia.

PubMed

Lysaker, P H; Clements, C A; Wright, D E; Evans, J; Marks, K A

2001-07-01

Persons with schizophrenia are widely recognized to experience potent feelings of hopelessness, helplessness, and a fragile sense of well-being. Although these subjective experiences have been linked to positive symptoms, little is known about their relationship to neurocognition. Accordingly, this study examined the relationship of self-reports of hope, self-efficacy, and well-being to measures of neurocognition, symptoms, and coping among 49 persons with schizophrenia or schizoaffective disorder. Results suggest that poorer executive function, verbal memory, and a greater reliance on escape avoidance as a coping mechanism predicted significantly higher levels of hope and well being with multiple regressions accounting for 34% and 20% of the variance (p < .0001), respectively. Self-efficacy predicted lower levels of positive symptoms and greater preference for escape avoidance as a coping mechanism with a multiple repression accounting for 9% of the variance (p < .05). Results may suggest that higher levels of neurocognitive impairment and an avoidant coping style may shield some with schizophrenia from painful subjective experiences. Theoretical and practical implications for rehabilitation are discussed.

Combining multiple regression and principal component analysis for accurate predictions for column ozone in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Rajab, Jasim M.; MatJafri, M. Z.; Lim, H. S.

2013-06-01

This study encompasses columnar ozone modelling in the peninsular Malaysia. Data of eight atmospheric parameters [air surface temperature (AST), carbon monoxide (CO), methane (CH4), water vapour (H2Ovapour), skin surface temperature (SSKT), atmosphere temperature (AT), relative humidity (RH), and mean surface pressure (MSP)] data set, retrieved from NASA's Atmospheric Infrared Sounder (AIRS), for the entire period (2003-2008) was employed to develop models to predict the value of columnar ozone (O3) in study area. The combined method, which is based on using both multiple regressions combined with principal component analysis (PCA) modelling, was used to predict columnar ozone. This combined approach was utilized to improve the prediction accuracy of columnar ozone. Separate analysis was carried out for north east monsoon (NEM) and south west monsoon (SWM) seasons. The O3 was negatively correlated with CH4, H2Ovapour, RH, and MSP, whereas it was positively correlated with CO, AST, SSKT, and AT during both the NEM and SWM season periods. Multiple regression analysis was used to fit the columnar ozone data using the atmospheric parameter's variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to acquire subsets of the predictor variables to be comprised in the linear regression model of the atmospheric parameter's variables. It was found that the increase in columnar O3 value is associated with an increase in the values of AST, SSKT, AT, and CO and with a drop in the levels of CH4, H2Ovapour, RH, and MSP. The result of fitting the best models for the columnar O3 value using eight of the independent variables gave about the same values of the R (≈0.93) and R2 (≈0.86) for both the NEM and SWM seasons. The common variables that appeared in both regression equations were SSKT, CH4 and RH, and the principal precursor of the columnar O3 value in both the NEM and SWM seasons was SSKT.

[Correlation of IL-8 and IL-6 in prostatic fluid with serum prostate-specific antigen level in patients with benign prostatic hyperplasia complicated by prostatitis].

PubMed

Ren, Xingfei; Wu, Chunlei; Yu, Qinnan; Zhu, Feng; Liu, Pei; Zhang, Huiqing

2016-01-01

To investigate the correlation of the levels of interleukin-8 (IL-8) and IL-6 in the prostatic fluid with serum levels of serum prostate-specific antigen (PSA) in patients with benign prostatic hyperplasia (BPH) complicated by prostatitis. A series of 211 patients undergoing surgery of BPH were divided into BPH group (n=75) and BPH with prostatitis group (n=136) according to the white blood cell count in the prostatic fluid. The clinical and laboratory findings were compared between the two groups, and stepwise regression analysis was used to assess the association of IL-8 and IL-6 with serum PSA level. No significant differences were found in age, BMI, blood pressure, blood glucose, blood lipids, IPSS score, PSA-Ratio, or prostate volume between the two groups (P<0.05). The patients with prostatitis had significantly increased serum PSA and prostate fluid IL-8 and IL-6 levels compared with those without prostatitis (P<0.001). Multiple linear regression analysis showed that IL-8 and IL-6 levels and white blood cell count in the prostatic fluid were all positively correlated with serum PSA level. Prostatitis is an important risk factor for elevated serum PSA level in patients with BPH, and both IL-8 and IL-6 levels in the prostatic fluid are correlated with serum PSA level.

Internet use and loneliness in older adults.

PubMed

Sum, Shima; Mathews, R Mark; Hughes, Ian; Campbell, Andrew

2008-04-01

Use of the Internet by seniors as a communication technology may lead to changes in older adult social relationships. This study used an online questionnaire to survey 222 Australians over 55 years of age on Internet use. Respondents primarily used the Internet for communication, seeking information, and commercial purposes. The results showed negative correlations between loneliness and well-being. Multiple regression analyses revealed that greater use of the Internet as a communication tool was associated with a lower level of social loneliness. In contrast, greater use of the Internet to find new people was associated with a higher level of emotional loneliness.

Factors Influencing Amount of Weekly Exercise Time in Colorectal Cancer Survivors.

PubMed

Chou, Yun-Jen; Lai, Yeur-Hur; Lin, Been-Ren; Liang, Jin-Tung; Shun, Shiow-Ching

Performing regular exercise of at least 150 minutes weekly has benefits for colorectal cancer survivors. However, barriers inhibit these survivors from performing regular exercise. The aim of this study was to explore exercise behaviors and significant factors influencing weekly exercise time of more than 150 minutes in colorectal cancer survivors. A cross-sectional study design was used to recruit participants in Taiwan. Guided by the ecological model of health behavior, exercise barriers were assessed including intrapersonal, interpersonal, and environment-related barriers. A multiple logistic regression was used to explore the factors associated with the amount of weekly exercise. Among 321 survivors, 57.0% of them had weekly exercise times of more than 150 minutes. The results identified multiple levels of significant factors related to weekly exercise times including intrapersonal factors (occupational status, functional status, pain, interest in exercise, and beliefs about the importance of exercise) and exercise barriers related to environmental factors (lack of time and bad weather). No interpersonal factors were found to be significant. Colorectal cancer survivors experienced low levels of physical and psychological distress. Multiple levels of significant factors related to exercise time including intrapersonal factors as well as exercise barriers related to environmental factors should be considered. Healthcare providers should discuss with their patients how to perform exercise programs; the discussion should address multiple levels of the ecological model such as any pain problems, functional status, employment status, and time limitations, as well as community environment.

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

A nonparametric multiple imputation approach for missing categorical data.

PubMed

Zhou, Muhan; He, Yulei; Yu, Mandi; Hsu, Chiu-Hsieh

2017-06-06

Incomplete categorical variables with more than two categories are common in public health data. However, most of the existing missing-data methods do not use the information from nonresponse (missingness) probabilities. We propose a nearest-neighbour multiple imputation approach to impute a missing at random categorical outcome and to estimate the proportion of each category. The donor set for imputation is formed by measuring distances between each missing value with other non-missing values. The distance function is calculated based on a predictive score, which is derived from two working models: one fits a multinomial logistic regression for predicting the missing categorical outcome (the outcome model) and the other fits a logistic regression for predicting missingness probabilities (the missingness model). A weighting scheme is used to accommodate contributions from two working models when generating the predictive score. A missing value is imputed by randomly selecting one of the non-missing values with the smallest distances. We conduct a simulation to evaluate the performance of the proposed method and compare it with several alternative methods. A real-data application is also presented. The simulation study suggests that the proposed method performs well when missingness probabilities are not extreme under some misspecifications of the working models. However, the calibration estimator, which is also based on two working models, can be highly unstable when missingness probabilities for some observations are extremely high. In this scenario, the proposed method produces more stable and better estimates. In addition, proper weights need to be chosen to balance the contributions from the two working models and achieve optimal results for the proposed method. We conclude that the proposed multiple imputation method is a reasonable approach to dealing with missing categorical outcome data with more than two levels for assessing the distribution of the outcome. In terms of the choices for the working models, we suggest a multinomial logistic regression for predicting the missing outcome and a binary logistic regression for predicting the missingness probability.

Quantification and regionalization of groundwater recharge in South-Central Kansas: Integrating field characterization, statistical analysis, and GIS

USGS Publications Warehouse

Sophocleous, M.

2000-01-01

A practical methodology for recharge characterization was developed based on several years of field-oriented research at 10 sites in the Great Bend Prairie of south-central Kansas. This methodology combines the soil-water budget on a storm-by-storm year-round basis with the resulting watertable rises. The estimated 1985-1992 average annual recharge was less than 50mm/year with a range from 15 mm/year (during the 1998 drought) to 178 mm/year (during the 1993 flood year). Most of this recharge occurs during the spring months. To regionalize these site-specific estimates, an additional methodology based on multiple (forward) regression analysis combined with classification and GIS overlay analyses was developed and implemented. The multiple regression analysis showed that the most influential variables were, in order of decreasing importance, total annual precipitation, average maximum springtime soil-profile water storage, average shallowest springtime depth to watertable, and average springtime precipitation rate. Therefore, four GIS (ARC/INFO) data "layers" or coverages were constructed for the study region based on these four variables, and each such coverage was classified into the same number of data classes to avoid biasing the results. The normalized regression coefficients were employed to weigh the class rankings of each recharge-affecting variable. This approach resulted in recharge zonations that agreed well with the site recharge estimates. During the "Great Flood of 1993," when rainfall totals exceeded normal levels by -200% in the northern portion of the study region, the developed regionalization methodology was tested against such extreme conditions, and proved to be both practical, based on readily available or easily measurable data, and robust. It was concluded that the combination of multiple regression and GIS overlay analyses is a powerful and practical approach to regionalizing small samples of recharge estimates.

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.

Association between injury pattern of patients with multiple injuries and circulating levels of soluble tumor necrosis factor receptors, interleukin-6 and interleukin-10, and polymorphonuclear neutrophil elastase.

PubMed

Hensler, Thorsten; Sauerland, Stefan; Bouillon, Bertil; Raum, Marcus; Rixen, Dieter; Helling, Hanns-J; Andermahr, Jonas; Neugebauer, Edmund A M

2002-05-01

Our knowledge about the bidirectional interactions between brain and whole organism after trauma is still limited. It was the purpose of this prospective clinical study to determine the influence of severe head trauma (SHT) as well as trauma in different anatomic injury regions on posttraumatic inflammatory mediator levels from patients with multiple injuries. Thirty-five healthy controls, 33 patients with an isolated SHT, 47 patients with multiple injuries without SHT, and 45 patients with both SHT and multiple injuries were studied. The posttraumatic plasma levels of soluble tumor necrosis factor receptors p55 and p75, interleukin (IL)-6, IL-10, and polymorphonuclear neutrophil (PMN) elastase were monitored using enzyme-linked immunosorbent assay technique. The influence of head injuries as well as thorax, abdomen, and extremity injuries on the mediator release from patients with multiple injuries was investigated by multivariate linear regression models. The soluble tumor necrosis factor receptor p55/p75 ratio was significantly elevated within 3 hours of trauma in all three injury groups and returned to reference ratios after 12 hours. The lowest increase was found in patients suffering from an isolated SHT. Lowest mediator levels in this patient population were also found for IL-6, IL-10, and PMN elastase during the first 36 hours after trauma. Additional injuries to the head, thorax, abdomen, and extremity modulated mediator levels to a different degree. No specific effect was found for SHT when compared with other injury groups. Thorax injuries caused the quickest rise in mediator levels, whereas abdominal injuries significantly increased PMN elastase levels 12 to 24 hours after trauma. Traumatic injuries cause the liberation of various mediators, without any specific association between anatomic injury pattern and the pattern of mediator release.

Ridge: a computer program for calculating ridge regression estimates

Treesearch

Donald E. Hilt; Donald W. Seegrist

1977-01-01

Least-squares coefficients for multiple-regression models may be unstable when the independent variables are highly correlated. Ridge regression is a biased estimation procedure that produces stable estimates of the coefficients. Ridge regression is discussed, and a computer program for calculating the ridge coefficients is presented.

Crop status evaluations and yield predictions

NASA Technical Reports Server (NTRS)

Haun, J. R.

1975-01-01

A model was developed for predicting the day 50 percent of the wheat crop is planted in North Dakota. This model incorporates location as an independent variable. The Julian date when 50 percent of the crop was planted for the nine divisions of North Dakota for seven years was regressed on the 49 variables through the step-down multiple regression procedure. This procedure begins with all of the independent variables and sequentially removes variables that are below a predetermined level of significance after each step. The prediction equation was tested on daily data. The accuracy of the model is considered satisfactory for finding the historic dates on which to initiate yield prediction model. Growth prediction models were also developed for spring wheat.

Estimation of crown closure from AVIRIS data using regression analysis

NASA Technical Reports Server (NTRS)

Staenz, K.; Williams, D. J.; Truchon, M.; Fritz, R.

1993-01-01

Crown closure is one of the input parameters used for forest growth and yield modelling. Preliminary work by Staenz et al. indicates that imaging spectrometer data acquired with sensors such as the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) have some potential for estimating crown closure on a stand level. The objectives of this paper are: (1) to establish a relationship between AVIRIS data and the crown closure derived from aerial photography of a forested test site within the Interior Douglas Fir biogeoclimatic zone in British Columbia, Canada; (2) to investigate the impact of atmospheric effects and the forest background on the correlation between AVIRIS data and crown closure estimates; and (3) to improve this relationship using multiple regression analysis.

A clinical study of electrophysiological correlates of behavioural comfort levels in cochlear implantees.

PubMed

Raghunandhan, S; Ravikumar, A; Kameswaran, Mohan; Mandke, Kalyani; Ranjith, R

2014-05-01

Indications for cochlear implantation have expanded today to include very young children and those with syndromes/multiple handicaps. Programming the implant based on behavioural responses may be tedious for audiologists in such cases, wherein matching an effective Measurable Auditory Percept (MAP) and appropriate MAP becomes the key issue in the habilitation program. In 'Difficult to MAP' scenarios, objective measures become paramount to predict optimal current levels to be set in the MAP. We aimed to (a) study the trends in multi-modal electrophysiological tests and behavioural responses sequentially over the first year of implant use; (b) generate normative data from the above; (c) correlate the multi-modal electrophysiological thresholds levels with behavioural comfort levels; and (d) create predictive formulae for deriving optimal comfort levels (if unknown), using linear and multiple regression analysis. This prospective study included 10 profoundly hearing impaired children aged between 2 and 7 years with normal inner ear anatomy and no additional handicaps. They received the Advanced Bionics HiRes 90 K Implant with Harmony Speech processor and used HiRes-P with Fidelity 120 strategy. They underwent, impedance telemetry, neural response imaging, electrically evoked stapedial response telemetry (ESRT), and electrically evoked auditory brainstem response (EABR) tests at 1, 4, 8, and 12 months of implant use, in conjunction with behavioural mapping. Trends in electrophysiological and behavioural responses were analyzed using paired t-test. By Karl Pearson's correlation method, electrode-wise correlations were derived for neural response imaging (NRI) thresholds versus most comfortable level (M-levels) and offset based (apical, mid-array, and basal array) correlations for EABR and ESRT thresholds versus M-levels were calculated over time. These were used to derive predictive formulae by linear and multiple regression analysis. Such statistically predicted M-levels were compared with the behaviourally recorded M-levels among the cohort, using Cronbach's alpha reliability test method for confirming the efficacy of this method. NRI, ESRT, and EABR thresholds showed statistically significant positive correlations with behavioural M-levels, which improved with implant use over time. These correlations were used to derive predicted M-levels using regression analysis. On an average, predicted M-levels were found to be statistically reliable and they were a fair match to the actual behavioural M-levels. When applied in clinical practice, the predicted values were found to be useful for programming members of the study group. However, individuals showed considerable deviations in behavioural M-levels, above and below the electrophysiologically predicted values, due to various factors. While the current method appears helpful as a reference to predict initial maps in 'difficult to Map' subjects, it is recommended that behavioural measures are mandatory to further optimize the maps for these individuals. The study explores the trends, correlations and individual variabilities that occur between electrophysiological tests and behavioural responses, recorded over time among a cohort of cochlear implantees. The statistical method shown may be used as a guideline to predict optimal behavioural levels in difficult situations among future implantees, bearing in mind that optimal M-levels for individuals can vary from predicted values. In 'Difficult to MAP' scenarios, following a protocol of sequential behavioural programming, in conjunction with electrophysiological correlates will provide the best outcomes.

Evolution of Space Dependent Growth in the Teleost Astyanax mexicanus

PubMed Central

Gallo, Natalya D.; Jeffery, William R.

2012-01-01

The relationship between growth rate and environmental space is an unresolved issue in teleosts. While it is known from aquaculture studies that stocking density has a negative relationship to growth, the underlying mechanisms have not been elucidated, primarily because the growth rate of populations rather than individual fish were the subject of all previous studies. Here we investigate this problem in the teleost Astyanax mexicanus, which consists of a sighted surface-dwelling form (surface fish) and several blind cave-dwelling (cavefish) forms. Surface fish and cavefish are distinguished by living in spatially contrasting environments and therefore are excellent models to study the effects of environmental size on growth. Multiple controlled growth experiments with individual fish raised in confined or unconfined spaces showed that environmental size has a major impact on growth rate in surface fish, a trait we have termed space dependent growth (SDG). In contrast, SDG has regressed to different degrees in the Pachón and Tinaja populations of cavefish. Mating experiments between surface and Pachón cavefish show that SDG is inherited as a dominant trait and is controlled by multiple genetic factors. Despite its regression in blind cavefish, SDG is not affected when sighted surface fish are raised in darkness, indicating that vision is not required to perceive and react to environmental space. Analysis of plasma cortisol levels showed that an elevation above basal levels occurred soon after surface fish were exposed to confined space. This initial cortisol peak was absent in Pachón cavefish, suggesting that the effects of confined space on growth may be mediated partly through a stress response. We conclude that Astyanax reacts to confined spaces by exhibiting SDG, which has a genetic component and shows evolutionary regression during adaptation of cavefish to confined environments. PMID:22870223

A retrospective study: correlation of histologic inflammation in biopsy specimens of Chinese men undergoing surgery for benign prostatic hyperplasia with serum prostate-specific antigen.

PubMed

Song, Lingmin; Zhu, Yuchun; Han, Ping; Chen, Ni; Lin, Dao; Lai, Jianyu; Wei, Qiang

2011-03-01

To reveal the correlation between benign prostatic hyperplasia (BPH) histologic inflammation and serum prostate-specific antigen (sPSA) concentrations, and the possible mechanism. Patients underwent surgery at the Urology Department of West China Hospital of Sichuan University were retrospectively studied. Preoperative sPSA and transrectal ultrasonography were measured. According to the histopathological classification system for chronic prostatic inflammation proposed by the Chronic Prostatitis Collaborative Research Network (CPCRN) and the International Prostatitis Collaborative Network (IPCN), we classified the histologic sections of prostatic biopsy into glandular, periglandular, and stromal inflammation by the anatomical location of inflammatory infiltration. The glandular inflammation was graded according to the inflammatory aggressiveness. The periglandular and stromal inflammation were graded according to the inflammatory density. The correlation between histologic inflammation and sPSA was studied by a multiple regression model in conjunction with age and total prostatic volume. A total of 454 patients with exclusively BPH were analyzed. The periglandular inflammatory infiltration was the most common pattern (95.6%). Single regression analysis revealed that total prostatic volume, the aggressiveness of glandular inflammation, and the intensity of periglandular and stromal inflammation were correlated with sPSA. However, the multiple regression analysis revealed that only the total prostatic volume and the aggressiveness of glandular inflammation were correlated significantly with sPSA (R = .389, 0.289; P = .000). The aggressiveness of glandular inflammatory infiltration in BPH is a significant contributor to elevated sPSA levels. The theory of leakage may be the most reasonable mechanism to reveal the correlation morphologically. We should take inflammation into consideration when interpreting the abnormal elevating of sPSA levels. Copyright © 2011 Elsevier Inc. All rights reserved.

Correlates and predictors of missed nursing care in hospitals.

PubMed

Bragadóttir, Helga; Kalisch, Beatrice J; Tryggvadóttir, Gudný Bergthora

2017-06-01

To identify the contribution of hospital, unit, staff characteristics, staffing adequacy and teamwork to missed nursing care in Iceland hospitals. A recently identified quality indicator for nursing care and patient safety is missed nursing care defined as any standard, required nursing care omitted or significantly delayed, indicating an error of omission. Former studies point to contributing factors to missed nursing care regarding hospital, unit and staff characteristics, perceptions of staffing adequacy as well as nursing teamwork, displayed in the Missed Nursing Care Model. This was a quantitative cross-sectional survey study. The samples were all registered nurses and practical nurses (n = 864) working on 27 medical, surgical and intensive care inpatient units in eight hospitals throughout Iceland. Response rate was 69·3%. Data were collected in March-April 2012 using the combined MISSCARE Survey-Icelandic and the Nursing Teamwork Survey-Icelandic. Descriptive, correlational and regression statistics were used for data analysis. Missed nursing care was significantly related to hospital and unit type, participants' age and role and their perception of adequate staffing and level of teamwork. The multiple regression testing of Model 1 indicated unit type, role, age and staffing adequacy to predict 16% of the variance in missed nursing care. Controlling for unit type, role, age and perceptions of staffing adequacy, the multiple regression testing of Model 2 showed that nursing teamwork predicted an additional 14% of the variance in missed nursing care. The results shed light on the correlates and predictors of missed nursing care in hospitals. This study gives direction as to the development of strategies for decreasing missed nursing care, including ensuring appropriate staffing levels and enhanced teamwork. By identifying contributing factors to missed nursing care, appropriate interventions can be developed and tested. © 2016 John Wiley & Sons Ltd.

A mixed-effects regression model for longitudinal multivariate ordinal data.

PubMed

Liu, Li C; Hedeker, Donald

2006-03-01

A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do not have to follow the proportional odds assumption and can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is proposed utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher scoring solution, which provides standard errors for all model parameters, is used. An analysis of a longitudinal substance use data set, where four items of substance use behavior (cigarette use, alcohol use, marijuana use, and getting drunk or high) are repeatedly measured over time, is used to illustrate application of the proposed model.

Multicollinearity may lead to artificial interaction: an example from a cross sectional study of biomarkers.

PubMed

Sithisarankul, P; Weaver, V M; Diener-West, M; Strickland, P T

1997-06-01

Collinearity is the situation which arises in multiple regression when some or all of the explanatory variables are so highly correlated with one another that it becomes very difficult, if not impossible, to disentangle their influences and obtain a reasonably precise estimate of their effects. Suppressor variable is one of the extreme situations of collinearity that one variable can substantially increase the multiple correlation when combined with a variable that is only modestly correlated with the response variable. In this study, we describe the process by which we disentangled and discovered multicollinearity and its consequences, namely artificial interaction, using the data from cross-sectional quantification of several biomarkers. We showed how the collinearity between one biomarker (blood lead level) and another (urinary trans, trans-muconic acid) and their interaction (blood lead level* urinary trans, trans-muconic acid) can lead to the observed artificial interaction on the third biomarker (urinary 5-aminolevulinic acid).

Short-term electric power demand forecasting based on economic-electricity transmission model

NASA Astrophysics Data System (ADS)

Li, Wenfeng; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Wang, Yubin Mao; Wang, Jiangbo; He, Dandan

2018-04-01

Short-term electricity demand forecasting is the basic work to ensure safe operation of the power system. In this paper, a practical economic electricity transmission model (EETM) is built. With the intelligent adaptive modeling capabilities of Prognoz Platform 7.2, the econometric model consists of three industrial added value and income levels is firstly built, the electricity demand transmission model is also built. By multiple regression, moving averages and seasonal decomposition, the problem of multiple correlations between variables is effectively overcome in EETM. The validity of EETM is proved by comparison with the actual value of Henan Province. Finally, EETM model is used to forecast the electricity consumption of the 1-4 quarter of 2018.

Studying Gene and Gene-Environment Effects of Uncommon and Common Variants on Continuous Traits: A Marker-Set Approach Using Gene-Trait Similarity Regression

PubMed Central

Tzeng, Jung-Ying; Zhang, Daowen; Pongpanich, Monnat; Smith, Chris; McCarthy, Mark I.; Sale, Michèle M.; Worrall, Bradford B.; Hsu, Fang-Chi; Thomas, Duncan C.; Sullivan, Patrick F.

2011-01-01

Genomic association analyses of complex traits demand statistical tools that are capable of detecting small effects of common and rare variants and modeling complex interaction effects and yet are computationally feasible. In this work, we introduce a similarity-based regression method for assessing the main genetic and interaction effects of a group of markers on quantitative traits. The method uses genetic similarity to aggregate information from multiple polymorphic sites and integrates adaptive weights that depend on allele frequencies to accomodate common and uncommon variants. Collapsing information at the similarity level instead of the genotype level avoids canceling signals that have the opposite etiological effects and is applicable to any class of genetic variants without the need for dichotomizing the allele types. To assess gene-trait associations, we regress trait similarities for pairs of unrelated individuals on their genetic similarities and assess association by using a score test whose limiting distribution is derived in this work. The proposed regression framework allows for covariates, has the capacity to model both main and interaction effects, can be applied to a mixture of different polymorphism types, and is computationally efficient. These features make it an ideal tool for evaluating associations between phenotype and marker sets defined by linkage disequilibrium (LD) blocks, genes, or pathways in whole-genome analysis. PMID:21835306

Statistical experiments using the multiple regression research for prediction of proper hardness in areas of phosphorus cast-iron brake shoes manufacturing

NASA Astrophysics Data System (ADS)

Kiss, I.; Cioată, V. G.; Ratiu, S. A.; Rackov, M.; Penčić, M.

2018-01-01

Multivariate research is important in areas of cast-iron brake shoes manufacturing, because many variables interact with each other simultaneously. This article focuses on expressing the multiple linear regression model related to the hardness assurance by the chemical composition of the phosphorous cast irons destined to the brake shoes, having in view that the regression coefficients will illustrate the unrelated contributions of each independent variable towards predicting the dependent variable. In order to settle the multiple correlations between the hardness of the cast-iron brake shoes, and their chemical compositions several regression equations has been proposed. Is searched a mathematical solution which can determine the optimum chemical composition for the hardness desirable values. Starting from the above-mentioned affirmations two new statistical experiments are effectuated related to the values of Phosphorus [P], Manganese [Mn] and Silicon [Si]. Therefore, the regression equations, which describe the mathematical dependency between the above-mentioned elements and the hardness, are determined. As result, several correlation charts will be revealed.

Comparison of Regression Methods to Compute Atmospheric Pressure and Earth Tidal Coefficients in Water Level Associated with Wenchuan Earthquake of 12 May 2008

NASA Astrophysics Data System (ADS)

He, Anhua; Singh, Ramesh P.; Sun, Zhaohua; Ye, Qing; Zhao, Gang

2016-07-01

The earth tide, atmospheric pressure, precipitation and earthquake fluctuations, especially earthquake greatly impacts water well levels, thus anomalous co-seismic changes in ground water levels have been observed. In this paper, we have used four different models, simple linear regression (SLR), multiple linear regression (MLR), principal component analysis (PCA) and partial least squares (PLS) to compute the atmospheric pressure and earth tidal effects on water level. Furthermore, we have used the Akaike information criterion (AIC) to study the performance of various models. Based on the lowest AIC and sum of squares for error values, the best estimate of the effects of atmospheric pressure and earth tide on water level is found using the MLR model. However, MLR model does not provide multicollinearity between inputs, as a result the atmospheric pressure and earth tidal response coefficients fail to reflect the mechanisms associated with the groundwater level fluctuations. On the premise of solving serious multicollinearity of inputs, PLS model shows the minimum AIC value. The atmospheric pressure and earth tidal response coefficients show close response with the observation using PLS model. The atmospheric pressure and the earth tidal response coefficients are found to be sensitive to the stress-strain state using the observed data for the period 1 April-8 June 2008 of Chuan 03# well. The transient enhancement of porosity of rock mass around Chuan 03# well associated with the Wenchuan earthquake (Mw = 7.9 of 12 May 2008) that has taken its original pre-seismic level after 13 days indicates that the co-seismic sharp rise of water well could be induced by static stress change, rather than development of new fractures.

Impact of Texas high school science teacher credentials on student performance in high school science

NASA Astrophysics Data System (ADS)

George, Anna Ray Bayless

A study was conducted to determine the relationship between the credentials held by science teachers who taught at a school that administered the Science Texas Assessment on Knowledge and Skills (Science TAKS), the state standardized exam in science, at grade 11 and student performance on a state standardized exam in science administered in grade 11. Years of teaching experience, teacher certification type(s), highest degree level held, teacher and school demographic information, and the percentage of students who met the passing standard on the Science TAKS were obtained through a public records request to the Texas Education Agency (TEA) and the State Board for Educator Certification (SBEC). Analysis was performed through the use of canonical correlation analysis and multiple linear regression analysis. The results of the multiple linear regression analysis indicate that a larger percentage of students met the passing standard on the Science TAKS state attended schools in which a large portion of the high school science teachers held post baccalaureate degrees, elementary and physical science certifications, and had 11-20 years of teaching experience.

Association of Alimentary Factors and Nutritional Status with Caries in Children of Leon, Mexico.

PubMed

Guizar, Juan Manuel; Muñoz, Nathalie; Amador, Norma; Garcia, Gabriela

To determine the association between types of food consumed, nutritional status (BMI) and caries in schoolchildren. A cross-sectional study was performed with 224 schoolchildren 6 to 12 years of age. DMFT/ dmft indices, level of oral hygiene, nutritional status as quantified by BMI and types of food consumed were determined in all participants. Data were analysed using multiple linear regression with significance set at p < 0.05. Caries prevalence was 36%. In the multiple linear regression analysis adjusted for BMI, variables related to a higher number of caries were younger age and lower intake of vitamin D, calcium and fiber, with higher consumption of phosphorous and carbohydrates (R2 = 0.30; p < 0.0001 for the model). Sweetened softdrinks and chewy candy were risk factors for higher caries prevalence, while consuming milk and carrots were protectors. Caries in schoolchildren is highly prevalent in this community and is related to younger age and lower intake of vitamin D, calcium and fiber, but a higher consumption of phosphorous and carbohydrates. No relationship was found between caries and nutritional status.

Quantification of the effects of quality investment on the Cost of Poor Quality: A quasi-experimental study

NASA Astrophysics Data System (ADS)

Tamimi, Abdallah Ibrahim

Quality management is a fundamental challenge facing businesses. This research attempted to quantify the effect of quality investment on the Cost of Poor Quality (COPQ) in an aerospace company utilizing 3 years of quality data at United Launch Alliance, a Boeing -- Lockheed Martin Joint Venture Company. Statistical analysis tools, like multiple regressions, were used to quantify the relationship between quality investments and COPQ. Strong correlations were evident by the high correlation coefficient R2 and very small p-values in multiple regression analysis. The models in the study helped produce an Excel macro that based on preset constraints, optimized the level of quality spending to minimize COPQ. The study confirmed that as quality investments were increased, the COPQ decreased steadily until a point of diminishing return was reached. The findings may be used to develop an approach to reduce the COPQ and enhance product performance. Achieving superior quality in rocket launching enhances the accuracy, reliability, and mission success of delivering satellites to their precise orbits in pursuit of knowledge, peace, and freedom while assuring safety for the end user.

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

Smith, Kandler; Shi, Ying; Santhanagopalan, Shriram

Predictive models of Li-ion battery lifetime must consider a multiplicity of electrochemical, thermal, and mechanical degradation modes experienced by batteries in application environments. To complicate matters, Li-ion batteries can experience different degradation trajectories that depend on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. We present a generalized battery life prognostic model framework for battery systems design and control. The model framework consists of trial functions that are statistically regressed to Li-ion cell life datasets wherein the cells have been aged under differentmore » levels of stress. Degradation mechanisms and rate laws dependent on temperature, storage, and cycling condition are regressed to the data, with multiple model hypotheses evaluated and the best model down-selected based on statistics. The resulting life prognostic model, implemented in state variable form, is extensible to arbitrary real-world scenarios. The model is applicable in real-time control algorithms to maximize battery life and performance. We discuss efforts to reduce lifetime prediction error and accommodate its inevitable impact in controller design.« less

A Semiparametric Change-Point Regression Model for Longitudinal Observations.

PubMed

Xing, Haipeng; Ying, Zhiliang

2012-12-01

Many longitudinal studies involve relating an outcome process to a set of possibly time-varying covariates, giving rise to the usual regression models for longitudinal data. When the purpose of the study is to investigate the covariate effects when experimental environment undergoes abrupt changes or to locate the periods with different levels of covariate effects, a simple and easy-to-interpret approach is to introduce change-points in regression coefficients. In this connection, we propose a semiparametric change-point regression model, in which the error process (stochastic component) is nonparametric and the baseline mean function (functional part) is completely unspecified, the observation times are allowed to be subject-specific, and the number, locations and magnitudes of change-points are unknown and need to be estimated. We further develop an estimation procedure which combines the recent advance in semiparametric analysis based on counting process argument and multiple change-points inference, and discuss its large sample properties, including consistency and asymptotic normality, under suitable regularity conditions. Simulation results show that the proposed methods work well under a variety of scenarios. An application to a real data set is also given.

Probabilistic Estimates of Global Mean Sea Level and its Underlying Processes

NASA Astrophysics Data System (ADS)

Hay, C.; Morrow, E.; Kopp, R. E.; Mitrovica, J. X.

2015-12-01

Local sea level can vary significantly from the global mean value due to a suite of processes that includes ongoing sea-level changes due to the last ice age, land water storage, ocean circulation changes, and non-uniform sea-level changes that arise when modern-day land ice rapidly melts. Understanding these sources of spatial and temporal variability is critical to estimating past and present sea-level change and projecting future sea-level rise. Using two probabilistic techniques, a multi-model Kalman smoother and Gaussian process regression, we have reanalyzed 20th century tide gauge observations to produce a new estimate of global mean sea level (GMSL). Our methods allow us to extract global information from the sparse tide gauge field by taking advantage of the physics-based and model-derived geometry of the contributing processes. Both methods provide constraints on the sea-level contribution of glacial isostatic adjustment (GIA). The Kalman smoother tests multiple discrete models of glacial isostatic adjustment (GIA), probabilistically computing the most likely GIA model given the observations, while the Gaussian process regression characterizes the prior covariance structure of a suite of GIA models and then uses this structure to estimate the posterior distribution of local rates of GIA-induced sea-level change. We present the two methodologies, the model-derived geometries of the underlying processes, and our new probabilistic estimates of GMSL and GIA.

The association between spiritual well-being and burnout in intensive care unit nurses: A descriptive study.

PubMed

Kim, Hyun Sook; Yeom, Hye-Ah

2018-06-01

To describe the spiritual well-being and burnout of intensive care unit nurses and examine the relationship between these factors. This was a cross-sectional descriptive study. The participants were 318 intensive care unit recruited from three university hospitals in South Korea. The survey questionnaire included demographic information, work-related characteristics and end-of-life care experience, along with the Spiritual Well-Being Scale and Burnout Questionnaire. The data were analysed using descriptive statistics, t-tests, ANOVA with Scheffé test and a multiple regression analysis. The burnout level among intensive care unit nurses was 3.15 out of 5. A higher level of burnout was significantly associated with younger age, lower education level, single marital status, having no religion, less work experience and previous end-of-life care experience. Higher levels of spiritual well-being were associated with lower levels of burnout, even after controlling for the general characteristics in the regression model. Intensive care unit nurses experience a high level of burnout in general. Increased spiritual well-being might reduce burnout among intensive care unit nurses. Younger and less experienced nurses should receive more attention as a vulnerable group with lower spirituality and greater burnout in intensive care unit settings. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimating Causal Effects of Education Interventions Using a Two-Rating Regression Discontinuity Design: Lessons from a Simulation Study

ERIC Educational Resources Information Center

Porter, Kristin E.; Reardon, Sean F.; Unlu, Fatih; Bloom, Howard S.; Robinson-Cimpian, Joseph P.

2014-01-01

A valuable extension of the single-rating regression discontinuity design (RDD) is a multiple-rating RDD (MRRDD). To date, four main methods have been used to estimate average treatment effects at the multiple treatment frontiers of an MRRDD: the "surface" method, the "frontier" method, the "binding-score" method, and…

Development of Multiple Regression Equations To Predict Fourth Graders' Achievement in Reading and Selected Content Areas.

ERIC Educational Resources Information Center

Hafner, Lawrence E.

A study developed a multiple regression prediction equation for each of six selected achievement variables in a popular standardized test of achievement. Subjects, 42 fourth-grade pupils randomly selected across several classes in a large elementary school in a north Florida city, were administered several standardized tests to determine predictor…

Physical and Cognitive-Affective Factors Associated with Fatigue in Individuals with Fibromyalgia: A Multiple Regression Analysis

ERIC Educational Resources Information Center

Muller, Veronica; Brooks, Jessica; Tu, Wei-Mo; Moser, Erin; Lo, Chu-Ling; Chan, Fong

2015-01-01

Purpose: The main objective of this study was to determine the extent to which physical and cognitive-affective factors are associated with fibromyalgia (FM) fatigue. Method: A quantitative descriptive design using correlation techniques and multiple regression analysis. The participants consisted of 302 members of the National Fibromyalgia &…

Some Applied Research Concerns Using Multiple Linear Regression Analysis.

ERIC Educational Resources Information Center

Newman, Isadore; Fraas, John W.

The intention of this paper is to provide an overall reference on how a researcher can apply multiple linear regression in order to utilize the advantages that it has to offer. The advantages and some concerns expressed about the technique are examined. A number of practical ways by which researchers can deal with such concerns as…

Predicting Final GPA of Graduate School Students: Comparing Artificial Neural Networking and Simultaneous Multiple Regression

ERIC Educational Resources Information Center

Anderson, Joan L.

2006-01-01

Data from graduate student applications at a large Western university were used to determine which factors were the best predictors of success in graduate school, as defined by cumulative graduate grade point average. Two statistical models were employed and compared: artificial neural networking and simultaneous multiple regression. Both models…

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…

Regression Models for the Analysis of Longitudinal Gaussian Data from Multiple Sources

PubMed Central

O’Brien, Liam M.; Fitzmaurice, Garrett M.

2006-01-01

We present a regression model for the joint analysis of longitudinal multiple source Gaussian data. Longitudinal multiple source data arise when repeated measurements are taken from two or more sources, and each source provides a measure of the same underlying variable and on the same scale. This type of data generally produces a relatively large number of observations per subject; thus estimation of an unstructured covariance matrix often may not be possible. We consider two methods by which parsimonious models for the covariance can be obtained for longitudinal multiple source data. The methods are illustrated with an example of multiple informant data arising from a longitudinal interventional trial in psychiatry. PMID:15726666

A Heckman selection model for the safety analysis of signalized intersections

PubMed Central

Wong, S. C.; Zhu, Feng; Pei, Xin; Huang, Helai; Liu, Youjun

2017-01-01

Purpose The objective of this paper is to provide a new method for estimating crash rate and severity simultaneously. Methods This study explores a Heckman selection model of the crash rate and severity simultaneously at different levels and a two-step procedure is used to investigate the crash rate and severity levels. The first step uses a probit regression model to determine the sample selection process, and the second step develops a multiple regression model to simultaneously evaluate the crash rate and severity for slight injury/kill or serious injury (KSI), respectively. The model uses 555 observations from 262 signalized intersections in the Hong Kong metropolitan area, integrated with information on the traffic flow, geometric road design, road environment, traffic control and any crashes that occurred during two years. Results The results of the proposed two-step Heckman selection model illustrate the necessity of different crash rates for different crash severity levels. Conclusions A comparison with the existing approaches suggests that the Heckman selection model offers an efficient and convenient alternative method for evaluating the safety performance at signalized intersections. PMID:28732050

Prediction of Vancomycin Dose for Recommended Trough Concentrations in Pediatric Patients With Cystic Fibrosis.

PubMed

Amin, Raid W; Guttmann, Rodney P; Harris, Quianna R; Thomas, Janesha W

2018-05-01

Vancomycin is a key antibiotic used in the treatment of multiple conditions including infections associated with cystic fibrosis and methicillin-resistant Staphylococcus aureus. The present study sought to develop a model based on empirical evidence of optimal vancomycin dose as judged by clinical observations that could accelerate the achievement of desired trough level in children with cystic fibrosis. Transformations of dose and trough were used to arrive at regression models with excellent fit for dose based on weight or age for a target trough. Results of this study indicate that the 2 proposed regression models are robust to changes in age or weight, suggesting that the daily dose on a per-kilogram basis is determined primarily by the desired trough level. The results show that to obtain a vancomycin trough level of 20 μg/mL, a dose of 80 mg/kg/day is needed. This analysis should improve the efficiency of vancomycin usage by reducing the number of titration steps, resulting in improved patient outcome and experience. © 2018, The American College of Clinical Pharmacology.

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.

Correlation between Volume of Apical Periodontitis Determined by Cone-beam Computed Tomography Analysis and Endotoxin Levels Found in Primary Root Canal Infection.

PubMed

Cardoso, Flávia G R; Ferreira, Nádia S; Martinho, Frederico C; Nascimento, Gustavo G; Manhães, Luiz R C; Rocco, Marco A; Carvalho, Cláudio A T; Valera, Marcia C

2015-07-01

This clinical study was conducted to correlate the levels of endotoxins and bacterial counts found in primary endodontic infection with the volume of periapical bone destruction determined by cone-beam computed tomography (CBCT) analysis. Moreover, the levels of bacteria and endotoxins were correlated with the development of clinical features. Twenty-four root canals with primary endodontic disease and apical periodontitis were selected. Clinical features such as pain on palpation, pain on percussion, and previous episode of pain were recorded. The volume (cubic millimeters) of periapical bone destruction was determined by CBCT analysis. Endotoxins and bacterial samplings were collected by using sterile/apyrogenic paper points. Endotoxins were quantified by using limulus amebocyte lysate assay (KQCL test), and bacterial count (colony-forming units [CFU]/mL) was determined by using anaerobic culture techniques. Data were analyzed by Pearson correlation and multiple logistic regression (P < .05). Endotoxins and bacteria were detected in 100% of the root canal samples (24 of 24), with median values of 10.92 endotoxin units (EU)/mL (1.75-128 EU/mL) and 7.5 × 10(5) CFU/mL (3.20 × 10(5)-8.16 × 10(6) CFU/mL), respectively. The median volume of bone destruction determined by CBCT analysis was 100 mm(3) (10-450 mm(3)). The multiple regression analysis revealed a positive correlation between higher levels of endotoxins present in root canal infection and larger volume of bone destruction (P < .05). Moreover, higher levels of endotoxins were also correlated with the presence of previous pain (P < .05). Our findings revealed that the levels of endotoxins found in root canal infection are related to the volume of periapical bone destruction determined by CBCT analysis. Moreover, the levels of endotoxin are related to the presence of previous pain. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Zinc Levels in Left Ventricular Hypertrophy.

PubMed

Huang, Lei; Teng, Tianming; Bian, Bo; Yao, Wei; Yu, Xuefang; Wang, Zhuoqun; Xu, Zhelong; Sun, Yuemin

2017-03-01

Zinc is one of the most important trace elements in the body and zinc homeostasis plays a critical role in maintaining cellular structure and function. Zinc dyshomeostasis can lead to many diseases, such as cardiovascular disease. Our aim was to investigate whether there is a relationship between zinc and left ventricular hypertrophy (LVH). A total of 519 patients was enrolled and their serum zinc levels were measured in this study. We performed analyses on the relationship between zinc levels and LVH and the four LV geometry pattern patients: normal LV geometry, concentric remodeling, eccentric LVH, and concentric LVH. We performed further linear and multiple regression analyses to confirm the relationship between zinc and left ventricular mass (LVM), left ventricular mass index (LVMI), and relative wall thickness (RWT). Our data showed that zinc levels were 710.2 ± 243.0 μg/L in the control group and were 641.9 ± 215.2 μg/L in LVH patients. We observed that zinc levels were 715 ± 243.5 μg/L, 694.2 ± 242.7 μg/L, 643.7 ± 225.0 μg/L, and 638.7 ± 197.0 μg/L in normal LV geometry, concentric remodeling, eccentric LVH, and concentric LVH patients, respectively. We further found that there was a significant inverse linear relationship between zinc and LVM (p = 0.001) and LVMI (p = 0.000) but did not show a significant relationship with RWT (p = 0.561). Multiple regression analyses confirmed that the linear relationship between zinc and LVM and LVMI remained inversely significant. The present study revealed that serum zinc levels were significantly decreased in the LVH patients, especially in the eccentric LVH and concentric LVH patients. Furthermore, zinc levels were significantly inversely correlated with LVM and LVMI.

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

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

Andrews, M; Abazeed, M; Woody, N

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less

Cross-national differences in the gender gap in subjective health in Europe: does country-level gender equality matter?

PubMed

Dahlin, Johanna; Härkönen, Juho

2013-12-01

Multiple studies have found that women report being in worse health despite living longer. Gender gaps vary cross-nationally, but relatively little is known about the causes of comparative differences. Existing literature is inconclusive as to whether gender gaps in health are smaller in more gender equal societies. We analyze gender gaps in self-rated health (SRH) and limiting longstanding illness (LLI) with five waves of European Social Survey data for 191,104 respondents from 28 countries. We use means, odds ratios, logistic regressions, and multilevel random slopes logistic regressions. Gender gaps in subjective health vary visibly across Europe. In many countries (especially in Eastern and Southern Europe), women report distinctly worse health, while in others (such as Estonia, Finland, and Great Britain) there are small or no differences. Logistic regressions ran separately for each country revealed that individual-level socioeconomic and demographic variables explain a majority of these gaps in some countries, but contribute little to their understanding in most countries. In yet other countries, men had worse health when these variables were controlled for. Cross-national variation in the gender gaps exists after accounting for individual-level factors. Against expectations, the remaining gaps are not systematically related to societal-level gender inequality in the multilevel analyses. Our findings stress persistent cross-national variability in gender gaps in health and call for further analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Interpretation of commonly used statistical regression models.

PubMed

Kasza, Jessica; Wolfe, Rory

2014-01-01

A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

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)

Trauma-Related Dissociation Is Linked With Maladaptive Personality Functioning

PubMed Central

Granieri, Antonella; Guglielmucci, Fanny; Costanzo, Antonino; Caretti, Vincenzo; Schimmenti, Adriano

2018-01-01

Background: Extensive research has demonstrated the positive associations among the exposure to traumatic experiences, the levels of dissociation, and the severity of psychiatric symptoms in adults. However, it has been hypothesized in clinical literature that an excessive activation of the dissociative processes following multiple traumatic experiences may jeopardize the psychological and behavioral functioning of the individuals, fostering higher levels of maladaptive personality functioning. Methods: The study involved 322 adult volunteers from Italy. Participants completed measures on traumatic experiences, dissociation, and maladaptive personality traits. Results: The number of traumatic experiences reported by participants were positively associated with dissociation scores and maladaptive personality scores. Mediation analyses showed that dissociation acted as a partial mediator in the relationship between traumatic experiences and overall maladaptive personality functioning. Regression curve analyses showed that the positive association between maladaptive personality functioning and dissociation was stronger among participants with higher exposure to traumatic experiences. Conclusion: Exposure to multiple traumatic experiences may increase the risk for an excessive activation of the dissociative processes, which in turn may generate severe impairments in multiple domains of personality functioning. PMID:29887807

The influence of campus experiences on the level of outness among trans-spectrum and queer-spectrum students.

PubMed

Garvey, Jason C; Rankin, Susan R

2015-01-01

This study utilized MANOVA and hierarchical multiple regression to examine the relationships between campus experiences and coming-out decisions among trans- and queer-spectrum undergraduates. Findings revealed higher levels of outness/disclosure for cisgender LGBQ women, and more negative perceptions of campus climate, classroom climate, and curriculum inclusivity and higher use of campus resources for trans-spectrum students. Results also revealed that higher levels of outness significantly related to poorer perceptions of campus responses and campus resources. Implications address the need to foster an encouraging and supportive campus and classroom climate and to improve the relationships with LGBTQ resource centers for trans- and queer-spectrum students.

Sociodemographic factors associated with pregnant women's level of knowledge about oral health

PubMed Central

Barbieri, Wander; Peres, Stela Verzinhasse; Pereira, Carla de Britto; Peres, João; de Sousa, Maria da Luz Rosário; Cortellazzi, Karine Laura

2018-01-01

ABSTRACT Objective To evaluate knowledge on oral health and associated sociodemographic factors in pregnant women. Methods A cross-sectional study with a sample of 195 pregnant women seen at the Primary Care Unit Paraisópolis I, in São Paulo (SP), Brazil. For statistical analysis, χ2 or Fisher's exact test and multiple logistic regression were used. A significance level of 5% was used in all analyses. Results Schooling level equal to or greater than 8 years and having one or two children were associated with an adequate knowledge about oral health. Conclusion Oral health promotion strategies during prenatal care should take into account sociodemographic aspects. PMID:29694612

Women's perceptions of their male batterers' characteristics and level of violence.

PubMed

Torres, Sara; Han, Hae-Ra

2003-01-01

This article describes the characteristics of male perpetrators of domestic violence and their relationship to the level of violence. The data about the male partners obtained from 151 battered women were used for this analysis. Using multiple regression, demographic variables and three behavioral indicators, including use of alcohol before a violent episode, history of arrests, and the generality of violence, were examined together for their relationship with the violence scores. With the level of violence as measured by the Conflict Tactics Scale (CTS) as the dependent variable, demographic variables explained 19.1% of the variability, with the behavioral indicators accounting for an additional 4.6% of the variability. Several research and clinical implications are addressed.

Prevalence and risk factors of non-carious cervical lesions related to occupational exposure to acid mists.

PubMed

Bomfim, Rafael Aiello; Crosato, Edgard; Mazzilli, Luiz Eugênio Nigro; Frias, Antonio Carlos

2015-01-01

This study evaluates the prevalence and risk factors of non-carious cervical lesions (NCCLs) in a Brazilian population of workers exposed and non-exposed to acid mists and chemical products. One hundred workers (46 exposed and 54 non-exposed) were evaluated in a Centro de Referência em Saúde do Trabalhador - CEREST (Worker's Health Reference Center). The workers responded to questionnaires regarding their personal information and about alcohol consumption and tobacco use. A clinical examination was conducted to evaluate the presence of NCCLs, according to WHO parameters. Statistical analyses were performed by unconditional logistic regression and multiple linear regression, with the critical level of p < 0.05. NCCLs were significantly associated with age groups (18-34, 35-44, 45-68 years). The unconditional logistic regression showed that the presence of NCCLs was better explained by age group (OR = 4.04; CI 95% 1.77-9.22) and occupational exposure to acid mists and chemical products (OR = 3.84; CI 95% 1.10-13.49), whereas the linear multiple regression revealed that NCCLs were better explained by years of smoking (p = 0.01) and age group (p = 0.04). The prevalence of NCCLs in the study population was particularly high (76.84%), and the risk factors for NCCLs were age, exposure to acid mists and smoking habit. Controlling risk factors through preventive and educative measures, allied to the use of personal protective equipment to prevent the occupational exposure to acid mists, may contribute to minimizing the prevalence of NCCLs.

Testing in Microbiome-Profiling Studies with MiRKAT, the Microbiome Regression-Based Kernel Association Test

PubMed Central

Zhao, Ni; Chen, Jun; Carroll, Ian M.; Ringel-Kulka, Tamar; Epstein, Michael P.; Zhou, Hua; Zhou, Jin J.; Ringel, Yehuda; Li, Hongzhe; Wu, Michael C.

2015-01-01

High-throughput sequencing technology has enabled population-based studies of the role of the human microbiome in disease etiology and exposure response. Distance-based analysis is a popular strategy for evaluating the overall association between microbiome diversity and outcome, wherein the phylogenetic distance between individuals’ microbiome profiles is computed and tested for association via permutation. Despite their practical popularity, distance-based approaches suffer from important challenges, especially in selecting the best distance and extending the methods to alternative outcomes, such as survival outcomes. We propose the microbiome regression-based kernel association test (MiRKAT), which directly regresses the outcome on the microbiome profiles via the semi-parametric kernel machine regression framework. MiRKAT allows for easy covariate adjustment and extension to alternative outcomes while non-parametrically modeling the microbiome through a kernel that incorporates phylogenetic distance. It uses a variance-component score statistic to test for the association with analytical p value calculation. The model also allows simultaneous examination of multiple distances, alleviating the problem of choosing the best distance. Our simulations demonstrated that MiRKAT provides correctly controlled type I error and adequate power in detecting overall association. “Optimal” MiRKAT, which considers multiple candidate distances, is robust in that it suffers from little power loss in comparison to when the best distance is used and can achieve tremendous power gain in comparison to when a poor distance is chosen. Finally, we applied MiRKAT to real microbiome datasets to show that microbial communities are associated with smoking and with fecal protease levels after confounders are controlled for. PMID:25957468

Relationship between Leadership among Peers and Burnout in Sports Teams.

PubMed

Torrado, Julio; Arce, Constantino; Vales-Vázquez, Ángel; Areces, Alberto; Iglesias, Gabriel; Valle, Iván; Patiño, Gabriel

2017-04-03

This study has been conducted with the aim of ascertaining the relationship between peer leaders in sport teams and the levels of burnout experienced by their team-mates. A total of 219 Spanish athletes involved in football and basketball participated in the study. To measure leadership among peers, we employed the Sports Peer Leadership Scale, which comprises 24 items, grouped into 6 primary factors: empathy, influence on decision making, sports values, social support, training orientation and competition orientation. And to measure burnout, we employed the Athlete Burnout Questionnaire, which comprises 15 items which are indicators of physical and emotional exhaustion, devaluation and reduced sense of accomplishment among athletes. The results led to the conclusion that there is a statistically significant negative relationship between perceived leadership capacity and the levels of burnout experience by a team. The greater the level of leadership capacity perceived, the lower the levels of burnout will be. A multiple regression analysis with total burnout as dependent variable and social and task orientations of the leader as predictors showed standardized regression coefficients of -.241 (p = .010) and -.076 (p = .413), respectively for social and task orientation, being the effect size equal to .089.

Ovarian stimulation length, number of follicles higher than 17 mm and estradiol on the day of human chorionic gonadotropin administration are risk factors for multiple pregnancy in intrauterine insemination

PubMed Central

MELO, MARCO A.B.; SIMÓN, CARLOS; REMOHÍ, JOSÉ; PELLICER, ANTONIO; MESEGUER, MARCOS

2007-01-01

Aim:  The aim of the present study was to identify the risk factors, their prognostic value on multiple pregnancies (MP) prediction and their thresholds in women undergoing controlled ovarian hyperstimulation (COH) with follicle stimulating hormone (FSH) and intrauterine insemination (IUI). Methods:  A case‐control study was carried out by identifying in our database all the pregnancies reached by donor and conjugal IUI (DIUI and CIUI, respectively), and compared cycle features, patients’ characteristics and sperm analysis results between women achieving single pregnancy (SP) versus MP. The number of gestational sacs, follicular sizes and estradiol levels on the human chorionic gonadotropin (hCG) administration day, COH length and semen parameters were obtained from each cycle and compared. Student's t‐tests for mean comparisons, receiver–operator curve (ROC) analysis to determine the predictive value of each parameter on MP achievement and multiple regression analysis to determine single parameter influence were carried out. Results:  Women with MP in IUI stimulated cycles reached the adequate size of the dominant follicle (17 mm) significantly earlier than those achieving SP. Also, the mean follicles number, and estradiol levels on the hCG day were higher in the CIUI and DIUI MP group. Nevertheless, only ROC curve analysis revealed good prognostic value for estradiol and follicles higher than 17 mm. Multiple regression analysis confirmed these results. No feature of the basic sperm analysis, either in the ejaculate or in the prepared sample, was different or predictive of MP. When using donor sperm, different thresholds of follicle number, stimulation length and estradiol in the prediction of MP were noted, in comparison with CIUI. Conclusions:  MP in stimulated IUI cycles are closely associated to stimulation length, number of developed follicles higher than 17 mm on the day of hCG administration and estradiol levels. Also, estradiol has a good predictive value over MP in IUI stimulated cycles. The establishment of clinical thresholds will certainly help in the management of these couples to avoid undesired multiple pregnancies by canceling cycles or converting them into in vitro fertilization procedures. (Reprod Med Biol 2007; 6: 19–26) PMID:29699262

The Utility of a Syndemic Framework in Understanding Chronic Disease Management Among HIV-Infected and Type 2 Diabetic Men Who Have Sex with Men.

PubMed

Byg, Blaire; Bazzi, Angela Robertson; Funk, Danielle; James, Bonface; Potter, Jennifer

2016-12-01

Syndemic theory posits that epidemics of multiple physical and psychosocial problems co-occur among disadvantaged groups due to adverse social conditions. Although sexual minority populations are often stigmatized and vulnerable to multiple health problems, the syndemic perspective has been underutilized in understanding chronic disease. To assess the potential utility of this perspective in understanding the management of co-occurring HIV and Type 2 diabetes, we used linear regression to examine glycemic control (A1c) among men who have sex with men (MSM) with both HIV and Type 2 diabetes (n = 88). Bivariable linear regression explored potential syndemic correlates of inadequate glycemic control. Compared to those with adequate glycemic control (A1c ≤ 7.5 %), more men with inadequate glycemic control (A1c > 7.5 %) had hypertension (70 vs. 46 %, p = 0.034), high triglycerides (93 vs. 61 %, p = 0.002), depression (67 vs. 39 %, p = 0.018), current substance abuse (15 vs. 2 %, p = 0.014), and detectable levels of HIV (i.e., viral load ≥75 copies per ml blood; 30 vs. 10 %, p = 0.019). In multivariable regression controlling for age, the factors that were independently associated with higher A1c were high triglycerides, substance use, and detectable HIV viral load, suggesting that chronic disease management among MSM is complex and challenging for patients and providers. Findings also suggest that syndemic theory can be a clarifying lens for understanding chronic disease management among sexual minority stigmatized populations. Interventions targeting single conditions may be inadequate when multiple conditions co-occur; thus, research using a syndemic framework may be helpful in identifying intervention strategies that target multiple co-occurring conditions.

Sample size estimation for alternating logistic regressions analysis of multilevel randomized community trials of under-age drinking.

PubMed

Reboussin, Beth A; Preisser, John S; Song, Eun-Young; Wolfson, Mark

2012-07-01

Under-age drinking is an enormous public health issue in the USA. Evidence that community level structures may impact on under-age drinking has led to a proliferation of efforts to change the environment surrounding the use of alcohol. Although the focus of these efforts is to reduce drinking by individual youths, environmental interventions are typically implemented at the community level with entire communities randomized to the same intervention condition. A distinct feature of these trials is the tendency of the behaviours of individuals residing in the same community to be more alike than that of others residing in different communities, which is herein called 'clustering'. Statistical analyses and sample size calculations must account for this clustering to avoid type I errors and to ensure an appropriately powered trial. Clustering itself may also be of scientific interest. We consider the alternating logistic regressions procedure within the population-averaged modelling framework to estimate the effect of a law enforcement intervention on the prevalence of under-age drinking behaviours while modelling the clustering at multiple levels, e.g. within communities and within neighbourhoods nested within communities, by using pairwise odds ratios. We then derive sample size formulae for estimating intervention effects when planning a post-test-only or repeated cross-sectional community-randomized trial using the alternating logistic regressions procedure.

Serum Uric Acid Is Associated with Poor Outcome in Black Africans in the Acute Phase of Stroke

PubMed Central

Ayeah, Chia Mark; Ba, H.; Mbahe, Salomon

2017-01-01

Background Prognostic significance of serum uric acid (SUA) in acute stroke still remains controversial. Objectives To determine the prevalence of hyperuricemia and its association with outcome of stroke patients in the Douala General Hospital (DGH). Methods This was a hospital based prospective cohort study which included acute stroke patients with baseline SUA levels and 3-month poststroke follow-up data. Associations between high SUA levels and stroke outcomes were analyzed using multiple logistic regression and survival analysis (Cox regression and Kaplan-Meier). Results A total of 701 acute stroke patients were included and the prevalence of hyperuricemia was 46.6% with a mean SUA level of 68.625 ± 24 mg/l. Elevated SUA after stroke was associated with death (OR = 2.067; 95% CI: 1.449–2.950; p < 0.001) but did not predict this issue. However, an independent association between increasing SUA concentration and mortality was noted in a Cox proportional hazards regression model (adjusted HR = 1.740; 95% CI: 1.305–2.320; p < 0.001). Furthermore, hyperuricemia was an independent predictor of poor functional outcome within 3 months after stroke (OR = 2.482; 95% CI: 1.399–4.404; p = 0.002). Conclusion The prevalence of hyperuricemia in black African stroke patients is quite high and still remains a predictor of poor outcome. PMID:29082062

The insulin effect on cerebrocortical theta activity is associated with serum concentrations of saturated nonesterified Fatty acids.

PubMed

Tschritter, Otto; Preissl, Hubert; Hennige, Anita M; Sartorius, Tina; Grichisch, Yuko; Stefan, Norbert; Guthoff, Martina; Düsing, Stephan; Machann, Jürgen; Schleicher, Erwin; Cegan, Alexander; Birbaumer, Niels; Fritsche, Andreas; Häring, Hans-Ulrich

2009-11-01

Insulin action in the brain contributes to adequate regulation of body weight, neuronal survival, and suppression of endogenous glucose production. We previously demonstrated by magnetoencephalography in lean humans that insulin stimulates activity in beta and theta frequency bands, whereas this effect was abolished in obese individuals. The present study aims to define metabolic signals associated with the suppression of the cerebrocortical response in obese humans. We determined insulin-mediated modulation of spontaneous cerebrocortical activity by magnetoencephalography during a hyperinsulinemic euglycemic clamp and related it to measures of ectopic fat deposition and mediators of peripheral insulin resistance. Visceral fat mass and intrahepatic lipid content were quantified by magnetic resonance imaging and spectroscopy. Multiple regression analysis was used to analyze associations of cerebrocortical insulin sensitivity and metabolic markers related to obesity. Forty-nine healthy, nondiabetic humans participated in the study. In a multiple regression, insulin-mediated stimulation of theta activity was negatively correlated to body mass index, visceral fat mass, and intrahepatic lipid content. Although fasting saturated nonesterified fatty acids mediated the correlations of theta activity with abdominal and intrahepatic lipid stores, adipocytokines displayed no independent correlation with insulin-mediated cortical activity in the theta frequency band. Thus, insulin action at the level of cerebrocortical activity in the brain is diminished in the presence of elevated levels of saturated nonesterified fatty acids.

The relationship between turbidity of mouth-rinsed water and oral health status.

PubMed

Takeuchi, Susumu; Ueno, Masayuki; Takehara, Sachiko; Pham, Thuy Anh Vu; Hakuta, Chiyoko; Morishima, Seiji; Shinada, Kayoko; Kawaguchi, Yoko

2013-01-01

The purpose of this study was to examine the relationship between turbidity of mouth rinsed water and oral health status such as dental and periodontal conditions, oral hygiene status, flow rate of saliva and oral bacteria. Subjects were 165 patients who visited the Dental Hospital, Tokyo Medical and Dental University. Oral health status, including dental and periodontal conditions, oral hygiene status and flow rate of saliva, was clinically examined. The turbidity was measured with a turbidimeter. Quantification of Fusobacterium spp, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola and total bacteria levels was performed using real-time PCR. The Pearson correlation and multiple regression analysis were used to explore the associations between the turbidity and oral health parameters. The turbidity showed significant correlations with the number of decayed teeth and deep pockets, the plaque index, extent of tongue coating and Fusobacterium spp, P. gingivalis, T. forsythia, T. denticola and total bacteria levels. In a multiple regression model, the turbidity was negatively associated with the flow rate of saliva and positively associated with the total number of bacteria (p < 0.001). Current findings suggested that turbidity of mouth rinsed water could be used as an indicator to evaluate oral health condition and the amount of bacteria in the oral cavity. In addition, the turbiditimeter appeared as a simple and objective device for screening abnormality of oral health condition at chair side as well as community-based research.

Intercellular adhesion molecule, plasma adiponectin and albuminuria in type 2 diabetic patients.

PubMed

Lenghel, Alina Ramona; Kacso, Ina Maria; Bondor, Cosmina Ioana; Rusu, Crina; Rahaian, Rodica; Gherman Caprioara, Mirela

2012-01-01

Our study addressed the influence of early inflammatory stages of diabetic kidney disease: leukocyte adhesion and monocyte activation (as assessed by intercellular leukocyte adhesion molecule-ICAM-1 and monocyte chemoatractant protein-MCP-1) on the degree of albuminuria. Plasma levels of adiponectin, a possible anti-inflammatory counteracting mechanism, were also studied in correlation to the above-mentioned cytokines. 79 consecutive type 2 diabetic outpatients and 46 controls were included. Routine laboratory analysis, urinary albumin to creatinine ratio (uACR), plasma adiponectin, plasma ICAM-1 and urinary MPC-1 were assessed. In multiple regression ICAM-1 (p=0.004) and adiponectin (p=0.04) were the main determinants of uACR. Plasma adiponectin positively correlated to ICAM-1 (p=0.03, r=0.24). In albuminuric patients (uACR ≥30 mg/g) plasma adiponectin was significantly higher compared to normoalbuminuric ones (uACR <30 mg/g). In albuminuric patients the main determinants of uACR were plasma ICAM-1 and adiponectin. In multiple regression ICAM-1 is the only one that retains statistical significance (p=0.02). Urinary MCP-1 did not correlate to uACR. In our type 2 diabetic patients, plasma levels of ICAM-1 and adiponectin are predictive for albuminuria. Urinary MCP-1 does not correlated to uACR. Plasma adiponectin positively correlates to adhesion molecule ICAM-1 in our cohort. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

An Application of Robust Method in Multiple Linear Regression Model toward Credit Card Debt

NASA Astrophysics Data System (ADS)

Amira Azmi, Nur; Saifullah Rusiman, Mohd; Khalid, Kamil; Roslan, Rozaini; Sufahani, Suliadi; Mohamad, Mahathir; Salleh, Rohayu Mohd; Hamzah, Nur Shamsidah Amir

2018-04-01

Credit card is a convenient alternative replaced cash or cheque, and it is essential component for electronic and internet commerce. In this study, the researchers attempt to determine the relationship and significance variables between credit card debt and demographic variables such as age, household income, education level, years with current employer, years at current address, debt to income ratio and other debt. The provided data covers 850 customers information. There are three methods that applied to the credit card debt data which are multiple linear regression (MLR) models, MLR models with least quartile difference (LQD) method and MLR models with mean absolute deviation method. After comparing among three methods, it is found that MLR model with LQD method became the best model with the lowest value of mean square error (MSE). According to the final model, it shows that the years with current employer, years at current address, household income in thousands and debt to income ratio are positively associated with the amount of credit debt. Meanwhile variables for age, level of education and other debt are negatively associated with amount of credit debt. This study may serve as a reference for the bank company by using robust methods, so that they could better understand their options and choice that is best aligned with their goals for inference regarding to the credit card debt.

Male Saudi Arabian freshman science majors at Jazan University: Their perceptions of parental educational practices on their science achievements

NASA Astrophysics Data System (ADS)

Alrehaly, Essa D.

Examination of Saudi Arabian educational practices is scarce, but increasingly important, especially in light of the country's pace in worldwide mathematics and science rankings. The purpose of the study is to understand and evaluate parental influence on male children's science education achievements in Saudi Arabia. Parental level of education and participant's choice of science major were used to identify groups for the purpose of data analysis. Data were gathered using five independent variables concerning parental educational practices (attitude, involvement, autonomy support, structure and control) and the dependent variable of science scores in high school. The sample consisted of 338 participants and was arbitrarily drawn from the science-based colleges (medical, engineering, and natural science) at Jazan University in Saudi Arabia. The data were tested using Pearson's analysis, backward multiple regression, one way ANOVA and independent t-test. The findings of the study reveal significant correlations for all five of the variables. Multiple regressions revealed that all five of the parents' educational practices indicators combined together could explain 19% of the variance in science scores and parental attitude toward science and educational involvement combined accounted for more than 18% of the variance. Analysis indicates that no significant difference is attributable to parental involvement and educational level. This finding is important because it indicates that, in Saudi Arabia, results are not consistent with research in Western or other Asian contexts.

Critical consciousness, racial and gender discrimination, and HIV disease markers in African American women with HIV.

PubMed

Kelso, Gwendolyn A; Cohen, Mardge H; Weber, Kathleen M; Dale, Sannisha K; Cruise, Ruth C; Brody, Leslie R

2014-07-01

Critical consciousness, the awareness of social oppression, is important to investigate as a buffer against HIV disease progression in HIV-infected African American women in the context of experiences with discrimination. Critical consciousness comprises several dimensions, including social group identification, discontent with distribution of social power, rejection of social system legitimacy, and a collective action orientation. The current study investigated self-reported critical consciousness as a moderator of perceived gender and racial discrimination on HIV viral load and CD4+ cell count in 67 African American HIV-infected women. Higher critical consciousness was found to be related to higher likelihood of having CD4+ counts over 350 and lower likelihood of detectable viral load when perceived racial discrimination was high, as revealed by multiple logistic regressions that controlled for highly active antiretroviral therapy (HAART) adherence. Multiple linear regressions showed that at higher levels of perceived gender and racial discrimination, women endorsing high critical consciousness had a larger positive difference between nadir CD4+ (lowest pre-HAART) and current CD4+ count than women endorsing low critical consciousness. These findings suggest that raising awareness of social oppression to promote joining with others to enact social change may be an important intervention strategy to improve HIV outcomes in African American HIV-infected women who report experiencing high levels of gender and racial discrimination.

The association between subgingival periodontal pathogens and systemic inflammation.

PubMed

Winning, Lewis; Patterson, Christopher C; Cullen, Kathy M; Stevenson, Kathryn A; Lundy, Fionnuala T; Kee, Frank; Linden, Gerard J

2015-09-01

To investigate associations between periodontal disease pathogens and levels of systemic inflammation measured by C-reactive protein (CRP). A representative sample of dentate 60-70-year-old men in Northern Ireland had a comprehensive periodontal examination. Men taking statins were excluded. Subgingival plaque samples were analysed by quantitative real time PCR to identify the presence of Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Treponema denticola and Tannerella forsythia. High-sensitivity CRP (mg/l) was measured from fasting blood samples. Multiple linear regression analysis was performed using log-transformed CRP concentration as the dependent variable, with the presence of each periodontal pathogen as predictor variables, with adjustment for various potential confounders. A total of 518 men (mean age 63.6 SD 3.0 years) were included in the analysis. Multiple regression analysis showed that body mass index (p < 0.001), current smoking (p < 0.01), the detectable presence of P. gingivalis (p < 0.01) and hypertension (p = 0.01), were independently associated with an increased CRP. The detectable presence of P. gingivalis was associated with a 20% (95% confidence interval 4-35%) increase in CRP (mg/l) after adjustment for all other predictor variables. In these 60-70-year-old dentate men, the presence of P. gingivalis in subgingival plaque was significantly associated with a raised level of C-reactive protein. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Age is no barrier: predictors of academic success in older learners

NASA Astrophysics Data System (ADS)

Imlach, Abbie-Rose; Ward, David D.; Stuart, Kimberley E.; Summers, Mathew J.; Valenzuela, Michael J.; King, Anna E.; Saunders, Nichole L.; Summers, Jeffrey; Srikanth, Velandai K.; Robinson, Andrew; Vickers, James C.

2017-11-01

Although predictors of academic success have been identified in young adults, such predictors are unlikely to translate directly to an older student population, where such information is scarce. The current study aimed to examine cognitive, psychosocial, lifetime, and genetic predictors of university-level academic performance in older adults (50-79 years old). Participants were mostly female (71%) and had a greater than high school education level (M = 14.06 years, SD = 2.76), on average. Two multiple linear regression analyses were conducted. The first examined all potential predictors of grade point average (GPA) in the subset of participants who had volunteered samples for genetic analysis (N = 181). Significant predictors of GPA were then re-examined in a second multiple linear regression using the full sample (N = 329). Our data show that the cognitive domains of episodic memory and language processing, in conjunction with midlife engagement in cognitively stimulating activities, have a role in predicting academic performance as measured by GPA in the first year of study. In contrast, it was determined that age, IQ, gender, working memory, psychosocial factors, and common brain gene polymorphisms linked to brain function, plasticity and degeneration (APOE, BDNF, COMT, KIBRA, SERT) did not influence academic performance. These findings demonstrate that ageing does not impede academic achievement, and that discrete cognitive skills as well as lifetime engagement in cognitively stimulating activities can promote academic success in older adults.

Critical Consciousness, Racial and Gender Discrimination, and HIV Disease Markers in African American Women with HIV

PubMed Central

Kelso, Gwendolyn A.; Cohen, Mardge H.; Weber, Kathleen M.; Dale, Sannisha K.; Cruise, Ruth C.; Brody, Leslie R.

2014-01-01

Critical consciousness, the awareness of social oppression, is important to investigate as a buffer against HIV disease progression in HIV-infected African American women in the context of experiences with discrimination. Critical consciousness comprises several dimensions, including social group identification, discontent with distribution of social power, rejection of social system legitimacy, and a collective action orientation. The current study investigated self-reported critical consciousness as a moderator of perceived gender and racial discrimination on HIV viral load and CD4+ cell count in 67 African American HIV-infected women. Higher critical consciousness was found to be related to higher likelihood of having CD4+ counts over 350 and lower likelihood of detectable viral load when perceived racial discrimination was high, as revealed by multiple logistic regressions that controlled for highly active antiretroviral therapy (HAART) adherence. Multiple linear regressions showed that at higher levels of perceived gender and racial discrimination, women endorsing high critical consciousness had a larger positive difference between nadir CD4+ (lowest pre-HAART) and current CD4+ count than women endorsing low critical consciousness. These findings suggest that raising awareness of social oppression to promote joining with others to enact social change may be an important intervention strategy to improve HIV outcomes in African American HIV-infected women who report experiencing high levels of gender and racial discrimination. PMID:24077930

Occupational exposure to potentially infectious biological material in a dental teaching environment.

PubMed

Machado-Carvalhais, Helenaura P; Ramos-Jorge, Maria L; Auad, Sheyla M; Martins, Laura H P M; Paiva, Saul M; Pordeus, Isabela A

2008-10-01

The aims of this cross-sectional study were to determine the prevalence of occupational accidents with exposure to biological material among undergraduate students of dentistry and to estimate potential risk factors associated with exposure to blood. Data were collected through a self-administered questionnaire (86.4 percent return rate), which was completed by a sample of 286 undergraduate dental students (mean age 22.4 +/-2.4 years). The students were enrolled in the clinical component of the curriculum, which corresponds to the final six semesters of study. Descriptive, bivariate, simple logistic regression and multiple logistic regression (Forward Stepwise Procedure) analyses were performed. The level of statistical significance was set at 5 percent. Percutaneous and mucous exposures to potentially infectious biological material were reported by 102 individuals (35.6 percent); 26.8 percent reported the occurrence of multiple episodes of exposure. The logistic regression analyses revealed that the incomplete use of individual protection equipment (OR=3.7; 95 percent CI 1.5-9.3), disciplines where surgical procedures are carried out (OR=16.3; 95 percent CI 7.1-37.2), and handling sharp instruments (OR=4.4; 95 percent CI 2.1-9.1), more specifically, hollow-bore needles (OR=6.8; 95 percent CI 2.1-19.0), were independently associated with exposure to blood. Policies of reviewing the procedures during clinical practice are recommended in order to reduce occupational exposure.

Economist intelligence unit democracy index in relation to health services accessibility: a regression analysis.

PubMed

Walker, Mary Ellen; Anonson, June; Szafron, Michael

2015-01-01

The relationship between political environment and health services accessibility (HSA) has not been the focus of any specific studies. The purpose of this study was to address this gap in the literature by examining the relationship between political environment and HSA. This relationship that HSA indicators (physicians, nurses and hospital beds per 10 000 people) has with political environment was analyzed with multiple least-squares regression using the components of democracy (electoral processes and pluralism, functioning of government, political participation, political culture, and civil liberties). The components of democracy were represented by the 2011 Economist Intelligence Unit Democracy Index (EIUDI) sub-scores. The EIUDI sub-scores and the HSA indicators were evaluated for significant relationships with multiple least-squares regression. While controlling for a country's geographic location and level of democracy, we found that two components of a nation's political environment: functioning of government and political participation, and their interaction had significant relationships with the three HSA indicators. These study findings are of significance to health professionals because they examine the political contexts in which citizens access health services, they come from research that is the first of its kind, and they help explain the effect political environment has on health. © The Author 2014. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

Enhancing the estimation of blood pressure using pulse arrival time and two confounding factors.

PubMed

Baek, Hyun Jae; Kim, Ko Keun; Kim, Jung Soo; Lee, Boreom; Park, Kwang Suk

2010-02-01

A new method of blood pressure (BP) estimation using multiple regression with pulse arrival time (PAT) and two confounding factors was evaluated in clinical and unconstrained monitoring situations. For the first analysis with clinical data, electrocardiogram (ECG), photoplethysmogram (PPG) and invasive BP signals were obtained by a conventional patient monitoring device during surgery. In the second analysis, ECG, PPG and non-invasive BP were measured using systems developed to obtain data under conditions in which the subject was not constrained. To enhance the performance of BP estimation methods, heart rate (HR) and arterial stiffness were considered as confounding factors in regression analysis. The PAT and HR were easily extracted from ECG and PPG signals. For arterial stiffness, the duration from the maximum derivative point to the maximum of the dicrotic notch in the PPG signal, a parameter called TDB, was employed. In two experiments that normally cause BP variation, the correlation between measured BP and the estimated BP was investigated. Multiple-regression analysis with the two confounding factors improved correlation coefficients for diastolic blood pressure and systolic blood pressure to acceptable confidence levels, compared to existing methods that consider PAT only. In addition, reproducibility for the proposed method was determined using constructed test sets. Our results demonstrate that non-invasive, non-intrusive BP estimation can be obtained using methods that can be applied in both clinical and daily healthcare situations.

Lipid levels among African and Middle-Eastern Bedouin populations.

PubMed

Dreiher, Jacob; Cohen, Arnon D; Weitzman, Shimon; Sharf, Amir; Shvartzman, Pesach

2008-06-01

Previous studies observed higher high-density lipoprotein (HDL) levels and lower triglycerides levels among people of African ancestry. The goal of this study was to characterize lipid levels in Bedouins of African vs. Middle-Eastern ethnicity. A cross-sectional study was conducted in a Bedouin primary care clinic in southern Israel, with 4470 listed individuals over the age of 21, of whom 402 (9%) were of African origin. A stratified random sample was included in the analysis. Associations between ethnicity, age, gender and lipid levels were assessed. Multiple linear regression and logistic regression models were used for multivariate analysis. The study included 261 African Bedouins and 406 Middle-Eastern Bedouins. (median age: 37 years, 58.6% females). The average total cholesterol and low-density lipoprotein (LDL) levels were 10 mg/dl lower among African Bedouins as compared to Middle-Eastern Bedouins (total cholesterol: 168.6 vs. 179.6 mg/dl, p<0.001; LDL: 99.5 vs. 109.0 mg/dl, respectively, p<0.001). Average triglycerides levels were 36 mg/dl lower among African Bedouins as compared to Middle-Eastern Bedouins (102.8 vs. 138.9 mg/dl, respectively, p<0.001). Average HDL levels were 3 mg/dl higher among African Bedouins as compared to Middle-Eastern Bedouins (48.3 vs. 44.6 mg/dl, respectively, p<0.001). A lower prevalence of dyslipidemia was found in African Bedouins, as compared with Middle-Eastern Bedouins.

Relationship between blood manganese and blood pressure in the Korean general population according to KNHANES 2008

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

Lee, Byung-Kook; Kim, Yangho, E-mail: yanghokm@nuri.net

Introduction: We present data on the association of manganese (Mn) level with hypertension in a representative sample of the adult Korean population who participated in the Korean National Health and Nutrition Examination Survey (KNHANES) 2008. Methods: This study was based on the data obtained by KNHANES 2008, which was conducted for three years (2007-2009) using a rolling sampling design involving a complex, stratified, multistage, probability-cluster survey of a representative sample of the noninstitutionalized civilian population of South Korea. Results: Multiple regression analysis after controlling for covariates, including gender, age, regional area, education level, smoking, drinking status, hemoglobin, and serum creatinine,more » showed that the beta coefficients of log blood Mn were 3.514, 1.878, and 2.517 for diastolic blood pressure, and 3.593, 2.449, and 2.440 for systolic blood pressure in female, male, and all participants, respectively. Multiple regression analysis including three other blood metals, lead, mercury, and cadmium, revealed no significant effects of the three metals on blood pressure and showed no effect on the association between blood Mn and blood pressure. In addition, doubling the blood Mn increased the risk of hypertension 1.828, 1.573, and 1.567 fold in women, men, and all participants, respectively, after adjustment for covariates. The addition of blood lead, mercury, and cadmium as covariates did not affect the association between blood Mn and the prevalence of hypertension. Conclusion: Blood Mn level was associated with an increased risk of hypertension in a representative sample of the Korean adult population. - Highlights: {yields} We showed the association of manganese with hypertension in Korean population. {yields} This study was based on the data obtained by KNHANES 2008. {yields} Blood manganese level was associated with an increased risk of hypertension.« less

Introduction of a paediatric anaesthesia comic information leaflet reduced preoperative anxiety in children.

PubMed

Kassai, B; Rabilloud, M; Dantony, E; Grousson, S; Revol, O; Malik, S; Ginhoux, T; Touil, N; Chassard, D; Pereira de Souza Neto, E

2016-07-01

The aim of the study was to determine whether the introduction of a paediatric anaesthesia comic information leaflet reduced preoperative anxiety levels of children undergoing major surgery. Secondary objectives were to determine whether the level of understanding of participants and other risk factors influence STAIC-S (State-Trait Anxiety Inventory for Children-State subscale) score in children. We performed a randomized controlled parallel-group trial comparing preoperative anxiety between two groups of children aged >6 and <17 yr. Before surgery, the intervention group received a comic information leaflet at home in addition to routine information given by the anaesthetist at least 1 day before surgery. The control group received the routine information only. The outcome measure was the difference between STAIC-S scores measured before any intervention and after the anaesthetist's visit. A multiple regression analysis was performed to explore the influence of the level of education, the anxiety of parents, and the childrens' intelligence quotient on STAIC-S scores. One hundred and fifteen children were randomized between April 2009 and April 2013. An intention-to-treat analysis on data from 111 patients showed a significant reduction (P=0.002) in STAIC-S in the intervention group (n=54, mean=-2.2) compared with the control group (n=57, mean=0.90). The multiple regression analysis did not show any influence on STAIC-S scores of the level of education, parental anxiety, or the intelligence quotient of the children. A paediatric anaesthesia comic information leaflet was a cheap and effective means of reducing preoperative anxiety, measured by STAIC-S, in children. NCT 00841022. © The Author 2016. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Introduction of a paediatric anaesthesia comic information leaflet reduced preoperative anxiety in children

PubMed Central

Kassai, B.; Rabilloud, M.; Dantony, E.; Grousson, S.; Revol, O.; Malik, S.; Ginhoux, T.; Touil, N.; Chassard, D.; Pereira de Souza Neto, E.

2016-01-01

Background The aim of the study was to determine whether the introduction of a paediatric anaesthesia comic information leaflet reduced preoperative anxiety levels of children undergoing major surgery. Secondary objectives were to determine whether the level of understanding of participants and other risk factors influence STAIC-S (State–Trait Anxiety Inventory for Children—State subscale) score in children. Methods We performed a randomized controlled parallel-group trial comparing preoperative anxiety between two groups of children aged >6 and <17 yr. Before surgery, the intervention group received a comic information leaflet at home in addition to routine information given by the anaesthetist at least 1 day before surgery. The control group received the routine information only. The outcome measure was the difference between STAIC-S scores measured before any intervention and after the anaesthetist's visit. A multiple regression analysis was performed to explore the influence of the level of education, the anxiety of parents, and the childrens' intelligence quotient on STAIC-S scores. Results One hundred and fifteen children were randomized between April 2009 and April 2013. An intention-to-treat analysis on data from 111 patients showed a significant reduction (P=0.002) in STAIC-S in the intervention group (n=54, mean=−2.2) compared with the control group (n=57, mean=0.90). The multiple regression analysis did not show any influence on STAIC-S scores of the level of education, parental anxiety, or the intelligence quotient of the children. Conclusions A paediatric anaesthesia comic information leaflet was a cheap and effective means of reducing preoperative anxiety, measured by STAIC-S, in children. Clinical trials registration NCT 00841022. PMID:27317708

Levels of soluble TREM-1 in children with newly diagnosed type 1 diabetes and their siblings without type 1 diabetes: a Danish case-control study.

PubMed

Thorsen, Steffen U; Pipper, Christian B; Mortensen, Henrik B; Skogstrand, Kristin; Pociot, Flemming; Johannesen, Jesper; Svensson, Jannet

2017-12-01

Type 1 diabetes (T1D) is an organ-specific autoimmune disease with an increase in incidence worldwide including Denmark. The triggering receptor expressed on myeloid cells-1 (TREM-1) is a potent amplifier of pro-inflammatory responses and has been linked to autoimmunity, severe psychiatric disorders, sepsis, and cancer. Our primary hypothesis was that levels of soluble TREM-1 (sTREM-1) differed between newly diagnosed children with T1D and their siblings without T1D. Since 1996, the Danish Childhood Diabetes Register has collected data on all patients who have developed T1D before the age of 18 years. Four hundred and eighty-one patients and 478 siblings with measurements of sTREM-1-blood samples were taken within 3 months after onset-were available for statistical analyses. Sample period was from 1997 through 2005. A robust log-normal regression model was used, which takes into account that measurements are left censored and accounts for correlation within siblings from the same family. In the multiple regression model (case status, gender, age, HLA-risk, season, and period of sampling), levels of sTREM-1 were found to be significantly higher in patients (relative change [95%CI], 1.5 [1.1; 2.2],P = 0.02), but after adjustment for multiple testing our result was no longer statistically significant (P adjust = 0.1). We observed a statistical significant temporal increase in levels of sTREM-1. Our results need to be replicated by independent studies, but our study suggests that the TREM-1 pathway may have a role in T1D pathogenesis. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Detection and Measurement of Unhealthy, Environment-Derived Aerosol Materials in an Emergency Department.

PubMed

Choi, Bryan Y; Kobayashi, Leo; Pathania, Shivany; Miller, Courtney B; Locke, Emma R; Stearns, Branden C; Hudepohl, Nathan J; Patefield, Scott S; Suner, Selim; Williams, Kenneth A; Machan, Jason T; Jay, Gregory D

2015-01-01

To measure unhealthy aerosol materials in an Emergency Department (ED) and identify their sources for mitigation efforts. Based on pilot findings of elevated ED particulate matter (PM) levels, investigators hypothesized that unhealthy aerosol materials derive from exogenous (vehicular) sources at ambulance receiving entrances. The Aerosol Environmental Toxicity in Healthcare-related Exposure and Risk program was conducted as an observational study. Calibrated sensors monitored PM and toxic gases at Ambulance Triage Exterior (ATE), Ambulance Triage Desk (ATD), and control Public Triage Desk (PTD) on a 3/3/3-day cycle. Cassette sampling characterized PM; meteorological and ambulance traffic data were logged. Descriptive and multiple linear regression analyses assessed for interactions between aerosol material levels, location, temporal variables, ambulance activity, and meteorological factors. Sensors acquired 93,682 PM0.3, 90,250 PM2.5, and 93,768 PM5 measurements over 366 days to generate a data set representing at least 85.6% of planned measurements. PM0.3, PM2.5, and PM5 mean counts were lowest in PTD; 56%, 224%, and 223% higher in ATD; and 996%, 200%, and 63% higher in ATE, respectively (all p < .001). Qualitative analyses showed similar PM compositions in ATD and ATE. On multiple linear regression analysis, PM0.3 counts correlated primarily with location; PM2.5 and PM5 counts correlated most strongly with location and ambulance presence. PM < 2.5 and toxic gas concentrations at ATD and PTD patient care areas did not exceed hazard levels; PM0.3 counts did not have formal safety thresholds for comparison. Higher levels of PM were linked with ED ambulance areas, although their health impact is unclear. © The Author(s) 2015.

Quality of life in children with infantile hemangioma: a case control study.

PubMed

Wang, Chuan; Li, Yanan; Xiang, Bo; Xiong, Fei; Li, Kai; Yang, Kaiying; Chen, Siyuan; Ji, Yi

2017-11-16

Infantile hemangioma (IH) is the most common vascular tumor in children. It is controversial whether IHs has effects on the quality of life (QOL) in patients of whom IH poses no threat or potential for complication. Thus, we conducted this study to evaluate the q QOL in patients with IH and find the predictors of poor QOL. The PedsQL 4.0 Genetic Core Scales and the PedsQL family information form were administered to parents of children with IH and healthy children both younger than 2-year-old. The quality-of-life instrument for IH (IH-QOL) and the PedsQL 4.0 family impact module were administered to parents of children with IH. We compared the PedsQL 4.0 Genetic Core Scales (GCIS) scores of the two groups. Multiple step-wise regression analysis was used to determine factors that influenced QOL in children with IH and their parents. Except for physical symptom, we found no significant difference in GCIS between patient group and healthy group (P = 0.409). The internal reliability of IH-QOL was excellent with the Cronbach's alpha coefficient for summary scores being 0.76. Multiple step-wise regression analysis showed that the predictors of poor IH-QOL total scores were hemangioma size, location, and mother's education level. The predictors of poor FIM total scores were hemangioma location and father's education level. The predictors of poor GCIS total scores were children's age, hemangioma location and father's education level. The findings support the feasibility and reliability of the Chinese version of IH-QOL to evaluate the QOL in children with IH and their parents. Hemangioma size, location and education level of mother are important impact factors for QOL in children with IH and their parents.

Early pregnancy fasting plasma glucose and lipid concentrations in pregnancy and association to offspring size: a retrospective cohort study.

PubMed

Liu, Bin; Geng, Huizhen; Yang, Juan; Zhang, Ying; Deng, Langhui; Chen, Weiqing; Wang, Zilian

2016-03-17

Hyperlipidemia and high fasting plasma glucose levels at the first prenatal visit (First Visit FPG) are both related to gestational diabetes mellitus, maternal obesity/overweight and fetal overgrowth. The purpose of the present study is to investigate the correlation between First Visit FPG and lipid concentrations, and their potential association with offspring size at delivery. Pregnant women that received regular prenatal care and delivered in our center in 2013 were recruited for the study. Fasting plasma glucose levels were tested at the first prenatal visit (First Visit FPG) and prior to delivery (Before Delivery FPG). HbA1c and lipid profiles were examined at the time of OGTT test. Maternal and neonatal clinical data were collected for analysis. Data was analyzed by independent sample t test, Pearson correlation, and Chi-square test, followed by partial correlation and multiple linear regression analyses to confirm association. Statistical significance level was α =0.05. Analyses were based on 1546 mother-baby pairs. First Visit FPG was not correlated with any lipid parameters after adjusting for maternal pregravid BMI, maternal age and gestational age at First Visit FPG. HbA1c was positively correlated with triglyceride and Apolipoprotein B in the whole cohort and in the NGT group after adjusting for maternal age and maternal BMI at OGTT test. Multiple linear regression analyses showed neonatal birth weight, head circumference and shoulder circumference were all associated with First Visit FPG and triglyceride levels. Fasting plasma glucose at first prenatal visit is not associated with lipid concentrations in mid-pregnancy, but may influence fetal growth together with triglyceride concentration.

Reduced gamma-aminobutyric acid concentration is associated with physical disability in progressive multiple sclerosis.

PubMed

Cawley, Niamh; Solanky, Bhavana S; Muhlert, Nils; Tur, Carmen; Edden, Richard A E; Wheeler-Kingshott, Claudia A M; Miller, David H; Thompson, Alan J; Ciccarelli, Olga

2015-09-01

Neurodegeneration is thought to be the major cause of ongoing, irreversible disability in progressive stages of multiple sclerosis. Gamma-aminobutyric acid is the principle inhibitory neurotransmitter in the brain. The aims of this study were to investigate if gamma-aminobutyric acid levels (i) are abnormal in patients with secondary progressive multiple sclerosis compared with healthy controls; and (ii) correlate with physical and cognitive performance in this patient population. Thirty patients with secondary progressive multiple sclerosis and 17 healthy control subjects underwent single-voxel MEGA-PRESS (MEscher-GArwood Point RESolved Spectroscopy) magnetic resonance spectroscopy at 3 T, to quantify gamma-aminobutyric acid levels in the prefrontal cortex, right hippocampus and left sensorimotor cortex. All subjects were assessed clinically and underwent a cognitive assessment. Multiple linear regression models were used to compare differences in gamma-aminobutyric acid concentrations between patients and controls adjusting for age, gender and tissue fractions within each spectroscopic voxel. Regression was used to examine the relationships between the cognitive function and physical disability scores specific for these regions with gamma-aminobuytric acid levels, adjusting for age, gender, and total N-acetyl-aspartate and glutamine-glutamate complex levels. When compared with controls, patients performed significantly worse on all motor and sensory tests, and were cognitively impaired in processing speed and verbal memory. Patients had significantly lower gamma-aminobutyric acid levels in the hippocampus (adjusted difference = -0.403 mM, 95% confidence intervals -0.792, -0.014, P = 0.043) and sensorimotor cortex (adjusted difference = -0.385 mM, 95% confidence intervals -0.667, -0.104, P = 0.009) compared with controls. In patients, reduced motor function in the right upper and lower limb was associated with lower gamma-aminobutyric acid concentration in the sensorimotor cortex. Specifically for each unit decrease in gamma-aminobutyric acid levels (in mM), there was a predicted -10.86 (95% confidence intervals -16.786 to -4.482) decrease in grip strength (kg force) (P < 0.001) and -8.74 (95% confidence intervals -13.943 to -3.015) decrease in muscle strength (P < 0.006). This study suggests that reduced gamma-aminobutyric acid levels reflect pathological abnormalities that may play a role in determining physical disability. These abnormalities may include decreases in the pre- and postsynaptic components of gamma-aminobutyric acid neurotransmission and in the density of inhibitory neurons. Additionally, the reduced gamma-aminobutyric acid concentration may contribute to the neurodegenerative process, resulting in increased firing of axons, with consequent increased energy demands, which may lead to neuroaxonal degeneration and loss of the compensatory mechanisms that maintain motor function. This study supports the idea that modulation of gamma-aminobutyric acid neurotransmission may be an important target for neuroprotection in multiple sclerosis.See De Stefano and Giorgio (doi:10.1093/brain/awv213) for a scientific commentary on this article. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The importance of proximal fusion level selection for outcomes of multi-level lumbar posterolateral fusion.

PubMed

Nam, Woo Dong; Cho, Jae Hwan

2015-03-01

There are few studies about risk factors for poor outcomes from multi-level lumbar posterolateral fusion limited to three or four level lumbar posterolateral fusions. The purpose of this study was to analyze the outcomes of multi-level lumbar posterolateral fusion and to search for possible risk factors for poor surgical outcomes. We retrospectively analyzed 37 consecutive patients who underwent multi-level lumbar or lumbosacral posterolateral fusion with posterior instrumentation. The outcomes were deemed either 'good' or 'bad' based on clinical and radiological results. Many demographic and radiological factors were analyzed to examine potential risk factors for poor outcomes. Student t-test, Fisher exact test, and the chi-square test were used based on the nature of the variables. Multiple logistic regression analysis was used to exclude confounding factors. Twenty cases showed a good outcome (group A, 54.1%) and 17 cases showed a bad outcome (group B, 45.9%). The overall fusion rate was 70.3%. The revision procedures (group A: 1/20, 5.0%; group B: 4/17, 23.5%), proximal fusion to L2 (group A: 5/20, 25.0%; group B: 10/17, 58.8%), and severity of stenosis (group A: 12/19, 63.3%; group B: 3/11, 27.3%) were adopted as possible related factors to the outcome in univariate analysis. Multiple logistic regression analysis revealed that only the proximal fusion level (superior instrumented vertebra, SIV) was a significant risk factor. The cases in which SIV was L2 showed inferior outcomes than those in which SIV was L3. The odds ratio was 6.562 (95% confidence interval, 1.259 to 34.203). The overall outcome of multi-level lumbar or lumbosacral posterolateral fusion was not as high as we had hoped it would be. Whether the SIV was L2 or L3 was the only significant risk factor identified for poor outcomes in multi-level lumbar or lumbosacral posterolateral fusion in the current study. Thus, the authors recommend that proximal fusion levels be carefully determined when multi-level lumbar fusions are considered.

The Importance of Proximal Fusion Level Selection for Outcomes of Multi-Level Lumbar Posterolateral Fusion

PubMed Central

Nam, Woo Dong

2015-01-01

Background There are few studies about risk factors for poor outcomes from multi-level lumbar posterolateral fusion limited to three or four level lumbar posterolateral fusions. The purpose of this study was to analyze the outcomes of multi-level lumbar posterolateral fusion and to search for possible risk factors for poor surgical outcomes. Methods We retrospectively analyzed 37 consecutive patients who underwent multi-level lumbar or lumbosacral posterolateral fusion with posterior instrumentation. The outcomes were deemed either 'good' or 'bad' based on clinical and radiological results. Many demographic and radiological factors were analyzed to examine potential risk factors for poor outcomes. Student t-test, Fisher exact test, and the chi-square test were used based on the nature of the variables. Multiple logistic regression analysis was used to exclude confounding factors. Results Twenty cases showed a good outcome (group A, 54.1%) and 17 cases showed a bad outcome (group B, 45.9%). The overall fusion rate was 70.3%. The revision procedures (group A: 1/20, 5.0%; group B: 4/17, 23.5%), proximal fusion to L2 (group A: 5/20, 25.0%; group B: 10/17, 58.8%), and severity of stenosis (group A: 12/19, 63.3%; group B: 3/11, 27.3%) were adopted as possible related factors to the outcome in univariate analysis. Multiple logistic regression analysis revealed that only the proximal fusion level (superior instrumented vertebra, SIV) was a significant risk factor. The cases in which SIV was L2 showed inferior outcomes than those in which SIV was L3. The odds ratio was 6.562 (95% confidence interval, 1.259 to 34.203). Conclusions The overall outcome of multi-level lumbar or lumbosacral posterolateral fusion was not as high as we had hoped it would be. Whether the SIV was L2 or L3 was the only significant risk factor identified for poor outcomes in multi-level lumbar or lumbosacral posterolateral fusion in the current study. Thus, the authors recommend that proximal fusion levels be carefully determined when multi-level lumbar fusions are considered. PMID:25729522

Inverse association linking serum levels of potential antioxidant vitamins with C-reactive protein levels using a novel analytical approach.

PubMed

Cheng, Hui G; Alshaarawy, Omayma; Cantave, Marven D; Anthony, James C

2016-10-01

Exposures to antioxidants (AO) are associated with levels of C-reactive protein (CRP), but the pattern of evidence is mixed, due in part to studying each potential AO, one at a time, when multiple AO exposures might affect CRP levels. By studying multiple AO via a composite indicator approach, we estimate the degree to which serum CRP level is associated with serum AO level. Standardised field survey protocols for the US National Health and Nutrition Examination Survey (NHANES) 2003-2006 yielded nationally representative cross-sectional samples of adults aged 20 years and older (n 8841). NHANES latex-enhanced nephelometry quantified serum CRP levels. Liquid chromatography quantified serum concentrations of vitamins A, E and C and carotenoids. Using structural equations, we regressed CRP level on AO levels, and derived a summary estimate for a composite of these potential antioxidants (CPA), with covariates held constant. The association linking CPA with CRP was inverse, stronger for slightly elevated CRP (1·8≤CRP<10 mg/l; slope= -1·08; 95 % CI -1·39, -0·77) and weaker for highly elevated CRP (≥10 mg/l; slope= -0·52; 95 % CI -0·68, -0·35), with little change when covariates were added. Vitamins A and C, as well as lutein+zeaxanthin, were prominent contributors to the composite. In these cross-sectional data studied via a composite indicator approach, the CPA level and the CRP level were inversely related. The stage is set for more confirmatory longitudinal or intervention research on multiple vitamins. The composite indicator approach might be most useful in epidemiology when several exposure constructs are too weakly inter-correlated to be studied via formal measurement models for underlying latent dimensions.

Persistence of Multiple Tumor-Specific T-Cell Clones Is Associated with Complete Tumor Regression in a Melanoma Patient Receiving Adoptive Cell Transfer Therapy

PubMed Central

Zhou, Juhua; Dudley, Mark E.; Rosenberg, Steven A.; Robbins, Paul F.

2007-01-01

Summary The authors recently reported that adoptive immunotherapy with autologous tumor-reactive tumor infiltrating lymphocytes (TILs) immediately following a conditioning nonmyeloablative chemotherapy regimen resulted in an enhanced clinical response rate in patients with metastatic melanoma. These observations led to the current studies, which are focused on a detailed analysis of the T-cell antigen reactivity as well as the in vivo persistence of T cells in melanoma patient 2098, who experienced a complete regression of all metastatic lesions in lungs and soft tissues following therapy. Screening of an autologous tumor cell cDNA library using transferred TILs resulted in the identification of novel mutated growth arrest-specific gene 7 (GAS7) and glyceral-dehyde-3-phosphate dehydrogenase (GAPDH) gene transcripts. Direct sequence analysis of the expressed T-cell receptor beta chain variable regions showed that the transferred TILs contained multiple T-cell clonotypes, at least six of which persisted in peripheral blood for a month or more following transfer. The persistent T cells recognized both the mutated GAS7 and GAPDH. These persistent tumor-reactive T-cell clones were detected in tumor cell samples obtained from the patient following adoptive cell transfer and appeared to be represented at higher levels in the tumor sample obtained 1 month following transfer than in the peripheral blood obtained at the same time. Overall, these results indicate that multiple tumor-reactive T cells can persist in the peripheral blood and at the tumor site for prolonged times following adoptive transfer and thus may be responsible for the complete tumor regression in this patient. PMID:15614045

[Association between hours of television watched, physical activity, sleep and excess weight among young adults].

PubMed

Martínez-Moyá, María; Navarrete-Muñoz, Eva M; García de la Hera, Manuela; Giménez-Monzo, Daniel; González-Palacios, Sandra; Valera-Gran, Desirée; Sempere-Orts, María; Vioque, Jesús

2014-01-01

To explore the association between excess weight or body mass index (BMI) and the time spent watching television, self-reported physical activity and sleep duration in a young adult population. We analyzed cross-sectional baseline data of 1,135 participants (17-35 years old) from the project Dieta, salud y antropometría en población universitaria (Diet, Health and Anthrompmetric Variables in Univeristy Students). Information about time spent watching television, sleep duration, self-reported physical activity and self-reported height and weight was provided by a baseline questionnaire. BMI was calculated as kg/m(2) and excess of weight was defined as ≥25. We used multiple logistic regression to explore the association between excess weight (no/yes) and independent variables, and multiple linear regression for BMI. The prevalence of excess weight was 13.7% (11.2% were overweight and 2.5% were obese). A significant positive association was found between excess weight and a greater amount of time spent watching television. Participants who reported watching television >2h a day had a higher risk of excess weight than those who watched television ≤1h a day (OR=2.13; 95%CI: 1.37-3.36; p-trend: 0.002). A lower level of physical activity was associated with an increased risk of excess weight, although the association was statistically significant only in multiple linear regression (p=0.037). No association was observed with sleep duration. A greater number of hours spent watching television and lower physical activity were significantly associated with a higher BMI in young adults. Both factors are potentially modifiable with preventive strategies. Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.

Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds.

PubMed

Ventura, Cristina; Latino, Diogo A R S; Martins, Filomena

2013-01-01

The performance of two QSAR methodologies, namely Multiple Linear Regressions (MLR) and Neural Networks (NN), towards the modeling and prediction of antitubercular activity was evaluated and compared. A data set of 173 potentially active compounds belonging to the hydrazide family and represented by 96 descriptors was analyzed. Models were built with Multiple Linear Regressions (MLR), single Feed-Forward Neural Networks (FFNNs), ensembles of FFNNs and Associative Neural Networks (AsNNs) using four different data sets and different types of descriptors. The predictive ability of the different techniques used were assessed and discussed on the basis of different validation criteria and results show in general a better performance of AsNNs in terms of learning ability and prediction of antitubercular behaviors when compared with all other methods. MLR have, however, the advantage of pinpointing the most relevant molecular characteristics responsible for the behavior of these compounds against Mycobacterium tuberculosis. The best results for the larger data set (94 compounds in training set and 18 in test set) were obtained with AsNNs using seven descriptors (R(2) of 0.874 and RMSE of 0.437 against R(2) of 0.845 and RMSE of 0.472 in MLRs, for test set). Counter-Propagation Neural Networks (CPNNs) were trained with the same data sets and descriptors. From the scrutiny of the weight levels in each CPNN and the information retrieved from MLRs, a rational design of potentially active compounds was attempted. Two new compounds were synthesized and tested against M. tuberculosis showing an activity close to that predicted by the majority of the models. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Estimating Causal Effects of Education Interventions Using a Two-Rating Regression Discontinuity Design: Lessons from a Simulation Study and an Application

ERIC Educational Resources Information Center

Porter, Kristin E.; Reardon, Sean F.; Unlu, Fatih; Bloom, Howard S.; Cimpian, Joseph R.

2017-01-01

A valuable extension of the single-rating regression discontinuity design (RDD) is a multiple-rating RDD (MRRDD). To date, four main methods have been used to estimate average treatment effects at the multiple treatment frontiers of an MRRDD: the "surface" method, the "frontier" method, the "binding-score" method, and…

How Variables Uncorrelated with the Dependent Variable Can Actually Make Excellent Predictors: The Important Suppressor Variable Case.

ERIC Educational Resources Information Center

Woolley, Kristin K.

Many researchers are unfamiliar with suppressor variables and how they operate in multiple regression analyses. This paper describes the role suppressor variables play in a multiple regression model and provides practical examples that explain how they can change research results. A variable that when added as another predictor increases the total…

Multicollinearity is a red herring in the search for moderator variables: A guide to interpreting moderated multiple regression models and a critique of Iacobucci, Schneider, Popovich, and Bakamitsos (2016).

PubMed

McClelland, Gary H; Irwin, Julie R; Disatnik, David; Sivan, Liron

2017-02-01

Multicollinearity is irrelevant to the search for moderator variables, contrary to the implications of Iacobucci, Schneider, Popovich, and Bakamitsos (Behavior Research Methods, 2016, this issue). Multicollinearity is like the red herring in a mystery novel that distracts the statistical detective from the pursuit of a true moderator relationship. We show multicollinearity is completely irrelevant for tests of moderator variables. Furthermore, readers of Iacobucci et al. might be confused by a number of their errors. We note those errors, but more positively, we describe a variety of methods researchers might use to test and interpret their moderated multiple regression models, including two-stage testing, mean-centering, spotlighting, orthogonalizing, and floodlighting without regard to putative issues of multicollinearity. We cite a number of recent studies in the psychological literature in which the researchers used these methods appropriately to test, to interpret, and to report their moderated multiple regression models. We conclude with a set of recommendations for the analysis and reporting of moderated multiple regression that should help researchers better understand their models and facilitate generalizations across studies.

Contributions of dopamine-related genes and environmental factors to highly sensitive personality: a multi-step neuronal system-level approach.

PubMed

Chen, Chunhui; Chen, Chuansheng; Moyzis, Robert; Stern, Hal; He, Qinghua; Li, He; Li, Jin; Zhu, Bi; Dong, Qi

2011-01-01

Traditional behavioral genetic studies (e.g., twin, adoption studies) have shown that human personality has moderate to high heritability, but recent molecular behavioral genetic studies have failed to identify quantitative trait loci (QTL) with consistent effects. The current study adopted a multi-step approach (ANOVA followed by multiple regression and permutation) to assess the cumulative effects of multiple QTLs. Using a system-level (dopamine system) genetic approach, we investigated a personality trait deeply rooted in the nervous system (the Highly Sensitive Personality, HSP). 480 healthy Chinese college students were given the HSP scale and genotyped for 98 representative polymorphisms in all major dopamine neurotransmitter genes. In addition, two environment factors (stressful life events and parental warmth) that have been implicated for their contributions to personality development were included to investigate their relative contributions as compared to genetic factors. In Step 1, using ANOVA, we identified 10 polymorphisms that made statistically significant contributions to HSP. In Step 2, these polymorphism's main effects and interactions were assessed using multiple regression. This model accounted for 15% of the variance of HSP (p<0.001). Recent stressful life events accounted for an additional 2% of the variance. Finally, permutation analyses ascertained the probability of obtaining these findings by chance to be very low, p ranging from 0.001 to 0.006. Dividing these loci by the subsystems of dopamine synthesis, degradation/transport, receptor and modulation, we found that the modulation and receptor subsystems made the most significant contribution to HSP. The results of this study demonstrate the utility of a multi-step neuronal system-level approach in assessing genetic contributions to individual differences in human behavior. It can potentially bridge the gap between the high heritability estimates based on traditional behavioral genetics and the lack of reproducible genetic effects observed currently from molecular genetic studies.

Contributions of Dopamine-Related Genes and Environmental Factors to Highly Sensitive Personality: A Multi-Step Neuronal System-Level Approach

PubMed Central

Chen, Chunhui; Chen, Chuansheng; Moyzis, Robert; Stern, Hal; He, Qinghua; Li, He; Li, Jin; Zhu, Bi; Dong, Qi

2011-01-01

Traditional behavioral genetic studies (e.g., twin, adoption studies) have shown that human personality has moderate to high heritability, but recent molecular behavioral genetic studies have failed to identify quantitative trait loci (QTL) with consistent effects. The current study adopted a multi-step approach (ANOVA followed by multiple regression and permutation) to assess the cumulative effects of multiple QTLs. Using a system-level (dopamine system) genetic approach, we investigated a personality trait deeply rooted in the nervous system (the Highly Sensitive Personality, HSP). 480 healthy Chinese college students were given the HSP scale and genotyped for 98 representative polymorphisms in all major dopamine neurotransmitter genes. In addition, two environment factors (stressful life events and parental warmth) that have been implicated for their contributions to personality development were included to investigate their relative contributions as compared to genetic factors. In Step 1, using ANOVA, we identified 10 polymorphisms that made statistically significant contributions to HSP. In Step 2, these polymorphism's main effects and interactions were assessed using multiple regression. This model accounted for 15% of the variance of HSP (p<0.001). Recent stressful life events accounted for an additional 2% of the variance. Finally, permutation analyses ascertained the probability of obtaining these findings by chance to be very low, p ranging from 0.001 to 0.006. Dividing these loci by the subsystems of dopamine synthesis, degradation/transport, receptor and modulation, we found that the modulation and receptor subsystems made the most significant contribution to HSP. The results of this study demonstrate the utility of a multi-step neuronal system-level approach in assessing genetic contributions to individual differences in human behavior. It can potentially bridge the gap between the high heritability estimates based on traditional behavioral genetics and the lack of reproducible genetic effects observed currently from molecular genetic studies. PMID:21765900

[Potential interaction effect on attention-deficit/hyperactivity disorder between mother's educational level and preschoolers' dietary pattern].

PubMed

Yan, S Q; Cao, H; Gu, C L; Gao, G P; Ni, L L; Tao, H H; Shao, T; Xu, Y Q; Tao, F B

2018-04-10

Objective: To explore the interaction effect between mother's educational level and preschoolers' dietary pattern on attention-deficit/hyperactivity disorder (ADHD). Methods: In 2014, there were 16 439 children aged 3-6 years old from 91 kindergartens in Ma'anshan municipality of China. A semi-quantitative food frequency questionnaire and the 10-item Chinese version of the Conners' Abbreviated Symptom Questionnaire (C-ASQ) were administered to assess the usual dietary intake and symptoms on ADHD. Social-demographic information was collected through questionnaires. Unconditional logistic regression was used to analyze the multiplication interaction effect between mother's educational level and preschoolers' dietary pattern on ADHD. Excel software was used to analyze the additive interaction effect of mother's educational level and preschoolers'dietary pattern on ADHD. Results: Results showed that factors as: mother's low educational level[a OR =1.31 (1.13-1.52)], scores related to preschoolers in the top quintile of "food processing" [a OR =1.31 (1.16-1.48)] and "snack" [a OR =1.45 (1.29-1.63)]patterns showed greater odds while preschoolers in the top quintile of "vegetarian" [a OR =0.80 (0.71-0.90)]showed less odds for having ADHD symptoms. Both multiplication and additive interactions were observed between mothers with less education. The processed dietary patterns ( OR =1.17, 95% CI : 1.11-1.25), relative excess risk of interaction ( RERI ), attributable proportion ( AP ) and the interaction index ( SI ) appeared as 0.21, 0.13 and 1.47, respectively. Multiplication interaction was observed between levels of mother's low education and the snack dietary pattern ( OR =1.21, 95% CI : 1.14-1.29), with RERI , AP and SI as 0.49, 0.26 and 2.36, respectively. However, neither multiplication interaction or additive interaction was noticed between levels of mother's low education and the vegetarian dietary pattern ( OR =0.97, 95% CI : 0.92-1.03), with RERI , AP and SI as 0.09, 0.05 and 1.15, respectively. Conclusions: Levels of mother's low education presented a risk factor for ADHD symptoms in preschool children. Both multiplication interaction and additive interaction were observed between mother's low education levels and the processed dietary pattern. Multiplication interaction was noticed between mother's education levels and the snack dietary pattern but not with the vegetarian dietary pattern.

Women's work stress and cortisol levels: a longitudinal study of the association between the psychosocial work environment and serum cortisol.

PubMed

Evolahti, Annika; Hultcrantz, Malou; Collins, Aila

2006-11-01

The aim of the present study was to investigate whether there is an association between serum cortisol and work-related stress, as defined by the demand-control model in a longitudinal design. One hundred ten women aged 47-53 years completed a health questionnaire, including the Swedish version of the Job Content Scale, and participated in a psychological interview at baseline and in a follow-up session 2 years later. Morning blood samples were drawn for analyses of cortisol. Multiple stepwise regression analyses and logistic regression analyses showed that work demands and lack of social support were significantly associated with cortisol. The results of this study showed that negative work characteristics in terms of high demands and low social support contributed significantly to the biological stress levels in middle-aged women. Participation in the study may have served as an intervention, increasing the women's awareness and thus improving their health profiles on follow-up.

Urinary inorganic arsenic concentrations and semen quality of male partners of subfertile couples in Tokyo.

PubMed

Oguri, Tomoko; Yoshinaga, Jun; Toshima, Hiroki; Mizumoto, Yoshifumi; Hatakeyama, Shota; Tokuoka, Susumu

2016-01-01

Inorganic arsenic (iAs) has been known as a testicular toxicant in experimental rodents. Possible association between iAs exposure and semen quality (semen volume, sperm concentration, and sperm motility) was explored in male partners of couples (n = 42) who visited a gynecology clinic in Tokyo for infertility consultation. Semen parameters were measured according to WHO guideline at the clinic, and urinary iAs and methylarsonic acid (MMA), and dimethylarsinic acid concentrations were determined by liquid chromatography-hydride generation-ICP mass spectrometry. Biological attributes, dietary habits, and exposure levels to other chemicals with known effects on semen parameters were taken into consideration as covariates. Multiple regression analyses and logistic regression analyses did not find iAs exposure as significant contributor to semen parameters. Lower exposure level of subjects (estimated to be 0.5 μg kg(-1) day(-1)) was considered a reason of the absence of adverse effects on semen parameters, which were seen in rodents dosed with 4-7.5 mg kg(-1).

Comparing multiple imputation methods for systematically missing subject-level data.

PubMed

Kline, David; Andridge, Rebecca; Kaizar, Eloise

2017-06-01

When conducting research synthesis, the collection of studies that will be combined often do not measure the same set of variables, which creates missing data. When the studies to combine are longitudinal, missing data can occur on the observation-level (time-varying) or the subject-level (non-time-varying). Traditionally, the focus of missing data methods for longitudinal data has been on missing observation-level variables. In this paper, we focus on missing subject-level variables and compare two multiple imputation approaches: a joint modeling approach and a sequential conditional modeling approach. We find the joint modeling approach to be preferable to the sequential conditional approach, except when the covariance structure of the repeated outcome for each individual has homogenous variance and exchangeable correlation. Specifically, the regression coefficient estimates from an analysis incorporating imputed values based on the sequential conditional method are attenuated and less efficient than those from the joint method. Remarkably, the estimates from the sequential conditional method are often less efficient than a complete case analysis, which, in the context of research synthesis, implies that we lose efficiency by combining studies. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Relationship between menopause and health-related quality of life in middle-aged Chinese women: a cross-sectional study.

PubMed

Liu, Kuo; He, Liu; Tang, Xun; Wang, Jinwei; Li, Na; Wu, Yiqun; Marshall, Roger; Li, Jingrong; Zhang, Zongxin; Liu, Jianjiang; Xu, Haitao; Yu, Liping; Hu, Yonghua

2014-01-10

Chinese menopausal women comprise a large population and the women in it experience menopausal symptoms in many different ways. Their health related quality of life (HRQOL) is not particularly well studied. Our study intends to evaluate the influence of menopause on HRQOL and explore other risk factors for HRQOL in rural China. An interview study was conducted from June to August 2010 in Beijing based on cross-sectional design. 1,351 women aged 40-59 were included in the study. HRQOL was measured using the EuroQol Group's 5-domain (EQ5D) questionnaire. Comparison of HRQOL measures (EQ5D index and EQ5D-VAS scores) was done between different menopausal groups. Logistic regression and multiple regression analysis were performed to adjust potential confounders and explore other risk factors for health problems and HRQOL measures. Postmenopausal women who had menopause for 2-5 years (+1b stage) were more likely to suffer mobility problems (OR = 1.835, p = 0.008) after multiple adjustment. Menopause was also related to impaired EQ5D index and EQ5D-VAS scores after adjustment for age. Among menopausal groups categorized by menopausal duration, a consistent decrement in EQ5D index and EQ5D-VAS scores, that is, worsening HRQOL, was observed (p < 0.05). Multiple regression analysis revealed low education level and physical activity were associated with EQ5D index (β = -0.080, p = 0.003, and β = 0.056, p = 0.040, respectively). Cigarette smoking and chronic disease were associated with EQ5D index (β = -0.135, p < 0.001 and β = -0.104, p < 0.001, respectively) and EQ5D-VAS (β = -0.057, P = 0.034 and β = -0.214, p < 0.001, respectively). Reduction in physical function was found within the first five years after menopause. Worsening EQ5D index and EQ5D-VAS scores were related to menopause. Education level, physical activity, cigarette smoking, and chronic disease history were associated with HRQOL in middle aged Chinese rural women.

[Establishment of multiple regression model for virulence factors of Saccharomyces albicans by random amplified polymorphic DNA bands].

PubMed

Liu, Qi; Wu, Youcong; Yuan, Youhua; Bai, Li; Niu, Kun

2011-12-01

To research the relationship between the virulence factors of Saccharomyces albicans (S. albicans) and the random amplified polymorphic DNA (RAPD) bands of them, and establish the regression model by multiple regression analysis. Extracellular phospholipase, secreted proteinase, ability to generate germ tubes and adhere to oral mucosal cells of 92 strains of S. albicans were measured in vitro; RAPD-polymerase chain reaction (RAPD-PCR) was used to get their bands. Multiple regression for virulence factors of S. albicans and RAPD-PCR bands was established. The extracellular phospholipase activity was associated with 4 RAPD bands: 350, 450, 650 and 1 300 bp (P < 0.05); secreted proteinase activity of S. albicans was associated with 2 bands: 350 and 1 200 bp (P < 0.05); the ability of germ tube produce was associated with 2 bands: 400 and 550 bp (P < 0.05). Some RAPD bands will reflect the virulence factors of S. albicans indirectly. These bands would contain some important messages for regulation of S. albicans virulence factors.

Antecedents of self-care in adults with congenital heart defects.

PubMed

McCabe, Nancy; Dunbar, Sandra B; Butler, Javed; Higgins, Melinda; Book, Wendy; Reilly, Carolyn

2015-12-15

Adults with congenital heart defects (ACHD) face long-term complications related to prior surgery, abnormal anatomy, and acquired cardiovascular conditions. Although self-care is an important part of chronic illness management, few studies have explored self-care in the ACHD population. The purpose of this study is to describe self-care and its antecedents in the ACHD population. Persons with moderate or severe ACHD (N=132) were recruited from a single ACHD center. Self-care (health maintenance behaviors, monitoring and management of symptoms), and potential antecedents including sociodemographic and clinical characteristics, ACHD knowledge, behavioral characteristics (depressive symptoms and self-efficacy), and family-related factors (parental overprotection and perceived family support) were collected via self-report and chart review. Multiple regression was used to identify antecedents of self-care maintenance, monitoring, and management. Only 44.7%, 27.3%, and 23.3% of participants performed adequate levels of self-care maintenance, monitoring and management, respectively. In multiple regression analysis, self-efficacy, education, gender, perceived family support, and comorbidities explained 25% of the variance in self-care maintenance (R(2)=.248, F(5, 123)=9.44, p<.001). Age, depressive symptoms, self-efficacy, and NYHA Class explained 23% of the variance in self-care monitoring (R(2)=.232, F(2, 124)=10.66, p<.001). Self-efficacy and NYHA Class explained 9% of the variance in self-care management (R(2)=.094, F(2, 80)=5.27, p=.007). Low levels of self-care are common among persons with ACHD. Multiple factors, including modifiable factors of self-efficacy, depressive symptoms, and perceived family support, are associated with self-care and should be considered in designing future interventions to improve outcomes in the ACHD population. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Antecedents of Self-Care in Adults with Congenital Heart Defects

PubMed Central

McCabe, Nancy; Dunbar, Sandra B.; Butler, Javed; Higgins, Melinda; Book, Wendy; Reilly, Carolyn

2015-01-01

Background Adults with congenital heart defects (ACHD) face long-term complications related to prior surgery, abnormal anatomy, and acquired cardiovascular conditions. Although self-care is an important part of chronic illness management, few studies have explored self-care in the ACHD population. The purpose of this study is to describe self-care and its antecedents in the ACHD population. Methods Persons with moderate or severe ACHD (N=132) were recruited from a single ACHD center. Self-care (health maintenance behaviors, monitoring and management of symptoms), and potential antecedents including sociodemographic and clinical characteristics, ACHD knowledge, behavioral characteristics (depressive symptoms and self-efficacy), and family-related factors (parental overprotection and perceived family support) were collected via self-report and chart review. Multiple regression was used to identify antecedents of self-care maintenance, monitoring, and management. Results Only 44.7%, 27.3%, and 23.3% of participants performed adequate levels of self-care maintenance, monitoring and management, respectively. In multiple regression analysis, self-efficacy, education, gender, perceived family support, and comorbidities explained 25% of the variance in self-care maintenance (R2=.248, F(5, 123)=9.44, p<.001). Age, depressive symptoms, self-efficacy, and NYHA Class explained 23% of the variance in self-care monitoring (R2=.232, F(2, 124)=10.66, p<.001). Self-efficacy and NYHA Class explained 9% of the variance in self-care management (R2=.094, F(2, 80)=5.27, p=.007). Conclusions Low levels of self-care are common among persons with ACHD. Multiple factors, including modifiable factors of self-efficacy, depressive symptoms, and perceived family support, are associated with self-care and should be considered in designing future interventions to improve outcomes in the ACHD population. PMID:26340127

BLZF1 expression is of prognostic significance in hepatocellular carcinoma

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

Huang, Run-Yue, E-mail: ry_huang@hotmail.com; Su, Shu-Guang; Wu, Dan-Chun

2015-11-20

BLZF1, a member of b-ZIP family, has been implicated in epigenetic regulation and Wnt/β-catenin signaling. Its expression and clinical significance in human cancers remain largely unknown. In this study, we showed that BLZF1 expression was reduced in hepatocellular carcinoma (HCC) tissues, compared to the paracarcinoma tissues, at both mRNA and protein levels. Results of immunohistochemistry revealed that BLZF1 was presented in both nuclear and cytoplasm. Decreased expression of nuclear and cytosolic BLZF1 in HCC was depicted in 68.2% and 79.2% of the 634 cases. Nuclear BLZF1 expression was significantly associated with tumor multiplicity (P = 0.048) and tumor capsule (P = 0.028), while cytosolicmore » BLZF1 expression was correlated with serum AFP level (P = 0.017), tumor differentiation (P = 0.001) and tumor capsule (P = 0.003). Kaplan–Meier analysis indicated both nuclear and cytosolic BLZF1 expression was associated with poor overall survival. Low nuclear BLZF1 also indicated unfavorable disease-free survival and high tendency of tumor recurrence. Furthermore, multiple Cox regression analysis revealed nuclear BLZF1 as an independent factor for overall survival (Hazard Ratio (HR) = 0.827, 95% confident interval (95%CI): 0.697–0.980, P = 0.029). The prognostic value of BLZF1 was further confirmed by stratified analyses. Collectively, our data suggest BLZF1 is a novel unfavorable biomarker for prognosis of patients with HCC. - Highlights: • BLZF1 expression was much lower in HCC tissues. • Low BLZF1 expression was associated with poor outcomes in a cohort of 634 HCC patients. • Multiple Cox regression analysis indicated nuclear BLZF1 as an independent predictor for overall survival.« less

Simultaneous multiple non-crossing quantile regression estimation using kernel constraints

PubMed Central

Liu, Yufeng; Wu, Yichao

2011-01-01

Quantile regression (QR) is a very useful statistical tool for learning the relationship between the response variable and covariates. For many applications, one often needs to estimate multiple conditional quantile functions of the response variable given covariates. Although one can estimate multiple quantiles separately, it is of great interest to estimate them simultaneously. One advantage of simultaneous estimation is that multiple quantiles can share strength among them to gain better estimation accuracy than individually estimated quantile functions. Another important advantage of joint estimation is the feasibility of incorporating simultaneous non-crossing constraints of QR functions. In this paper, we propose a new kernel-based multiple QR estimation technique, namely simultaneous non-crossing quantile regression (SNQR). We use kernel representations for QR functions and apply constraints on the kernel coefficients to avoid crossing. Both unregularised and regularised SNQR techniques are considered. Asymptotic properties such as asymptotic normality of linear SNQR and oracle properties of the sparse linear SNQR are developed. Our numerical results demonstrate the competitive performance of our SNQR over the original individual QR estimation. PMID:22190842

Comparing Effects of Biologic Agents in Treating Patients with Rheumatoid Arthritis: A Multiple Treatment Comparison Regression Analysis.

PubMed

Tvete, Ingunn Fride; Natvig, Bent; Gåsemyr, Jørund; Meland, Nils; Røine, Marianne; Klemp, Marianne

2015-01-01

Rheumatoid arthritis patients have been treated with disease modifying anti-rheumatic drugs (DMARDs) and the newer biologic drugs. We sought to compare and rank the biologics with respect to efficacy. We performed a literature search identifying 54 publications encompassing 9 biologics. We conducted a multiple treatment comparison regression analysis letting the number experiencing a 50% improvement on the ACR score be dependent upon dose level and disease duration for assessing the comparable relative effect between biologics and placebo or DMARD. The analysis embraced all treatment and comparator arms over all publications. Hence, all measured effects of any biologic agent contributed to the comparison of all biologic agents relative to each other either given alone or combined with DMARD. We found the drug effect to be dependent on dose level, but not on disease duration, and the impact of a high versus low dose level was the same for all drugs (higher doses indicated a higher frequency of ACR50 scores). The ranking of the drugs when given without DMARD was certolizumab (ranked highest), etanercept, tocilizumab/ abatacept and adalimumab. The ranking of the drugs when given with DMARD was certolizumab (ranked highest), tocilizumab, anakinra/rituximab, golimumab/ infliximab/ abatacept, adalimumab/ etanercept [corrected]. Still, all drugs were effective. All biologic agents were effective compared to placebo, with certolizumab the most effective and adalimumab (without DMARD treatment) and adalimumab/ etanercept (combined with DMARD treatment) the least effective. The drugs were in general more effective, except for etanercept, when given together with DMARDs.

Comparing Effects of Biologic Agents in Treating Patients with Rheumatoid Arthritis: A Multiple Treatment Comparison Regression Analysis

PubMed Central

Tvete, Ingunn Fride; Natvig, Bent; Gåsemyr, Jørund; Meland, Nils; Røine, Marianne; Klemp, Marianne

2015-01-01

Rheumatoid arthritis patients have been treated with disease modifying anti-rheumatic drugs (DMARDs) and the newer biologic drugs. We sought to compare and rank the biologics with respect to efficacy. We performed a literature search identifying 54 publications encompassing 9 biologics. We conducted a multiple treatment comparison regression analysis letting the number experiencing a 50% improvement on the ACR score be dependent upon dose level and disease duration for assessing the comparable relative effect between biologics and placebo or DMARD. The analysis embraced all treatment and comparator arms over all publications. Hence, all measured effects of any biologic agent contributed to the comparison of all biologic agents relative to each other either given alone or combined with DMARD. We found the drug effect to be dependent on dose level, but not on disease duration, and the impact of a high versus low dose level was the same for all drugs (higher doses indicated a higher frequency of ACR50 scores). The ranking of the drugs when given without DMARD was certolizumab (ranked highest), etanercept, tocilizumab/ abatacept and adalimumab. The ranking of the drugs when given with DMARD was certolizumab (ranked highest), tocilizumab, anakinra, rituximab, golimumab/ infliximab/ abatacept, adalimumab/ etanercept. Still, all drugs were effective. All biologic agents were effective compared to placebo, with certolizumab the most effective and adalimumab (without DMARD treatment) and adalimumab/ etanercept (combined with DMARD treatment) the least effective. The drugs were in general more effective, except for etanercept, when given together with DMARDs. PMID:26356639

Clinical predictors of effective continuous positive airway pressure in patients with obstructive sleep apnea/hypopnea syndrome.

PubMed

Lai, Chi-Chih; Friedman, Michael; Lin, Hsin-Ching; Wang, Pa-Chun; Hwang, Michelle S; Hsu, Cheng-Ming; Lin, Meng-Chih; Chin, Chien-Hung

2015-08-01

To identify standard clinical parameters that may predict the optimal level of continuous positive airway pressure (CPAP) in adult patients with obstructive sleep apnea/hypopnea syndrome (OSAHS). This is a retrospective study in a tertiary academic medical center that included 129 adult patients (117 males and 12 females) with OSAHS confirmed by diagnostic polysomnography (PSG). All OSAHS patients underwent successful full-night manual titration to determine the optimal CPAP pressure level for OSAHS treatment. The PSG parameters and completed physical examination, including body mass index, tonsil size grading, modified Mallampati grade (also known as updated Friedman's tongue position [uFTP]), uvular length, neck circumference, waist circumference, hip circumference, thyroid-mental distance, and hyoid-mental distance (HMD) were recorded. When the physical examination variables and OSAHS disease were correlated singly with the optimal CPAP pressure, we found that uFTP, HMD, and apnea/hypopnea index (AHI) were reliable predictors of CPAP pressures (P = .013, P = .002, and P < .001, respectively, by multiple regression). When all important factors were considered in a stepwise multiple linear regression analysis, a significant correlation with optimal CPAP pressure was formulated by factoring the uFTP, HMD, and AHI (optimal CPAP pressure = 1.01 uFTP + 0.74 HMD + 0.059 AHI - 1.603). This study distinguished the correlation between uFTP, HMD, and AHI with the optimal CPAP pressure. The structure of the upper airway (especially tongue base obstruction) and disease severity may predict the effective level of CPAP pressure. 4. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

Seasonal variations of 25-OH vitamin D serum levels are associated with clinical disease activity in multiple sclerosis patients.

PubMed

Hartl, Christina; Obermeier, Viola; Gerdes, Lisa Ann; Brügel, Mathias; von Kries, Rüdiger; Kümpfel, Tania

2017-04-15

Low 25-hydroxy vitamin D (25-[OH]-D) serum concentrations have been associated with higher disease activity in multiple sclerosis (MS) patients. In a large cross-sectional study we assessed the vitamin D status in MS patients in relation to seasonality and relapse rate. 415 MS-patients (355 relapsing-remitting MS and 60 secondary-progressive, 282 female, mean age 39.1years) of whom 25-(OH)-D serum concentrations were determined at visits between 2010 and 2013 were included in the study. All clinical data including relapse at visit and expanded disability status scale were recorded in a standardized manner by an experienced neurologist. Seasonal variations of 25-(OH)-D serum concentrations were modelled by sinusoidal regression and seasonal variability in the prevalence of relapse by cubic regression. The mean 25-(OH)-D serum concentration was 24.8ng/ml (range 8.3-140ng/ml) with peak levels of 32.2ng/ml in July/August and nadir in January/February (17.2ng/ml). The lowest modelled prevalence of relapse was in September/October (28%) and the highest modelled prevalence in March/April (47%). The nadir of 25-(OH)-D serum concentrations preceded the peak in prevalence of relapses by two months. In summary, seasonal variation of 25-(OH)-D serum levels were inversely associated with clinical disease activity in MS patients. Future studies should investigate whether vitamin D supplementation in MS patients may decrease the seasonal risk for MS relapses. Copyright © 2017 Elsevier B.V. All rights reserved.

Elevated visfatin/pre-B-cell colony-enhancing factor plasma concentration in ischemic stroke.

PubMed

Lu, Li-Fen; Yang, Sheng-Shan; Wang, Chao-Ping; Hung, Wei-Chin; Yu, Teng-Hung; Chiu, Cheng-An; Chung, Fu-Mei; Shin, Shyi-Jang; Lee, Yau-Jiunn

2009-01-01

Visfatin/pre-B-cell colony-enhancing factor is a cytokine that is expressed as a protein in several tissues (e.g., liver, skeletal muscle, immune cells), including adipose tissue, and is reported to stimulate inflammatory cytokine expressions and promote vascular smooth cell maturation. Visfatin may act as a proinflammatory cytokine and be involved in the process of atherosclerosis. In this study, we investigated whether plasma visfatin levels were altered in patients with ischemic stroke. Plasma visfatin concentrations were measured through enzyme immunoassays in patients with ischemic stroke and in control subjects without stroke. The mean plasma concentration of visfatin in the 120 patients with ischemic stroke was significantly higher than that of the 120 control subjects without stroke (51.5 +/- 48.4 v 23.0 +/- 23.9 ng/mL, P < .001). Multiple logistic regression analysis confirmed plasma visfatin to be an independent factor associated with ischemic stroke. Increasing concentrations of visfatin were independently and significantly associated with a higher risk of ischemic stroke when concentrations were analyzed as both a quartile and a continuous variable. The multiple logistic regression analysis-adjusted odds ratios and 95% confidence intervals for ischemic stroke in the second, third, and fourth quartiles were 2.3 (0.7-7.7), 6.9 (2.2-23.3), and 20.1 (4.9-97.7), respectively. Plasma visfatin concentration was positively associated with high-sensitivity C-reactive protein levels and negatively associated with low-density lipoprotein cholesterol. Our results indicate that higher visfatin levels are associated with ischemic stroke in the Chinese population.

Glutamatergic system abnormalities in posttraumatic stress disorder.

PubMed

Nishi, Daisuke; Hashimoto, Kenji; Noguchi, Hiroko; Hamazaki, Kei; Hamazaki, Tomohito; Matsuoka, Yutaka

2015-12-01

Accumulating evidence suggests involvement of the glutamatergic system in the biological mechanisms of posttraumatic stress disorder (PTSD), but few studies have demonstrated an association between glutamatergic system abnormalities and PTSD diagnosis or severity. We aimed to examine whether abnormalities in serum glutamate and in the glutamine/glutamate ratio were associated with PTSD diagnosis and severity in severely injured patients at risk for PTSD and major depressive disorder (MDD). This is a nested case-control study in TPOP (Tachikawa project for prevention of posttraumatic stress disorder with polyunsaturated fatty acid) trial. Diagnosis and severity of PTSD were assessed 3 months after the accidents using the Clinician-Administered PTSD Scale. The associations of glutamate levels and the glutamine/glutamate ratio with diagnosis and severity of PTSD and MDD were investigated by univariate and multiple linear regression analyses. Ninety-seven of 110 participants (88 %) completed assessments at 3 months. Serum glutamate levels were significantly higher for participants with full or partial PTSD than for participants without PTSD (p = 0.049) and for participants with MDD than for participants without MDD (p = 0.048). Multiple linear regression analyses showed serum glutamate levels were significantly positively associated with PTSD severity (p = 0.02) and MDD severity (p = 0.03). The glutamine/glutamate ratio was also significantly inversely associated with PTSD severity (p = 0.03), but not with MDD severity (p = 0.07). These findings suggest that the glutamatergic system may play a major role in the pathogenesis of PTSD and the need for new treatments targeting the glutamatergic system to be developed for PTSD.

Comparison of Mental Toughness and Power Test Performances in High-Level Kickboxers by Competitive Success

PubMed Central

Slimani, Maamer; Miarka, Bianca; Briki, Walid; Cheour, Foued

2016-01-01

Background Kickboxing is a high-intensity intermittent striking combat sport, which is characterized by complex skills and tactical key actions with short duration. Objectives The present study compared and verified the relationship between mental toughness (MT), countermovement jump (CMJ) and medicine ball throw (MBT) power tests by outcomes of high-level kickboxers during National Championship. Materials and Methods Thirty two high-level male kickboxers (winner = 16 and loser = 16: 21.2 ± 3.1 years, 1.73 ± 0.07 m, and 70.2 ± 9.4 kg) were analyzed using the CMJ, MBT tests and sports mental toughness questionnaire (SMTQ; based in confidence, constancy and control subscales), before the fights of the 2015 national championship (16 bouts). In statistical analysis, Mann-Withney test and a multiple linear regression were used to compare groups and to observe relationships, respectively, P ≤ 0.05. Results The present results showed significant differences between losers vs. winners, respectively, of total MT (7(7;8) vs. 11(10.2;11), confidence (3(3;3) vs. 4(4;4)), constancy (2(2;2) vs. 3(3;3)), control (2(2;3) vs. 4(4;4)) subscales and MBT (4.1(4;4.3) vs. 4.6(4.4;4.8)). The multiple linear regression showed a strong associations between MT results and outcome (r = 0.89), MBT (r = 0.84) and CMJ (r = 0.73). Conclusions The findings suggest that MT will be more predictive of performance in those sports and in the outcome of competition. PMID:27625755

The prevalence of low serum zinc and copper levels and dietary habits associated with serum zinc and copper in 12- to 36-month-old children from low-income families at risk for iron deficiency.

PubMed

Schneider, Julie M; Fujii, Mary L; Lamp, Catherine L; Lönnerdal, Bo; Zidenberg-Cherr, Sheri

2007-11-01

Iron and zinc share common food sources, and children at risk of iron deficiency may also develop zinc deficiency. We determined the prevalence of zinc and copper deficiency and examined factors associated with serum zinc and copper in young children from low-income families at risk of iron deficiency. A cross-sectional study design was used to assess serum zinc and copper, along with an interview-assisted survey to assess factors associated with serum zinc and copper in a convenience sample. Participants were 435 children aged 12 to 36 months recruited from select clinics of the Special Supplemental Nutrition Program for Women, Infants, and Children in Contra Costa and Tulare Counties, California. Frequencies were used to report prevalence. Multiple linear regressions were conducted to examine factors associated with serum zinc and copper, controlling for age, sex, and ethnicity. The prevalence of low serum zinc level (<70 microg/dL [<10.7 micromol/L]) was 42.8%, and low serum copper level (<90 microg/dL [<14.2 micromol/L]) was <1%. Mean+/-standard deviation of serum copper was 150+/-22 microg/dL (23.6+/-3.5 micromol/L) and 140+/-24 microg/dL (22.1+/-3.8 micromol/L) for anemic and non-anemic children, respectively (t test, P=0.026). In multiple linear regression consumption of sweetened beverages was negatively associated with serum zinc level, and consumption of >15 g/day meat was positively associated with serum zinc level, whereas current consumption of breast milk and >15 g/day beans were positively associated with serum copper level. The prevalence of low serum zinc concentration in the sample was high, and warrants further investigation amongst vulnerable populations.

Circulating Zinc-α2-glycoprotein levels and Insulin Resistance in Polycystic Ovary Syndrome

PubMed Central

Lai, Yerui; Chen, Jinhua; Li, Ling; Yin, Jingxia; He, Junying; Yang, Mengliu; Jia, Yanjun; Liu, Dongfang; Liu, Hua; Liao, Yong; Yang, Gangyi

2016-01-01

The aim of study was to assess the relationship between zinc-α2-glycoprotein (ZAG) and androgen excess with insulin resistance in polycystic ovary syndrome (PCOS) women. 99 PCOS women and 100 healthy controls were recruited. Euglycemic-hyperinsulinemic clamp (EHC) was preformed to assess their insulin sensitivity. Circulating ZAG was determined with an ELISA kit. In healthy subjects, circulating ZAG levels exhibited a characteristic diurnal rhythm in humans, with a major nocturnal rise occurring between midnight and early morning. Circulating ZAG and M-value were much lower in PCOS women than in the controls. In all population, overweight/obese subjects had significantly lower circulating ZAG levels than lean individuals. Multiple linear regression analysis revealed that only M-value and the area under the curve for glucose were independently related factors to circulating ZAG in PCOS women. Multivariate logistic regression analysis showed that circulating ZAG was significantly associated with PCOS even after controlling for anthropometric variables, blood pressure, lipid profile and hormone levels. The PCOS women with high ZAG had fewer MetS, IGT and polycystic ovaries as compared with the low ZAG PCOS women. Taken together, circulating ZAG levels are reduced in women with PCOS and ZAG may be a cytokine associated with insulin resistance in PCOS women. PMID:27180914

Effect of Air Pollution on Exacerbations of Bronchiectasis in Badalona, Spain, 2008-2016.

PubMed

Garcia-Olivé, Ignasi; Stojanovic, Zoran; Radua, Joaquim; Rodriguez-Pons, Laura; Martinez-Rivera, Carlos; Ruiz Manzano, Juan

2018-05-17

Air pollution has been widely associated with respiratory diseases. Nevertheless, the association between air pollution and exacerbations of bronchiectasis has been less studied. To analyze the effect of air pollution on exacerbations of bronchiectasis. This was a retrospective observational study conducted in Badalona. The number of daily hospital admissions and emergency room visits related to exacerbation of bronchiectasis (ICD-9 code 494.1) between 2008 and 2016 was obtained. We used simple Poisson regressions to test the effects of daily mean temperature, SO2, NO2, CO, and PM10 levels on bronchiectasis-related emergencies and hospitalizations on the same day and 1-4 days after. All p values were corrected for multiple comparisons. SO2 was significantly associated with an increase in the number of hospitalizations (lags 0, 1, 2, and 3). None of these associations remained significant after correcting for multiple comparisons. The number of emergency room visits was associated with higher levels of SO2 (lags 0-4). After correcting for multiple comparisons, the association between emergency room visits and SO2 levels was statistically significant for lag 0 (p = 0.043), lag 1 (p = 0.018), and lag 3 (p = 0.050). The number of emergency room visits for exacerbation of bronchiectasis is associated with higher levels of SO2. © 2018 S. Karger AG, Basel.

Is It the Intervention or the Students? Using Linear Regression to Control for Student Characteristics in Undergraduate STEM Education Research

PubMed Central

Theobald, Roddy; Freeman, Scott

2014-01-01

Although researchers in undergraduate science, technology, engineering, and mathematics education are currently using several methods to analyze learning gains from pre- and posttest data, the most commonly used approaches have significant shortcomings. Chief among these is the inability to distinguish whether differences in learning gains are due to the effect of an instructional intervention or to differences in student characteristics when students cannot be assigned to control and treatment groups at random. Using pre- and posttest scores from an introductory biology course, we illustrate how the methods currently in wide use can lead to erroneous conclusions, and how multiple linear regression offers an effective framework for distinguishing the impact of an instructional intervention from the impact of student characteristics on test score gains. In general, we recommend that researchers always use student-level regression models that control for possible differences in student ability and preparation to estimate the effect of any nonrandomized instructional intervention on student performance. PMID:24591502

Adulteration of Argentinean milk fats with animal fats: Detection by fatty acids analysis and multivariate regression techniques.

PubMed

Rebechi, S R; Vélez, M A; Vaira, S; Perotti, M C

2016-02-01

The aims of the present study were to test the accuracy of the fatty acid ratios established by the Argentinean Legislation to detect adulterations of milk fat with animal fats and to propose a regression model suitable to evaluate these adulterations. For this purpose, 70 milk fat, 10 tallow and 7 lard fat samples were collected and analyzed by gas chromatography. Data was utilized to simulate arithmetically adulterated milk fat samples at 0%, 2%, 5%, 10% and 15%, for both animal fats. The fatty acids ratios failed to distinguish adulterated milk fats containing less than 15% of tallow or lard. For each adulterant, Multiple Linear Regression (MLR) was applied, and a model was chosen and validated. For that, calibration and validation matrices were constructed employing genuine and adulterated milk fat samples. The models were able to detect adulterations of milk fat at levels greater than 10% for tallow and 5% for lard. Copyright © 2015 Elsevier Ltd. All rights reserved.

Is it the intervention or the students? using linear regression to control for student characteristics in undergraduate STEM education research.

PubMed

Theobald, Roddy; Freeman, Scott

2014-01-01

Although researchers in undergraduate science, technology, engineering, and mathematics education are currently using several methods to analyze learning gains from pre- and posttest data, the most commonly used approaches have significant shortcomings. Chief among these is the inability to distinguish whether differences in learning gains are due to the effect of an instructional intervention or to differences in student characteristics when students cannot be assigned to control and treatment groups at random. Using pre- and posttest scores from an introductory biology course, we illustrate how the methods currently in wide use can lead to erroneous conclusions, and how multiple linear regression offers an effective framework for distinguishing the impact of an instructional intervention from the impact of student characteristics on test score gains. In general, we recommend that researchers always use student-level regression models that control for possible differences in student ability and preparation to estimate the effect of any nonrandomized instructional intervention on student performance.

Multiple metals predict prolactin and thyrotropin (TSH) levels in men

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

Meeker, John D., E-mail: meekerj@umich.edu; Rossano, Mary G.; Protas, Bridget

2009-10-15

Exposure to a number of metals can affect neuroendocrine and thyroid signaling, which can result in adverse effects on development, behavior, metabolism, reproduction, and other functions. The present study assessed the relationship between metal concentrations in blood and serum prolactin (PRL) and thyrotropin (TSH) levels, markers of dopaminergic, and thyroid function, respectively, among men participating in a study of environmental influences on male reproductive health. Blood samples from 219 men were analyzed for concentrations of 11 metals and serum levels of PRL and TSH. In multiple linear regression models adjusted for age, BMI and smoking, PRL was inversely associated withmore » arsenic, cadmium, copper, lead, manganese, molybdenum, and zinc, but positively associated with chromium. Several of these associations (Cd, Pb, Mo) are consistent with limited studies in humans or animals, and a number of the relationships (Cr, Cu, Pb, Mo) remained when additionally considering multiple metals in the model. Lead and copper were associated with non-monotonic decrease in TSH, while arsenic was associated with a dose-dependent increase in TSH. For arsenic these findings were consistent with recent experimental studies where arsenic inhibited enzymes involved in thyroid hormone synthesis and signaling. More research is needed for a better understanding of the role of metals in neuroendocrine and thyroid function and related health implications.« less

A principal component regression model to forecast airborne concentration of Cupressaceae pollen in the city of Granada (SE Spain), during 1995-2006.

PubMed

Ocaña-Peinado, Francisco M; Valderrama, Mariano J; Bouzas, Paula R

2013-05-01

The problem of developing a 2-week-on ahead forecast of atmospheric cypress pollen levels is tackled in this paper by developing a principal component multiple regression model involving several climatic variables. The efficacy of the proposed model is validated by means of an application to real data of Cupressaceae pollen concentration in the city of Granada (southeast of Spain). The model was applied to data from 11 consecutive years (1995-2005), with 2006 being used to validate the forecasts. Based on the work of different authors, factors as temperature, humidity, hours of sun and wind speed were incorporated in the model. This methodology explains approximately 75-80% of the variability in the airborne Cupressaceae pollen concentration.

Monitoring heavy metal Cr in soil based on hyperspectral data using regression analysis

NASA Astrophysics Data System (ADS)

Zhang, Ningyu; Xu, Fuyun; Zhuang, Shidong; He, Changwei

2016-10-01

Heavy metal pollution in soils is one of the most critical problems in the global ecology and environment safety nowadays. Hyperspectral remote sensing and its application is capable of high speed, low cost, less risk and less damage, and provides a good method for detecting heavy metals in soil. This paper proposed a new idea of applying regression analysis of stepwise multiple regression between the spectral data and monitoring the amount of heavy metal Cr by sample points in soil for environmental protection. In the measurement, a FieldSpec HandHeld spectroradiometer is used to collect reflectance spectra of sample points over the wavelength range of 325-1075 nm. Then the spectral data measured by the spectroradiometer is preprocessed to reduced the influence of the external factors, and the preprocessed methods include first-order differential equation, second-order differential equation and continuum removal method. The algorithms of stepwise multiple regression are established accordingly, and the accuracy of each equation is tested. The results showed that the accuracy of first-order differential equation works best, which makes it feasible to predict the content of heavy metal Cr by using stepwise multiple regression.

Inferential Processing among Adequate and Struggling Adolescent Comprehenders and Relations to Reading Comprehension

PubMed Central

Barth, Amy E.; Barnes, Marcia; Francis, David J.; Vaughn, Sharon; York, Mary

2015-01-01

Separate mixed model analyses of variance (ANOVA) were conducted to examine the effect of textual distance on the accuracy and speed of text consistency judgments among adequate and struggling comprehenders across grades 6–12 (n = 1203). Multiple regressions examined whether accuracy in text consistency judgments uniquely accounted for variance in comprehension. Results suggest that there is considerable growth across the middle and high school years, particularly for adequate comprehenders in those text integration processes that maintain local coherence. Accuracy in text consistency judgments accounted for significant unique variance for passage-level, but not sentence-level comprehension, particularly for adequate comprehenders. PMID:26166946

Forecasting USAF JP-8 Fuel Needs

DTIC Science & Technology

2009-03-01

versus complex ones. When we consider long -term forecasts, 5-years in this case, multiple regression outperforms ANN modeling within the specified...with more simple and easy-to-implement methods, versus complex ones. When we consider long -term 5-year forecasts, our multiple regression model...effort. The insight and experience was certainly appreciated. Special thanks to my Turkish peers for their continuous support and help during this long

The Overall Odds Ratio as an Intuitive Effect Size Index for Multiple Logistic Regression: Examination of Further Refinements

ERIC Educational Resources Information Center

Le, Huy; Marcus, Justin

2012-01-01

This study used Monte Carlo simulation to examine the properties of the overall odds ratio (OOR), which was recently introduced as an index for overall effect size in multiple logistic regression. It was found that the OOR was relatively independent of study base rate and performed better than most commonly used R-square analogs in indexing model…

Future Performance Trend Indicators: A Current Value Approach to Human Resources Accounting. Report III. Multivariate Predictions of Organizational Performance Across Time.

ERIC Educational Resources Information Center

Pecorella, Patricia A.; Bowers, David G.

Multiple regression in a double cross-validated design was used to predict two performance measures (total variable expense and absence rate) by multi-month period in five industrial firms. The regressions do cross-validate, and produce multiple coefficients which display both concurrent and predictive effects, peaking 18 months to two years…

Using multiple calibration sets to improve the quantitative accuracy of partial least squares (PLS) regression on open-path fourier transform infrared (OP/FT-IR) spectra of ammonia over wide concentration ranges

USDA-ARS?s Scientific Manuscript database

A technique of using multiple calibration sets in partial least squares regression (PLS) was proposed to improve the quantitative determination of ammonia from open-path Fourier transform infrared spectra. The spectra were measured near animal farms, and the path-integrated concentration of ammonia...

FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors.

PubMed

Lorenzo-Seva, Urbano; Ferrando, Pere J

2011-03-01

We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.

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…

Agent Orange exposure and prevalence of self-reported diseases in Korean Vietnam veterans.

PubMed

Yi, Sang-Wook; Ohrr, Heechoul; Hong, Jae-Seok; Yi, Jee-Jeon

2013-09-01

The aim of this study was to evaluate the association between Agent Orange exposure and self-reported diseases in Korean Vietnam veterans. A postal survey of 114 562 Vietnam veterans was conducted. The perceived exposure to Agent Orange was assessed by a 6-item questionnaire. Two proximity-based Agent Orange exposure indices were constructed using division/brigade-level and battalion/company-level unit information. Adjusted odds ratios (ORs) for age and other confounders were calculated using a logistic regression model. The prevalence of all self-reported diseases showed monotonically increasing trends as the levels of perceived self-reported exposure increased. The ORs for colon cancer (OR, 1.13), leukemia (OR, 1.56), hypertension (OR, 1.03), peripheral vasculopathy (OR, 1.07), enterocolitis (OR, 1.07), peripheral neuropathy (OR, 1.07), multiple nerve palsy (OR, 1.14), multiple sclerosis (OR, 1.24), skin diseases (OR, 1.05), psychotic diseases (OR, 1.07) and lipidemia (OR, 1.05) were significantly elevated for the high exposure group in the division/brigade-level proximity-based exposure analysis, compared to the low exposure group. The ORs for cerebral infarction (OR, 1.08), chronic bronchitis (OR, 1.05), multiple nerve palsy (OR, 1.07), multiple sclerosis (OR, 1.16), skin diseases (OR, 1.05), and lipidemia (OR, 1.05) were significantly elevated for the high exposure group in the battalion/company-level analysis. Korean Vietnam veterans with high exposure to Agent Orange experienced a higher prevalence of several self-reported chronic diseases compared to those with low exposure by proximity-based exposure assessment. The strong positive associations between perceived self-reported exposure and all self-reported diseases should be evaluated with discretion because the likelihood of reporting diseases was directly related to the perceived intensity of Agent Orange exposure.

Evaluation of the comprehensive palatability of Japanese sake paired with dishes by multiple regression analysis based on subdomains.

PubMed

Nakamura, Ryo; Nakano, Kumiko; Tamura, Hiroyasu; Mizunuma, Masaki; Fushiki, Tohru; Hirata, Dai

2017-08-01

Many factors contribute to palatability. In order to evaluate the palatability of Japanese alcohol sake paired with certain dishes by integrating multiple factors, here we applied an evaluation method previously reported for palatability of cheese by multiple regression analysis based on 3 subdomain factors (rewarding, cultural, and informational). We asked 94 Japanese participants/subjects to evaluate the palatability of sake (1st evaluation/E1 for the first cup, 2nd/E2 and 3rd/E3 for the palatability with aftertaste/afterglow of certain dishes) and to respond to a questionnaire related to 3 subdomains. In E1, 3 factors were extracted by a factor analysis, and the subsequent multiple regression analyses indicated that the palatability of sake was interpreted by mainly the rewarding. Further, the results of attribution-dissections in E1 indicated that 2 factors (rewarding and informational) contributed to the palatability. Finally, our results indicated that the palatability of sake was influenced by the dish eaten just before drinking.

The effects of community-wide dissemination of information on perceptions of palliative care, knowledge about opioids, and sense of security among cancer patients, their families, and the general public.

PubMed

Akiyama, Miki; Hirai, Kei; Takebayashi, Toru; Morita, Tatsuya; Miyashita, Mitsunori; Takeuchi, Ayano; Yamagishi, Akemi; Kinoshita, Hiroya; Shirahige, Yutaka; Eguchi, Kenji

2016-01-01

Prejudices against palliative care are a potential barrier to quality end-of-life care. There have been few large-scale community-wide interventions to distribute appropriate information about palliative care, and no studies have investigated their impact on cancer patients, their families, and the general public. Thus, we conducted a 3-year community intervention and evaluated the effects of distributing such information at the community level, and explored associations among levels of exposure, perceptions, knowledge, and the sense of security achieved. Over a period of 3 years, we provided flyers, booklets, posters, and public lectures about palliative care in four regions of Japan, and carried out pre- and post-intervention surveys with repeated cross-sectional samplings of cancer patients (pre 859, post 857), bereaved family members (1110, 1137), and the general public (3984, 1435). The levels of exposure to the provided information were measured by a multiple-choice questionnaire after intervention. Multiple logistic regression analyses were used to estimate multivariable-adjusted odds ratios (ORs) for perceptions of palliative care, knowledge about opioids, and sense of security among the exposure groups. Overall perceptions of palliative care, opioids, and receiving care at home improved significantly among the general public and families, but not among the patients at the community level. However, multiple regression revealed that patients of extensive exposure category had significantly more positive perceptions of palliative care to those of non-exposure category (p = 0.02). The sense of security regarding cancer care of all patients, family members, and the general public improved. Among others, the respondents who reported extensive exposure in the general public and family members scored significantly higher sense of security. Our findings indicate that providing palliative care information via small media and lectures in the community is effective in improving perceptions of palliative care and knowledge about opioids among the community dwellers, especially for caregivers of the patients. The acquisition of adequate knowledge about palliative care from various information sources may improve people's sense of security regarding cancer.

Error Rates Resulting From Anemia Can Be Corrected in Multiple Commonly Used Point of Care Glucometers

DTIC Science & Technology

2008-01-01

strategies, increasing the prevalence of both hypoglycemia and anemia in the ICU.14–20 The change in allogeneic blood transfusion practices occurred in...measurements in samples with low HCT levels.4,5,7,8,12 The error occurs because de- creased red blood cell causes less displacement of plasma, resulting...Nonlinear component regression was performed be- cause HCT has a nonlinear effect on accuracy of POC glucometers. A dual parameter correction factor was

Ultraviolet B Irradiance and Vitamin D Status are Inversely Associated With Incidence Rates of Pancreatic Cancer Worldwide

DTIC Science & Technology

2010-01-01

exposure of most of the skin to solar irradiance, especially Muslim countries. In these countries, 25(OH)D levels, partic- ularly in women wearing a hijab ...exceptions. Key Words: pancreatic neoplasms, incidence, vitamin D, alcohol, smoking, multiple regression (Pancreas 2010;00: 00Y00) A pproximately...The possibility that vita- min D might play a role in the etiology of pancreatic cancer was raised by studies showing that populations living at

The utility of gravity and water-level monitoring at alluvial aquifer wells in southern Arizona

USGS Publications Warehouse

Pool, D.R.

2008-01-01

Coincident monitoring of gravity and water levels at 39 wells in southern Arizona indicate that water-level change might not be a reliable indicator of aquifer-storage change for alluvial aquifer systems. One reason is that water levels in wells that are screened across single or multiple aquifers might not represent the hydraulic head and storage change in a local unconfined aquifer. Gravity estimates of aquifer-storage change can be approximated as a one-dimensional feature except near some withdrawal wells and recharge sources. The aquifer storage coefficient is estimated by the linear regression slope of storage change (estimated using gravity methods) and water-level change. Nonaquifer storage change that does not percolate to the aquifer can be significant, greater than 3 ??Gal, when water is held in the root zone during brief periods following extreme rates of precipitation. Monitor-ing of storage change using gravity methods at wells also can improve understanding of local hydrogeologic conditions. In the study area, confined aquifer conditions are likely at three wells where large water-level variations were accompanied by little gravity change. Unconfined conditions were indicated at 15 wells where significant water-level and gravity change were positively linearly correlated. Good positive linear correlations resulted in extremely large specific-yield values, greater than 0.35, at seven wells where it is likely that significant ephemeral streamflow infiltration resulted in unsaturated storage change. Poor or negative linear correlations indicate the occurrence of confined, multiple, or perched aquifers. Monitoring of a multiple compressible aquifer system at one well resulted in negative correlation of rising water levels and subsidence-corrected gravity change, which suggests that water-level trends at the well are not a good indicatior of overall storage change. ?? 2008 Society of Exploration Geophysicists. All rights reserved.

Correlation and simple linear regression.

PubMed

Eberly, Lynn E

2007-01-01

This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression.

Evaluating the performance of different predictor strategies in regression-based downscaling with a focus on glacierized mountain environments

NASA Astrophysics Data System (ADS)

Hofer, Marlis; Nemec, Johanna

2016-04-01

This study presents first steps towards verifying the hypothesis that uncertainty in global and regional glacier mass simulations can be reduced considerably by reducing the uncertainty in the high-resolution atmospheric input data. To this aim, we systematically explore the potential of different predictor strategies for improving the performance of regression-based downscaling approaches. The investigated local-scale target variables are precipitation, air temperature, wind speed, relative humidity and global radiation, all at a daily time scale. Observations of these target variables are assessed from three sites in geo-environmentally and climatologically very distinct settings, all within highly complex topography and in the close proximity to mountain glaciers: (1) the Vernagtbach station in the Northern European Alps (VERNAGT), (2) the Artesonraju measuring site in the tropical South American Andes (ARTESON), and (3) the Brewster measuring site in the Southern Alps of New Zealand (BREWSTER). As the large-scale predictors, ERA interim reanalysis data are used. In the applied downscaling model training and evaluation procedures, particular emphasis is put on appropriately accounting for the pitfalls of limited and/or patchy observation records that are usually the only (if at all) available data from the glacierized mountain sites. Generalized linear models and beta regression are investigated as alternatives to ordinary least squares regression for the non-Gaussian target variables. By analyzing results for the three different sites, five predictands and for different times of the year, we look for systematic improvements in the downscaling models' skill specifically obtained by (i) using predictor data at the optimum scale rather than the minimum scale of the reanalysis data, (ii) identifying the optimum predictor allocation in the vertical, and (iii) considering multiple (variable, level and/or grid point) predictor options combined with state-of-art empirical feature selection tools. First results show that in particular for air temperature, those downscaling models based on direct predictor selection show comparative skill like those models based on multiple predictors. For all other target variables, however, multiple predictor approaches can considerably outperform those models based on single predictors. Including multiple variable types emerges as the most promising predictor option (in particular for wind speed at all sites), even if the same predictor set is used across the different cases.

Noise in restaurants: levels and mathematical model.

PubMed

To, Wai Ming; Chung, Andy

2014-01-01

Noise affects the dining atmosphere and is an occupational hazard to restaurant service employees worldwide. This paper examines the levels of noise in dining areas during peak hours in different types of restaurants in Hong Kong SAR, China. A mathematical model that describes the noise level in a restaurant is presented. The 1-h equivalent continuous noise level (L(eq,1-h)) was measured using a Type-1 precision integral sound level meter while the occupancy density, the floor area of the dining area, and the ceiling height of each of the surveyed restaurants were recorded. It was found that the measured noise levels using Leq,1-h ranged from 67.6 to 79.3 dBA in Chinese restaurants, from 69.1 to 79.1 dBA in fast food restaurants, and from 66.7 to 82.6 dBA in Western restaurants. Results of the analysis of variance show that there were no significant differences between means of the measured noise levels among different types of restaurants. A stepwise multiple regression analysis was employed to determine the relationships between geometrical and operational parameters and the measured noise levels. Results of the regression analysis show that the measured noise levels depended on the levels of occupancy density only. By reconciling the measured noise levels and the mathematical model, it was found that people in restaurants increased their voice levels when the occupancy density increased. Nevertheless, the maximum measured hourly noise level indicated that the noise exposure experienced by restaurant service employees was below the regulated daily noise exposure value level of 85 dBA.

Perioperative factors associated with pressure ulcer development after major surgery.

PubMed

Kim, Jeong Min; Lee, Hyunjeong; Ha, Taehoon; Na, Sungwon

2018-02-01

Postoperative pressure ulcers are important indicators of perioperative care quality, and are serious and expensive complications during critical care. This study aimed to identify perioperative risk factors for postoperative pressure ulcers. This retrospective case-control study evaluated 2,498 patients who underwent major surgery. Forty-three patients developed postoperative pressure ulcers and were matched to 86 control patients based on age, sex, surgery, and comorbidities. The pressure ulcer group had lower baseline hemoglobin and albumin levels, compared to the control group. The pressure ulcer group also had higher values for lactate levels, blood loss, and number of packed red blood cell ( p RBC) units. Univariate analysis revealed that pressure ulcer development was associated with preoperative hemoglobin levels, albumin levels, lactate levels, intraoperative blood loss, number of p RBC units, Acute Physiologic and Chronic Health Evaluation II score, Braden scale score, postoperative ventilator care, and patient restraint. In the multiple logistic regression analysis, only preoperative low albumin levels (odds ratio [OR]: 0.21, 95% CI: 0.05-0.82; P < 0.05) and high lactate levels (OR: 1.70, 95% CI: 1.07-2.71; P < 0.05) were independently associated with pressure ulcer development. A receiver operating characteristic curve was used to assess the predictive power of the logistic regression model, and the area under the curve was 0.88 (95% CI: 0.79-0.97; P < 0.001). The present study revealed that preoperative low albumin levels and high lactate levels were significantly associated with pressure ulcer development after surgery.

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.

Genetic variations in the serotonergic system contribute to amygdala volume in humans.

PubMed

Li, Jin; Chen, Chunhui; Wu, Karen; Zhang, Mingxia; Zhu, Bi; Chen, Chuansheng; Moyzis, Robert K; Dong, Qi

2015-01-01

The amygdala plays a critical role in emotion processing and psychiatric disorders associated with emotion dysfunction. Accumulating evidence suggests that amygdala structure is modulated by serotonin-related genes. However, there is a gap between the small contributions of single loci (less than 1%) and the reported 63-65% heritability of amygdala structure. To understand the "missing heritability," we systematically explored the contribution of serotonin genes on amygdala structure at the gene set level. The present study of 417 healthy Chinese volunteers examined 129 representative polymorphisms in genes from multiple biological mechanisms in the regulation of serotonin neurotransmission. A system-level approach using multiple regression analyses identified that nine SNPs collectively accounted for approximately 8% of the variance in amygdala volume. Permutation analyses showed that the probability of obtaining these findings by chance was low (p = 0.043, permuted for 1000 times). Findings showed that serotonin genes contribute moderately to individual differences in amygdala volume in a healthy Chinese sample. These results indicate that the system-level approach can help us to understand the genetic basis of a complex trait such as amygdala structure.

Multiple injections of electroporated autologous T cells expressing a chimeric antigen receptor mediate regression of human disseminated tumor.

PubMed

Zhao, Yangbing; Moon, Edmund; Carpenito, Carmine; Paulos, Chrystal M; Liu, Xiaojun; Brennan, Andrea L; Chew, Anne; Carroll, Richard G; Scholler, John; Levine, Bruce L; Albelda, Steven M; June, Carl H

2010-11-15

Redirecting T lymphocyte antigen specificity by gene transfer can provide large numbers of tumor-reactive T lymphocytes for adoptive immunotherapy. However, safety concerns associated with viral vector production have limited clinical application of T cells expressing chimeric antigen receptors (CAR). T lymphocytes can be gene modified by RNA electroporation without integration-associated safety concerns. To establish a safe platform for adoptive immunotherapy, we first optimized the vector backbone for RNA in vitro transcription to achieve high-level transgene expression. CAR expression and function of RNA-electroporated T cells could be detected up to a week after electroporation. Multiple injections of RNA CAR-electroporated T cells mediated regression of large vascularized flank mesothelioma tumors in NOD/scid/γc(-/-) mice. Dramatic tumor reduction also occurred when the preexisting intraperitoneal human-derived tumors, which had been growing in vivo for >50 days, were treated by multiple injections of autologous human T cells electroporated with anti-mesothelin CAR mRNA. This is the first report using matched patient tumor and lymphocytes showing that autologous T cells from cancer patients can be engineered to provide an effective therapy for a disseminated tumor in a robust preclinical model. Multiple injections of RNA-engineered T cells are a novel approach for adoptive cell transfer, providing flexible platform for the treatment of cancer that may complement the use of retroviral and lentiviral engineered T cells. This approach may increase the therapeutic index of T cells engineered to express powerful activation domains without the associated safety concerns of integrating viral vectors. Copyright © 2010 AACR.

Multiple injections of electroporated autologous T cells expressing a chimeric antigen receptor mediate regression of human disseminated tumor

PubMed Central

Zhao, Yangbing; Moon, Edmund; Carpenito, Carmine; Paulos, Chrystal M.; Liu, Xiaojun; Brennan, Andrea L; Chew, Anne; Carroll, Richard G.; Scholler, John; Levine, Bruce L.; Albelda, Steven M.; June, Carl H.

2010-01-01

Redirecting T lymphocyte antigen specificity by gene transfer can provide large numbers of tumor reactive T lymphocytes for adoptive immunotherapy. However, safety concerns associated with viral vector production have limited clinical application of T cells expressing chimeric antigen receptors (CARs). T lymphocytes can be gene modified by RNA electroporation without integration-associated safety concerns. To establish a safe platform for adoptive immunotherapy, we first optimized the vector backbone for RNA in vitro transcription to achieve high level transgene expression. CAR expression and function of RNA-electroporated T cells could be detected up to a week post electroporation. Multiple injections of RNA CAR electroporated T cells mediated regression of large vascularized flank mesothelioma tumors in NOD/scid/γc(−/−) mice. Dramatic tumor reduction also occurred when the pre-existing intraperitoneal human-derived tumors, that had been growing in vivo for over 50 days, were treated by multiple injections of autologous human T cells electroporated with anti-mesothelin CAR mRNA. This is the first report using matched patient tumor and lymphocytes demonstrating that autologous T cells from cancer patients can be engineered to provide an effective therapy for a disseminated tumor in a robust preclinical model. Multiple injections of RNA engineered T cells are a novel approach for adoptive cell transfer, providing flexible platform for the treatment of cancer that may complement the use of retroviral and lentiviral engineered T cells. This approach may increase the therapeutic index of T cells engineered to express powerful activation domains without the associated safety concerns of integrating viral vectors. PMID:20926399

An Update of the Bodeker Scientific Vertically Resolved, Global, Gap-Free Ozone Database

NASA Astrophysics Data System (ADS)

Kremser, S.; Bodeker, G. E.; Lewis, J.; Hassler, B.

2016-12-01

High vertical resolution ozone measurements from multiple satellite-based instruments have been merged with measurements from the global ozonesonde network to calculate monthly mean ozone values in 5º latitude zones. Ozone number densities and ozone mixing ratios are provided on 70 altitude levels (1 to 70 km) and on 70 pressure levels spaced approximately 1 km apart (878.4 hPa to 0.046 hPa). These data are sparse and do not cover the entire globe or altitude range. To provide a gap-free database, a least squares regression model is fitted to these data and then evaluated globally. By applying a single fit at each level, and using the approach of allowing the regression fits to change only slightly from one level to the next, the regression is less sensitive to measurement anomalies at individual stations or to individual satellite-based instruments. Particular attention is paid to ensuring that the low ozone abundances in the polar regions are captured. This presentation reports on updates to an earlier version of the vertically resolved ozone database, including the incorporation of new ozone measurements and new techniques for combining the data. Compared to previous versions of the database, particular attention is paid to avoiding spatial and temporal sampling biases and tracing uncertainties through to the final product. This updated database, developed within the New Zealand Deep South National Science Challenge, is suitable for assessing ozone fields from chemistry-climate model simulations or for providing the ozone boundary conditions for global climate model simulations that do not treat stratospheric chemistry interactively.

Neighborhood education inequality and drinking behavior.

PubMed

Lê, Félice; Ahern, Jennifer; Galea, Sandro

2010-11-01

The neighborhood distribution of education (education inequality) may influence substance use among neighborhood residents. Using data from the New York Social Environment Study (conducted in 2005; n=4000), we examined the associations of neighborhood education inequality (measured using Gini coefficients of education) with alcohol use prevalence and levels of alcohol consumption among alcohol users. Analyses were adjusted for neighborhood education level, income level and income inequality, as well as for individual demographic and socioeconomic characteristics and history of drinking prior to residence in the current neighborhood. Neighborhood social norms about drinking were examined as a possible mediator. In adjusted generalized estimating equation regression models, one-standard-deviation-higher education inequality was associated with 1.18 times higher odds of alcohol use (logistic regression odds ratio=1.18, 95% confidence interval 1.08-1.30) but 0.79 times lower average daily alcohol consumption among alcohol users (Poisson regression relative rate=0.79, 95% confidence interval 0.68-0.92). The results tended to differ in magnitude depending on respondents' individual educational levels. There was no evidence that these associations were mediated by social drinking norms, although norms did vary with education inequality. Our results provide further evidence of a relation between education inequality and drinking behavior while illustrating the importance of considering different drinking outcomes and heterogeneity between neighborhood subgroups. Future research could fruitfully consider other potential mechanisms, such as alcohol availability or the role of stress; research that considers multiple mechanisms and their combined effects may be most informative. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Assessing the impact of local meteorological variables on surface ozone in Hong Kong during 2000-2015 using quantile and multiple line regression models

NASA Astrophysics Data System (ADS)

Zhao, Wei; Fan, Shaojia; Guo, Hai; Gao, Bo; Sun, Jiaren; Chen, Laiguo

2016-11-01

The quantile regression (QR) method has been increasingly introduced to atmospheric environmental studies to explore the non-linear relationship between local meteorological conditions and ozone mixing ratios. In this study, we applied QR for the first time, together with multiple linear regression (MLR), to analyze the dominant meteorological parameters influencing the mean, 10th percentile, 90th percentile and 99th percentile of maximum daily 8-h average (MDA8) ozone concentrations in 2000-2015 in Hong Kong. The dominance analysis (DA) was used to assess the relative importance of meteorological variables in the regression models. Results showed that the MLR models worked better at suburban and rural sites than at urban sites, and worked better in winter than in summer. QR models performed better in summer for 99th and 90th percentiles and performed better in autumn and winter for 10th percentile. And QR models also performed better in suburban and rural areas for 10th percentile. The top 3 dominant variables associated with MDA8 ozone concentrations, changing with seasons and regions, were frequently associated with the six meteorological parameters: boundary layer height, humidity, wind direction, surface solar radiation, total cloud cover and sea level pressure. Temperature rarely became a significant variable in any season, which could partly explain the peak of monthly average ozone concentrations in October in Hong Kong. And we found the effect of solar radiation would be enhanced during extremely ozone pollution episodes (i.e., the 99th percentile). Finally, meteorological effects on MDA8 ozone had no significant changes before and after the 2010 Asian Games.

Optimum pelvic incidence minus lumbar lordosis value can be determined by individual pelvic incidence.

PubMed

Inami, Satoshi; Moridaira, Hiroshi; Takeuchi, Daisaku; Shiba, Yo; Nohara, Yutaka; Taneichi, Hiroshi

2016-11-01

Adult spinal deformity (ASD) classification showing that ideal pelvic incidence minus lumbar lordosis (PI-LL) value is within 10° has been received widely. But no study has focused on the optimum level of PI-LL value that reflects wide variety in PI among patients. This study was conducted to determine the optimum PI-LL value specific to an individual's PI in postoperative ASD patients. 48 postoperative ASD patients were recruited. Spino-pelvic parameters and Oswestry Disability Index (ODI) were measured at the final follow-up. Factors associated with good clinical results were determined by stepwise multiple regression model using the ODI. The patients with ODI under the 75th percentile cutoff were designated into the "good" health related quality of life (HRQOL) group. In this group, the relationship between the PI-LL and PI was assessed by regression analysis. Multiple regression analysis revealed PI-LL as significant parameters associated with ODI. Thirty-six patients with an ODI <22 points (75th percentile cutoff) were categorized into a good HRQOL group, and linear regression models demonstrated the following equation: PI-LL = 0.41PI-11.12 (r = 0.45, P = 0.0059). On the basis of this equation, in the patients with a PI = 50°, the PI-LL is 9°. Whereas in those with a PI = 30°, the optimum PI-LL is calculated to be as low as 1°. In those with a PI = 80°, PI-LL is estimated at 22°. Consequently, an optimum PI-LL is inconsistent in that it depends on the individual PI.

Weather Impact on Airport Arrival Meter Fix Throughput

NASA Technical Reports Server (NTRS)

Wang, Yao

2017-01-01

Time-based flow management provides arrival aircraft schedules based on arrival airport conditions, airport capacity, required spacing, and weather conditions. In order to meet a scheduled time at which arrival aircraft can cross an airport arrival meter fix prior to entering the airport terminal airspace, air traffic controllers make regulations on air traffic. Severe weather may create an airport arrival bottleneck if one or more of airport arrival meter fixes are partially or completely blocked by the weather and the arrival demand has not been reduced accordingly. Under these conditions, aircraft are frequently being put in holding patterns until they can be rerouted. A model that predicts the weather impacted meter fix throughput may help air traffic controllers direct arrival flows into the airport more efficiently, minimizing arrival meter fix congestion. This paper presents an analysis of air traffic flows across arrival meter fixes at the Newark Liberty International Airport (EWR). Several scenarios of weather impacted EWR arrival fix flows are described. Furthermore, multiple linear regression and regression tree ensemble learning approaches for translating multiple sector Weather Impacted Traffic Indexes (WITI) to EWR arrival meter fix throughputs are examined. These weather translation models are developed and validated using the EWR arrival flight and weather data for the period of April-September in 2014. This study also compares the performance of the regression tree ensemble with traditional multiple linear regression models for estimating the weather impacted throughputs at each of the EWR arrival meter fixes. For all meter fixes investigated, the results from the regression tree ensemble weather translation models show a stronger correlation between model outputs and observed meter fix throughputs than that produced from multiple linear regression method.

Practical Guidance for Conducting Mediation Analysis With Multiple Mediators Using Inverse Odds Ratio Weighting

PubMed Central

Nguyen, Quynh C.; Osypuk, Theresa L.; Schmidt, Nicole M.; Glymour, M. Maria; Tchetgen Tchetgen, Eric J.

2015-01-01

Despite the recent flourishing of mediation analysis techniques, many modern approaches are difficult to implement or applicable to only a restricted range of regression models. This report provides practical guidance for implementing a new technique utilizing inverse odds ratio weighting (IORW) to estimate natural direct and indirect effects for mediation analyses. IORW takes advantage of the odds ratio's invariance property and condenses information on the odds ratio for the relationship between the exposure (treatment) and multiple mediators, conditional on covariates, by regressing exposure on mediators and covariates. The inverse of the covariate-adjusted exposure-mediator odds ratio association is used to weight the primary analytical regression of the outcome on treatment. The treatment coefficient in such a weighted regression estimates the natural direct effect of treatment on the outcome, and indirect effects are identified by subtracting direct effects from total effects. Weighting renders treatment and mediators independent, thereby deactivating indirect pathways of the mediators. This new mediation technique accommodates multiple discrete or continuous mediators. IORW is easily implemented and is appropriate for any standard regression model, including quantile regression and survival analysis. An empirical example is given using data from the Moving to Opportunity (1994–2002) experiment, testing whether neighborhood context mediated the effects of a housing voucher program on obesity. Relevant Stata code (StataCorp LP, College Station, Texas) is provided. PMID:25693776

Structured association analysis leads to insight into Saccharomyces cerevisiae gene regulation by finding multiple contributing eQTL hotspots associated with functional gene modules.

PubMed

Curtis, Ross E; Kim, Seyoung; Woolford, John L; Xu, Wenjie; Xing, Eric P

2013-03-21

Association analysis using genome-wide expression quantitative trait locus (eQTL) data investigates the effect that genetic variation has on cellular pathways and leads to the discovery of candidate regulators. Traditional analysis of eQTL data via pairwise statistical significance tests or linear regression does not leverage the availability of the structural information of the transcriptome, such as presence of gene networks that reveal correlation and potentially regulatory relationships among the study genes. We employ a new eQTL mapping algorithm, GFlasso, which we have previously developed for sparse structured regression, to reanalyze a genome-wide yeast dataset. GFlasso fully takes into account the dependencies among expression traits to suppress false positives and to enhance the signal/noise ratio. Thus, GFlasso leverages the gene-interaction network to discover the pleiotropic effects of genetic loci that perturb the expression level of multiple (rather than individual) genes, which enables us to gain more power in detecting previously neglected signals that are marginally weak but pleiotropically significant. While eQTL hotspots in yeast have been reported previously as genomic regions controlling multiple genes, our analysis reveals additional novel eQTL hotspots and, more interestingly, uncovers groups of multiple contributing eQTL hotspots that affect the expression level of functional gene modules. To our knowledge, our study is the first to report this type of gene regulation stemming from multiple eQTL hotspots. Additionally, we report the results from in-depth bioinformatics analysis for three groups of these eQTL hotspots: ribosome biogenesis, telomere silencing, and retrotransposon biology. We suggest candidate regulators for the functional gene modules that map to each group of hotspots. Not only do we find that many of these candidate regulators contain mutations in the promoter and coding regions of the genes, in the case of the Ribi group, we provide experimental evidence suggesting that the identified candidates do regulate the target genes predicted by GFlasso. Thus, this structured association analysis of a yeast eQTL dataset via GFlasso, coupled with extensive bioinformatics analysis, discovers a novel regulation pattern between multiple eQTL hotspots and functional gene modules. Furthermore, this analysis demonstrates the potential of GFlasso as a powerful computational tool for eQTL studies that exploit the rich structural information among expression traits due to correlation, regulation, or other forms of biological dependencies.

Lithium and neuroleptics in combination: is there enhancement of neurotoxicity leading to permanent sequelae?

PubMed

Goldman, S A

1996-10-01

Neurotoxicity in relation to concomitant administration of lithium and neuroleptic drugs, particularly haloperidol, has been an ongoing issue. This study examined whether use of lithium with neuroleptic drugs enhances neurotoxicity leading to permanent sequelae. The Spontaneous Reporting System database of the United States Food and Drug Administration and extant literature were reviewed for spectrum cases of lithium/neuroleptic neurotoxicity. Groups taking lithium alone (Li), lithium/haloperidol (LiHal) and lithium/ nonhaloperidol neuroleptics (LiNeuro), each paired for recovery and sequelae, were established for 237 cases. Statistical analyses included pairwise comparisons of lithium levels using the Wilcoxon Rank Sum procedure and logistic regression to analyze the relationship between independent variables and development of sequelae. The Li and Li-Neuro groups showed significant statistical differences in median lithium levels between recovery and sequelae pairs, whereas the LiHal pair did not differ significantly. Lithium level was associated with sequelae development overall and within the Li and LiNeuro groups; no such association was evident in the LiHal group. On multivariable logistic regression analysis, lithium level and taking lithium/haloperidol were significant factors in the development of sequelae, with multiple possibly confounding factors (e.g., age, sex) not statistically significant. Multivariable logistic regression analyses with neuroleptic dose as five discrete dose ranges or actual dose did not show an association between development of sequelae and dose. Database limitations notwithstanding, the lack of apparent impact of serum lithium level on the development of sequelae in patients treated with haloperidol contrasts notably with results in the Li and LiNeuro groups. These findings may suggest a possible effect of pharmacodynamic factors in lithium/neuroleptic combination therapy.

A Statistical Multimodel Ensemble Approach to Improving Long-Range Forecasting in Pakistan

DTIC Science & Technology

2012-03-01

Impact of global warming on monsoon variability in Pakistan. J. Anim. Pl. Sci., 21, no. 1, 107–110. Gillies, S., T. Murphree, and D. Meyer, 2012...are generated by multiple regression models that relate globally distributed oceanic and atmospheric predictors to local predictands. The...generated by multiple regression models that relate globally distributed oceanic and atmospheric predictors to local predictands. The predictands are

Suppression Situations in Multiple Linear Regression

ERIC Educational Resources Information Center

Shieh, Gwowen

2006-01-01

This article proposes alternative expressions for the two most prevailing definitions of suppression without resorting to the standardized regression modeling. The formulation provides a simple basis for the examination of their relationship. For the two-predictor regression, the author demonstrates that the previous results in the literature are…

Reduction of shading-derived artifacts in skin chromophore imaging without measurements or assumptions about the shape of the subject

NASA Astrophysics Data System (ADS)

Yoshida, Kenichiro; Nishidate, Izumi; Ojima, Nobutoshi; Iwata, Kayoko

2014-01-01

To quantitatively evaluate skin chromophores over a wide region of curved skin surface, we propose an approach that suppresses the effect of the shading-derived error in the reflectance on the estimation of chromophore concentrations, without sacrificing the accuracy of that estimation. In our method, we use multiple regression analysis, assuming the absorbance spectrum as the response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as the predictor variables. The concentrations of melanin and total hemoglobin are determined from the multiple regression coefficients using compensation formulae (CF) based on the diffuse reflectance spectra derived from a Monte Carlo simulation. To suppress the shading-derived error, we investigated three different combinations of multiple regression coefficients for the CF. In vivo measurements with the forearm skin demonstrated that the proposed approach can reduce the estimation errors that are due to shading-derived errors in the reflectance. With the best combination of multiple regression coefficients, we estimated that the ratio of the error to the chromophore concentrations is about 10%. The proposed method does not require any measurements or assumptions about the shape of the subjects; this is an advantage over other studies related to the reduction of shading-derived errors.

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.