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

Ergonomics study on mobile phones for thumb physiology discomfort

NASA Astrophysics Data System (ADS)

Bendero, J. M. S.; Doon, M. E. R.; Quiogue, K. C. A.; Soneja, L. C.; Ong, N. R.; Sauli, Z.; Vairavan, R.

2017-09-01

The study was conducted on Filipino undergraduate college students and aimed to find out about the significant factors associated with mobile phone usage and its effect on thumb pain.A correlation-prediction analysisand Multiple Linear Regression was adopted and used as the main tool in determining the significant factors and coming up with predictive models on thumb related pain. With the use of the software Statistical Package for the Social Sciences or SPSS in conducting linear regression, 2 significant factors on thumb-related pain (percentage of time using portrait as screen orientation when text messaging, amount of time playing games using one hand in a day) were found.

Utilization of Offender Case Information by "Lenient" vs. "Punitive" Clinicians

ERIC Educational Resources Information Center

Holland, Terrill R.; Holt, Norman

1978-01-01

Presentence evaluations conducted by psychologists and psychiatrists (clinicians) and correctional counselors (caseworkers) were subjected to multiple regression analyses in order to specify the relative contribution of inmate characteristics (offense severity and recidivism probability) and decision-maker response biases to sentencing…

Estimation of nutrients and organic matter in Korean swine slurry using multiple regression analysis of physical and chemical properties.

PubMed

Suresh, Arumuganainar; Choi, Hong Lim

2011-10-01

Swine waste land application has increased due to organic fertilization, but excess application in an arable system can cause environmental risk. Therefore, in situ characterizations of such resources are important prior to application. To explore this, 41 swine slurry samples were collected from Korea, and wide differences were observed in the physico-biochemical properties. However, significant (P<0.001) multiple property correlations (R²) were obtained between nutrients with specific gravity (SG), electrical conductivity (EC), total solids (TS) and pH. The different combinations of hydrometer, EC meter, drying oven and pH meter were found useful to estimate Mn, Fe, Ca, K, Al, Na, N and 5-day biochemical oxygen demands (BOD₅) at improved R² values of 0.83, 0.82, 0.77, 0.75, 0.67, 0.47, 0.88 and 0.70, respectively. The results from this study suggest that multiple property regressions can facilitate the prediction of micronutrients and organic matter much better than a single property regression for livestock waste. Copyright © 2011 Elsevier Ltd. All rights reserved.

Theory of mind and executive function: working-memory capacity and inhibitory control as predictors of false-belief task performance.

PubMed

Mutter, Brigitte; Alcorn, Mark B; Welsh, Marilyn

2006-06-01

This study of the relationship between theory of mind and executive function examined whether on the false-belief task age differences between 3 and 5 ears of age are related to development of working-memory capacity and inhibitory processes. 72 children completed tasks measuring false belief, working memory, and inhibition. Significant age effects were observed for false-belief and working-memory performance, as well as for the false-alarm and perseveration measures of inhibition. A simultaneous multiple linear regression specified the contribution of age, inhibition, and working memory to the prediction of false-belief performance. This model was significant, explaining a total of 36% of the variance. To examine the independent contributions of the working-memory and inhibition variables, after controlling for age, two hierarchical multiple linear regressions were conducted. These multiple regression analyses indicate that working memory and inhibition make small, overlapping contributions to false-belief performance after accounting for age, but that working memory, as measured in this study, is a somewhat better predictor of false-belief understanding than is inhibition.

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.

Validation of the Juhnke-Balkin Life Balance Inventory

ERIC Educational Resources Information Center

Davis, R. J.; Balkin, Richard S.; Juhnke, Gerald A.

2014-01-01

Life balance is an important construct within the counseling profession. A validation study utilizing exploratory factor analysis and multiple regression was conducted on the Juhnke-Balkin Life Balance Inventory. Results from the study serve as evidence of validity for an assessment instrument designed to measure life balance.

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.

A Comparison of Three Tests of Mediation

ERIC Educational Resources Information Center

Warbasse, Rosalia E.

2009-01-01

A simulation study was conducted to evaluate the performance of three tests of mediation: the bias-corrected and accelerated bootstrap (Efron & Tibshirani, 1993), the asymmetric confidence limits test (MacKinnon, 2008), and a multiple regression approach described by Kenny, Kashy, and Bolger (1998). The evolution of these methods is reviewed and…

New Zealand Management Students' Perceptions of Communication Technologies in Correspondence Education.

ERIC Educational Resources Information Center

Ostman, Ronald E.; Wagner, Graham A.

1987-01-01

Describes a survey of 724 management students in New Zealand's Technical Correspondence Institute which was conducted to determine whether the introduction of educational technologies could decrease the dropout rate. The multiple linear regression model that was used to analyze the questionnaire responses is presented, and predictor variables are…

Practical guidance for conducting mediation analysis with multiple mediators using inverse odds ratio weighting.

PubMed

Nguyen, Quynh C; Osypuk, Theresa L; Schmidt, Nicole M; Glymour, M Maria; Tchetgen Tchetgen, Eric J

2015-03-01

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. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Thermal conductance measurements of bolted copper joints for SuperCDMS

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

Schmitt, R.; Tatkowski, Greg; Ruschman, M.

2015-09-01

Joint thermal conductance testing has been undertaken for bolted copper to copper connections from 60 mK to 26 K. This testing was performed to validate an initial design basis for the SuperCDMS experiment, where a dilution refrigerator will be coupled to a cryostat via multiple bolted connections. Copper used during testing was either gold plated or passivated with citric acid to prevent surface oxidation. Results obtained are well fit by a power law regression of joint thermal conductance to temperature and match well with data collected during a literature review.

Intent to Persist in College Freshmen: The Role of Self-Efficacy and Mentorship

ERIC Educational Resources Information Center

Baier, Stefanie T.; Markman, Barry S.; Pernice-Duca, Francesca M.

2016-01-01

We surveyed 237 first-time college students to examine the extent to which social-cognitive factors--self-efficacy, perceptions of mentorship, high school GPA, ACT scores, first-semester college GPA, and demographic characteristics-- influence freshmen's intent to persist. Standard multiple regression and MANOVA were conducted to determine the…

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…

A mass transfer model of ethanol emission from thin layers of corn silage

USDA-ARS?s Scientific Manuscript database

A mass transfer model of ethanol emission from thin layers of corn silage was developed and validated. The model was developed based on data from wind tunnel experiments conducted at different temperatures and air velocities. Multiple regression analysis was used to derive an equation that related t...

Computer-Assisted, Programmed Text, and Lecture Modes of Instruction in Three Medical Training Courses: Comparative Evaluation. Final Report.

ERIC Educational Resources Information Center

Deignan, Gerard M.; And Others

This report contains a comparative analysis of the differential effectiveness of computer-assisted instruction (CAI), programmed instructional text (PIT), and lecture methods of instruction in three medical courses--Medical Laboratory, Radiology, and Dental. The summative evaluation includes (1) multiple regression analyses conducted to predict…

Analyzing Preservice Teachers' Technological Pedagogical Content Knowledge Development in the Context of a Multidimensional Teacher Preparation Program

ERIC Educational Resources Information Center

Shinas, Valerie Harlow; Karchmer-Klein, Rachel; Mouza, Chrystalla; Yilmaz-Ozden, Sule; Glutting, Joseph J.

2015-01-01

In this quantitative study, correlational and multiple regression analyses were conducted to examine the technological pedagogical content knowledge (TPACK) development of 299 preservice teachers in response to the technology preparation they received during their initial teacher licensure program. Survey data were analyzed to determine the…

Factors of Role Conflict among Livestock Extension Professionals in Andhra Pradesh, India

ERIC Educational Resources Information Center

Sasidhar, P. V. K.; Rao, B. Sudhakar; Sreeramulu, Piedy

2008-01-01

To know the factors of role conflict among livestock extension professionals in Andhra Pradesh, India. Study was conducted following ex-post facto research design. Data were collected from 180 respondents through survey questionnaires. The data were subjected to multiple regression and path analyses to know the factors of role conflict.…

African American Career Aspirations: Examining the Relative Influence of Internalized Racism

ERIC Educational Resources Information Center

Brown, Danice L.; Segrist, Daniel

2016-01-01

The present study examined the relative influence of aspects of internalized racism on the career aspirations of a sample of African American adults. Participants (N = 315), ranging in age from 18 to 62 years, completed measures of internalized racism and career aspirations online. A hierarchical multiple regression analysis was conducted to…

Bullied Status and Physical Activity in Texas Adolescents

ERIC Educational Resources Information Center

Case, Kathleen R.; Pérez, Adriana; Saxton, Debra L.; Hoelscher, Deanna M.; Springer, Andrew E.

2016-01-01

This study examined the association between having been bullied at school during the past 6 months ("bullied status") and not meeting physical activity (PA) recommendations of 60 minutes of daily PA during the past week among 8th- and 11th-grade Texas adolescents. Multiple logistic regression analysis was conducted to examine this…

Association between response rates and survival outcomes in patients with newly diagnosed multiple myeloma. A systematic review and meta-regression analysis.

PubMed

Mainou, Maria; Madenidou, Anastasia-Vasiliki; Liakos, Aris; Paschos, Paschalis; Karagiannis, Thomas; Bekiari, Eleni; Vlachaki, Efthymia; Wang, Zhen; Murad, Mohammad Hassan; Kumar, Shaji; Tsapas, Apostolos

2017-06-01

We performed a systematic review and meta-regression analysis of randomized control trials to investigate the association between response to initial treatment and survival outcomes in patients with newly diagnosed multiple myeloma (MM). Response outcomes included complete response (CR) and the combined outcome of CR or very good partial response (VGPR), while survival outcomes were overall survival (OS) and progression-free survival (PFS). We used random-effect meta-regression models and conducted sensitivity analyses based on definition of CR and study quality. Seventy-two trials were included in the systematic review, 63 of which contributed data in meta-regression analyses. There was no association between OS and CR in patients without autologous stem cell transplant (ASCT) (regression coefficient: .02, 95% confidence interval [CI] -0.06, 0.10), in patients undergoing ASCT (-.11, 95% CI -0.44, 0.22) and in trials comparing ASCT with non-ASCT patients (.04, 95% CI -0.29, 0.38). Similarly, OS did not correlate with the combined metric of CR or VGPR, and no association was evident between response outcomes and PFS. Sensitivity analyses yielded similar results. This meta-regression analysis suggests that there is no association between conventional response outcomes and survival in patients with newly diagnosed MM. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

PubMed

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

2014-12-01

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

Does vagotomy protect against multiple sclerosis?

PubMed

Sundbøll, Jens; Horváth-Puhó, Erzsébet; Adelborg, Kasper; Svensson, Elisabeth

2017-07-01

To examine the association between vagotomy and multiple sclerosis. We conducted a matched cohort study of all patients who underwent truncal or super-selective vagotomy and a comparison cohort, by linking Danish population-based medical registries (1977-1995). Hazard ratios (HRs) for multiple sclerosis, adjusting for potential confounders were computed by means of Cox regression analysis. Median age of multiple sclerosis onset corresponded to late onset multiple sclerosis. No association with multiple sclerosis was observed for truncal vagotomy (0-37 year adjusted HR=0.91, 95% confidence interval [CI]: 0.48-1.74) or super-selective vagotomy (0-37 year adjusted HR=1.28, 95% CI: 0.79-2.09) compared with the general population. We found no association between vagotomy and later risk of late onset multiple sclerosis. Copyright © 2017 Elsevier B.V. All rights reserved.

Assessment of Risk Factors of Intrauterine Adhesions in Patients With Induced Abortion and the Curative Effect of Hysteroscopic Surgery.

PubMed

Mo, Xiaoliang; Qin, Guirong; Zhou, Zhoulin; Jiang, Xiaoli

2017-10-03

To explore the risk factors for intrauterine adhesions in patients with artificial abortion and clinical efficacy of hysteroscopic dissection. 1500 patients undergoing artificial abortion between January 2014 and June 2015 were enrolled into this study. The patients were divided into two groups with or without intrauterine adhesions. Univariate and Multiple logistic regression were conducted to assess the effects of multiple factors on the development of intrauterine adhesions following induced abortion. The incidence rate for intrauterine adhesions following induced abortion is 17.0%. Univariate showed that preoperative inflammation, multiple pregnancies and suction evacuation time are the influence risk factors of intrauterine adhesions. Multiple logistic regression demonstrates that multiple pregnancies, high intrauterine negative pressure, and long suction evacuation time are independent risk factors for the development of intrauterine adhesions following induced abortion. Additionally, intrauterine adhesions were observed in 105 mild, 80 moderate, and 70 severe cases. The cure rates for these three categories of intrauterine adhesions by hysteroscopic surgery were 100.0%, 93.8%, and 85.7%, respectively. Multiple pregnancies, high negative pressure suction evacuation and long suction evacuation time are independent risk factors for the development of intrauterine adhesions following induced abortions. Hysteroscopic surgery substantially improves the clinical outcomes of intrauterine adhesions.

A study of the effect of selected material properties on the ablation performance of artificial graphite

NASA Technical Reports Server (NTRS)

Maahs, H. G.

1972-01-01

Eighteen material properties were measured on 45 different, commercially available, artificial graphites. Ablation performance of these same graphites were also measured in a Mach 2 airstream at a stagnation pressure of 5.6 atm. Correlations were developed, where possible, between pairs of the material properties. Multiple regression equations were then formulated relating ablation performance to the various material properties, thus identifying those material properties having the strongest effect on ablation performance. These regression equations reveal that ablation performance in the present test environment depends primarily on maximum grain size, density, ash content, thermal conductivity, and mean pore radius. For optimization of ablation performance, grain size should be small, ash content low, density and thermal conductivity high, and mean pore radius large.

Nonlinear-regression flow model of the Gulf Coast aquifer systems in the south-central United States

USGS Publications Warehouse

Kuiper, L.K.

1994-01-01

A multiple-regression methodology was used to help answer questions concerning model reliability, and to calibrate a time-dependent variable-density ground-water flow model of the gulf coast aquifer systems in the south-central United States. More than 40 regression models with 2 to 31 regressions parameters are used and detailed results are presented for 12 of the models. More than 3,000 values for grid-element volume-averaged head and hydraulic conductivity are used for the regression model observations. Calculated prediction interval half widths, though perhaps inaccurate due to a lack of normality of the residuals, are the smallest for models with only four regression parameters. In addition, the root-mean weighted residual decreases very little with an increase in the number of regression parameters. The various models showed considerable overlap between the prediction inter- vals for shallow head and hydraulic conductivity. Approximate 95-percent prediction interval half widths for volume-averaged freshwater head exceed 108 feet; for volume-averaged base 10 logarithm hydraulic conductivity, they exceed 0.89. All of the models are unreliable for the prediction of head and ground-water flow in the deeper parts of the aquifer systems, including the amount of flow coming from the underlying geopressured zone. Truncating the domain of solution of one model to exclude that part of the system having a ground-water density greater than 1.005 grams per cubic centimeter or to exclude that part of the systems below a depth of 3,000 feet, and setting the density to that of freshwater does not appreciably change the results for head and ground-water flow, except for locations close to the truncation surface.

Effects of Parental Divorce or a Father's Death on High School Completion

ERIC Educational Resources Information Center

Sapharas, Nicole K.; Estell, David B.; Doran, Kelly A.; Waldron, Mary

2016-01-01

Associations between parental loss and high school (HS) completion were examined in data drawn from 1,761 male and 1,689 female offspring born in wedlock to mothers participating in a nationally representative study. Multiple logistic regression models were conducted predicting HS completion by age 19 among offspring whose parents divorced or…

Correlates of Geriatric Loneliness in Philippine Nursing Homes: A Multiple Regression Model

ERIC Educational Resources Information Center

de Guzman, Allan B.; Maravilla, Katrina N.; Maravilla, Veniza Anne M.; Marfil, Jomille D. V.; Marinas, Janine Angelica R.; Marquez, Jorelle Michael B.

2012-01-01

Numerous studies have been conducted worldwide about loneliness in older adults living in nursing homes and the factors associated with it. However, only a few studies have focused on social factors that may predispose these older adults to experience loneliness. The purpose of this study was to examine the interplay between and among loneliness,…

An improved approach for measuring the impact of multiple CO2 conductances on the apparent photorespiratory CO2 compensation point through slope-intercept regression

USDA-ARS?s Scientific Manuscript database

Biochemical models of leaf photosynthesis, which are essential for understanding the impact of photosynthesis to changing environments, depend on accurate parameterizations. The CO2 photocompensation point can be especially difficult to determine accurately but can be measured from the intersection ...

Complex Intellect vs the IQ Test as a Predictor of Performance.

ERIC Educational Resources Information Center

Dees, James W.

In order to test the ubiquity of the structure of the intellect for predictors of performance, a psychomotor skill (M 16 rifle proficiency test), a measure of perseverance (completion or resignation from OCS Program), and a measure of leadership ability (peer ratings) were selected as criteria on which multiple regressions were conducted with a…

Linking Life Skills and Norms with Adolescent Substance Use and Delinquency in South Africa

ERIC Educational Resources Information Center

Lai, Mary H.; Graham, John W.; Caldwell, Linda L.; Smith, Edward A.; Bradley, Stephanie A.; Vergnani, Tania; Mathews, Cathy; Wegner, Lisa

2013-01-01

We examined factors targeted in two popular prevention approaches with adolescent drug use and delinquency in South Africa. We hypothesized adolescent life skills to be inversely related and perceived norms to be directly related to later drug use and delinquency. Multiple regression and a relative weights approach were conducted for each outcome…

The Relationship of Core Self-Evaluations and Life Satisfaction in College Students with Disabilities: Evaluation of a Mediator Model

ERIC Educational Resources Information Center

Smedema, Susan Miller; Chan, Fong; Yaghmaian, Rana A.; Cardoso, Elizabeth DaSilva; Muller, Veronica; Keegan, John; Dutta, Alo; Ebener, Deborah J.

2015-01-01

This study examined the factorial structure of the construct core self-evaluations (CSE) and tested a mediational model of the relationship between CSE and life satisfaction in college students with disabilities. We conducted a quantitative descriptive design using exploratory and confirmatory factor analysis and multiple regression analysis.…

The Unique Effects of Parental Alcohol and Affective Disorders, Parenting, and Parental Negative Affect on Adolescent Maladjustment

ERIC Educational Resources Information Center

Haller, Moira; Chassin, Laurie

2011-01-01

Using a high-risk community sample, multiple regression analyses were conducted separately for mothers (n = 416) and fathers (n = 346) to test the unique, prospective influence of parental negative affect on adolescent maladjustment (internalizing symptoms, externalizing symptoms, and negative emotionality) 2 years later over and above parental…

Thermal conductance measurements of bolted copper joints for SuperCDMS

DOE PAGES

Schmitt, R. L.; Tatkowski, G.; Ruschman, M.; ...

2015-04-28

Joint thermal conductance testing has been undertaken for bolted copper to copper connections from 60 mK to 26 K. This testing was performed to validate an initial design basis for the SuperCDMS experiment, where a dilution refrigerator will be coupled to a cryostat via multiple bolted connections. Copper used during testing was either gold plated or passivated with citric acid to prevent surface oxidation. Finally, the results we obtained are well fit by a power law regression of joint thermal conductance to temperature and match well with data collected during a literature review.

Development of multiple regression analysis instruments to predict success in advanced placement chemistry

NASA Astrophysics Data System (ADS)

Wagner, Kurt Collins

2001-10-01

This research asks the fundamental question: "What is the profile of the successful AP chemistry student?" Two populations of students are studied. The first population is comprised of students who attend or attended the South Carolina Governor's School for Science and Mathematics, a specialized high school for high ability students, and who have taken the Advanced Placement (AP) chemistry examination in the past five years. The second population is comprised of the 581 South Carolina public school students at 46 high schools who took the AP chemistry examination in 2000. The first part of the study is intended to be useful in recruitment and placement decisions for schools in the National Consortium for Specialized Secondary Schools of Mathematics, Science and Technology. The second part of the study is intended to facilitate AP chemistry recruitment in South Carolina public schools. The first part of the study was conducted by ex post facto searches of teacher and school records at the South Carolina Governor's School for Science and Mathematics. The second part of the study was conducted by obtaining school participation information from the SC Department of Education and soliciting data from the public schools. Data were collected from 440 of 581 (75.7%) of students in 35 of 46 (76.1%) of schools. Intercorrelational and Multiple Regression Analyses (MRA) have yielded different results for these two populations. For the specialized school population, the significant predictors for success in AP chemistry are PSAT Math, placement test, and PSAT Writing. For the population of SC students, significant predictors for success are PSAT Math, count of prior science courses, and PSAT Writing. Multiple Regressions have been successfully developed for the two populations studied. Recommendations for their application are made.

Examination of Factors that Influence the Operation Income and Expenditure Balance Difference Rate of 20 Educational Foundation Universities.

PubMed

Nakajima, Hisato; Yano, Kouya; Nagasawa, Kaoko; Katou, Satoka; Yokota, Kuninobu

2017-01-01

The objective of this study is to examine the factors that influence the operation income and expenditure balance ratio of school corporations running university hospitals by multiple regression analysis. 1. We conducted cluster analysis of the financial ratio and classified the school corporations into those running colleges and universities.2. We conducted multiple regression analysis using the operation income and expenditure balance ratio of the colleges as the variables and the Diagnosis Procedure Combination data as the explaining variables.3. The predictive expression was used for multiple regression analysis. 1. The school corporations were divided into those running universities (7), colleges (20) and others. The medical income ratio and the debt ratio were high and the student payment ratio was low in the colleges.2. The numbers of emergency care hospitalizations, operations, radiation therapies, and ambulance conveyances, and the complexity index had a positive influence on the operation income and expenditure balance ratio. On the other hand, the number of general anesthesia procedures, the cover rate index, and the emergency care index had a negative influence.3. The predictive expression was as follows.Operation income and expenditure balance ratio = 0.027 × number of emergency care hospitalizations + 0.005 × number of operations + 0.019 × number of radiation therapies + 0.007 × number of ambulance conveyances - 0.003 × number of general anesthesia procedures + 648.344 × complexity index - 5877.210 × cover rate index - 2746.415 × emergency care index - 38.647Conclusion: In colleges, the number of emergency care hospitalizations, the number of operations, the number of radiation therapies, and the number of ambulance conveyances and the complexity index were factors for gaining ordinary profit.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Generalized regression neural network (GRNN)-based approach for colored dissolved organic matter (CDOM) retrieval: case study of Connecticut River at Middle Haddam Station, USA.

PubMed

Heddam, Salim

2014-11-01

The prediction of colored dissolved organic matter (CDOM) using artificial neural network approaches has received little attention in the past few decades. In this study, colored dissolved organic matter (CDOM) was modeled using generalized regression neural network (GRNN) and multiple linear regression (MLR) models as a function of Water temperature (TE), pH, specific conductance (SC), and turbidity (TU). Evaluation of the prediction accuracy of the models is based on the root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (CC), and Willmott's index of agreement (d). The results indicated that GRNN can be applied successfully for prediction of colored dissolved organic matter (CDOM).

Determination of grain-size characteristics from electromagnetic seabed mapping data: A NW Iberian shelf study

NASA Astrophysics Data System (ADS)

Baasch, Benjamin; Müller, Hendrik; von Dobeneck, Tilo; Oberle, Ferdinand K. J.

2017-05-01

The electric conductivity and magnetic susceptibility of sediments are fundamental parameters in environmental geophysics. Both can be derived from marine electromagnetic profiling, a novel, fast and non-invasive seafloor mapping technique. Here we present statistical evidence that electric conductivity and magnetic susceptibility can help to determine physical grain-size characteristics (size, sorting and mud content) of marine surficial sediments. Electromagnetic data acquired with the bottom-towed electromagnetic profiler MARUM NERIDIS III were analysed and compared with grain size data from 33 samples across the NW Iberian continental shelf. A negative correlation between mean grain size and conductivity (R=-0.79) as well as mean grain size and susceptibility (R=-0.78) was found. Simple and multiple linear regression analyses were carried out to predict mean grain size, mud content and the standard deviation of the grain-size distribution from conductivity and susceptibility. The comparison of both methods showed that multiple linear regression models predict the grain-size distribution characteristics better than the simple models. This exemplary study demonstrates that electromagnetic benthic profiling is capable to estimate mean grain size, sorting and mud content of marine surficial sediments at a very high significance level. Transfer functions can be calibrated using grains-size data from a few reference samples and extrapolated along shelf-wide survey lines. This study suggests that electromagnetic benthic profiling should play a larger role for coastal zone management, seafloor contamination and sediment provenance studies in worldwide continental shelf systems.

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

PubMed

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

2006-07-01

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

A 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.

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

PubMed

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

2017-05-01

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

Relationship between single and multiple perpetrator rape perpetration in South Africa: A comparison of risk factors in a population-based sample.

PubMed

R, Jewkes; Y, Sikweyiya; K, Dunkle; R, Morrell

2015-07-07

Studies of rape of women seldom distinguish between men's participation in acts of single and multiple perpetrator rape. Multiple perpetrator rape (MPR) occurs globally with serious consequences for women. In South Africa it is a cultural practice with defined circumstances in which it commonly occurs. Prevention requires an understanding of whether it is a context specific intensification of single perpetrator rape, or a distinctly different practice of different men. This paper aims to address this question. We conducted a cross-sectional household study with a multi-stage, randomly selected sample of 1686 men aged 18-49 who completed a questionnaire administered using an Audio-enhanced Personal Digital Assistant. We attempted to fit an ordered logistic regression model for factors associated with rape perpetration. 27.6 % of men had raped and 8.8 % had perpetrated multiple perpetrator rape (MPR). Thus 31.9 % of men who had ever raped had done so with other perpetrators. An ordered regression model was fitted, showing that the same associated factors, albeit at higher prevalence, are associated with SPR and MPR. Multiple perpetrator rape appears as an intensified form of single perpetrator rape, rather than a different form of rape. Prevention approaches need to be mainstreamed among young men.

Association between Caregiving, Meaning in Life, and Life Satisfaction beyond 50 in an Asian Sample: Age as a Moderator

ERIC Educational Resources Information Center

Ang, Rebecca P.; O, Jiaqing

2012-01-01

The association between caregiving, meaning in life, and life satisfaction was examined in sample of 519 older Asian adults beyond 50 years of age. Two hierarchical multiple regression analyses were conducted to examine age as moderator of the associations between caregiving, meaning in life, and life satisfaction. Age moderated the association…

Photosynthesis, water relations, and growth of planted Pinus strobus L. on burned sites in the southern Appalachians

Treesearch

Katherine J. Elliott; James M. Vose

1994-01-01

We measured net photosynthesis,leaf conductance, xylem water potential, and growth of Pinus strbus L. seedlings two years after planting on two clear-cut and burned sites in the southern Appalachians. Multiple regression analysis was used to relate seedling net pholosynthesis to vapor pressure deficit, seedling crown temperature, photosynthetically active radiation (...

Influence of Child Behavioral Problems and Parenting Stress on Parent-Child Conflict among Low-Income Families: The Moderating Role of Maternal Nativity

ERIC Educational Resources Information Center

Garcia, Aileen S.; Ren, Lixin; Esteraich, Jan M.; Raikes, Helen H.

2017-01-01

This study was designed to examine whether parenting stress and child behavioral problems are significant predictors of parent-child conflict in the context of low-income families and how these relations are moderated by maternal nativity. The authors conducted multiple regression analyses to examine relations between teachers' report of…

An Examination on the Effect of Prior Knowledge, Personal Goals, and Incentive in an Online Employee Training Program

ERIC Educational Resources Information Center

Zha, Shenghua; Adams, Andrea Harpine; Calcagno-Roach, Jamie Marie; Stringham, David A.

2017-01-01

This study explored factors that predicted learners' transformative learning in an online employee training program in a higher education institution in the U.S. A multivariate multiple regression analysis was conducted with a sample of 74 adult learners on their learning of a new learning management system. Four types of participants' behaviors…

Mediator and Moderator Role of Loneliness in the Relationship between Peer Victimization and Depressive Symptoms

ERIC Educational Resources Information Center

Baker, Ozgur Erdur; Bugay, Asli

2011-01-01

The goal of this study was to examine the mediator and moderator roles of loneliness in the relationship between peer victimisation and depressive symptoms. The participants of the study were 144 adolescents (66 girls, 78 boys) ranging in age from 11 to 15 years. Hierarchical multiple regression analyses were conducted to test the relations of…

Social determinants of cataract surgery utilization in south India. The Operations Research Group.

PubMed

Brilliant, G E; Lepkowski, J M; Zurita, B; Thulasiraj, R D

1991-04-01

A field trial was conducted to compare the effects of eight health education and economic incentive interventions on the awareness and acceptance of cataract surgery. Cataract screening and follow-up surgery were offered to more than 19,000 residents age 40 years and older in a probability sample of 90 villages in south India. Eight months after intervention, an evaluation was conducted to identify those in need of surgery who had been operated on. Two principal measures of program effectiveness are examined: awareness of cataract surgery and acceptance of the surgery. The type of intervention had a negligible effect on awareness of cataract surgery. A multiple logistic regression analysis revealed that individuals who were aware of surgery tended to be male, literate, and more affluent than those who were unaware of that option. Interventions that covered the complete costs of surgery had higher surgery acceptance rates. One health education strategy, house-to-house visits by a subject with aphakia, increased acceptance of the procedure more than others. In a multiple logistic regression analysis of acceptance rates, persons accepting surgery tended to be male; other factors were not important in explaining variation in acceptance rates.

Experimental validation of a coupled neutron-photon inverse radiation transport solver

NASA Astrophysics Data System (ADS)

Mattingly, John; Mitchell, Dean J.; Harding, Lee T.

2011-10-01

Sandia National Laboratories has developed an inverse radiation transport solver that applies nonlinear regression to coupled neutron-photon deterministic transport models. The inverse solver uses nonlinear regression to fit a radiation transport model to gamma spectrometry and neutron multiplicity counting measurements. The subject of this paper is the experimental validation of that solver. This paper describes a series of experiments conducted with a 4.5 kg sphere of α-phase, weapons-grade plutonium. The source was measured bare and reflected by high-density polyethylene (HDPE) spherical shells with total thicknesses between 1.27 and 15.24 cm. Neutron and photon emissions from the source were measured using three instruments: a gross neutron counter, a portable neutron multiplicity counter, and a high-resolution gamma spectrometer. These measurements were used as input to the inverse radiation transport solver to evaluate the solver's ability to correctly infer the configuration of the source from its measured radiation signatures.

Assessment of Communications-related Admissions Criteria in a Three-year Pharmacy Program

PubMed Central

Tejada, Frederick R.; Lang, Lynn A.; Purnell, Miriam; Acedera, Lisa; Ngonga, Ferdinand

2015-01-01

Objective. To determine if there is a correlation between TOEFL and other admissions criteria that assess communications skills (ie, PCAT variables: verbal, reading, essay, and composite), interview, and observational scores and to evaluate TOEFL and these admissions criteria as predictors of academic performance. Methods. Statistical analyses included two sample t tests, multiple regression and Pearson’s correlations for parametric variables, and Mann-Whitney U for nonparametric variables, which were conducted on the retrospective data of 162 students, 57 of whom were foreign-born. Results. The multiple regression model of the other admissions criteria on TOEFL was significant. There was no significant correlation between TOEFL scores and academic performance. However, significant correlations were found between the other admissions criteria and academic performance. Conclusion. Since TOEFL is not a significant predictor of either communication skills or academic success of foreign-born PharmD students in the program, it may be eliminated as an admissions criterion. PMID:26430273

Assessment of Communications-related Admissions Criteria in a Three-year Pharmacy Program.

PubMed

Parmar, Jayesh R; Tejada, Frederick R; Lang, Lynn A; Purnell, Miriam; Acedera, Lisa; Ngonga, Ferdinand

2015-08-25

To determine if there is a correlation between TOEFL and other admissions criteria that assess communications skills (ie, PCAT variables: verbal, reading, essay, and composite), interview, and observational scores and to evaluate TOEFL and these admissions criteria as predictors of academic performance. Statistical analyses included two sample t tests, multiple regression and Pearson's correlations for parametric variables, and Mann-Whitney U for nonparametric variables, which were conducted on the retrospective data of 162 students, 57 of whom were foreign-born. The multiple regression model of the other admissions criteria on TOEFL was significant. There was no significant correlation between TOEFL scores and academic performance. However, significant correlations were found between the other admissions criteria and academic performance. Since TOEFL is not a significant predictor of either communication skills or academic success of foreign-born PharmD students in the program, it may be eliminated as an admissions criterion.

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.

Climate variations and salmonellosis transmission in Adelaide, South Australia: a comparison between regression models

NASA Astrophysics Data System (ADS)

Zhang, Ying; Bi, Peng; Hiller, Janet

2008-01-01

This is the first study to identify appropriate regression models for the association between climate variation and salmonellosis transmission. A comparison between different regression models was conducted using surveillance data in Adelaide, South Australia. By using notified salmonellosis cases and climatic variables from the Adelaide metropolitan area over the period 1990-2003, four regression methods were examined: standard Poisson regression, autoregressive adjusted Poisson regression, multiple linear regression, and a seasonal autoregressive integrated moving average (SARIMA) model. Notified salmonellosis cases in 2004 were used to test the forecasting ability of the four models. Parameter estimation, goodness-of-fit and forecasting ability of the four regression models were compared. Temperatures occurring 2 weeks prior to cases were positively associated with cases of salmonellosis. Rainfall was also inversely related to the number of cases. The comparison of the goodness-of-fit and forecasting ability suggest that the SARIMA model is better than the other three regression models. Temperature and rainfall may be used as climatic predictors of salmonellosis cases in regions with climatic characteristics similar to those of Adelaide. The SARIMA model could, thus, be adopted to quantify the relationship between climate variations and salmonellosis transmission.

Mediation of the relationship between callous-unemotional traits and proactive aggression by amygdala response to fear among children with conduct problems.

PubMed

Lozier, Leah M; Cardinale, Elise M; VanMeter, John W; Marsh, Abigail A

2014-06-01

Among youths with conduct problems, callous-unemotional (CU) traits are known to be an important determinant of symptom severity, prognosis, and treatment responsiveness. But positive correlations between conduct problems and CU traits result in suppressor effects that may mask important neurobiological distinctions among subgroups of children with conduct problems. To assess the unique neurobiological covariates of CU traits and externalizing behaviors in youths with conduct problems and determine whether neural dysfunction linked to CU traits mediates the link between callousness and proactive aggression. This cross-sectional case-control study involved behavioral testing and neuroimaging that were conducted at a university research institution. Neuroimaging was conducted using a 3-T Siemens magnetic resonance imaging scanner. It included 46 community-recruited male and female juveniles aged 10 to 17 years, including 16 healthy control participants and 30 youths with conduct problems with both low and high levels of CU traits. Blood oxygenation level-dependent signal as measured via functional magnetic resonance imaging during an implicit face-emotion processing task and analyzed using whole-brain and region of interest-based analysis of variance and multiple-regression analyses. Analysis of variance revealed no group differences in the amygdala. By contrast, consistent with the existence of suppressor effects, multiple-regression analysis found amygdala responses to fearful expressions to be negatively associated with CU traits (x = 26, y = 0, z = -12; k = 1) and positively associated with externalizing behavior (x = 24, y = 0, z = -14; k = 8) when both variables were modeled simultaneously. Reduced amygdala responses mediated the relationship between CU traits and proactive aggression. The results linked proactive aggression in youths with CU traits to hypoactive amygdala responses to emotional distress cues, consistent with theories that externalizing behaviors, particularly proactive aggression, in youths with these traits stem from deficient empathic responses to distress. Amygdala hypoactivity may represent an intermediate phenotype, offering new insights into effective treatment strategies for conduct problems.

Maximum margin multiple instance clustering with applications to image and text clustering.

PubMed

Zhang, Dan; Wang, Fei; Si, Luo; Li, Tao

2011-05-01

In multiple instance learning problems, patterns are often given as bags and each bag consists of some instances. Most of existing research in the area focuses on multiple instance classification and multiple instance regression, while very limited work has been conducted for multiple instance clustering (MIC). This paper formulates a novel framework, maximum margin multiple instance clustering (M(3)IC), for MIC. However, it is impractical to directly solve the optimization problem of M(3)IC. Therefore, M(3)IC is relaxed in this paper to enable an efficient optimization solution with a combination of the constrained concave-convex procedure and the cutting plane method. Furthermore, this paper presents some important properties of the proposed method and discusses the relationship between the proposed method and some other related ones. An extensive set of empirical results are shown to demonstrate the advantages of the proposed method against existing research for both effectiveness and efficiency.

Quantifying components of the hydrologic cycle in Virginia using chemical hydrograph separation and multiple regression analysis

USGS Publications Warehouse

Sanford, Ward E.; Nelms, David L.; Pope, Jason P.; Selnick, David L.

2012-01-01

This study by the U.S. Geological Survey, prepared in cooperation with the Virginia Department of Environmental Quality, quantifies the components of the hydrologic cycle across the Commonwealth of Virginia. Long-term, mean fluxes were calculated for precipitation, surface runoff, infiltration, total evapotranspiration (ET), riparian ET, recharge, base flow (or groundwater discharge) and net total outflow. Fluxes of these components were first estimated on a number of real-time-gaged watersheds across Virginia. Specific conductance was used to distinguish and separate surface runoff from base flow. Specific-conductance data were collected every 15 minutes at 75 real-time gages for approximately 18 months between March 2007 and August 2008. Precipitation was estimated for 1971–2000 using PRISM climate data. Precipitation and temperature from the PRISM data were used to develop a regression-based relation to estimate total ET. The proportion of watershed precipitation that becomes surface runoff was related to physiographic province and rock type in a runoff regression equation. Component flux estimates from the watersheds were transferred to flux estimates for counties and independent cities using the ET and runoff regression equations. Only 48 of the 75 watersheds yielded sufficient data, and data from these 48 were used in the final runoff regression equation. The base-flow proportion for the 48 watersheds averaged 72 percent using specific conductance, a value that was substantially higher than the 61 percent average calculated using a graphical-separation technique (the USGS program PART). Final results for the study are presented as component flux estimates for all counties and independent cities in Virginia.

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.

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)

An Investigation of the Relations Between Student Knowledge, Personal Contact, and Attitudes Toward Individuals with Schizophrenia

PubMed Central

Eack, Shaun M.; Newhill, Christina E.

2013-01-01

A survey of 118 MSW students was conducted to examine the relationship between social work students’ knowledge about, contact with, and attitudes toward persons with schizophrenia. Hierarchical regression analyses indicated that students’ knowledge about and contact with persons with schizophrenia were significantly related to better attitudes toward this population. Moderated multiple regression analyses revealed a significant interaction between knowledge about and contact with persons with schizophrenia, such that knowledge was only related to positive attitudes among students who had more personal contact with persons with the illness. Implications for social work training in severe mental illness are discussed (99 words). PMID:24353396

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.

Analysis on the Correlation of Traffic Flow in Hainan Province Based on Baidu Search

NASA Astrophysics Data System (ADS)

Chen, Caixia; Shi, Chun

2018-03-01

Internet search data records user’s search attention and consumer demand, providing necessary database for the Hainan traffic flow model. Based on Baidu Index, with Hainan traffic flow as example, this paper conduct both qualitative and quantitative analysis on the relationship between search keyword from Baidu Index and actual Hainan tourist traffic flow, and build multiple regression model by SPSS.

A Comparative Analysis of the Effects of Instructional Design Factors on Student Success in E-Learning: Multiple-Regression versus Neural Networks

ERIC Educational Resources Information Center

Cebeci, Halil Ibrahim; Yazgan, Harun Resit; Geyik, Abdulkadir

2009-01-01

This study explores the relationship between the student performance and instructional design. The research was conducted at the E-Learning School at a university in Turkey. A list of design factors that had potential influence on student success was created through a review of the literature and interviews with relevant experts. From this, the…

The Need for an Ecological Approach to Parental Stress in Autism Spectrum Disorders: The Combined Role of Individual and Environmental Factors

ERIC Educational Resources Information Center

Derguy, C.; M'Bailara, K.; Michel, G.; Roux, S.; Bouvard, M.

2016-01-01

This study aimed to identify parental stress predictors in ASD by considering individual and environmental factors in an ecological approach. Participants were 115 parents of children with ASD aged from 3 to 10 years. Multiple regression analyses were conducted to determine the best predictors of parental stress among child-related, parent-related…

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)

Simultaneous high-speed schlieren and OH chemiluminescence imaging in a hybrid rocket combustor at elevated pressures

NASA Astrophysics Data System (ADS)

Miller, Victor; Jens, Elizabeth T.; Mechentel, Flora S.; Cantwell, Brian J.; Stanford Propulsion; Space Exploration Group Team

2014-11-01

In this work, we present observations of the overall features and dynamics of flow and combustion in a slab-type hybrid rocket combustor. Tests were conducted in the recently upgraded Stanford Combustion Visualization Facility, a hybrid rocket combustor test platform capable of generating constant mass-flux flows of oxygen. High-speed (3 kHz) schlieren and OH chemiluminescence imaging were used to visualize the flow. We present imaging results for the combustion of two different fuel grains, a classic, low regression rate polymethyl methacrylate (PMMA), and a high regression rate paraffin, and all tests were conducted in gaseous oxygen. Each fuel grain was tested at multiple free-stream pressures at constant oxidizer mass flux (40 kg/m2s). The resulting image sequences suggest that aspects of the dynamics and scaling of the system depend strongly on both pressure and type of fuel.

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.

Adherence to preferable behavior for lipid control by high-risk dyslipidemic Japanese patients under pravastatin treatment: the APPROACH-J study.

PubMed

Kitagawa, Yasuhisa; Teramoto, Tamio; Daida, Hiroyuki

2012-01-01

We evaluated the impact of adherence to preferable behavior on serum lipid control assessed by a self-reported questionnaire in high-risk patients taking pravastatin for primary prevention of coronary artery disease. High-risk patients taking pravastatin were followed for 2 years. Questionnaire surveys comprising 21 questions, including 18 questions concerning awareness of health, and current status of diet, exercise, and drug therapy, were conducted at baseline and after 1 year. Potential domains were established by factor analysis from the results of questionnaires, and adherence scores were calculated in each domain. The relationship between adherence scores and lipid values during the 1-year treatment period was analyzed by each domain using multiple regression analysis. A total of 5,792 patients taking pravastatin were included in the analysis. Multiple regression analysis showed a significant correlation in terms of "Intake of high fat/cholesterol/sugar foods" (regression coefficient -0.58, p=0.0105) and "Adherence to instructions for drug therapy" (regression coefficient -6.61, p<0.0001). Low-density lipoprotein cholesterol (LDL-C) values were significantly lower in patients who had an increase in the adherence score in the "Awareness of health" domain compared with those with a decreased score. There was a significant correlation between high-density lipoprotein (HDL-C) values and "Awareness of health" (regression coefficient 0.26; p= 0.0037), "Preferable dietary behaviors" (regression coefficient 0.75; p<0.0001), and "Exercise" (regression coefficient 0.73; p= 0.0002). Similar relations were seen with triglycerides. In patients who have a high awareness of their health, a positive attitude toward lipid-lowering treatment including diet, exercise, and high adherence to drug therapy, is related with favorable overall lipid control even in patients under treatment with pravastatin.

Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants.

PubMed

Pierce, Brandon L; Ahsan, Habibul; Vanderweele, Tyler J

2011-06-01

Mendelian Randomization (MR) studies assess the causality of an exposure-disease association using genetic determinants [i.e. instrumental variables (IVs)] of the exposure. Power and IV strength requirements for MR studies using multiple genetic variants have not been explored. We simulated cohort data sets consisting of a normally distributed disease trait, a normally distributed exposure, which affects this trait and a biallelic genetic variant that affects the exposure. We estimated power to detect an effect of exposure on disease for varying allele frequencies, effect sizes and samples sizes (using two-stage least squares regression on 10,000 data sets-Stage 1 is a regression of exposure on the variant. Stage 2 is a regression of disease on the fitted exposure). Similar analyses were conducted using multiple genetic variants (5, 10, 20) as independent or combined IVs. We assessed IV strength using the first-stage F statistic. Simulations of realistic scenarios indicate that MR studies will require large (n > 1000), often very large (n > 10,000), sample sizes. In many cases, so-called 'weak IV' problems arise when using multiple variants as independent IVs (even with as few as five), resulting in biased effect estimates. Combining genetic factors into fewer IVs results in modest power decreases, but alleviates weak IV problems. Ideal methods for combining genetic factors depend upon knowledge of the genetic architecture underlying the exposure. The feasibility of well-powered, unbiased MR studies will depend upon the amount of variance in the exposure that can be explained by known genetic factors and the 'strength' of the IV set derived from these genetic factors.

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

PubMed

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

2014-12-01

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

[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.

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...

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…

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

PubMed

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

2016-05-01

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

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)

Modeling Pan Evaporation for Kuwait by Multiple Linear Regression

PubMed Central

Almedeij, Jaber

2012-01-01

Evaporation is an important parameter for many projects related to hydrology and water resources systems. This paper constitutes the first study conducted in Kuwait to obtain empirical relations for the estimation of daily and monthly pan evaporation as functions of available meteorological data of temperature, relative humidity, and wind speed. The data used here for the modeling are daily measurements of substantial continuity coverage, within a period of 17 years between January 1993 and December 2009, which can be considered representative of the desert climate of the urban zone of the country. Multiple linear regression technique is used with a procedure of variable selection for fitting the best model forms. The correlations of evaporation with temperature and relative humidity are also transformed in order to linearize the existing curvilinear patterns of the data by using power and exponential functions, respectively. The evaporation models suggested with the best variable combinations were shown to produce results that are in a reasonable agreement with observation values. PMID:23226984

Crime prediction modeling

NASA Technical Reports Server (NTRS)

1971-01-01

A study of techniques for the prediction of crime in the City of Los Angeles was conducted. Alternative approaches to crime prediction (causal, quasicausal, associative, extrapolative, and pattern-recognition models) are discussed, as is the environment within which predictions were desired for the immediate application. The decision was made to use time series (extrapolative) models to produce the desired predictions. The characteristics of the data and the procedure used to choose equations for the extrapolations are discussed. The usefulness of different functional forms (constant, quadratic, and exponential forms) and of different parameter estimation techniques (multiple regression and multiple exponential smoothing) are compared, and the quality of the resultant predictions is assessed.

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.

Diphenylhydantoin and lidocaine modification of A-V conduction in halothane-anesthetized dogs.

PubMed

Atlee, J L; Homer, L D; Tobey, R E

1975-07-01

The effect of halothane on A-V conduction was evaluated in gods during atrial pacing using the technique of His-bundle electrocardiography. In addition, the effects of lidocaine and diphenylkydantoin (DPH) on A-V conuction were examined during halothane anesthesia. Effects of these drugs on three subintervals of A-V conduction were compared. These included the -H (stimulus atifact of His-bundle deflection-atrioventricular conduction), H-Q (His-budnle deflection onset of QRS complex-His-Purkinje conduction), and H-S intervals(His-bundle delfection to end of QRS COmplex-total intraventricular conduction). Linear regression best described the relationship between duration of interval (P-H, H-V,and H-S) and heart rate during incremental increases in the atrial paced rate. Data from these experiments were fitted to a multiple lenear regression model that predicted the effect of increasing concentrations of halothan, lidocaine, and DPH on slope and intercept coefficients. In creasing concentrations of halothan ( 30 and 45 mg/100 ml arterial). Both lidocaine and DPH further depressed conduction at all levels of halothan anesthesia. The P-H interval was particularly sensitive todrug effefts. This may represent potentiation of the normal slowing of conduction through the AVnode in response to incremental increases in heart rate (fatigue response.) We conclude thatboth lidocaine and DPH fail to reverse the depressant effect of halothane on A-V conduction. This may explain their ineffectiveness in treating certain types of arrhythmias during halothane anesthesia.

[Psychoactive substances use and health-related quality of life among school age adolescents].

PubMed

Vilugrón Aravena, Fabiola; Hidalgo-Rasmussen, Carlos Alejandro; Molina G, Temístocles; Gras Pérez, María Eugenia; Font-Mayolas, Silvia

2017-12-01

Background The use of psychoactive substances among adolescents is a major social and public health concern. Aim To analyze association of substance abuse and multiple drug use with health-related quality of life (HRQOL) in adolescents attending a high school in Valparaiso, Chile. Material and Methods Analytical cross-sectional study conducted in a sample of adolescents attending high school. HRQOL was assessed using KIDSCREEN-52 questionnaire and substance use was measured using the Global school-based student health survey. Participants had to complete online, self-administered, anonymous questionnaires. Multiple logistic regression analyses were conducted to calculate Odd ratios. Results A total of 550 adolescents aged 16 ± 1 years old completed the questionnaires. Thirty nine percent consumed alcohol during the last month, 31% smoked, 33% used marijuana and 33% admitted the use of multiple drugs. High-risk alcohol consumption was associated with a lower perception of psychological well-being, self-perception and school environment. This last dimension was affected in those who admitted marijuana use during the last month. Multiple drug use (three substances) was associated with a lower perception of physical and psychological well-being, self-perception, relationship with parents, family life and school environment. Conclusions High-risk alcohol consumption and multiple drug use (three substances) have a negative impact on the HRQOL of school age adolescents.

Organizational Justice and Physiological Coronary Heart Disease Risk Factors in Japanese Employees: a Cross-Sectional Study.

PubMed

Inoue, Akiomi; Kawakami, Norito; Eguchi, Hisashi; Miyaki, Koichi; Tsutsumi, Akizumi

2015-12-01

Growing evidence has shown that lack of organizational justice (i.e., procedural justice and interactional justice) is associated with coronary heart disease (CHD) while biological mechanisms underlying this association have not yet been fully clarified. The purpose of the present study was to investigate the cross-sectional association of organizational justice with physiological CHD risk factors (i.e., blood pressure, high-density lipoprotein [HDL] cholesterol, low-density lipoprotein [LDL] cholesterol, and triglyceride) in Japanese employees. Overall, 3598 male and 901 female employees from two manufacturing companies in Japan completed self-administered questionnaires measuring organizational justice, demographic characteristics, and lifestyle factors. They completed health checkup, which included blood pressure and serum lipid measurements. Multiple logistic regression analyses and trend tests were conducted. Among male employees, multiple logistic regression analyses and trend tests showed significant associations of low procedural justice and low interactional justice with high triglyceride (defined as 150 mg/dL or greater) after adjusting for demographic characteristics and lifestyle factors. Among female employees, trend tests showed significant dose-response relationship between low interactional justice and high LDL cholesterol (defined as 140 mg/dL or greater) while multiple logistic regression analysis showed only marginally significant or insignificant odds ratio of high LDL cholesterol among the low interactional justice group. Neither procedural justice nor interactional justice was associated with blood pressure or HDL cholesterol. Organizational justice may be an important psychosocial factor associated with increased triglyceride at least among Japanese male employees.

Evaluating the Relationships Between NTNU/SINTEF Drillability Indices with Index Properties and Petrographic Data of Hard Igneous Rocks

NASA Astrophysics Data System (ADS)

Aligholi, Saeed; Lashkaripour, Gholam Reza; Ghafoori, Mohammad; Azali, Sadegh Tarigh

2017-11-01

Thorough and realistic performance predictions are among the main requisites for estimating excavation costs and time of the tunneling projects. Also, NTNU/SINTEF rock drillability indices, including the Drilling Rate Index™ (DRI), Bit Wear Index™ (BWI), and Cutter Life Index™ (CLI), are among the most effective indices for determining rock drillability. In this study, brittleness value (S20), Sievers' J-Value (SJ), abrasion value (AV), and Abrasion Value Cutter Steel (AVS) tests are conducted to determine these indices for a wide range of Iranian hard igneous rocks. In addition, relationships between such drillability parameters with petrographic features and index properties of the tested rocks are investigated. The results from multiple regression analysis revealed that the multiple regression models prepared using petrographic features provide a better estimation of drillability compared to those prepared using index properties. Also, it was found that the semiautomatic petrography and multiple regression analyses provide a suitable complement to determine drillability properties of igneous rocks. Based on the results of this study, AV has higher correlations with studied mineralogical indices than AVS. The results imply that, in general, rock surface hardness of hard igneous rocks is very high, and the acidic igneous rocks have a lower strength and density and higher S20 than those of basic rocks. Moreover, DRI is higher, while BWI is lower in acidic igneous rocks, suggesting that drill and blast tunneling is more convenient in these rocks than basic rocks.

Mediation of the Relationship Between Callous-Unemotional Traits and Proactive Aggression by Amygdala Response to Fear Among Children With Conduct Problems

PubMed Central

Lozier, Leah M.; Cardinale, Elise M.; VanMeter, John W.; Marsh, Abigail A.

2015-01-01

Importance Among youths with conduct problems, callous-unemotional (CU) traits are known to be an important determinant of symptom severity, prognosis, and treatment responsiveness. But positive correlations between conduct problems and CU traits result in suppressor effects that may mask important neurobiological distinctions among subgroups of children with conduct problems. Objective To assess the unique neurobiological covariates of CU traits and externalizing behaviors in youths with conduct problems and determine whether neural dysfunction linked to CU traits mediates the link between callousness and proactive aggression. Design, Setting, and Participants This cross-sectional case-control study involved behavioral testing and neuroimaging that were conducted at a university research institution. Neuroimaging was conducted using a 3-T Siemens magnetic resonance imaging scanner. It included 46 community-recruited male and female juveniles aged 10 to 17 years, including 16 healthy control participants and 30 youths with conduct problems with both low and high levels of CU traits. Main Outcomes and Measures Blood oxygenation level–dependent signal as measured via functional magnetic resonance imaging during an implicit face-emotion processing task and analyzed using whole-brain and region of interest–based analysis of variance and multiple-regression analyses. Results Analysis of variance revealed no group differences in the amygdala. By contrast, consistent with the existence of suppressor effects, multiple-regression analysis found amygdala responses to fearful expressions to be negatively associated with CU traits (x = 26, y = 0, z = −12; k = 1) and positively associated with externalizing behavior (x = 24, y = 0, z = −14; k = 8) when both variables were modeled simultaneously. Reduced amygdala responses mediated the relationship between CU traits and proactive aggression. Conclusions and Relevance The results linked proactive aggression in youths with CU traits to hypoactive amygdala responses to emotional distress cues, consistent with theories that externalizing behaviors, particularly proactive aggression, in youths with these traits stem from deficient empathic responses to distress. Amygdala hypoactivity may represent an intermediate phenotype, offering new insights into effective treatment strategies for conduct problems. PMID:24671141

Prevalence and Determinants of Preterm Birth in Tehran, Iran: A Comparison between Logistic Regression and Decision Tree Methods.

PubMed

Amini, Payam; Maroufizadeh, Saman; Samani, Reza Omani; Hamidi, Omid; Sepidarkish, Mahdi

2017-06-01

Preterm birth (PTB) is a leading cause of neonatal death and the second biggest cause of death in children under five years of age. The objective of this study was to determine the prevalence of PTB and its associated factors using logistic regression and decision tree classification methods. This cross-sectional study was conducted on 4,415 pregnant women in Tehran, Iran, from July 6-21, 2015. Data were collected by a researcher-developed questionnaire through interviews with mothers and review of their medical records. To evaluate the accuracy of the logistic regression and decision tree methods, several indices such as sensitivity, specificity, and the area under the curve were used. The PTB rate was 5.5% in this study. The logistic regression outperformed the decision tree for the classification of PTB based on risk factors. Logistic regression showed that multiple pregnancies, mothers with preeclampsia, and those who conceived with assisted reproductive technology had an increased risk for PTB ( p < 0.05). Identifying and training mothers at risk as well as improving prenatal care may reduce the PTB rate. We also recommend that statisticians utilize the logistic regression model for the classification of risk groups for PTB.

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.

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

A non-destructive selection criterion for fibre content in jute : II. Regression approach.

PubMed

Arunachalam, V; Iyer, R D

1974-01-01

An experiment with ten populations of jute, comprising varieties and mutants of the two species Corchorus olitorius and C.capsularis was conducted at two different locations with the object of evolving an effective criterion for selecting superior single plants for fibre yield. At Delhi, variation existed only between varieties as a group and mutants as a group, while at Pusa variation also existed among the mutant populations of C. capsularis.A multiple regression approach was used to find the optimum combination of characters for prediction of fibre yield. A process of successive elimination of characters based on the coefficient of determination provided by individual regression equations was employed to arrive at the optimal set of characters for predicting fibre yield. It was found that plant height, basal and mid-diameters and basal and mid-dry fibre weights would provide such an optimal set.

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

PubMed Central

Tighe, Elizabeth L.; Schatschneider, Christopher

2015-01-01

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 awareness and vocabulary knowledge at multiple points (quantiles) along the continuous distribution of reading comprehension. To demonstrate the efficacy of our multiple quantile regression analysis, we compared and contrasted our results with a traditional multiple regression analytic approach. Our results indicated that morphological awareness and vocabulary knowledge accounted for a large portion of the variance (82-95%) in reading comprehension skills across all quantiles. Morphological awareness exhibited the greatest unique predictive ability at lower levels of reading comprehension whereas vocabulary knowledge exhibited the greatest unique predictive ability at higher levels of reading comprehension. These results indicate the utility of using multiple quantile regression to assess trajectories of component skills across multiple levels of reading comprehension. The implications of our findings for ABE programs are discussed. PMID:25351773

Risk factors for retinal breaks in patients with symptom of floaters.

PubMed

Singalavanija, Apichart; Amornrattanapan, Chutiwan; Nitiruangjarus, Kanjanee; Tongsai, Sasima

2010-06-01

To identify the risk factors of retinal breaks in patients with the symptom of floaters, and to determine the association between those risk factors and retinal breaks. A retrospective analytic study of 184 patients (55 males and 129 females) that included 220 eyes was conducted. Patient information such as age, symptoms (multiple floaters, flashing), duration of symptom, refractive error, history of cataract surgery, family history of retinal detachment, and complete eye examination were recorded. The patients were divided into two groups, the first group (control group) had symptoms of floaters and no retinal breaks, the second group (retinal breaks group) had symptoms of floaters with retinal breaks. Chi-square test, and the multiple logistic regression were used for statistical analysis. Two hundred twenty eyes, 175 eyes of the control group and 45 eyes of the retinal breaks group were examined and included in this study. The multiple logistic regression analysis revealed that patients with multiple floaters, and floaters and flashing increased the risk of retinal breaks to 5.8 and 4.3 times, respectively, when compared to patients with single floater or floaters alone. Lattice degeneration increased the risk of retinal breaks to 5.9 times when compared to eyes that did not have lattice degeneration. Multiple floaters, flashing and lattice degeneration are risk factors of retinal breaks in patients with symptoms of floaters. Therefore, it is important for the ophthalmologists to be aware of these risk factors and the patients at risk should have follow-up examinations.

[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.

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.

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.

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.

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.

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…

Predictors of anemia among pregnant women in Westmoreland, Jamaica

PubMed Central

Charles, Alyson M.; Campbell-Stennett, Dianne; Yatich, Nelly; Jolly, Pauline E.

2010-01-01

Anemia in pregnancy is a worldwide problem, but it is most prevalent in the developing world. This research project was conducted to determine the predictors of anemia in pregnant women in Westmoreland, Jamaica. A cross-sectional study design was conducted and descriptive, bivariate, and multiple logistic regression analyses were used. Body mass index, Mid-upper arm circumference, and the number of antenatal care visits showed a statistically significant association with anemia. Based on the results, we believe that maintaining a healthy body weight, and frequently visiting an antenatal clinic, will help to lower the prevalence of anemia among pregnant women in Westmoreland. PMID:20526925

Analysis of the thermal comfort model in an environment of metal mechanical branch.

PubMed

Pinto, N M; Xavier, A A P; do Amaral, Regiane T

2012-01-01

This study aims to identify the correlation between the Predicted Mean Vote (PMV) with the thermal sensation (S) of 55 employees, establishing a linear multiple regression equation. The measurement of environmental variables followed established standards. The survey was conducted in a metal industry located in Ponta Grossa of the State of Parana in Brazil. It was applied the physical model of thermal comfort to the environmental variables and also to the subjective data on the thermal sensations of employees. The survey was conducted from May to November, 2010, with 48 measurements. This study will serve as the basis for a dissertation consisting of 72 measurements.

Confidence intervals for distinguishing ordinal and disordinal interactions in multiple regression.

PubMed

Lee, Sunbok; Lei, Man-Kit; Brody, Gene H

2015-06-01

Distinguishing between ordinal and disordinal interaction in multiple regression is useful in testing many interesting theoretical hypotheses. Because the distinction is made based on the location of a crossover point of 2 simple regression lines, confidence intervals of the crossover point can be used to distinguish ordinal and disordinal interactions. This study examined 2 factors that need to be considered in constructing confidence intervals of the crossover point: (a) the assumption about the sampling distribution of the crossover point, and (b) the possibility of abnormally wide confidence intervals for the crossover point. A Monte Carlo simulation study was conducted to compare 6 different methods for constructing confidence intervals of the crossover point in terms of the coverage rate, the proportion of true values that fall to the left or right of the confidence intervals, and the average width of the confidence intervals. The methods include the reparameterization, delta, Fieller, basic bootstrap, percentile bootstrap, and bias-corrected accelerated bootstrap methods. The results of our Monte Carlo simulation study suggest that statistical inference using confidence intervals to distinguish ordinal and disordinal interaction requires sample sizes more than 500 to be able to provide sufficiently narrow confidence intervals to identify the location of the crossover point. (c) 2015 APA, all rights reserved).

Multiple regression equations modelling of groundwater of Ajmer-Pushkar railway line region, Rajasthan (India).

PubMed

Mathur, Praveen; Sharma, Sarita; Soni, Bhupendra

2010-01-01

In the present work, an attempt is made to formulate multiple regression equations using all possible regressions method for groundwater quality assessment of Ajmer-Pushkar railway line region in pre- and post-monsoon seasons. Correlation studies revealed the existence of linear relationships (r 0.7) for electrical conductivity (EC), total hardness (TH) and total dissolved solids (TDS) with other water quality parameters. The highest correlation was found between EC and TDS (r = 0.973). EC showed highly significant positive correlation with Na, K, Cl, TDS and total solids (TS). TH showed highest correlation with Ca and Mg. TDS showed significant correlation with Na, K, SO4, PO4 and Cl. The study indicated that most of the contamination present was water soluble or ionic in nature. Mg was present as MgCl2; K mainly as KCl and K2SO4, and Na was present as the salts of Cl, SO4 and PO4. On the other hand, F and NO3 showed no significant correlations. The r2 values and F values (at 95% confidence limit, alpha = 0.05) for the modelled equations indicated high degree of linearity among independent and dependent variables. Also the error % between calculated and experimental values was contained within +/- 15% limit.

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)

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.

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

PubMed

Tighe, Elizabeth L; Schatschneider, Christopher

2016-07-01

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 awareness and vocabulary knowledge at multiple points (quantiles) along the continuous distribution of reading comprehension. To demonstrate the efficacy of our multiple quantile regression analysis, we compared and contrasted our results with a traditional multiple regression analytic approach. Our results indicated that morphological awareness and vocabulary knowledge accounted for a large portion of the variance (82%-95%) in reading comprehension skills across all quantiles. Morphological awareness exhibited the greatest unique predictive ability at lower levels of reading comprehension whereas vocabulary knowledge exhibited the greatest unique predictive ability at higher levels of reading comprehension. These results indicate the utility of using multiple quantile regression to assess trajectories of component skills across multiple levels of reading comprehension. The implications of our findings for ABE programs are discussed. © Hammill Institute on Disabilities 2014.

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…

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.

Waste generated in high-rise buildings construction: a quantification model based on statistical multiple regression.

PubMed

Parisi Kern, Andrea; Ferreira Dias, Michele; Piva Kulakowski, Marlova; Paulo Gomes, Luciana

2015-05-01

Reducing construction waste is becoming a key environmental issue in the construction industry. The quantification of waste generation rates in the construction sector is an invaluable management tool in supporting mitigation actions. However, the quantification of waste can be a difficult process because of the specific characteristics and the wide range of materials used in different construction projects. Large variations are observed in the methods used to predict the amount of waste generated because of the range of variables involved in construction processes and the different contexts in which these methods are employed. This paper proposes a statistical model to determine the amount of waste generated in the construction of high-rise buildings by assessing the influence of design process and production system, often mentioned as the major culprits behind the generation of waste in construction. Multiple regression was used to conduct a case study based on multiple sources of data of eighteen residential buildings. The resulting statistical model produced dependent (i.e. amount of waste generated) and independent variables associated with the design and the production system used. The best regression model obtained from the sample data resulted in an adjusted R(2) value of 0.694, which means that it predicts approximately 69% of the factors involved in the generation of waste in similar constructions. Most independent variables showed a low determination coefficient when assessed in isolation, which emphasizes the importance of assessing their joint influence on the response (dependent) variable. Copyright © 2015 Elsevier Ltd. All rights reserved.

Flood-frequency characteristics of Wisconsin streams

USGS Publications Warehouse

Walker, John F.; Peppler, Marie C.; Danz, Mari E.; Hubbard, Laura E.

2017-05-22

Flood-frequency characteristics for 360 gaged sites on unregulated rural streams in Wisconsin are presented for percent annual exceedance probabilities ranging from 0.2 to 50 using a statewide skewness map developed for this report. Equations of the relations between flood-frequency and drainage-basin characteristics were developed by multiple-regression analyses. Flood-frequency characteristics for ungaged sites on unregulated, rural streams can be estimated by use of the equations presented in this report. The State was divided into eight areas of similar physiographic characteristics. The most significant basin characteristics are drainage area, soil saturated hydraulic conductivity, main-channel slope, and several land-use variables. The standard error of prediction for the equation for the 1-percent annual exceedance probability flood ranges from 56 to 70 percent for Wisconsin Streams; these values are larger than results presented in previous reports. The increase in the standard error of prediction is likely due to increased variability of the annual-peak discharges, resulting in increased variability in the magnitude of flood peaks at higher frequencies. For each of the unregulated rural streamflow-gaging stations, a weighted estimate based on the at-site log Pearson type III analysis and the multiple regression results was determined. The weighted estimate generally has a lower uncertainty than either the Log Pearson type III or multiple regression estimates. For regulated streams, a graphical method for estimating flood-frequency characteristics was developed from the relations of discharge and drainage area for selected annual exceedance probabilities. Graphs for the major regulated streams in Wisconsin are presented in the report.

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.

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…

Modeling Longitudinal Data Containing Non-Normal Within Subject Errors

NASA Technical Reports Server (NTRS)

Feiveson, Alan; Glenn, Nancy L.

2013-01-01

The mission of the National Aeronautics and Space Administration’s (NASA) human research program is to advance safe human spaceflight. This involves conducting experiments, collecting data, and analyzing data. The data are longitudinal and result from a relatively few number of subjects; typically 10 – 20. A longitudinal study refers to an investigation where participant outcomes and possibly treatments are collected at multiple follow-up times. Standard statistical designs such as mean regression with random effects and mixed–effects regression are inadequate for such data because the population is typically not approximately normally distributed. Hence, more advanced data analysis methods are necessary. This research focuses on four such methods for longitudinal data analysis: the recently proposed linear quantile mixed models (lqmm) by Geraci and Bottai (2013), quantile regression, multilevel mixed–effects linear regression, and robust regression. This research also provides computational algorithms for longitudinal data that scientists can directly use for human spaceflight and other longitudinal data applications, then presents statistical evidence that verifies which method is best for specific situations. This advances the study of longitudinal data in a broad range of applications including applications in the sciences, technology, engineering and mathematics fields.

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.

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).

[Domestic violence during pregnancy and its relationship with birth weight].

PubMed

Valdez-Santiago, R; Sanín-Aguirre, L H

1996-01-01

To determine the prevalence of domestic violence during pregnancy and its impact on birth weight and the immediate post-partum period. We conducted a survey of 110 pregnant women who delivered at the Hospital Civil in Cuernavaca, Morelos. The questionnaire was applied by specialized personal. We used multiple linear regression to adjust for differences between birth weight means and multiple logistic regression for complications. In our study, women who suffered violence during pregnancy had three times more complications during delivery (Cl 95% 1.3-7.9). The difference in birth weight of newborns of these women was 560 g less (p < 0.01 adjusted by age and parity) in comparison with women who did not undergo violence during pregnancy. Women who suffered violence during pregnancy had a four times greater risk for having low birth weight babies (Cl 95% 1.3-12.3) than the non-battered women. We propose more research be done on this topic, including studies of other population groups. Also, health personnel should be educated that violence towards women could constitute a reproductive risk.

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…

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…

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

Passenger comfort during terminal-area flight maneuvers. M.S. Thesis.

NASA Technical Reports Server (NTRS)

Schoonover, W. E., Jr.

1976-01-01

A series of flight experiments was conducted to obtain passenger subjective responses to closely controlled and repeatable flight maneuvers. In 8 test flights, reactions were obtained from 30 passenger subjects to a wide range of terminal-area maneuvers, including descents, turns, decelerations, and combinations thereof. Analysis of the passenger rating variance indicated that the objective of a repeatable flight passenger environment was achieved. Multiple linear regression models developed from the test data were used to define maneuver motion boundaries for specified degrees of passenger acceptance.

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

Automated Pathogenesis-Based Diagnosis of Lumbar Neural Foraminal Stenosis via Deep Multiscale Multitask Learning.

PubMed

Han, Zhongyi; Wei, Benzheng; Leung, Stephanie; Nachum, Ilanit Ben; Laidley, David; Li, Shuo

2018-02-15

Pathogenesis-based diagnosis is a key step to prevent and control lumbar neural foraminal stenosis (LNFS). It conducts both early diagnosis and comprehensive assessment by drawing crucial pathological links between pathogenic factors and LNFS. Automated pathogenesis-based diagnosis would simultaneously localize and grade multiple spinal organs (neural foramina, vertebrae, intervertebral discs) to diagnose LNFS and discover pathogenic factors. The automated way facilitates planning optimal therapeutic schedules and relieving clinicians from laborious workloads. However, no successful work has been achieved yet due to its extreme challenges since 1) multiple targets: each lumbar spine has at least 17 target organs, 2) multiple scales: each type of target organ has structural complexity and various scales across subjects, and 3) multiple tasks, i.e., simultaneous localization and diagnosis of all lumbar organs, are extremely difficult than individual tasks. To address these huge challenges, we propose a deep multiscale multitask learning network (DMML-Net) integrating a multiscale multi-output learning and a multitask regression learning into a fully convolutional network. 1) DMML-Net merges semantic representations to reinforce the salience of numerous target organs. 2) DMML-Net extends multiscale convolutional layers as multiple output layers to boost the scale-invariance for various organs. 3) DMML-Net joins a multitask regression module and a multitask loss module to prompt the mutual benefit between tasks. Extensive experimental results demonstrate that DMML-Net achieves high performance (0.845 mean average precision) on T1/T2-weighted MRI scans from 200 subjects. This endows our method an efficient tool for clinical LNFS diagnosis.

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.

The comparison between several robust ridge regression estimators in the presence of multicollinearity and multiple outliers

NASA Astrophysics Data System (ADS)

Zahari, Siti Meriam; Ramli, Norazan Mohamed; Moktar, Balkiah; Zainol, Mohammad Said

2014-09-01

In the presence of multicollinearity and multiple outliers, statistical inference of linear regression model using ordinary least squares (OLS) estimators would be severely affected and produces misleading results. To overcome this, many approaches have been investigated. These include robust methods which were reported to be less sensitive to the presence of outliers. In addition, ridge regression technique was employed to tackle multicollinearity problem. In order to mitigate both problems, a combination of ridge regression and robust methods was discussed in this study. The superiority of this approach was examined when simultaneous presence of multicollinearity and multiple outliers occurred in multiple linear regression. This study aimed to look at the performance of several well-known robust estimators; M, MM, RIDGE and robust ridge regression estimators, namely Weighted Ridge M-estimator (WRM), Weighted Ridge MM (WRMM), Ridge MM (RMM), in such a situation. Results of the study showed that in the presence of simultaneous multicollinearity and multiple outliers (in both x and y-direction), the RMM and RIDGE are more or less similar in terms of superiority over the other estimators, regardless of the number of observation, level of collinearity and percentage of outliers used. However, when outliers occurred in only single direction (y-direction), the WRMM estimator is the most superior among the robust ridge regression estimators, by producing the least variance. In conclusion, the robust ridge regression is the best alternative as compared to robust and conventional least squares estimators when dealing with simultaneous presence of multicollinearity and outliers.

An improved multiple linear regression and data analysis computer program package

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

Influence of Disruptive Behavior Disorders on Academic Performance and School Functions of Youths with Attention-Deficit/Hyperactivity Disorder.

PubMed

Liu, Chao-Yu; Huang, Wei-Lieh; Kao, Wei-Chih; Gau, Susan Shur-Fen

2017-12-01

Childhood attention-deficit/hyperactivity disorder (ADHD) and comorbid oppositional defiant disorder/conduct disorder (ODD/CD) are associated with negative school outcomes. The study aimed to examine the impact of ADHD and ODD/CD on various school functions. 395 youths with ADHD (244 with ADHD + ODD/CD and 151 with ADHD only) and 156 controls received semi-structured psychiatric interviews. School functions were assessed and compared between each group with a multiple-level model. The results showed that youths with ADHD had poorer performance across different domains of school functioning. Youths with ADHD + ODD/CD had more behavioral problems but similar academic performance than those with ADHD only. The multiple linear regression models revealed that ADHD impaired academic performance while ODD/CD aggravated behavioral problems. Our findings imply that comorbid ODD/CD may specifically contribute to social difficulties in youths with ADHD. Measures of early detection and intervention for ODD/CD should be conducted to prevent adverse outcomes.

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…

Evaluating the relationship between wildfire extent and nitrogen dry deposition in a boreal forest in interior Alaska

NASA Astrophysics Data System (ADS)

Nagano, Hirohiko; Iwata, Hiroki

2017-03-01

Alaska wildfires may play an important role in nitrogen (N) dry deposition in Alaskan boreal forests. Here we used annual N dry deposition data measured by CASTNET at Denali National Park (DEN417) during 1999-2013, to evaluate the relationships between wildfire extent and N dry deposition in Alaska. We established six potential factors for multiple regression analysis, including burned area within 100 km of DEN417 (BA100km) and in other distant parts of Alaska (BAAK), the sum of indexes of North Atlantic Oscillation and Arctic Oscillation (OI), number of days with negative OI (OIday), precipitation (PRCP), and number of days with PRCP (PRCPday). Multiple regression analysis was conducted for both time scales, annual (using only annual values of factors) and six-month (using annual values of BAAK and BA100km, and fire and non-fire seasons' values of other four factors) time scales. Together, BAAK, BA100km, and OIday, along with PRCPday in the case of the six-month scale, explained more than 92% of the interannual variation in N dry deposition. The influence of BA100km on N dry deposition was ten-fold greater than from BAAK; the qualitative contribution was almost zero, however, due to the small BA100km. BAAK was the leading explanatory factor, with a 15 ± 14% contribution. We further calculated N dry deposition during 1950-2013 using the obtained regression equation and long-term records for the factors. The N dry deposition calculated for 1950-2013 revealed that an increased occurrence of wildfires during the 2000s led to the maximum N dry deposition exhibited during this decade. As a result, the effect of BAAK on N dry deposition remains sufficiently large, even when large possible uncertainties (>40%) in the measurement of N dry deposition are taken into account for the multiple regression analysis.

Shift work schedule and night work load: Effects on body mass index - a four-year longitudinal study.

PubMed

Buchvold, Hogne Vikanes; Pallesen, Ståle; Waage, Siri; Bjorvatn, Bjørn

2018-05-01

Objectives The aim of this study was to investigate changes in body mass index (BMI) between different work schedules and different average number of yearly night shifts over a four-year follow-up period. Methods A prospective study of Norwegian nurses (N=2965) with different work schedules was conducted: day only, two-shift rotation (day and evening shifts), three-shift rotation (day, evening and night shifts), night only, those who changed towards night shifts, and those who changed away from schedules containing night shifts. Paired student's t-tests were used to evaluate within subgroup changes in BMI. Multiple linear regression analysis was used to evaluate between groups effects on BMI when adjusting for BMI at baseline, sex, age, marital status, children living at home, and years since graduation. The same regression model was used to evaluate the effect of average number of yearly night shifts on BMI change. Results We found that night workers [mean difference (MD) 1.30 (95% CI 0.70-1.90)], two shift workers [MD 0.48 (95% CI 0.20-0.75)], three shift workers [MD 0.46 (95% CI 0.30-0.62)], and those who changed work schedule away from [MD 0.57 (95% CI 0.17-0.84)] or towards night work [MD 0.63 (95% CI 0.20-1.05)] all had significant BMI gain (P<0.01) during the follow-up period. However, day workers had a non-significant BMI gain. Using adjusted multiple linear regressions, we found that night workers had significantly larger BMI gain compared to day workers [B=0.89 (95% CI 0.06-1.72), P<0.05]. We did not find any significant association between average number of yearly night shifts and BMI change using our multiple linear regression model. Conclusions After adjusting for possible confounders, we found that BMI increased significantly more among night workers compared to day workers.

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.

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.

Audiometric analyses confirm a cochlear component, disproportional to age, in stapedial otosclerosis.

PubMed

Topsakal, Vedat; Fransen, Erik; Schmerber, Sébastien; Declau, Frank; Yung, Matthew; Gordts, Frans; Van Camp, Guy; Van de Heyning, Paul

2006-09-01

To report the preoperative audiometric profile of surgically confirmed otosclerosis. Retrospective, multicenter study. Four tertiary referral centers. One thousand sixty-four surgically confirmed patients with otosclerosis. Therapeutic ear surgery for hearing improvement. Preoperative audiometric air conduction (AC) and bone conduction (BC) hearing thresholds were obtained retrospectively for 1064 patients with otosclerosis. A cross-sectional multiple linear regression analysis was performed on audiometric data of affected ears. Influences of age and sex were analyzed and age-related typical audiograms were created. Bone conduction thresholds were corrected for Carhart effect and presbyacusis; in addition, we tested to see if separate cochlear otosclerosis component existed. Corrected thresholds were than analyzed separately for progression of cochlear otosclerosis. The study population consisted of 35% men and 65% women (mean age, 44 yr). The mean pure-tone average at 0.5, 1, and 2 kHz was 57 dB hearing level. Multiple linear regression analysis showed significant progression for all measured AC and BC thresholds. The average annual threshold deterioration for AC was 0.45 dB/yr and the annual threshold deterioration for BC was 0.37 dB/yr. The average annual gap expansion was 0.08 dB/year. The corrected BC thresholds for Carhart effect and presbyacusis remained significantly different from zero, but only showed progression at 2 kHz. The preoperative audiological profile of otosclerosis is described. There is a significant sensorineural component in patients with otosclerosis planned for stapedotomy, which is worse than age-related hearing loss by itself. Deterioration rates of AC and BC thresholds have been reported, which can be helpful in clinical practice and might also guide the characterization of allegedly different phenotypes for familial and sporadic otosclerosis.

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.

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

PubMed Central

Kim, Seong-Gil

2018-01-01

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

Periodicity analysis of tourist arrivals to Banda Aceh using smoothing SARIMA approach

NASA Astrophysics Data System (ADS)

Miftahuddin, Helida, Desri; Sofyan, Hizir

2017-11-01

Forecasting the number of tourist arrivals who enters a region is needed for tourism businesses, economic and industrial policies, so that the statistical modeling needs to be conducted. Banda Aceh is the capital of Aceh province more economic activity is driven by the services sector, one of which is the tourism sector. Therefore, the prediction of the number of tourist arrivals is needed to develop further policies. The identification results indicate that the data arrival of foreign tourists to Banda Aceh to contain the trend and seasonal nature. Allegedly, the number of arrivals is influenced by external factors, such as economics, politics, and the holiday season caused the structural break in the data. Trend patterns are detected by using polynomial regression with quadratic and cubic approaches, while seasonal is detected by a periodic regression polynomial with quadratic and cubic approach. To model the data that has seasonal effects, one of the statistical methods that can be used is SARIMA (Seasonal Autoregressive Integrated Moving Average). The results showed that the smoothing, a method to detect the trend pattern is cubic polynomial regression approach, with the modified model and the multiplicative periodicity of 12 months. The AIC value obtained was 70.52. While the method for detecting the seasonal pattern is a periodic regression polynomial cubic approach, with the modified model and the multiplicative periodicity of 12 months. The AIC value obtained was 73.37. Furthermore, the best model to predict the number of foreign tourist arrivals to Banda Aceh in 2017 to 2018 is SARIMA (0,1,1)(1,1,0) with MAPE is 26%.

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

PubMed

Kim, Seong-Gil; Kim, Wan-Soo

2018-05-15

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

The association between financial literacy and Problematic Internet Shopping in a multinational sample.

PubMed

Lam, Lawrence T; Lam, Mary K

2017-12-01

To examine the association between financial literacy and Problematic Internet Shopping in adults. This cross-sectional online survey recruited participants, aged between 18 and 60 years, through an online research facility. The sample consisted of multinational participants from mainly three continents including Europe, North America, and Asia. Problematic Internet Shopping was assessed using the Bergen Shopping Addiction Scale (BSAS). Financial Literacy was measured by the Financial Literacy subscale of the Financial Wellbeing Questionnaire. Multiple linear regression analyses were conducted to elucidate the relationship between the study and outcome variables with adjustment for other potential risk factors. Of the total of 997 respondents with an average age of 30.9 (s.d. = 8.8), 135 (13.8%) could be classified as having a high risk of being Problematic Internet Shoppers. Results from the multiple regression analyses suggested a significant and negative relationship between financial literacy and Problematic Internet Shopping with a regression coefficient of - 0.13, after controlling for the effects of potential risk factors such as age, region of birth, employment, income, shopping frequency, self-regulation and anxiety (t = - 6.42, p < 0.001). The clinical management of PIS should include a financial counselling as a component of the treatment regime. Enhancement of financial literacy in the general population, particularly among young people, will likely have a positive effect on the occurrence of PIS.

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws.

PubMed

Xiao, Xiao; White, Ethan P; Hooten, Mevin B; Durham, Susan L

2011-10-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.

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…

Co-occurring psychiatric symptoms in opioid-dependent women: the prevalence of antenatal and postnatal depression.

PubMed

Holbrook, Amber; Kaltenbach, Karol

2012-11-01

Despite the high prevalence of psychiatric symptoms in substance-dependent women, little evidence is available on postpartum depression in this population. To determine whether demographic variables and prenatal depression predict postpartum depression and select substance abuse treatment outcomes in a sample of pregnant women. A retrospective chart review was conducted on 125 pregnant women enrolled in a comprehensive substance abuse treatment program. Data on demographic variables, prenatal care attendance, urine drug screen (UDS) results, and psychiatric symptoms were abstracted from patient medical and substance abuse treatment charts. The Postpartum Depression Screening Scale (PDSS) was administered 6 weeks post-delivery. Multiple linear regression was conducted to identify predictors of prenatal care attendance and total PDSS scores at 6 weeks postpartum. Multiple logistic regression was used to examine predictors of positive UDS at delivery. Nearly one-third (30.4%) of the sample screened positive for moderate or severe depression at treatment entry. Psychiatric symptoms did not predict either prenatal care compliance or UDS results at delivery. Almost half of the sample (43.7%) exhibited postpartum depression at 6 weeks post-delivery. No demographic variables correlated with incidence of postnatal depression. Only antenatal depression at treatment entry predicted PDSS scores. Prevalence of antenatal psychiatric disorders and postpartum depression was high in this sample of women seeking substance abuse treatment. Results support prior history of depression as a predictor of risk for developing postpartum depression. Routine screening for perinatal and postpartum depression is indicated for women diagnosed with substance abuse disorders.

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.

Prevalence of consistent condom use with various types of sex partners and associated factors among money boys in Changsha, China.

PubMed

Wang, Lian-Hong; Yan, Jin; Yang, Guo-Li; Long, Shuo; Yu, Yong; Wu, Xi-Lin

2015-04-01

Money boys with inconsistent condom use (less than 100% of the time) are at high risk of infection by human immunodeficiency virus (HIV) or sexually transmitted infection (STI), but relatively little research has examined their risk behaviors. We investigated the prevalence of consistent condom use (100% of the time) and associated factors among money boys. A cross-sectional study using a structured questionnaire was conducted among money boys in Changsha, China, between July 2012 and January 2013. Independent variables included socio-demographic data, substance abuse history, work characteristics, and self-reported HIV and STI history. Dependent variables included the consistent condom use with different types of sex partners. Among the participants, 82.4% used condoms consistently with male clients, 80.2% with male sex partners, and 77.1% with female sex partners in the past 3 months. A multiple stepwise logistic regression model identified four statistically significant factors associated with lower likelihoods of consistent condom use with male clients: age group, substance abuse, lack of an "employment" arrangement, and having no HIV test within the prior 6 months. In a similar model, only one factor associated significantly with lower likelihoods of consistent condom use with male sex partners was identified in multiple stepwise logistic regression analyses: having no HIV test within the prior six months. As for female sex partners, two significant variables were statistically significant in the multiple stepwise logistic regression analysis: having no HIV test within the prior 6 months and having STI history. Interventions which are linked with more realistic and acceptable HIV prevention methods are greatly warranted and should increase risk awareness and the behavior of consistent condom use in both commercial and personal relationship. © 2015 International Society for Sexual Medicine.

Relationships among personality traits, metabolic syndrome, and metabolic syndrome scores: The Kakegawa cohort study.

PubMed

Ohseto, Hisashi; Ishikuro, Mami; Kikuya, Masahiro; Obara, Taku; Igarashi, Yuko; Takahashi, Satomi; Kikuchi, Daisuke; Shigihara, Michiko; Yamanaka, Chizuru; Miyashita, Masako; Mizuno, Satoshi; Nagai, Masato; Matsubara, Hiroko; Sato, Yuki; Metoki, Hirohito; Tachibana, Hirofumi; Maeda-Yamamoto, Mari; Kuriyama, Shinichi

2018-04-01

Metabolic syndrome and the presence of metabolic syndrome components are risk factors for cardiovascular disease (CVD). However, the association between personality traits and metabolic syndrome remains controversial, and few studies have been conducted in East Asian populations. We measured personality traits using the Japanese version of the Eysenck Personality Questionnaire (Revised Short Form) and five metabolic syndrome components-elevated waist circumference, elevated triglycerides, reduced high-density lipoprotein cholesterol, elevated blood pressure, and elevated fasting glucose-in 1322 participants aged 51.1±12.7years old from Kakegawa city, Japan. Metabolic syndrome score (MS score) was defined as the number of metabolic syndrome components present, and metabolic syndrome as having the MS score of 3 or higher. We performed multiple logistic regression analyses to examine the relationship between personality traits and metabolic syndrome components and multiple regression analyses to examine the relationship between personality traits and MS scores adjusted for age, sex, education, income, smoking status, alcohol use, and family history of CVD and diabetes mellitus. We also examine the relationship between personality traits and metabolic syndrome presence by multiple logistic regression analyses. "Extraversion" scores were higher in those with metabolic syndrome components (elevated waist circumference: P=0.001; elevated triglycerides: P=0.01; elevated blood pressure: P=0.004; elevated fasting glucose: P=0.002). "Extraversion" was associated with the MS score (coefficient=0.12, P=0.0003). No personality trait was significantly associated with the presence of metabolic syndrome. Higher "extraversion" scores were related to higher MS scores, but no personality trait was significantly associated with the presence of metabolic syndrome. Copyright © 2018 Elsevier Inc. All rights reserved.

The relationship of exposure to air pollutants in pregnancy with surrogate markers of endothelial dysfunction in umbilical cord.

PubMed

Poursafa, Parinaz; Baradaran-Mahdavi, Sadegh; Moradi, Bita; Haghjooy Javanmard, Shaghayegh; Tajadini, Mohammadhasan; Mehrabian, Ferdous; Kelishadi, Roya

2016-04-01

This study aims to investigate the association of exposure to ambient air pollution during pregnancy with cord blood concentrations of surrogate markers of endothelial dysfunction. This population-based cohort was conducted from March 2014 to March 2015 among 250 mother-neonate pairs in urban areas of Isfahan, the second large and air-polluted city in Iran. We analyzed the association between the ambient carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), particular matter 10 (PM10), and air quality index (AQI) with cord blood levels of endothelin-1, vascular adhesion molecule (VCAM), and intercellular adhesion molecule (ICAM). Multiple regression analysis was conducted after adjustment for potential confounding factors and covariates. The regression coefficient (beta), standard error of the estimate (SE), and 95% confidence intervals for each regression coefficient (95% CI) are reported. Data of 233 mother-neonate pairs were complete, and included in the analysis. Multiple regression analyses showed that AQI, CO and O3 had significant correlation with cord blood ICAM-1 [Beta (SE), 95%CI: 2.93 (0.72), 1.33,5.54; 2.28(1.44), 1.56,5.12; and 2.02(0.01), 1.03,2.04, respectively] as well as with VCAM-1 [2.78(0.91), 1.69,4.57; 2.47(1.47), 1.43,5.37; and 2.01(0.01),1.07,2.04, respectively]. AQI, PM10, and SO2 were significantly associated with Endothelin-1 concentrations [Beta (SE), 95%CI: 10.16(5.08),7.61,14.28; 9.70(3.46), 2.88,16.52; and 1.07(0.02), 1.03,2.11, respectively]. The significant associations of air pollutants with markers of endothelial dysfunction during fetal period may provide another evidence on the adverse health effects of air pollutants on early stages of atherosclerosis from fetal period. Our findings underscore the importance of considering environmental factors in primordial prevention of chronic diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

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.)

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.

Improved model of the retardance in citric acid coated ferrofluids using stepwise regression

NASA Astrophysics Data System (ADS)

Lin, J. F.; Qiu, X. R.

2017-06-01

Citric acid (CA) coated Fe3O4 ferrofluids (FFs) have been conducted for biomedical application. The magneto-optical retardance of CA coated FFs was measured by a Stokes polarimeter. Optimization and multiple regression of retardance in FFs were executed by Taguchi method and Microsoft Excel previously, and the F value of regression model was large enough. However, the model executed by Excel was not systematic. Instead we adopted the stepwise regression to model the retardance of CA coated FFs. From the results of stepwise regression by MATLAB, the developed model had highly predictable ability owing to F of 2.55897e+7 and correlation coefficient of one. The average absolute error of predicted retardances to measured retardances was just 0.0044%. Using the genetic algorithm (GA) in MATLAB, the optimized parametric combination was determined as [4.709 0.12 39.998 70.006] corresponding to the pH of suspension, molar ratio of CA to Fe3O4, CA volume, and coating temperature. The maximum retardance was found as 31.712°, close to that obtained by evolutionary solver in Excel and a relative error of -0.013%. Above all, the stepwise regression method was successfully used to model the retardance of CA coated FFs, and the maximum global retardance was determined by the use of GA.

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.

Sociocultural and Victimization Factors That Impact Attitudes Toward Intimate Partner Violence Among Kenyan Women.

PubMed

Mugoya, George C T; Witte, Tricia H; Ernst, Kacey C

2015-10-01

This study investigates the association between acceptance of intimate partner violence (IPV) and reported IPV victimization among Kenyan women, taking into consideration select sociocultural factors that may also influence acceptance of IPV. Data from a nationally representative, cross-sectional, household survey conducted between November 2008 and February 2009 in Kenya were analyzed. Hierarchical multiple regression was conducted to estimate the effect of select sociodemographic characteristics and reported IPV victimization on acceptance of IPV. The results showed that while both sociodemographic characteristics and reported IPV victimization were significantly associated with IPV acceptance, sociocultural factors had a greater impact. Programs aimed at empowering women and culturally competent IPV prevention strategies may be the key elements to reducing IPV. © The Author(s) 2014.

Harsh parenting and child externalizing behavior: skin conductance level reactivity as a moderator.

PubMed

Erath, Stephen A; El-Sheikh, Mona; Mark Cummings, E

2009-01-01

Skin conductance level reactivity (SCLR) was examined as a moderator of the association between harsh parenting and child externalizing behavior. Participants were 251 boys and girls (8-9 years). Mothers and fathers provided reports of harsh parenting and their children's externalizing behavior; children also provided reports of harsh parenting. SCLR was assessed in response to a socioemotional stress task and a problem-solving challenge task. Regression analyses revealed that the association between harsh parenting and externalizing behavior was stronger among children with lower SCLR, as compared to children with higher SCLR. SCLR may be a more robust moderator among boys compared to girls. Results are discussed with regard to theories on antisocial behavior and multiple-domain models of child development.

Results of the 2009 AORN salary survey.

PubMed

Bacon, Donald

2009-12-01

AORN conducted its seventh annual compensation survey for perioperative nurses in August of 2009. 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 2009 data 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. Additional analyses explore the effect of the current economic downturn on the perioperative work environment. (c) AORN, Inc, 2009.

Bayesian quantile regression-based partially linear mixed-effects joint models for longitudinal data with multiple features.

PubMed

Zhang, Hanze; Huang, Yangxin; Wang, Wei; Chen, Henian; Langland-Orban, Barbara

2017-01-01

In longitudinal AIDS studies, it is of interest to investigate the relationship between HIV viral load and CD4 cell counts, as well as the complicated time effect. Most of common models to analyze such complex longitudinal data are based on mean-regression, which fails to provide efficient estimates due to outliers and/or heavy tails. Quantile regression-based partially linear mixed-effects models, a special case of semiparametric models enjoying benefits of both parametric and nonparametric models, have the flexibility to monitor the viral dynamics nonparametrically and detect the varying CD4 effects parametrically at different quantiles of viral load. Meanwhile, it is critical to consider various data features of repeated measurements, including left-censoring due to a limit of detection, covariate measurement error, and asymmetric distribution. In this research, we first establish a Bayesian joint models that accounts for all these data features simultaneously in the framework of quantile regression-based partially linear mixed-effects models. The proposed models are applied to analyze the Multicenter AIDS Cohort Study (MACS) data. Simulation studies are also conducted to assess the performance of the proposed methods under different scenarios.

Dysfunctional Metacognitive Beliefs in Body Dysmorphic Disorder

PubMed Central

Zeinodini, Zahra; Sedighi, Sahar; Rahimi, Mandana Baghertork; Noorbakhsh, Simasadat; Esfahani, Sepideh Rajezi

2016-01-01

The present study aims to examine the correlation of body dysmorphic disorder, with metacognitive subscales, metaworry and thought-fusion. The study was conducted in a correlation framework. Sample included 155 high school students in Isfahan, Iran in 2013-2014, gathered through convenience sampling. To gather data about BDD, Yale-Brown Obsessive Compulsive Scale Modified for BDD was applied. Then, Meta Cognitive Questionnaire, Metaworry Questionnaire, and Thought-Fusion Inventory were used to assess metacognitive subscales, metaworry and thought-fusion. Data obtained from this study were analyzed using Pearson correlation and multiple regressions in SPSS 18. Result indicated YBOCS-BDD scores had a significant correlation with scores from MCQ (P<0.05), MWG (P<0.05), and TFI (P<0.05). Also, multiple regressions were run to predict YBOCS from TFI, MWQ, and MCQ-30. These variables significantly predicted YBOCS [F (3,151) =32.393, R2=0.57]. Findings indicated that body dysmorphic disorder was significantly related to metacognitive subscales, metaworry, and thought fusion in high school students in Isfahan, which is in line with previous studies. A deeper understanding of these processes can broaden theory and treatment of BDD, thereby improve the lives of sufferers and potentially protect others from developing this devastating disorder. PMID:26493420

The relationship among self-efficacy, perfectionism and academic burnout in medical school students.

PubMed

Yu, Ji Hye; Chae, Su Jin; Chang, Ki Hong

2016-03-01

The purpose of this study was to examine the relationship among academic self-efficacy, socially-prescribed perfectionism, and academic burnout in medical school students and to determine whether academic self-efficacy had a mediating role in the relationship between perfectionism and academic burnout. A total of 244 first-year and second-year premed medical students and first- to fourth-year medical students were enrolled in this study. As study tools, socially-prescribed perfectionism, academic self-efficacy, and academic burnout scales were utilized. For data analysis, correlation analysis, multiple regression analysis, and hierarchical multiple regression analyses were conducted. Academic burnout had correlation with socially-prescribed perfectionism. It had negative correlation with academic self-efficacy. Socially-prescribed perfectionism and academic self-efficacy had 54% explanatory power for academic burnout. When socially-prescribed perfectionism and academic self-efficacy were simultaneously used as input, academic self-efficacy partially mediated the relationship between socially-prescribed perfectionism and academic burnout. Socially-prescribed perfectionism had a negative effect on academic self-efficacy, ultimately triggering academic burnout. This suggests that it is important to have educational and counseling interventions to improve academic self-efficacy by relieving academic burnout of medical school students.

Motor excitability measurements: the influence of gender, body mass index, age and temperature in healthy controls.

PubMed

Casanova, I; Diaz, A; Pinto, S; de Carvalho, M

2014-04-01

The technique of threshold tracking to test axonal excitability gives information about nodal and internodal ion channel function. We aimed to investigate variability of the motor excitability measurements in healthy controls, taking into account age, gender, body mass index (BMI) and small changes in skin temperature. We examined the left median nerve of 47 healthy controls using the automated threshold-tacking program, QTRAC. Statistical multiple regression analysis was applied to test relationship between nerve excitability measurements and subject variables. Comparisons between genders did not find any significant difference (P>0.2 for all comparisons). Multiple regression analysis showed that motor amplitude decreases with age and temperature, stimulus-response slope decreases with age and BMI, and that accommodation half-time decrease with age and temperature. The changes related to demographic features on TRONDE protocol parameters are small and less important than in conventional nerve conduction studies. Nonetheless, our results underscore the relevance of careful temperature control, and indicate that interpretation of stimulus-response slope and accommodation half-time should take into account age and BMI. In contrast, gender is not of major relevance to axonal threshold findings in motor nerves. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

The relationship among self-efficacy, perfectionism and academic burnout in medical school students

PubMed Central

Yu, Ji Hye; Chae, Su Jin; Chang, Ki Hong

2016-01-01

Purpose: The purpose of this study was to examine the relationship among academic self-efficacy, socially-prescribed perfectionism, and academic burnout in medical school students and to determine whether academic self-efficacy had a mediating role in the relationship between perfectionism and academic burnout. Methods: A total of 244 first-year and second-year premed medical students and first- to fourth-year medical students were enrolled in this study. As study tools, socially-prescribed perfectionism, academic self-efficacy, and academic burnout scales were utilized. For data analysis, correlation analysis, multiple regression analysis, and hierarchical multiple regression analyses were conducted. Results: Academic burnout had correlation with socially-prescribed perfectionism. It had negative correlation with academic self-efficacy. Socially-prescribed perfectionism and academic self-efficacy had 54% explanatory power for academic burnout. When socially-prescribed perfectionism and academic self-efficacy were simultaneously used as input, academic self-efficacy partially mediated the relationship between socially-prescribed perfectionism and academic burnout. Conclusion: Socially-prescribed perfectionism had a negative effect on academic self-efficacy, ultimately triggering academic burnout. This suggests that it is important to have educational and counseling interventions to improve academic self-efficacy by relieving academic burnout of medical school students. PMID:26838568

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.

An Optimization of Inventory Demand Forecasting in University Healthcare Centre

NASA Astrophysics Data System (ADS)

Bon, A. T.; Ng, T. K.

2017-01-01

Healthcare industry becomes an important field for human beings nowadays as it concerns about one’s health. With that, forecasting demand for health services is an important step in managerial decision making for all healthcare organizations. Hence, a case study was conducted in University Health Centre to collect historical demand data of Panadol 650mg for 68 months from January 2009 until August 2014. The aim of the research is to optimize the overall inventory demand through forecasting techniques. Quantitative forecasting or time series forecasting model was used in the case study to forecast future data as a function of past data. Furthermore, the data pattern needs to be identified first before applying the forecasting techniques. Trend is the data pattern and then ten forecasting techniques are applied using Risk Simulator Software. Lastly, the best forecasting techniques will be find out with the least forecasting error. Among the ten forecasting techniques include single moving average, single exponential smoothing, double moving average, double exponential smoothing, regression, Holt-Winter’s additive, Seasonal additive, Holt-Winter’s multiplicative, seasonal multiplicative and Autoregressive Integrated Moving Average (ARIMA). According to the forecasting accuracy measurement, the best forecasting technique is regression analysis.

Factors associated with discontinuation of aripiprazole treatment after switching from other antipsychotics in patients with chronic schizophrenia: A prospective observational study.

PubMed

Takaesu, Yoshikazu; Kishimoto, Taishiro; Murakoshi, Akiko; Takahashi, Nobutada; Inoue, Yuichi

2016-02-28

The purpose of the study was to identify factors associated with discontinuation of aripiprazole after switching from other antipsychotics in patients with schizophrenia in real world clinical settings. From January 2011 to December 2012, a prospective, 48-week open-label study was undertaken. Thirty-eight subjects on antipsychotic monotherapy were switched to aripiprazole. Patients who discontinued aripiprazole were compared to those who continued with regards to demographic characteristics as well as treatment factors. Multiple regression analysis was conducted to identify predictors for aripiprazole discontinuation. Thirteen out of 38 patients (34.2%) discontinued aripiprazole during the follow up period. Nine patients (23.7%) discontinued aripiprazole due to worsening of psychotic symptoms. Multiple logistic regression analysis revealed that only the duration of previous antipsychotic treatment was associated with aripiprazole discontinuation after switching to aripiprazole. The receiver operating curve (ROC) analysis identified that the cut-off length for duration of illness to predict aripiprazole discontinuation was 10.5 years. Longer duration of illness was associated with aripiprazole discontinuation. Greater caution may be required when treating such patients with aripiprazole. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

[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.

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

Neutropenia is independently associated with sub-therapeutic serum concentration of vancomycin.

PubMed

Choi, Min Hyuk; Choe, Yeon Hwa; Lee, Sang-Guk; Jeong, Seok Hoon; Kim, Jeong-Ho

2017-02-01

We aimed to identify the impact of the presence of neutropenia on serum vancomycin concentration (SVC). A retrospective study was conducted from January 2005 to December 2015. The study population was comprised of adult patients who were performed serum concentration of vancomycin. Patients with renal failure or using non-conventional dosages of vancomycin were excluded. A total of 1307 adult patients were included in this study, of whom 163 (12.4%) were neutropenic. Patients with neutropenia presented significantly lower SVCs than non-neutropenic patients (P<0.0001). Multiple linear regressions showed significant association between neutropenia and trough SVC (beta coefficients, -2.351; P=0.004). Multiple logistic regression analysis also revealed a significant association between sub-therapeutic vancomycin concentrations (trough SVC values<10mg/l) and neutropenia (odds ratio, 1.75, P=0.029) CONCLUSIONS: The presence of neutropenia is significantly associated with low SVC, even after adjusting for other variables. Therefore, neutropenic patients had a higher risk of sub-therapeutic SVC compared with non-neutropenic patients. We recommended that vancomycin therapy should be monitored with TDM-guided optimization of dosage and intervals, especially in neutropenic patients. Copyright © 2016 Elsevier B.V. All rights reserved.

[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.

Analyzing the association between fish consumption and osteoporosis in a sample of Chinese men.

PubMed

Li, Xia; Lei, Tao; Tang, Zihui; Dong, Jingcheng

2017-04-19

The main purpose of this study was to estimate the associations between frequency of fish food consumption and osteoporosis (OP) in general Chinese men. We conducted a large-scale, community-based, cross-sectional study to investigate the associations by using self-report questionnaire to access frequency of fish food intake. A total of 1092 men were available for data analysis in this study. Multiple regression models controlling for confounding factors to include frequency of fish food consumption variable were performed to investigate the relationships for OP. Positive correlations between frequency of fish food consumption and T score were reported (β = 0.084, P value = 0.025). Multiple regression analysis indicated that the frequency of fish food consumption was significantly associated with OP (P < 0.05 for model 1 and model 2). The men with high frequency of fish food consumption had a lower prevalence of OP. The findings indicated that frequency of fish food consumption was independently and significantly associated with OP. The prevalence of OP was less frequent in Chinese men preferring fish food habits. ClinicalTrials.gov Identifier: NCT02451397 retrospectively registered 28 May 2015.

Barriers to pelvic floor physical therapy utilization for treatment of female urinary incontinence.

PubMed

Washington, Blair B; Raker, Christina A; Sung, Vivian W

2011-08-01

The purpose of this study was to estimate the effect of insurance status on pelvic floor physical therapy (PFPT) nonparticipation for the treatment of urinary incontinence. A cross-sectional study of women referred to PFPT for urinary incontinence between January 2009 and June 2010 was conducted. A telephone questionnaire was administered. Multiple logistic regression was used to identify risk factors for nonparticipation. Thirty-three percent of women with private insurance and 17% with other insurance were PFPT nonparticipants. On multiple logistic regression, women with Medicare were more likely to participate in PFPT (odds ratio [OR], 0.12; 95% confidence interval [CI], 0.01-0.72). Risk factors for nonparticipation included insurance noncoverage (OR, 103.85; 95% CI, 6.21-infinity) and a negative perception regarding the benefit of PFPT (OR, 5.07; 95% CI, 2.16-12.49). Among women who were referred to PFPT for urinary incontinence, insurance noncoverage and negative patient perception of efficacy were risk factors for nonparticipation, although having Medicare was protective. Improving patient education and insurance coverage for PFPT may increase usage. Copyright © 2011 Mosby, Inc. All rights reserved.

The use of regression analysis in determining reference intervals for low hematocrit and thrombocyte count in multiple electrode aggregometry and platelet function analyzer 100 testing of platelet function.

PubMed

Kuiper, Gerhardus J A J M; Houben, Rik; Wetzels, Rick J H; Verhezen, Paul W M; Oerle, Rene van; Ten Cate, Hugo; Henskens, Yvonne M C; Lancé, Marcus D

2017-11-01

Low platelet counts and hematocrit levels hinder whole blood point-of-care testing of platelet function. Thus far, no reference ranges for MEA (multiple electrode aggregometry) and PFA-100 (platelet function analyzer 100) devices exist for low ranges. Through dilution methods of volunteer whole blood, platelet function at low ranges of platelet count and hematocrit levels was assessed on MEA for four agonists and for PFA-100 in two cartridges. Using (multiple) regression analysis, 95% reference intervals were computed for these low ranges. Low platelet counts affected MEA in a positive correlation (all agonists showed r 2 ≥ 0.75) and PFA-100 in an inverse correlation (closure times were prolonged with lower platelet counts). Lowered hematocrit did not affect MEA testing, except for arachidonic acid activation (ASPI), which showed a weak positive correlation (r 2 = 0.14). Closure time on PFA-100 testing was inversely correlated with hematocrit for both cartridges. Regression analysis revealed different 95% reference intervals in comparison with originally established intervals for both MEA and PFA-100 in low platelet or hematocrit conditions. Multiple regression analysis of ASPI and both tests on the PFA-100 for combined low platelet and hematocrit conditions revealed that only PFA-100 testing should be adjusted for both thrombocytopenia and anemia. 95% reference intervals were calculated using multiple regression analysis. However, coefficients of determination of PFA-100 were poor, and some variance remained unexplained. Thus, in this pilot study using (multiple) regression analysis, we could establish reference intervals of platelet function in anemia and thrombocytopenia conditions on PFA-100 and in thrombocytopenia conditions on MEA.

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.

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...

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

Periodontal disease in Chinese patients with systemic lupus erythematosus.

PubMed

Zhang, Qiuxiang; Zhang, Xiaoli; Feng, Guijaun; Fu, Ting; Yin, Rulan; Zhang, Lijuan; Feng, Xingmei; Li, Liren; Gu, Zhifeng

2017-08-01

Disease of systemic lupus erythematosus (SLE) and periodontal disease (PD) shares the common multiple characteristics. The aims of the present study were to evaluate the prevalence and severity of periodontal disease in Chinese SLE patients and to determine the association between SLE features and periodontal parameters. A cross-sectional study of 108 SLE patients together with 108 age- and sex-matched healthy controls was made. Periodontal status was conducted by two dentists independently. Sociodemographic characteristics, lifestyle factors, medication use, and clinical parameters were also assessed. The periodontal status was significantly worse in SLE patients compared to controls. In univariate logistic regression, SLE had a significant 2.78-fold [95% confidence interval (CI) 1.60-4.82] increase in odds of periodontitis compared to healthy controls. Adjusted for potential risk factors, patients with SLE had 13.98-fold (95% CI 5.10-38.33) increased odds against controls. In multiple linear regression model, the independent variable negatively and significantly associated with gingival index was education (P = 0.005); conversely, disease activity (P < 0.001) and plaque index (P = 0.002) were positively associated; Age was the only variable independently associated with periodontitis of SLE in multivariate logistic regression (OR 1.348; 95% CI: 1.183-1.536, P < 0.001). Chinese SLE patients were likely to suffer from higher odds of PD. These findings confirmed the importance of early interventions in combination with medical therapy. It is necessary for a close collaboration between dentists and clinicians when treating those patients.

Protective Effect of HLA-DQB1 Alleles Against Alloimmunization in Patients with Sickle Cell Disease

PubMed Central

Tatari-Calderone, Zohreh; Gordish-Dressman, Heather; Fasano, Ross; Riggs, Michael; Fortier, Catherine; Andrew; Campbell, D.; Charron, Dominique; Gordeuk, Victor R.; Luban, Naomi L.C.; Vukmanovic, Stanislav; Tamouza, Ryad

2015-01-01

Background Alloimmunization or the development of alloantibodies to Red Blood Cell (RBC) antigens is considered one of the major complications after RBC transfusions in patients with sickle cell disease (SCD) and can lead to both acute and delayed hemolytic reactions. It has been suggested that polymorphisms in HLA genes, may play a role in alloimmunization. We conducted a retrospective study analyzing the influence of HLA-DRB1 and DQB1 genetic diversity on RBC-alloimmunization. Study design Two-hundred four multi-transfused SCD patients with and without RBC-alloimmunization were typed at low/medium resolution by PCR-SSO, using IMGT-HLA Database. HLA-DRB1 and DQB1 allele frequencies were analyzed using logistic regression models, and global p-value was calculated using multiple logistic regression. Results While only trends towards associations between HLA-DR diversity and alloimmunization were observed, analysis of HLA-DQ showed that HLA-DQ2 (p=0.02), -DQ3 (p=0.02) and -DQ5 (p=0.01) alleles were significantly higher in non-alloimmunized patients, likely behaving as protective alleles. In addition, multiple logistic regression analysis showed both HLA-DQ2/6 (p=0.01) and HLA-DQ5/5 (p=0.03) combinations constitute additional predictor of protective status. Conclusion Our data suggest that particular HLA-DQ alleles influence the clinical course of RBC transfusion in patients with SCD, which could pave the way towards predictive strategies. PMID:26476208

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.

Simple and multiple linear regression: sample size considerations.

PubMed

Hanley, James A

2016-11-01

The suggested "two subjects per variable" (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression. This article distinguishes two of the major uses of regression models that imply very different sample size considerations, neither served well by the 2SPV rule. The first is etiological research, which contrasts mean Y levels at differing "exposure" (X) values and thus tends to focus on a single regression coefficient, possibly adjusted for confounders. The second research genre guides clinical practice. It addresses Y levels for individuals with different covariate patterns or "profiles." It focuses on the profile-specific (mean) Y levels themselves, estimating them via linear compounds of regression coefficients and covariates. By drawing on long-established closed-form variance formulae that lie beneath the standard errors in multiple regression, and by rearranging them for heuristic purposes, one arrives at quite intuitive sample size considerations for both research genres. Copyright © 2016 Elsevier Inc. All rights reserved.

Physiological and Psychological Predictors of Short-Term Disability in Workers with a History of Low Back Pain: A Longitudinal Study

PubMed Central

Dubois, Jean-Daniel; Cantin, Vincent; Piché, Mathieu; Descarreaux, Martin

2016-01-01

Despite an elusive pathophysiology, common characteristics are often observed in individuals with chronic low back pain (LBP). These include psychological symptoms, altered pain perception, altered pain modulation and altered muscle activation. These factors have been explored as possible determinants of disability, either separately or in cross-sectional studies, but were never assessed in a single longitudinal study. Therefore, the objective was to determine the relative contribution of psychological and neurophysiological factors to future disability in individuals with past LBP. The study included two experimental sessions (baseline and six months later) to assess cutaneous heat pain and pain tolerance thresholds, pain inhibition, as well as trunk muscle activation. Both sessions included the completion of validated questionnaires to determine clinical pain, disability, pain catastrophizing, fear-avoidance beliefs and pain vigilance. One hundred workers with a history of LBP and 19 healthy individuals took part in the first experimental session. The second experimental session was exclusively conducted on workers with a history of LBP (77/100). Correlation analyses between initial measures and disability at six months were conducted, and measures significantly associated with disability were used in multiple regression analyses. A first regression analysis showed that psychological symptoms contributed unique variance to future disability (R2 = 0.093, p = .009). To control for the fluctuating nature of LBP, a hierarchical regression was conducted while controlling for clinical pain at six months (R2 = 0.213, p < .001) where pain inhibition contributed unique variance in the second step of the regression (R2 change = 0.094, p = .005). These results indicate that pain inhibition processes may constitute potential targets for treatment to alleviate future disability in individuals with past or present LBP. Then again, the link between psychological symptoms and pain inhibition needs to be clarified as both of these factors are linked together and influence disability in their own way. PMID:27783666

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)

Explanation of the variance in quality of life and activity capacity of patients with heart failure by laboratory data.

PubMed

Athanasopoulos, Leonidas V; Dritsas, Athanasios; Doll, Helen A; Cokkinos, Dennis V

2010-08-01

This study was conducted to explain the variance in quality of life (QoL) and activity capacity of patients with congestive heart failure from pathophysiological changes as estimated by laboratory data. Peak oxygen consumption (peak VO2) and ventilation (VE)/carbon dioxide output (VCO2) slope derived from cardiopulmonary exercise testing, plasma N-terminal prohormone of B-type natriuretic peptide (NT-proBNP), and echocardiographic markers [left atrium (LA), left ventricular ejection fraction (LVEF)] were measured in 62 patients with congestive heart failure, who also completed the Minnesota Living with Heart Failure Questionnaire and the Specific Activity Questionnaire. All regression models were adjusted for age and sex. On linear regression analysis, peak VO2 with P value less than 0.001, VE/VCO2 slope with P value less than 0.01, LVEF with P value less than 0.001, LA with P=0.001, and logNT-proBNP with P value less than 0.01 were found to be associated with QoL. On stepwise multiple linear regression, peak VO2 and LVEF continued to be predictive, accounting for 40% of the variability in Minnesota Living with Heart Failure Questionnaire score. On linear regression analysis, peak VO2 with P value less than 0.001, VE/VCO2 slope with P value less than 0.001, LVEF with P value less than 0.05, LA with P value less than 0.001, and logNT-proBNP with P value less than 0.001 were found to be associated with activity capacity. On stepwise multiple linear regression, peak VO2 and LA continued to be predictive, accounting for 53% of the variability in Specific Activity Questionnaire score. Peak VO2 is independently associated both with QoL and activity capacity. In addition to peak VO2, LVEF is independently associated with QoL, and LA with activity capacity.

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.

A comparison of two microscale laboratory reporting methods in a secondary chemistry classroom

NASA Astrophysics Data System (ADS)

Martinez, Lance Michael

This study attempted to determine if there was a difference between the laboratory achievement of students who used a modified reporting method and those who used traditional laboratory reporting. The study also determined the relationships between laboratory performance scores and the independent variables score on the Group Assessment of Logical Thinking (GALT) test, chronological age in months, gender, and ethnicity for each of the treatment groups. The study was conducted using 113 high school students who were enrolled in first-year general chemistry classes at Pueblo South High School in Colorado. The research design used was the quasi-experimental Nonequivalent Control Group Design. The statistical treatment consisted of the Multiple Regression Analysis and the Analysis of Covariance. Based on the GALT, students in the two groups were generally in the concrete and transitional stages of the Piagetian cognitive levels. The findings of the study revealed that the traditional and the modified methods of laboratory reporting did not have any effect on the laboratory performance outcome of the subjects. However, the students who used the traditional method of reporting showed a higher laboratory performance score when evaluation was conducted using the New Standards rubric recommended by the state. Multiple Regression Analysis revealed that there was a significant relationship between the criterion variable student laboratory performance outcome of individuals who employed traditional laboratory reporting methods and the composite set of predictor variables. On the contrary, there was no significant relationship between the criterion variable student laboratory performance outcome of individuals who employed modified laboratory reporting methods and the composite set of predictor variables.

Changes in Perceived Filial Obligation Norms Among Coresident Family Caregivers in Japan

PubMed Central

Tsutsui, Takako; Muramatsu, Naoko; Higashino, Sadanori

2014-01-01

Purpose of the Study: Japan introduced a nationwide long-term care insurance (LTCI) system in 2000, making long-term care (LTC) a right for older adults regardless of income and family availability. To shed light on its implications for family caregiving, we investigated perceived filial obligation norms among coresident primary family caregivers before and after the policy change. Design and Methods: Descriptive and multiple regression analyses were conducted to examine changes in perceived filial obligation norms and its subdimensions (financial, physical, and emotional support), using 2-wave panel survey data of coresident primary family caregivers (N = 611) in 1 city. The baseline survey was conducted in 1999, and a follow-up survey 2 years later. Results: On average, perceived filial obligation norms declined (p < .05). Daughters-in-law had the most significant declines (global and physical: p < .01, emotional: p < .05) among family caregivers. In particular, physical support, which Japan’s LTC reform targeted, declined significantly among daughters and daughters-in-law (p < .01). Multiple regression analysis indicated that daughters-in-law had significantly lower perceived filial obligation norms after the policy introduction than sons and daughters (p < .01 and p < .05, respectively), controlling for the baseline filial obligation and situational factors. Implications: Our research indicates declining roles of daughters-in-law in elder care during Japan’s LTCI system implementation period. Further international efforts are needed to design and implement longitudinal studies that help promote understanding of the interplay among national LTC policies, social changes, and caregiving norms and behaviors. PMID:24009170

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%).

Prediction of human core body temperature using non-invasive measurement methods.

PubMed

Niedermann, Reto; Wyss, Eva; Annaheim, Simon; Psikuta, Agnes; Davey, Sarah; Rossi, René Michel

2014-01-01

The measurement of core body temperature is an efficient method for monitoring heat stress amongst workers in hot conditions. However, invasive measurement of core body temperature (e.g. rectal, intestinal, oesophageal temperature) is impractical for such applications. Therefore, the aim of this study was to define relevant non-invasive measures to predict core body temperature under various conditions. We conducted two human subject studies with different experimental protocols, different environmental temperatures (10 °C, 30 °C) and different subjects. In both studies the same non-invasive measurement methods (skin temperature, skin heat flux, heart rate) were applied. A principle component analysis was conducted to extract independent factors, which were then used in a linear regression model. We identified six parameters (three skin temperatures, two skin heat fluxes and heart rate), which were included for the calculation of two factors. The predictive value of these factors for core body temperature was evaluated by a multiple regression analysis. The calculated root mean square deviation (rmsd) was in the range from 0.28 °C to 0.34 °C for all environmental conditions. These errors are similar to previous models using non-invasive measures to predict core body temperature. The results from this study illustrate that multiple physiological parameters (e.g. skin temperature and skin heat fluxes) are needed to predict core body temperature. In addition, the physiological measurements chosen in this study and the algorithm defined in this work are potentially applicable as real-time core body temperature monitoring to assess health risk in broad range of working conditions.

The influence of consumers' preferences and perceptions of oral solid dosage forms on their treatment.

PubMed

Ibrahim, Inas Rifaat; Ibrahim, Mohamed Izham Mohamed; Al-Haddad, Mahmoud Sa'di

2012-10-01

Beyond the direct pharmacological effect of medicines, preferences and perceptions toward a particular oral solid dosage form (OSDF) play a crucial role in recovery and may reduce adherence to the prescribed treatment. This study conducted to investigate the most preferred OSDF and the degree to which swallowing solid medication is an issue, to assess perceptions of the therapeutic benefits of the OSDF, and to find predictors of the most preferred OSDF. A cross-sectional study, through convenience sample method, was conducted to survey consumers visiting community pharmacies in Baghdad, Iraq. Data was collected by self-administered and pre-piloted questionnaires, and analyzed using Statistical Package for Social Science. Multiple logistic regression analysis and Chi-square tests were used at alpha level = 0.05. A total of 1,000 questionnaire were included in the analysis. Of all respondents, 52.9 % preferred capsule among other OSDF and this preference varied significantly with a number of socio-demographic factors. Ease of swallowing solid medication was the main issue which resulted in preferences for a particular form. A negative perception of the therapeutic benefits of the OSDF was found among 89.1 % of the consumers. Multiple logistic regression analysis indicated that gender, ease of swallowing, and perceptions of the therapeutic benefits of the OSDF were significant predictors of capsule preferences. Given the fact that consumers are the end users of medicines and their preferences may influence response to the treatment, efforts are worthwhile by the prescribers and medicines' manufactures to understand consumers' preferences of a particular dosage form in order to achieve successful therapy outcomes.

Changes in perceived filial obligation norms among coresident family caregivers in Japan.

PubMed

Tsutsui, Takako; Muramatsu, Naoko; Higashino, Sadanori

2014-10-01

Japan introduced a nationwide long-term care insurance (LTCI) system in 2000, making long-term care (LTC) a right for older adults regardless of income and family availability. To shed light on its implications for family caregiving, we investigated perceived filial obligation norms among coresident primary family caregivers before and after the policy change. Descriptive and multiple regression analyses were conducted to examine changes in perceived filial obligation norms and its subdimensions (financial, physical, and emotional support), using 2-wave panel survey data of coresident primary family caregivers (N = 611) in 1 city. The baseline survey was conducted in 1999, and a follow-up survey 2 years later. On average, perceived filial obligation norms declined (p < .05). Daughters-in-law had the most significant declines (global and physical: p < .01, emotional: p < .05) among family caregivers. In particular, physical support, which Japan's LTC reform targeted, declined significantly among daughters and daughters-in-law (p < .01). Multiple regression analysis indicated that daughters-in-law had significantly lower perceived filial obligation norms after the policy introduction than sons and daughters (p < .01 and p < .05, respectively), controlling for the baseline filial obligation and situational factors. Our research indicates declining roles of daughters-in-law in elder care during Japan's LTCI system implementation period. Further international efforts are needed to design and implement longitudinal studies that help promote understanding of the interplay among national LTC policies, social changes, and caregiving norms and behaviors. © The Author 2013. Published by Oxford University Press on behalf of The Gerontological Society of America.

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.

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)

Psychological factors influence the gastroesophageal reflux disease (GERD) and their effect on quality of life among firefighters in South Korea.

PubMed

Jang, Seung-Ho; Ryu, Han-Seung; Choi, Suck-Chei; Lee, Sang-Yeol

2016-10-01

The purpose of this study was to examine psychosocial factors related to gastroesophageal reflux disease (GERD) and their effects on quality of life (QOL) in firefighters. Data were collected from 1217 firefighters in a Korean province. We measured psychological symptoms using the scale. In order to observe the influence of the high-risk group on occupational stress, we conduct logistic multiple linear regression. The correlation between psychological factors and QOL was also analyzed and performed a hierarchical regression analysis. GERD was observed in 32.2% of subjects. Subjects with GERD showed higher depressive symptom, anxiety and occupational stress scores, and lower self-esteem and QOL scores relative to those observed in GERD - negative subject. GERD risk was higher for the following occupational stress subcategories: job demand, lack of reward, interpersonal conflict, and occupational climate. The stepwise regression analysis showed that depressive symptoms, occupational stress, self-esteem, and anxiety were the best predictors of QOL. The results suggest that psychological and medical approaches should be combined in GERD assessment.

Psychological factors influence the gastroesophageal reflux disease (GERD) and their effect on quality of life among firefighters in South Korea

PubMed Central

Jang, Seung-Ho; Ryu, Han-Seung; Choi, Suck-Chei; Lee, Sang-Yeol

2016-01-01

Objectives The purpose of this study was to examine psychosocial factors related to gastroesophageal reflux disease (GERD) and their effects on quality of life (QOL) in firefighters. Methods Data were collected from 1217 firefighters in a Korean province. We measured psychological symptoms using the scale. In order to observe the influence of the high-risk group on occupational stress, we conduct logistic multiple linear regression. The correlation between psychological factors and QOL was also analyzed and performed a hierarchical regression analysis. Results GERD was observed in 32.2% of subjects. Subjects with GERD showed higher depressive symptom, anxiety and occupational stress scores, and lower self-esteem and QOL scores relative to those observed in GERD – negative subject. GERD risk was higher for the following occupational stress subcategories: job demand, lack of reward, interpersonal conflict, and occupational climate. The stepwise regression analysis showed that depressive symptoms, occupational stress, self-esteem, and anxiety were the best predictors of QOL. Conclusions The results suggest that psychological and medical approaches should be combined in GERD assessment. PMID:27691373

Mathematical models application for mapping soils spatial distribution on the example of the farm from the North of Udmurt Republic of Russia

NASA Astrophysics Data System (ADS)

Dokuchaev, P. M.; Meshalkina, J. L.; Yaroslavtsev, A. M.

2018-01-01

Comparative analysis of soils geospatial modeling using multinomial logistic regression, decision trees, random forest, regression trees and support vector machines algorithms was conducted. The visual interpretation of the digital maps obtained and their comparison with the existing map, as well as the quantitative assessment of the individual soil groups detection overall accuracy and of the models kappa showed that multiple logistic regression, support vector method, and random forest models application with spatial prediction of the conditional soil groups distribution can be reliably used for mapping of the study area. It has shown the most accurate detection for sod-podzolics soils (Phaeozems Albic) lightly eroded and moderately eroded soils. In second place, according to the mean overall accuracy of the prediction, there are sod-podzolics soils - non-eroded and warp one, as well as sod-gley soils (Umbrisols Gleyic) and alluvial soils (Fluvisols Dystric, Umbric). Heavy eroded sod-podzolics and gray forest soils (Phaeozems Albic) were detected by methods of automatic classification worst of all.

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws

USGS Publications Warehouse

Xiao, X.; White, E.P.; Hooten, M.B.; Durham, S.L.

2011-01-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain. ?? 2011 by the Ecological Society of America.

A comparison of multiple imputation methods for incomplete longitudinal binary data.

PubMed

Yamaguchi, Yusuke; Misumi, Toshihiro; Maruo, Kazushi

2018-01-01

Longitudinal binary data are commonly encountered in clinical trials. Multiple imputation is an approach for getting a valid estimation of treatment effects under an assumption of missing at random mechanism. Although there are a variety of multiple imputation methods for the longitudinal binary data, a limited number of researches have reported on relative performances of the methods. Moreover, when focusing on the treatment effect throughout a period that has often been used in clinical evaluations of specific disease areas, no definite investigations comparing the methods have been available. We conducted an extensive simulation study to examine comparative performances of six multiple imputation methods available in the SAS MI procedure for longitudinal binary data, where two endpoints of responder rates at a specified time point and throughout a period were assessed. The simulation study suggested that results from naive approaches of a single imputation with non-responders and a complete case analysis could be very sensitive against missing data. The multiple imputation methods using a monotone method and a full conditional specification with a logistic regression imputation model were recommended for obtaining unbiased and robust estimations of the treatment effect. The methods were illustrated with data from a mental health research.

Clinical Pharmacology Quality Assurance (CPQA) Program: Models for Longitudinal Analysis of Antiretroviral (ARV) Proficiency Testing for International Laboratories

PubMed Central

DiFrancesco, Robin; Rosenkranz, Susan L.; Taylor, Charlene R.; Pande, Poonam G.; Siminski, Suzanne M.; Jenny, Richard W.; Morse, Gene D.

2013-01-01

Among National Institutes of Health (NIH) HIV Research Networks conducting multicenter trials, samples from protocols that span several years are analyzed at multiple clinical pharmacology laboratories (CPLs) for multiple antiretrovirals (ARV). Drug assay data are, in turn, entered into study-specific datasets that are used for pharmacokinetic analyses, merged to conduct cross-protocol pharmacokinetic analysis and integrated with pharmacogenomics research to investigate pharmacokinetic-pharmacogenetic associations. The CPLs participate in a semi-annual proficiency testing (PT) program implemented by the Clinical Pharmacology Quality Assurance (CPQA) program. Using results from multiple PT rounds, longitudinal analyses of recovery are reflective of accuracy and precision within/across laboratories. The objectives of this longitudinal analysis of PT across multiple CPLs were to develop and test statistical models that longitudinally: (1)assess the precision and accuracy of concentrations reported by individual CPLs; (2)determine factors associated with round-specific and long-term assay accuracy, precision and bias using a new regression model. A measure of absolute recovery is explored as a simultaneous measure of accuracy and precision. Overall, the analysis outcomes assured 97% accuracy (±20% of the final target concentration of all (21)drug concentration results reported for clinical trial samples by multiple CPLs).Using the CLIA acceptance of meeting criteria for ≥2/3 consecutive rounds, all ten laboratories that participated in three or more rounds per analyte maintained CLIA proficiency. Significant associations were present between magnitude of error and CPL (Kruskal Wallis [KW]p<0.001), and ARV (KW p<0.001). PMID:24052065

Clinical pharmacology quality assurance program: models for longitudinal analysis of antiretroviral proficiency testing for international laboratories.

PubMed

DiFrancesco, Robin; Rosenkranz, Susan L; Taylor, Charlene R; Pande, Poonam G; Siminski, Suzanne M; Jenny, Richard W; Morse, Gene D

2013-10-01

Among National Institutes of Health HIV Research Networks conducting multicenter trials, samples from protocols that span several years are analyzed at multiple clinical pharmacology laboratories (CPLs) for multiple antiretrovirals. Drug assay data are, in turn, entered into study-specific data sets that are used for pharmacokinetic analyses, merged to conduct cross-protocol pharmacokinetic analysis, and integrated with pharmacogenomics research to investigate pharmacokinetic-pharmacogenetic associations. The CPLs participate in a semiannual proficiency testing (PT) program implemented by the Clinical Pharmacology Quality Assurance program. Using results from multiple PT rounds, longitudinal analyses of recovery are reflective of accuracy and precision within/across laboratories. The objectives of this longitudinal analysis of PT across multiple CPLs were to develop and test statistical models that longitudinally: (1) assess the precision and accuracy of concentrations reported by individual CPLs and (2) determine factors associated with round-specific and long-term assay accuracy, precision, and bias using a new regression model. A measure of absolute recovery is explored as a simultaneous measure of accuracy and precision. Overall, the analysis outcomes assured 97% accuracy (±20% of the final target concentration of all (21) drug concentration results reported for clinical trial samples by multiple CPLs). Using the Clinical Laboratory Improvement Act acceptance of meeting criteria for ≥2/3 consecutive rounds, all 10 laboratories that participated in 3 or more rounds per analyte maintained Clinical Laboratory Improvement Act proficiency. Significant associations were present between magnitude of error and CPL (Kruskal-Wallis P < 0.001) and antiretroviral (Kruskal-Wallis P < 0.001).

Dose-response relationships between internally-deposited uranium and select health outcomes in gaseous diffusion plant workers, 1948-2011.

PubMed

Yiin, James H; Anderson, Jeri L; Bertke, Stephen J; Tollerud, David J

2018-05-09

To examine dose-response relationships between internal uranium exposures and select outcomes among a cohort of uranium enrichment workers. Cox regression was conducted to examine associations between selected health outcomes and cumulative internal uranium with consideration for external ionizing radiation, work-related medical X-rays and contaminant radionuclides technetium ( 99 Tc) and plutonium ( 239 Pu) as potential confounders. Elevated and monotonically increasing mortality risks were observed for kidney cancer, chronic renal diseases, and multiple myeloma, and the association with internal uranium absorbed organ dose was statistically significant for multiple myeloma. Adjustment for potential confounders had minimal impact on the risk estimates. Kidney cancer, chronic renal disease, and multiple myeloma mortality risks were elevated with increasing internal uranium absorbed organ dose. The findings add to evidence of an association between internal exposure to uranium and cancer. Future investigation includes a study of cancer incidence in this cohort. © 2018 Wiley Periodicals, Inc.

Predictors of hopelessness among clinically depressed youth.

PubMed

Becker-Weidman, Emily G; Reinecke, Mark A; Jacobs, Rachel H; Martinovich, Zoran; Silva, Susan G; March, John S

2009-05-01

Factors that distinguish depressed individuals who become hopeless from those who do not are poorly understood. In this study, predictors of hopelessness were examined in a sample of 439 clinically depressed adolescents participating in the Treatment for Adolescents with Depression Study (TADS). The total score of the Beck Hopelessness Scale (BHS) was used to assess hopelessness at baseline. Multiple regression and logistic regression analyses were conducted to evaluate the extent to which variables were associated with hopelessness and determine which cluster of measures best predicted clinically significantly hopelessness. Hopelessness was associated with greater depression severity, poor social problem-solving, cognitive distortions, and family conflict. View of self, view of the world, internal attributional style, need for social approval, positive problem-solving orientation, and family problems consistently emerged as the best predictors of hopelessness in depressed youth. Cognitive and familial factors predict those depressed youth who have high levels of hopelessness.

Modeling the language learning strategies and English language proficiency of pre-university students in UMS: A case study

NASA Astrophysics Data System (ADS)

Kiram, J. J.; Sulaiman, J.; Swanto, S.; Din, W. A.

2015-10-01

This study aims to construct a mathematical model of the relationship between a student's Language Learning Strategy usage and English Language proficiency. Fifty-six pre-university students of University Malaysia Sabah participated in this study. A self-report questionnaire called the Strategy Inventory for Language Learning was administered to them to measure their language learning strategy preferences before they sat for the Malaysian University English Test (MUET), the results of which were utilised to measure their English language proficiency. We attempted the model assessment specific to Multiple Linear Regression Analysis subject to variable selection using Stepwise regression. We conducted various assessments to the model obtained, including the Global F-test, Root Mean Square Error and R-squared. The model obtained suggests that not all language learning strategies should be included in the model in an attempt to predict Language Proficiency.

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.

E-cigarette Dual Users, Exclusive Users and Perceptions of Tobacco Products.

PubMed

Cooper, Maria; Case, Kathleen R; Loukas, Alexandra; Creamer, Melisa R; Perry, Cheryl L

2016-01-01

We examined differences in the characteristics of youth non-users, cigarette-only, e-cigarette-only, and dual e-cigarette and cigarette users. Using weighted, representative data, logistic regression analyses were conducted to examine differences in demographic characteristics and tobacco use behaviors across tobacco usage groups. Multiple linear regression analyses were conducted to examine differences in harm perceptions of various tobacco products and perceived peer use of e-cigarettes by tobacco usage group. Compared to non-users, dual users were more likely to be white, male, and high school students. Dual users had significantly higher prevalence of current use of all products (except hookah) than e-cigarette-only users, and higher prevalence of current use of snus and hookah than the cigarette-only group. Dual users had significantly lower harm perceptions for all tobacco products except for e-cigarettes and hookah as compared to e-cigarette-only users. Dual users reported higher peer use of cigarettes as compared to both exclusive user groups. Findings highlight dual users' higher prevalence of use of most other tobacco products, their lower harm perceptions of most tobacco products compared to e-cigarette-only users, and their higher perceived peer use of cigarettes compared to exclusive users.

The association between season of pregnancy and birth-sex among Chinese.

PubMed

Xu, Tan; Lin, Dongdong; Liang, Hui; Chen, Mei; Tong, Weijun; Mu, Yongping; Feng, Cindy Xin; Gao, Yongqing; Zheng, Yumei; Sun, Wenjie

2014-08-11

although numerous studies have reported the association between birth season and sex ratio, few studies have been conducted in subtropical regions in a non-Western setting. The present study assessed the effects of pregnancy season on birth sex ratio in China. We conducted a national population-based retrospective study from 2006-2008 with 3175 children-parents pairs enrolled in the Northeast regions of China. Demographics and data relating to pregnancy and birth were collected and analyzed. A multiple logistical regression model was fitted to estimate the regression coefficient and 95% confidence interval (CI) of refractive error for mother pregnancy season, adjusting for potential confounders. After adjusting for parental age (cut-off point was 30 years), region, nationality, mother education level, and mother miscarriage history, there is a significant statistical different mother pregnancy season on birth-sex. Compared with mothers who were pregnant in spring, those pregnant in summer or winter had a high probability of delivering girls (p < 0.05). The birth-sex ratio varied with months. Our results suggested that mothers pregnant in summer and winter were more likely to deliver girls, compared with those pregnant in spring. Pregnancy season may play an important role in the birth-sex.

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.

Deriving percentage study weights in multi-parameter meta-analysis models: with application to meta-regression, network meta-analysis and one-stage individual participant data models.

PubMed

Riley, Richard D; Ensor, Joie; Jackson, Dan; Burke, Danielle L

2017-01-01

Many meta-analysis models contain multiple parameters, for example due to multiple outcomes, multiple treatments or multiple regression coefficients. In particular, meta-regression models may contain multiple study-level covariates, and one-stage individual participant data meta-analysis models may contain multiple patient-level covariates and interactions. Here, we propose how to derive percentage study weights for such situations, in order to reveal the (otherwise hidden) contribution of each study toward the parameter estimates of interest. We assume that studies are independent, and utilise a decomposition of Fisher's information matrix to decompose the total variance matrix of parameter estimates into study-specific contributions, from which percentage weights are derived. This approach generalises how percentage weights are calculated in a traditional, single parameter meta-analysis model. Application is made to one- and two-stage individual participant data meta-analyses, meta-regression and network (multivariate) meta-analysis of multiple treatments. These reveal percentage study weights toward clinically important estimates, such as summary treatment effects and treatment-covariate interactions, and are especially useful when some studies are potential outliers or at high risk of bias. We also derive percentage study weights toward methodologically interesting measures, such as the magnitude of ecological bias (difference between within-study and across-study associations) and the amount of inconsistency (difference between direct and indirect evidence in a network meta-analysis).

[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.

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…

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…

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…

The Normative Environment for Drug Use: Comparisons among American Indian and White Adolescents

PubMed Central

Dieterich, Sara E.; Swaim, Randall C.; Beauvais, Fred

2013-01-01

The present study examined the influence of descriptive norms, injunctive norms, perceived outcome expectancies, and ethnicity on marijuana and inhalant use among 2334 American Indian and white high school students who lived on or near reservations in the United States. Hierarchical multiple regression analyses were conducted with survey data collected during the 2009-2010 and 2010-2011 school years. Results suggest differences between ethnicities in the influence of the normative environment and outcome expectancies on both marijuana and inhalant use. Study limitations are noted, and future research is suggested. PMID:23768429

Results of the 2012 AORN salary and compensation survey.

PubMed

Bacon, Donald R

2012-12-01

AORN conducted its 10th annual compensation survey for perioperative nurses in June 2012. A multiple regression model was used to examine how a number of variables, including job title, education level, certification, experience, and geographic region, affect nurse compensation. Comparisons between the 2012 data and previous years' data are presented. The effects of other forms of compensation, such as on-call compensation, overtime, bonuses, and shift differentials on base compensation rates, also are examined. Additional analyses explore the effect of the current economic downturn on the perioperative work environment. Copyright © 2012 AORN, Inc. Published by Elsevier Inc. All rights reserved.

Results of the 2016 AORN Salary and Compensation Survey.

PubMed

Bacon, Donald R; Stewart, Kim A

2016-12-01

AORN conducted its 14th annual compensation survey for perioperative nurses in June 2016. A multiple regression model was used to examine how several variables, including job title, education level, certification, experience, and geographic region, affect nurse compensation. Comparisons between the 2016 data and data from previous years are presented. The effects of other forms of compensation (eg, on-call compensation, overtime, bonuses, shift differentials, benefits) on base compensation rates also are examined. Additional analyses explore the effect of the economic downturn on the perioperative work environment. Copyright © 2016 AORN, Inc. Published by Elsevier Inc. All rights reserved.

Results of the 2013 AORN Salary and Compensation Survey.

PubMed

Bacon, Donald R; Stewart, Kim A

2013-12-01

AORN conducted its 11th annual compensation survey for perioperative nurses in June 2013. A multiple regression model was used to examine how a number of variables, including job title, education level, certification, experience, and geographic region affect nurse compensation. Comparisons among the 2013 data and previous years' data are presented. The effects of other forms of compensation, such as on-call compensation, overtime, bonuses, and shift differentials on base compensation rates are also examined. Additional analyses explore the effect of the current economic downturn on the perioperative work environment. Copyright © 2013 AORN, Inc. Published by Elsevier Inc. All rights reserved.

Results of the 2017 AORN Salary and Compensation Survey.

PubMed

Bacon, Donald R; Stewart, Kim A

2017-12-01

AORN conducted its 15th annual compensation survey for perioperative nurses in June 2017. A multiple regression model was used to examine how several variables, including job title, educational level, certification, experience, and geographic region, affect nurse compensation. Comparisons between the 2017 data and data from previous years are presented. The effects of other forms of compensation (eg, on-call compensation, overtime, bonuses, shift differentials, benefits) on base compensation rates are examined. Additional analyses explore the current state of the nursing shortage and the sources of job satisfaction and dissatisfaction. Copyright © 2017 AORN, Inc. Published by Elsevier Inc. All rights reserved.

Results of the 2010 AORN Salary and Compensation Survey.

PubMed

Bacon, Donald

2010-12-01

AORN conducted its eighth annual compensation survey for perioperative nurses in June and July 2010. A multiple regression model was used to examine how a number of variables, including job title, education level, certification, experience, and geographic region, affect nurse compensation. Comparisons between the 2010 data and data from previous years are presented. The effects of other forms of compensation, such as on-call compensation, overtime, bonuses, and shift differentials, on base compensation rates are also examined. Additional analyses explore the effect of the current economic downturn on the perioperative work environment. Published by Elsevier Inc. All rights reserved.

Infant malnutrition predicts conduct problems in adolescents

PubMed Central

Galler, Janina R.; Bryce, Cyralene P.; Waber, Deborah P.; Hock, Rebecca S.; Harrison, Robert; Eaglesfield, G. David; Fitzmaurice, Garret

2013-01-01

Objectives The purpose of this study was to compare the prevalence of conduct problems in a well-documented sample of Barbadian adolescents malnourished as infants and a demographic comparison group and to determine the extent to which cognitive impairment and environmental factors account for this association. Methods Behavioral symptoms were assessed using a 76-item self-report scale in 56 Barbadian youth (11–17 years of age) with histories of protein–energy malnutrition (PEM) limited to the first year of life and 60 healthy classmates. Group comparisons were carried out by longitudinal and cross-sectional multiple regression analyses at 3 time points in childhood and adolescence. Results Self-reported conduct problems were more prevalent among previously malnourished youth (P < 0.01). Childhood IQ and home environmental circumstances partially mediated the association with malnutrition. Teacher-reported classroom behaviors at earlier ages were significantly correlated with youth conduct problems, confirming the continuity of conduct problems through childhood and adolescence. Discussion Self-reported conduct problems are elevated in children and adolescents with histories of early childhood malnutrition. Later vulnerability to increased conduct problems appears to be mediated by the more proximal neurobehavioral effects of the malnutrition on cognitive function and by adverse conditions in the early home environment. PMID:22584048

Infant malnutrition predicts conduct problems in adolescents.

PubMed

Galler, Janina R; Bryce, Cyralene P; Waber, Deborah P; Hock, Rebecca S; Harrison, Robert; Eaglesfield, G David; Fitzmaurice, Garret

2012-07-01

The purpose of this study was to compare the prevalence of conduct problems in a well-documented sample of Barbadian adolescents malnourished as infants and a demographic comparison group and to determine the extent to which cognitive impairment and environmental factors account for this association. Behavioral symptoms were assessed using a 76-item self-report scale in 56 Barbadian youth (11-17 years of age) with histories of protein-energy malnutrition (PEM) limited to the first year of life and 60 healthy classmates. Group comparisons were carried out by longitudinal and cross-sectional multiple regression analyses at 3 time points in childhood and adolescence. Self-reported conduct problems were more prevalent among previously malnourished youth (P < 0.01). Childhood IQ and home environmental circumstances partially mediated the association with malnutrition. Teacher-reported classroom behaviors at earlier ages were significantly correlated with youth conduct problems, confirming the continuity of conduct problems through childhood and adolescence. Self-reported conduct problems are elevated in children and adolescents with histories of early childhood malnutrition. Later vulnerability to increased conduct problems appears to be mediated by the more proximal neurobehavioral effects of the malnutrition on cognitive function and by adverse conditions in the early home environment.

Depression is a predictor for balance in people with multiple sclerosis.

PubMed

Alghwiri, Alia A; Khalil, Hanan; Al-Sharman, Alham; El-Salem, Khalid

2018-05-26

Balance impairments are common and multifactorial among people with multiple sclerosis (MS). Depression is the most common psychological disorder in MS population and is strongly correlated with MS disease. Depression might be one of the factors that contribute to balance deficits in this population. However, the relationship between depression and balance impairments has not been explored in people with MS. To investigate the association between depression and balance impairments in people with MS. Cross sectional design was used in patients with MS. The Activities-specific Balance Confidence scale (ABC) and Berg Balance Scale (BBS) was used to assess balance. Beck Depression Inventory (BDI-II) was used to quantify depression and Kurtizki Expanded Disability Status Scale (EDSS) was utilized for the evaluation of MS disability severity. Pearson correlation coefficient was used to examine the association between depression and balance measurements. Multiple linear stepwise regressions were also conducted to find out if depression is a potential predictor for balance deficits. Seventy-five individuals with MS (Female = 69%) with a mean age (SD) of 38.8 (10) and a mean (SD) EDSS score of 3.0 (1.4) were recruited in this study. Depression was present in 53% of the patients. Depression was significantly correlated with balance measurements and EDSS. However, multiple linear stepwise regressions found that only depression and age significantly predict balance. Depression and balance were found frequent and associated in people with MS. Importantly depression was a significant predictor for balance impairments in individuals with MS. Balance rehabilitation may be hindered by depression. Therefore, depression should be evaluated and treated properly in individuals with MS. Copyright © 2018 Elsevier B.V. All rights reserved.

The relationship between employment and health and health care among working-age adults with and without disabilities in the United States.

PubMed

Reichard, Amanda; Stransky, Michelle; Brucker, Debra; Houtenville, Andrew

2018-05-20

To better understand the relationship between employment and health and health care for people with disabilities in the United States (US). We pooled US Medical Expenditure Panel Survey (2004-2010) data to examine health status, and access to health care among working-age adults, comparing people with physical disabilities or multiple disabilities to people without disabilities, based on their employment status. Logistic regression and least squares regression were conducted, controlling for sociodemographics, health insurance (when not the outcome), multiple chronic conditions, and need for assistance. Employment was inversely related to access to care, insurance, and obesity. Yet, people with disabilities employed in the past year reported better general and mental health than their peers with the same disabilities who were not employed. Those who were employed were more likely to have delayed/forgone necessary care, across disability groups. Part-time employment, especially for people with multiple limitations, was associated with better health and health care outcomes than full-time employment. Findings highlight the importance of addressing employment-related causes of delayed or foregone receipt of necessary care (e.g., flex-time for attending appointments) that exist for all workers, especially those with physical or multiple disabilities. Implications for rehabilitation These findings demonstrate that rehabilitation professionals who are seeking to support employment for persons with physical limitations need to ensure that overall health concerns are adequately addressed, both for those seeking employment and for those who are currently employed. Assisting clients in prioritizing health equally with employment can ensure that both areas receive sufficient attention. Engaging with employers to develop innovative practices to improve health, health behaviors and access to care for employees with disabilities can decrease turnover, increase productivity, and ensure longer job tenure.

Temporal trend and climate factors of hemorrhagic fever with renal syndrome epidemic in Shenyang City, China

PubMed Central

2011-01-01

Background Hemorrhagic fever with renal syndrome (HFRS) is an important infectious disease caused by different species of hantaviruses. As a rodent-borne disease with a seasonal distribution, external environmental factors including climate factors may play a significant role in its transmission. The city of Shenyang is one of the most seriously endemic areas for HFRS. Here, we characterized the dynamic temporal trend of HFRS, and identified climate-related risk factors and their roles in HFRS transmission in Shenyang, China. Methods The annual and monthly cumulative numbers of HFRS cases from 2004 to 2009 were calculated and plotted to show the annual and seasonal fluctuation in Shenyang. Cross-correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on HFRS transmission and the autocorrelation of monthly HFRS cases. Principal component analysis was constructed by using climate data from 2004 to 2009 to extract principal components of climate factors to reduce co-linearity. The extracted principal components and autocorrelation terms of monthly HFRS cases were added into a multiple regression model called principal components regression model (PCR) to quantify the relationship between climate factors, autocorrelation terms and transmission of HFRS. The PCR model was compared to a general multiple regression model conducted only with climate factors as independent variables. Results A distinctly declining temporal trend of annual HFRS incidence was identified. HFRS cases were reported every month, and the two peak periods occurred in spring (March to May) and winter (November to January), during which, nearly 75% of the HFRS cases were reported. Three principal components were extracted with a cumulative contribution rate of 86.06%. Component 1 represented MinRH0, MT1, RH1, and MWV1; component 2 represented RH2, MaxT3, and MAP3; and component 3 represented MaxT2, MAP2, and MWV2. The PCR model was composed of three principal components and two autocorrelation terms. The association between HFRS epidemics and climate factors was better explained in the PCR model (F = 446.452, P < 0.001, adjusted R2 = 0.75) than in the general multiple regression model (F = 223.670, P < 0.000, adjusted R2 = 0.51). Conclusion The temporal distribution of HFRS in Shenyang varied in different years with a distinctly declining trend. The monthly trends of HFRS were significantly associated with local temperature, relative humidity, precipitation, air pressure, and wind velocity of the different previous months. The model conducted in this study will make HFRS surveillance simpler and the control of HFRS more targeted in Shenyang. PMID:22133347

Binding affinity toward human prion protein of some anti-prion compounds - Assessment based on QSAR modeling, molecular docking and non-parametric ranking.

PubMed

Kovačević, Strahinja; Karadžić, Milica; Podunavac-Kuzmanović, Sanja; Jevrić, Lidija

2018-01-01

The present study is based on the quantitative structure-activity relationship (QSAR) analysis of binding affinity toward human prion protein (huPrP C ) of quinacrine, pyridine dicarbonitrile, diphenylthiazole and diphenyloxazole analogs applying different linear and non-linear chemometric regression techniques, including univariate linear regression, multiple linear regression, partial least squares regression and artificial neural networks. The QSAR analysis distinguished molecular lipophilicity as an important factor that contributes to the binding affinity. Principal component analysis was used in order to reveal similarities or dissimilarities among the studied compounds. The analysis of in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) parameters was conducted. The ranking of the studied analogs on the basis of their ADMET parameters was done applying the sum of ranking differences, as a relatively new chemometric method. The main aim of the study was to reveal the most important molecular features whose changes lead to the changes in the binding affinities of the studied compounds. Another point of view on the binding affinity of the most promising analogs was established by application of molecular docking analysis. The results of the molecular docking were proven to be in agreement with the experimental outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

Extreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Cao, Faxian; Yang, Zhijing; Ren, Jinchang; Ling, Wing-Kuen; Zhao, Huimin; Marshall, Stephen

2017-12-01

Although the sparse multinomial logistic regression (SMLR) has provided a useful tool for sparse classification, it suffers from inefficacy in dealing with high dimensional features and manually set initial regressor values. This has significantly constrained its applications for hyperspectral image (HSI) classification. In order to tackle these two drawbacks, an extreme sparse multinomial logistic regression (ESMLR) is proposed for effective classification of HSI. First, the HSI dataset is projected to a new feature space with randomly generated weight and bias. Second, an optimization model is established by the Lagrange multiplier method and the dual principle to automatically determine a good initial regressor for SMLR via minimizing the training error and the regressor value. Furthermore, the extended multi-attribute profiles (EMAPs) are utilized for extracting both the spectral and spatial features. A combinational linear multiple features learning (MFL) method is proposed to further enhance the features extracted by ESMLR and EMAPs. Finally, the logistic regression via the variable splitting and the augmented Lagrangian (LORSAL) is adopted in the proposed framework for reducing the computational time. Experiments are conducted on two well-known HSI datasets, namely the Indian Pines dataset and the Pavia University dataset, which have shown the fast and robust performance of the proposed ESMLR framework.

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.

BAYESIAN LARGE-SCALE MULTIPLE REGRESSION WITH SUMMARY STATISTICS FROM GENOME-WIDE ASSOCIATION STUDIES1

PubMed Central

Zhu, Xiang; Stephens, Matthew

2017-01-01

Bayesian methods for large-scale multiple regression provide attractive approaches to the analysis of genome-wide association studies (GWAS). For example, they can estimate heritability of complex traits, allowing for both polygenic and sparse models; and by incorporating external genomic data into the priors, they can increase power and yield new biological insights. However, these methods require access to individual genotypes and phenotypes, which are often not easily available. Here we provide a framework for performing these analyses without individual-level data. Specifically, we introduce a “Regression with Summary Statistics” (RSS) likelihood, which relates the multiple regression coefficients to univariate regression results that are often easily available. The RSS likelihood requires estimates of correlations among covariates (SNPs), which also can be obtained from public databases. We perform Bayesian multiple regression analysis by combining the RSS likelihood with previously proposed prior distributions, sampling posteriors by Markov chain Monte Carlo. In a wide range of simulations RSS performs similarly to analyses using the individual data, both for estimating heritability and detecting associations. We apply RSS to a GWAS of human height that contains 253,288 individuals typed at 1.06 million SNPs, for which analyses of individual-level data are practically impossible. Estimates of heritability (52%) are consistent with, but more precise, than previous results using subsets of these data. We also identify many previously unreported loci that show evidence for association with height in our analyses. Software is available at https://github.com/stephenslab/rss. PMID:29399241

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.

Socioeconomic disparities and chronic respiratory diseases in Thailand: The National Socioeconomics Survey.

PubMed

Luenam, Amornrat; Laohasiriwong, Wongsa; Puttanapong, Nattapong; Saengsuwan, Jiamjit; Phajan, Teerasak

2018-05-10

This study aimed to determine the association between socioeconomic determinants and Chronic Respiratory Diseases (CRDs) in Thailand. The data were used from the National Socioeconomics Survey (NSS), a cross-sectional study conducted by the National Statistical Office (NSO), in 2010 and 2012. The survey used stratified two-stage sampling to select a nationally representative sample to respond to a structured questionnaire. A total of 17,040 and 16,905 individuals in 2010 and 2012, respectively, were included in this analysis. Multiple logistic regressions were used to identify the association between socioeconomic factors while controlling for other covariates. The prevalence of CRDs was 3.81% and 2.79% in 2010 and 2012, respectively. The bivariate analysis indicated that gender, family size, geographic location, fuels used for cooking and smoking were significantly associated with CRDs in 2010, whereas education, family size, occupation, region, geographic location, and smoking were significantly associated with CRDs in 2012. Both in 2010 and 2012, the multiple logistic regression indicated that the odds of having CRDs were significantly higher among those who lived in urban areas, females, those aged ≥41-50 or ≥61 yr old, and smokers when controlling for other covariates. However, fuels used for cooking, wood and gas, are associated with CRDs in 2010.

Delta neutrophil index: A reliable marker to differentiate perforated appendicitis from non-perforated appendicitis in the elderly.

PubMed

Shin, Dong Hyuk; Cho, Young Suk; Kim, Yoon Sung; Ahn, Hee Cheol; Oh, Young Taeck; Park, Sang O; Won, Moo-Ho; Cho, Jun Hwi; Kim, Young Myeong; Seo, Jeong Yeol; Lee, Young Hwan

2018-01-01

Delta neutrophil index (DNI) is a new inflammatory marker and the present study aimed to evaluate the predictive value of the DNI for the presence of a perforation in elderly with acute appendicitis. This retrospective observational study was conducted on 108 consecutive elderly patients (≥65 years old) with acute appendicitis treated over a 24-month period. Sixty-nine of the 108 patients (median, IQR: 72, 67-77 years) were allocated to the perforated appendicitis group (63.9%) and 39 to the non-perforated appendicitis group (36.1%). WBC, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio and DNI were significantly higher in the perforated group. In multiple logistic regression analyses, initial DNI was the only independent marker that can significantly predict the presence of perforation in multiple regression [odds ratio 9.38, 95% confidence interval (2.51-35.00), P=.001]. Receiver operator characteristic curve analysis showed that DNI is a good predictor for the presence of appendiceal perforation at an optimal cut-off for DNI being 1.4% (sensitivity 67.7%, specificity 90.0%, AUC 0.807). Clinicians can reliably differentiate acute perforated appendicitis from non-perforated appendicitis by DNI level of 1.4 or more in elderly patients. © 2017 Wiley Periodicals, Inc.

Maternal and perinatal outcomes in pregnancies with multiple sclerosis: a case-control study.

PubMed

Yalcin, Serenat Eris; Yalcin, Yakup; Yavuz, And; Akkurt, Mehmet Ozgur; Sezik, Mekin

2017-05-24

To assess whether maternal multiple sclerosis (MS) is associated with adverse pregnancy outcomes by determining the clinical course of disease during pregnancy and postpartum throughout a 10-year-period in a single tertiary center. We conducted a case-control study that included pregnancies with a definitive diagnosis of MS (n=43), matched with 100 healthy pregnant women with similar characteristics. Maternal and perinatal data were retrieved from hospital files. Groups were compared with the Mann-Whitney and χ2 tests. Logistic regression models were constructed to determine independent effects. Maternal demographic and baseline laboratory data were similar across the groups. Rates of preterm delivery, fetal growth restriction, preeclampsia, gestational diabetes, stillbirth, cesarean delivery, congenital malformation, and 5-min Apgar score were comparable (P>0.05 for all). General anesthesia during cesarean delivery (96% vs. 39%, P=0.002), urinary tract infection (UTI) (12% vs. 3%, P=0.04), low 1-min Apgar score (21% vs. 9%, P=0.04), and nonbreastfeeding (33% vs. 2%, P=0.001) were more frequent in women with MS. The low 1-min Apgar score and breastfeeding rates were independent of general anesthesia and UTI in regression models. MS during pregnancy was not associated with adverse maternal and perinatal outcomes except UTI, low 1-min Apgar scores, and decreased breastfeeding rates.

Relation between trinucleotide GAA repeat length and sensory neuropathy in Friedreich's ataxia.

PubMed

Santoro, L; De Michele, G; Perretti, A; Crisci, C; Cocozza, S; Cavalcanti, F; Ragno, M; Monticelli, A; Filla, A; Caruso, G

1999-01-01

To verify if GAA expansion size in Friedreich's ataxia could account for the severity of sensory neuropathy. Retrospective study of 56 patients with Friedreich's ataxia selected according to homozygosity for GAA expansion and availability of electrophysiological findings. Orthodromic sensory conduction velocity in the median nerve was available in all patients and that of the tibial nerve in 46 of them. Data of sural nerve biopsy and of a morphometric analysis were available in 12 of the selected patients. The sensory action potential amplitude at the wrist (wSAP) and at the medial malleolus (m mal SAP) and the percentage of myelinated fibres with diameter larger than 7, 9, and 11 microm in the sural nerve were correlated with disease duration and GAA expansion size on the shorter (GAA1) and larger (GAA2) expanded allele in each pair. Pearson's correlation test and stepwise multiple regression were used for statistical analysis. A significant inverse correlation between GAA1 size and wSAP, m mal SAP, and percentage of myelinated fibres was found. Stepwise multiple regression showed that GAA1 size significantly affects electrophysiological and morphometric data, whereas duration of disease has no effect. The data suggest that the severity of the sensory neuropathy is probably genetically determined and that it is not progressive.

Internal versus External Dose for Describing Ternary Metal Mixture (Ni, Cu, Cd) Chronic Toxicity to Lemna minor.

PubMed

Gopalapillai, Yamini; Hale, Beverley A

2017-05-02

Simultaneous determinations of internal dose ([M] tiss ) and external doses ([M] tot , {M 2+ } in solution) were conducted to study ternary mixture (Ni, Cu, Cd) chronic toxicity to Lemna minor in alkaline solution (pH 8.3). Also, concentration addition (CA) based on internal dose was evaluated as a tool for risk assessment of metal mixture. Multiple regression analysis of dose versus root growth inhibition, as well as saturation binding kinetics, provided insight into interactions. Multiple regressions were simpler for [M] tiss than [M] tot and {M 2+ }, and along with saturation kinetics to the internal biotic ligand(s) in the cytoplasm, they indicated that Ni-Cu-Cd competed for uptake into plant, but once inside, only Cu-Cd shared a binding site. Copper inorganic complexes (hydroxides, carbonates) played a role in metal bioavailability in single metal exposure but not in mixtures. Regardless of interactions, the current regulatory approach of using CA based on [M] tot can sufficiently predict mixture toxicity (∑TU close to 1), but CA based on [M] tiss was closest to unity across a range of doses. Internal dose integrates all metal-metal interactions in solution and during uptake into the organism, thereby providing a more direct metric describing toxicity.

Bioavailability of atrazine, pyrene and benzo[a]pyrene in European river waters

USGS Publications Warehouse

Akkanen, J.; Penttinen, S.; Haitzer, M.; Kukkonen, J.V.K.

2001-01-01

Thirteen river waters and one humic lake water were characterized. The effects of dissolved organic matter (DOM) on the bioavailability of atrazine, pyrene and benzo[a]pyrene (B[a]P) was evaluated. Binding of the chemicals by DOM was analyzed with the equilibrium dialysis technique. For each of the water samples, 24 h bioconcentration factors (BCFs) of the chemicals were measured in Daphnia magna. The relationship between DOM and other water characteristics (including conductivity, water hardness and pH), and bioavailability of the chemicals was studied by performing several statistical analyses, including multiple regression analyses, to determine how much of the variation of BCF values could be explained by the quantity and quality of DOM. The bioavailability of atrazine was not affected by DOM or any other water characteristics. Although equilibrium dialysis showed binding of pyrene to DOM, the bioavailability of pyrene was not significantly affected by DOM. The bioavailability of B[a]P was significantly affected by both the quality and quantity of DOM. Multiple regression analyses, using the quality (ABS270 and HbA%) and quantity of DOM as variables, explainedup to 70% of the variation in BCF of B[a]P in the waters studied. ?? 2001 Elsevier Science 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 &…

Latent Variable Regression 4-Level Hierarchical Model Using Multisite Multiple-Cohorts Longitudinal Data. CRESST Report 801

ERIC Educational Resources Information Center

Choi, Kilchan

2011-01-01

This report explores a new latent variable regression 4-level hierarchical model for monitoring school performance over time using multisite multiple-cohorts longitudinal data. This kind of data set has a 4-level hierarchical structure: time-series observation nested within students who are nested within different cohorts of students. These…

What Is Wrong with ANOVA and Multiple Regression? Analyzing Sentence Reading Times with Hierarchical Linear Models

ERIC Educational Resources Information Center

Richter, Tobias

2006-01-01

Most reading time studies using naturalistic texts yield data sets characterized by a multilevel structure: Sentences (sentence level) are nested within persons (person level). In contrast to analysis of variance and multiple regression techniques, hierarchical linear models take the multilevel structure of reading time data into account. They…

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…

A Spreadsheet Tool for Learning the Multiple Regression F-Test, T-Tests, and Multicollinearity

ERIC Educational Resources Information Center

Martin, David

2008-01-01

This note presents a spreadsheet tool that allows teachers the opportunity to guide students towards answering on their own questions related to the multiple regression F-test, the t-tests, and multicollinearity. The note demonstrates approaches for using the spreadsheet that might be appropriate for three different levels of statistics classes,…

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…

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

Determinants of postnatal care utilization in urban community among women in Debre Birhan Town, Northern Shewa, Ethiopia.

PubMed

Angore, Banchalem Nega; Tufa, Efrata Girma; Bisetegen, Fithamlak Solomon

2018-04-19

Reducing maternal mortality and improving maternal health care through increased utilization of postnatal care utilization is a global and local priority. However studies that have been carried out in Ethiopia regarding determinants are limited. So This study aims to assess the magnitude of postnatal care utilization and its determinants in Debre Birhan Town, North Ethiopia. A community-based cross-sectional study was conducted from March 1 to April 25, 2015, in Debre Birhan Town. Data were collected through face-to-face interviews using structured pre-tested questionnaires. The data were entered and cleaned in Epi Info version 3.5 and analyzed using SPSS version 20. Bivariate and multiple logistic regression analyses were used. Variable with p value less than or equal to 0.2 at bivariate analysis were entered into multiple logistic regression. Significance was declared at 0.05 in multiple logistic regressions and considered to be an independent factor. From the total respondents, we found that 327 (83.3%) mothers utilized the postnatal care services. Single mothers were less likely to utilize postnatal care services than those mothers who are married and live together [adjusted odds ratio (AOR) = 0.06, 95% CI (0.01, 0.45)]. This study revealed that respondent's knowledge about postnatal care services is an important predictor of postnatal care utilization [AOR = 0.03, 95% CI (0.00, 0.44)] and mothers who delivered in a health care facility were more likely to receive PNC than mothers who did not deliver in a health care facility [AOR = 0.65, 95% CI (0.58, 0.94)]. The postnatal care utilization rate in Debre Birhan town was 83.3%. Marital status, maternal knowledge, and place of delivery were predictors of postnatal care service utilization. So specific attention should be directed towards the improvement of women's education since the perception of the need for PNC services were positively correlated with the mother's education.

The base rates and factors associated with reported access to firearms in psychiatric inpatients.

PubMed

Kolla, Bhanu Prakash; O'Connor, Stephen S; Lineberry, Timothy W

2011-01-01

The aim of this study was to define whether specific patient demographic groups, diagnoses or other factors are associated with psychiatric inpatients reporting firearms access. A retrospective medical records review study was conducted using information on access to firearms from electronic medical records for all patients 16 years and older admitted between July 2007 and May 2008 at the Mayo Clinic Psychiatric Hospital in Rochester, MN. Data were obtained only on patients providing authorization for record review. Data were analyzed using univariate and multivariate logistic regression analyses accounting for gender, diagnostic groups, comorbid substance use, history of suicide attempts and family history of suicide/suicide attempts. Seventy-four percent (1169/1580) of patients provided research authorization. The ratio of men to women was identical in both research and nonresearch authorization groups. There were 14.6% of inpatients who reported firearms access. In univariate analysis, men were more likely (P<.0001) to report access than women, and a history of previous suicide attempt(s) was associated with decreased access (P=.02). Multiple logistic regression analyses controlling for other factors found females and patients with history of previous suicide attempt(s) less likely to report access, while patients with a family history of suicide or suicide attempts reported increased firearms access. Diagnostic groups were not associated with access on univariate or multiple logistic regression analyses. Men and inpatients with a family history of suicide/suicide attempts were more likely to report firearms access. Clinicians should develop standardized systems of identification of firearms access and provide guidance on removal. Copyright © 2011 Elsevier Inc. All rights reserved.

A multiple linear regression analysis of factors affecting the simulated Basic Life Support (BLS) performance with Automated External Defibrillator (AED) in Flemish lifeguards.

PubMed

Iserbyt, Peter; Schouppe, Gilles; Charlier, Nathalie

2015-04-01

Research investigating lifeguards' performance of Basic Life Support (BLS) with Automated External Defibrillator (AED) is limited. Assessing simulated BLS/AED performance in Flemish lifeguards and identifying factors affecting this performance. Six hundred and sixteen (217 female and 399 male) certified Flemish lifeguards (aged 16-71 years) performed BLS with an AED on a Laerdal ResusciAnne manikin simulating an adult victim of drowning. Stepwise multiple linear regression analysis was conducted with BLS/AED performance as outcome variable and demographic data as explanatory variables. Mean BLS/AED performance for all lifeguards was 66.5%. Compression rate and depth adhered closely to ERC 2010 guidelines. Ventilation volume and flow rate exceeded the guidelines. A significant regression model, F(6, 415)=25.61, p<.001, ES=.38, explained 27% of the variance in BLS performance (R2=.27). Significant predictors were age (beta=-.31, p<.001), years of certification (beta=-.41, p<.001), time on duty per year (beta=-.25, p<.001), practising BLS skills (beta=.11, p=.011), and being a professional lifeguard (beta=-.13, p=.029). 71% of lifeguards reported not practising BLS/AED. Being young, recently certified, few days of employment per year, practising BLS skills and not being a professional lifeguard are factors associated with higher BLS/AED performance. Measures should be taken to prevent BLS/AED performances from decaying with age and longer certification. Refresher courses could include a formal skills test and lifeguards should be encouraged to practise their BLS/AED skills. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Deadlines at work and sleep quality. Cross-sectional and longitudinal findings among Danish knowledge workers.

PubMed

Rugulies, Reiner; Martin, Marie H T; Garde, Anne Helene; Persson, Roger; Albertsen, Karen

2012-03-01

Exposure to deadlines at work is increasing in several countries and may affect health. We aimed to investigate cross-sectional and longitudinal associations between frequency of difficult deadlines at work and sleep quality. Study participants were knowledge workers, drawn from a representative sample of Danish employees who responded to a baseline questionnaire in 2006 (n = 363) and a follow-up questionnaire in 2007 (n = 302). Frequency of difficult deadlines was measured by self-report and categorized into low, intermediate, and high. Sleep quality was measured with a Total Sleep Quality Score and two indexes (Awakening Index and Disturbed Sleep Index) derived from the Karolinska Sleep Questionnaire. Analyses on the association between frequency of deadlines and sleep quality scores were conducted with multiple linear regression models, adjusted for potential confounders. In addition, we used multiple logistic regression models to analyze whether frequency of deadlines at baseline predicted caseness of sleep problems at follow-up among participants free of sleep problems at baseline. Frequent deadlines were cross-sectionally and longitudinally associated with poorer sleep quality on all three sleep quality measures. Associations in the longitudinal analyses were greatly attenuated when we adjusted for baseline sleep quality. The logistic regression analyses showed that frequent deadlines at baseline were associated with elevated odds ratios for caseness of sleep problems at follow-up, however, confidence intervals were wide in these analyses. Frequent deadlines at work were associated with poorer sleep quality among Danish knowledge workers. We recommend investigating the relation between deadlines and health endpoints in large-scale epidemiologic studies. Copyright © 2011 Wiley Periodicals, Inc.

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)

Insulin therapy refusal among type II diabetes mellitus patients in Kubang Pasu district, Kedah, Malaysia

PubMed Central

Tan, Wei Leong; Asahar, Siti Fairus; Harun, Noor Liani

2015-01-01

INTRODUCTION Diabetes mellitus is a rising non-communicable disease in Malaysia. Insulin therapy refusal is a challenge for healthcare providers, as it results in delayed insulin initiation. This study was conducted to determine the prevalence of insulin therapy refusal and its associated factors. METHODS This cross-sectional study was conducted at seven public health clinics in Kubang Pasu district of Kedah, Malaysia, from March to October 2012. A newly developed and validated questionnaire was used and participants were selected via systematic random sampling. Only patients diagnosed with type II diabetes mellitus (T2DM) and under the public health clinic care in Kubang Pasu were included in the study. Multiple logistic regression was used to study the association between insulin therapy refusal and its associated factors. RESULTS There were 461 respondents and the response rate was 100%. Among these 461 patients with T2DM, 74.2% refused insulin therapy. The most common reason given for refusal was a lack of confidence in insulin injection (85.4%). Multiple logistic regression revealed that respondents who had secondary education were 55.0% less likely to refuse insulin therapy than those who had primary education or no formal education (adjusted odds ratio [OR] 0.45, 95% confidence interval [CI] 0.25–0.82, p = 0.009). There was also a significant inverse association between glycated haemoglobin (HbA1c) level and insulin therapy refusal (adjusted OR 0.87, 95% CI 0.76–1.00, p = 0.047). CONCLUSION Insulin therapy refusal is common in Kubang Pasu. Educational status and HbA1c level should be taken into consideration when counselling patients on insulin therapy initiation. PMID:25532511

Factors associated with women's autonomy regarding maternal and child health care utilization in Bale Zone: a community based cross-sectional study.

PubMed

Nigatu, Dabere; Gebremariam, Abebe; Abera, Muluemebet; Setegn, Tesfaye; Deribe, Kebede

2014-07-03

Women's autonomy in health-care decision is a prerequisite for improvements in maternal and child health. Little is known about women's autonomy and its influencing factors on maternal and child health care in Ethiopia. Therefore, this study was conducted to assess women's autonomy and identify associated factors in Southeast Ethiopia. A community based cross-sectional study was conducted from March 19th until March 28th, 2011. A total of 706 women were selected using stratified sampling technique from rural and urban kebeles. The quantitative data were collected by interviewer administered questionnaire and analyzed using SPSS for window version 16.0. Descriptive statistics, bivariate and multiple logistic regression analyses were carried out to identify factors associated with women's autonomy for health care utilization. Out of 706 women less than half (41.4%) had higher autonomy regarding their own and their children's health. In the multiple logistic regression model monthly household income >1000 ETB [adjusted odds ratio(AOR):3.32(95% C.I: 1.62-6.78)], having employed husband [AOR: 3.75 (95% C.I:1.24-11.32)], being in a nuclear family structure [AOR: 0.53(95% C.I: 0.33-0.87)], being in monogamous marriage [AOR: 3.18(95% C.I: 1.35-7.50)], being knowledgeable and having favorable attitude toward maternal and child health care services were independently associated with an increased odds of women's autonomy. Socio-demographic and maternal factors (knowledge and attitude) were found to influence women's autonomy. Interventions targeting women's autonomy with regards to maternal and child health care should focus on addressing increasing awareness and priority should be given to women with a lower socioeconomic status.

Insulin therapy refusal among type II diabetes mellitus patients in Kubang Pasu district, the state of Kedah, Malaysia.

PubMed

Tan, Wei Leong; Asahar, Siti Fairus; Harun, Noor Liani

2015-04-01

Diabetes mellitus is a rising non-communicable disease in Malaysia. Insulin therapy refusal is a great challenge for healthcare providers, as it results in delayed insulin initiation. This study was conducted to determine the prevalence of insulin therapy refusal and its associated factors. This cross sectional study was conducted at seven public health clinics in Kubang Pasu district, Malaysia, from March to October 2012. A newly developed and validated questionnaire was used and participants were selected via systematic random sampling. Only patients diagnosed with type II diabetes mellitus (T2DM) and under the public health clinic care in Kubang Pasu were included in the study. Multiple logistic regressions were used to study the association between insulin therapy refusal and its associated factors. There were 461 respondents and the response rate was 100%. Among these 461 patients with T2DM, 74.2% refused insulin therapy. The most common reason given for refusal was a lack of confidence in insulin injection (85.4%). Multiple logistic regression revealed that respondents who had secondary education were 55.0% less likely to refuse insulin therapy than those who had primary or no formal education (p = 0.009, adjusted odds ratio [OR] = 0.45, 95% confidence interval [CI] = 0.25-0.82). There was also a significant inverse association between glycated haemoglobin (HbA1c) and insulin therapy refusal (p = 0.047, adjusted OR = 0.87, 95% CI = 0.76-1.00). Insulin therapy refusal is common in Kubang Pasu. Education status and HbA1c should be taken into consideration when counselling patients on insulin therapy initiation.

Predicting the reading skill of Japanese children.

PubMed

Ogino, Tatsuya; Hanafusa, Kaoru; Morooka, Teruko; Takeuchi, Akihito; Oka, Makio; Ohtsuka, Yoko

2017-02-01

To clarify cognitive processes underlining the development of reading in children speaking Japanese as their first language, we examined relationships between performances of cognitive tasks in the preschool period and later reading abilities. Ninety-one normally developing preschoolers (41 girls and 50 boys; 5years 4months to 6years 4months, mean 5years 10months) participated as subjects. We conducted seven cognitive tasks including phonological awareness tasks, naming tasks, and working memory tasks in the preschool period. In terms of reading tasks, the hiragana naming task was administered in the preschool period; the reading times, which is a composite score of the monomoraic syllable reading task, the word and the non-word reading tasks, and the single sentence reading task, was evaluated in first and second grade; and the kanji reading task (naming task) was tested in second grade. Raven's colored progressive matrices and picture vocabulary test revised were also conducted in first grade. Correlation analyses between task scores and stepwise multiple regression analyses were implemented. Tasks tapping phonological awareness, lexical access, and verbal working memory showed significant correlations with reading tasks. In the multiple regression analyses the performances in the verbal working memory task played a key role in predicting character naming task scores (the hiragana naming task and the kanji reading task) while the digit naming task was an important predictor of reading times. Unexpectedly, the role of phonological (mora) awareness was modest among children speaking Japanese. Cognitive functions including phonological awareness, digit naming, and verbal working memory (especially the latter two) were involved in the development of reading skills of children speaking Japanese. Copyright © 2016 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Lifestyle and health-related quality of life: a cross-sectional study among civil servants in China.

PubMed

Xu, Jun; Qiu, Jincai; Chen, Jie; Zou, Liai; Feng, Liyi; Lu, Yan; Wei, Qian; Zhang, Jinhua

2012-05-04

Health-related quality of life (HRQoL) has been increasingly acknowledged as a valid and appropriate indicator of public health and chronic morbidity. However, limited research was conducted among Chinese civil servants owing to the different lifestyle. The aim of the study was to evaluate the HRQoL among Chinese civil servants and to identify factors might be associated with their HRQoL. A cross-sectional study was conducted to investigate HRQoL of 15,000 civil servants in China using stratified random sampling methods. Independent-Samples t-Test, one-way ANOVA, and multiple stepwise regression were used to analyse the influencing factors and the HRQoL of the civil servants. A univariate analysis showed that there were significant differences among physical component summary (PCS), mental component summary (MCS), and TS between lifestyle factors, such as smoking, drinking alcohol, having breakfast, sleep time, physical exercise, work time, operating computers, and sedentariness (P < 0.05). Multiple stepwise regressions showed that there were significant differences among TS between lifestyle factors, such as breakfast, sleep time, physical exercise, operating computers, sedentariness, work time, and drinking (P < 0.05). In this study, using Short Form 36 items (SF-36), we assessed the association of HRQoL with lifestyle factors, including smoking, drinking alcohol, having breakfast, sleep time, physical exercise, work time, operating computers, and sedentariness in China. The performance of the questionnaire in the large-scale survey is satisfactory and provides a large picture of the HRQoL status in Chinese civil servants. Our results indicate that lifestyle factors such as smoking, drinking alcohol, having breakfast, sleep time, physical exercise, work time, operating computers, and sedentariness affect the HRQoL of civil servants in China.

Lifestyle and health-related quality of life: A cross-sectional study among civil servants in China

PubMed Central

2012-01-01

Background Health-related quality of life (HRQoL) has been increasingly acknowledged as a valid and appropriate indicator of public health and chronic morbidity. However, limited research was conducted among Chinese civil servants owing to the different lifestyle. The aim of the study was to evaluate the HRQoL among Chinese civil servants and to identify factors might be associated with their HRQoL. Methods A cross-sectional study was conducted to investigate HRQoL of 15,000 civil servants in China using stratified random sampling methods. Independent-Samples t-Test, one-way ANOVA, and multiple stepwise regression were used to analyse the influencing factors and the HRQoL of the civil servants. Results A univariate analysis showed that there were significant differences among physical component summary (PCS), mental component summary (MCS), and TS between lifestyle factors, such as smoking, drinking alcohol, having breakfast, sleep time, physical exercise, work time, operating computers, and sedentariness (P < 0.05). Multiple stepwise regressions showed that there were significant differences among TS between lifestyle factors, such as breakfast, sleep time, physical exercise, operating computers, sedentariness, work time, and drinking (P < 0.05). Conclusion In this study, using Short Form 36 items (SF-36), we assessed the association of HRQoL with lifestyle factors, including smoking, drinking alcohol, having breakfast, sleep time, physical exercise, work time, operating computers, and sedentariness in China. The performance of the questionnaire in the large-scale survey is satisfactory and provides a large picture of the HRQoL status in Chinese civil servants. Our results indicate that lifestyle factors such as smoking, drinking alcohol, having breakfast, sleep time, physical exercise, work time, operating computers, and sedentariness affect the HRQoL of civil servants in China. PMID:22559315

Factors associated with women’s autonomy regarding maternal and child health care utilization in Bale Zone: a community based cross-sectional study

PubMed Central

2014-01-01

Background Women's autonomy in health-care decision is a prerequisite for improvements in maternal and child health. Little is known about women’s autonomy and its influencing factors on maternal and child health care in Ethiopia. Therefore, this study was conducted to assess women’s autonomy and identify associated factors in Southeast Ethiopia. Method A community based cross-sectional study was conducted from March 19th until March 28th, 2011. A total of 706 women were selected using stratified sampling technique from rural and urban kebeles. The quantitative data were collected by interviewer administered questionnaire and analyzed using SPSS for window version 16.0. Descriptive statistics, bivariate and multiple logistic regression analyses were carried out to identify factors associated with women’s autonomy for health care utilization. Result Out of 706 women less than half (41.4%) had higher autonomy regarding their own and their children’s health. In the multiple logistic regression model monthly household income >1000 ETB [adjusted odds ratio(AOR):3.32(95% C.I: 1.62-6.78)], having employed husband [AOR: 3.75 (95% C.I:1.24-11.32)], being in a nuclear family structure [AOR: 0.53(95% C.I: 0.33-0.87)], being in monogamous marriage [AOR: 3.18(95% C.I: 1.35-7.50)], being knowledgeable and having favorable attitude toward maternal and child health care services were independently associated with an increased odds of women’s autonomy. Conclusion Socio-demographic and maternal factors (knowledge and attitude) were found to influence women’s autonomy. Interventions targeting women’s autonomy with regards to maternal and child health care should focus on addressing increasing awareness and priority should be given to women with a lower socioeconomic status. PMID:24990689

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.

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

PubMed

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

2014-03-01

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

A study of satisfaction of medical students on their mentoring programs at one medical school in Korea

PubMed Central

2017-01-01

Purpose The purpose of this study was to investigate the awareness levels of medical students regarding the characteristics of each function within a mentoring program conducted within Kyung Hee University and to ultimately suggest points for reformation. Medical students’ awareness levels were determined using a 29-item questionnaire. Methods The questionnaire was conducted on 347 medical students, excluding 25 students who either marked multiple answers or did not reply. The assessment of the program was based on a questionnaire with the use of a 5-point Likert scale using SPSS version 22.0. Multiple regression was conducted to examine the relationship between the satisfaction level, regarding functions of mentoring programs, and characteristics of mentoring programs. Interviews were conducted to supplement additional information that was hard to gain from the questionnaire. Results The results on demographic and functional characteristics revealed that there was no statistically significant differences in satisfaction levels across gender, whereas there were significant differences across grade levels. In addition, there were significant differences in the frequency of meetings and topics of conversation while the length of meetings and meeting place were not significantly different. Conclusion For the improved mentoring programs for medical students, the program should focus on the frequency of meetings and the topics of conversation. Furthermore, mentoring programs of high quality can be expected if professors take interview results into consideration. Also, students want to be provided with psychosocial advice from mentors in various ways such as role model function. PMID:29207456

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…

Death Anxiety as a Predictor of Posttraumatic Stress Levels among Individuals with Spinal Cord Injuries

ERIC Educational Resources Information Center

Martz, Erin

2004-01-01

Because the onset of a spinal cord injury may involve a brush with death and because serious injury and disability can act as a reminder of death, death anxiety was examined as a predictor of posttraumatic stress levels among individuals with disabilities. This cross-sectional study used multiple regression and multivariate multiple regression to…

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.

Is Adolescent Poly-tobacco Use Associated with Alcohol and Other Drug Use?

PubMed Central

Creamer, MeLisa R.; Portillo, Gabriela V.; Clendennen, Stephanie L.; Perry, Cheryl L.

2016-01-01

Objectives To examine associations between current multiple tobacco product use, and current use of alcohol and marijuana, binge drinking, and lifetime use of marijuana, alcohol, and other drugs among US high school students. Methods Using 2013 Youth Risk Behavior Survey data (N = 13,583 high school students), logistic regression analyses were conducted to determine if single tobacco product or multiple tobacco product users are more likely to engage in other risk behaviors than zero tobacco product users, controlling for demographic variables. Results Overall, 23% of the sample used tobacco products and 10% of students reported current use of at least 2 tobacco products. Among single tobacco product users, the odds for engaging in risk behaviors ranged from 3.3 to 9.9 compared to non-tobacco users (p < .0001). Among multiple tobacco product users, the odds ranged from 1.5 to 4.7 (p < .01) compared to single tobacco product users. Conclusions Results suggest dual users are significantly more likely to engage in risk behavior than non-users and single product users. Future interventions should consider identifying dual-users as at higher risk, and targeting multiple risk behaviors. PMID:26685820

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.

[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.

Statistical Methods for Generalized Linear Models with Covariates Subject to Detection Limits.

PubMed

Bernhardt, Paul W; Wang, Huixia J; Zhang, Daowen

2015-05-01

Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we consider statistical methods for dealing with multiple predictors subject to detection limits within the context of generalized linear models. We investigate and adapt several conventional methods and develop a new multiple imputation approach for analyzing data sets with predictors censored due to detection limits. We establish the consistency and asymptotic normality of the proposed multiple imputation estimator and suggest a computationally simple and consistent variance estimator. We also demonstrate that the conditional mean imputation method often leads to inconsistent estimates in generalized linear models, while several other methods are either computationally intensive or lead to parameter estimates that are biased or more variable compared to the proposed multiple imputation estimator. In an extensive simulation study, we assess the bias and variability of different approaches within the context of a logistic regression model and compare variance estimation methods for the proposed multiple imputation estimator. Lastly, we apply several methods to analyze the data set from a recently-conducted GenIMS study.

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

Association between length of storage of red blood cell units and outcome of critically ill children: a prospective observational study

PubMed Central

2010-01-01

Introduction Transfusion is a common treatment in pediatric intensive care units (PICUs). Studies in adults suggest that prolonged storage of red blood cell units is associated with worse clinical outcome. No prospective study has been conducted in children. Our objectives were to assess the clinical impact of the length of storage of red blood cell units on clinical outcome of critically ill children. Methods Prospective, observational study conducted in 30 North American centers, in consecutive patients aged <18 years with a stay ≥ 48 hours in a PICU. The primary outcome measure was the incidence of multiple organ dysfunction syndrome after transfusion. The secondary outcomes were 28-day mortality and PICU length of stay. Odds ratios were adjusted for gender, age, number of organ dysfunctions at admission, total number of transfusions, and total dose of transfusion, using a multiple logistic regression model. Results The median length of storage was 14 days in 296 patients with documented length of storage. For patients receiving blood stored ≥ 14 days, the adjusted odds ratio for an increased incidence of multiple organ dysfunction syndrome was 1.87 (95% CI 1.04;3.27, P = 0.03). There was also a significant difference in the total PICU length of stay (adjusted median difference +3.7 days, P < 0.001) and no significant change in mortality. Conclusions In critically ill children, transfusion of red blood cell units stored for ≥ 14 days is independently associated with an increased occurrence of multiple organ dysfunction syndrome and prolonged PICU stay. PMID:20377853

Parametric Analysis to Study the Influence of Aerogel-Based Renders' Components on Thermal and Mechanical Performance.

PubMed

Ximenes, Sofia; Silva, Ana; Soares, António; Flores-Colen, Inês; de Brito, Jorge

2016-05-04

Statistical models using multiple linear regression are some of the most widely used methods to study the influence of independent variables in a given phenomenon. This study's objective is to understand the influence of the various components of aerogel-based renders on their thermal and mechanical performance, namely cement (three types), fly ash, aerial lime, silica sand, expanded clay, type of aerogel, expanded cork granules, expanded perlite, air entrainers, resins (two types), and rheological agent. The statistical analysis was performed using SPSS (Statistical Package for Social Sciences), based on 85 mortar mixes produced in the laboratory and on their values of thermal conductivity and compressive strength obtained using tests in small-scale samples. The results showed that aerial lime assumes the main role in improving the thermal conductivity of the mortars. Aerogel type, fly ash, expanded perlite and air entrainers are also relevant components for a good thermal conductivity. Expanded clay can improve the mechanical behavior and aerogel has the opposite effect.

Parametric Analysis to Study the Influence of Aerogel-Based Renders’ Components on Thermal and Mechanical Performance

PubMed Central

Ximenes, Sofia; Silva, Ana; Soares, António; Flores-Colen, Inês; de Brito, Jorge

2016-01-01

Statistical models using multiple linear regression are some of the most widely used methods to study the influence of independent variables in a given phenomenon. This study’s objective is to understand the influence of the various components of aerogel-based renders on their thermal and mechanical performance, namely cement (three types), fly ash, aerial lime, silica sand, expanded clay, type of aerogel, expanded cork granules, expanded perlite, air entrainers, resins (two types), and rheological agent. The statistical analysis was performed using SPSS (Statistical Package for Social Sciences), based on 85 mortar mixes produced in the laboratory and on their values of thermal conductivity and compressive strength obtained using tests in small-scale samples. The results showed that aerial lime assumes the main role in improving the thermal conductivity of the mortars. Aerogel type, fly ash, expanded perlite and air entrainers are also relevant components for a good thermal conductivity. Expanded clay can improve the mechanical behavior and aerogel has the opposite effect. PMID:28773460

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

Functional Capacity Evaluation in Different Societal Contexts: Results of a Multicountry Study.

PubMed

Ansuategui Echeita, Jone; Bethge, Matthias; van Holland, Berry J; Gross, Douglas P; Kool, Jan; Oesch, Peter; Trippolini, Maurizio A; Chapman, Elizabeth; Cheng, Andy S K; Sellars, Robert; Spavins, Megan; Streibelt, Marco; van der Wurff, Peter; Reneman, Michiel F

2018-05-25

Purpose To examine factors associated with Functional Capacity Evaluation (FCE) results in patients with painful musculoskeletal conditions, with focus on social factors across multiple countries. Methods International cross-sectional study was performed within care as usual. Simple and multiple multilevel linear regression analyses which considered measurement's dependency within clinicians and country were conducted: FCE characteristics and biopsychosocial variables from patients and clinicians as independent variables; and FCE results (floor-to-waist lift, six-minute walk, and handgrip strength) as dependent variables. Results Data were collected for 372 patients, 54 clinicians, 18 facilities and 8 countries. Patients' height and reported pain intensity were consistently associated with every FCE result. Patients' sex, height, reported pain intensity, effort during FCE, social isolation, and disability, clinician's observed physical effort, and whether FCE test was prematurely ended were associated with lift. Patient's height, Body Mass Index, post-test heart-rate, reported pain intensity and effort during FCE, days off work, and whether FCE test was prematurely ended were associated with walk. Patient's age, sex, height, affected body area, reported pain intensity and catastrophizing, and physical work demands were associated with handgrip. Final regression models explained 38‒65% of total variance. Clinician and country random effects composed 1-39% of total residual variance in these models. Conclusion Biopsychosocial factors were associated with every FCE result across multiple countries; specifically, patients' height, reported pain intensity, clinician, and measurement country. Social factors, which had been under-researched, were consistently associated with FCE performances. Patients' FCE results should be considered from a biopsychosocial perspective, including different social contexts.

Quality of search strategies reported in systematic reviews published in stereotactic radiosurgery.

PubMed

Faggion, Clovis M; Wu, Yun-Chun; Tu, Yu-Kang; Wasiak, Jason

2016-06-01

Systematic reviews require comprehensive literature search strategies to avoid publication bias. This study aimed to assess and evaluate the reporting quality of search strategies within systematic reviews published in the field of stereotactic radiosurgery (SRS). Three electronic databases (Ovid MEDLINE(®), Ovid EMBASE(®) and the Cochrane Library) were searched to identify systematic reviews addressing SRS interventions, with the last search performed in October 2014. Manual searches of the reference lists of included systematic reviews were conducted. The search strategies of the included systematic reviews were assessed using a standardized nine-question form based on the Cochrane Collaboration guidelines and Assessment of Multiple Systematic Reviews checklist. Multiple linear regression analyses were performed to identify the important predictors of search quality. A total of 85 systematic reviews were included. The median quality score of search strategies was 2 (interquartile range = 2). Whilst 89% of systematic reviews reported the use of search terms, only 14% of systematic reviews reported searching the grey literature. Multiple linear regression analyses identified publication year (continuous variable), meta-analysis performance and journal impact factor (continuous variable) as predictors of higher mean quality scores. This study identified the urgent need to improve the quality of search strategies within systematic reviews published in the field of SRS. This study is the first to address how authors performed searches to select clinical studies for inclusion in their systematic reviews. Comprehensive and well-implemented search strategies are pivotal to reduce the chance of publication bias and consequently generate more reliable systematic review findings.

Water and solute absorption from carbohydrate-electrolyte solutions in the human proximal small intestine: a review and statistical analysis.

PubMed

Shi, Xiaocai; Passe, Dennis H

2010-10-01

The purpose of this study is to summarize water, carbohydrate (CHO), and electrolyte absorption from carbohydrate-electrolyte (CHO-E) solutions based on all of the triple-lumen-perfusion studies in humans since the early 1960s. The current statistical analysis included 30 reports from which were obtained information on water absorption, CHO absorption, total solute absorption, CHO concentration, CHO type, osmolality, sodium concentration, and sodium absorption in the different gut segments during exercise and at rest. Mean differences were assessed using independent-samples t tests. Exploratory multiple-regression analyses were conducted to create prediction models for intestinal water absorption. The factors influencing water and solute absorption are carefully evaluated and extensively discussed. The authors suggest that in the human proximal small intestine, water absorption is related to both total solute and CHO absorption; osmolality exerts various impacts on water absorption in the different segments; the multiple types of CHO in the ingested CHO-E solutions play a critical role in stimulating CHO, sodium, total solute, and water absorption; CHO concentration is negatively related to water absorption; and exercise may result in greater water absorption than rest. A potential regression model for predicting water absorption is also proposed for future research and practical application. In conclusion, water absorption in the human small intestine is influenced by osmolality, solute absorption, and the anatomical structures of gut segments. Multiple types of CHO in a CHO-E solution facilitate water absorption by stimulating CHO and solute absorption and lowering osmolality in the intestinal lumen.

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.

Reported gum disease as a cardiovascular risk factor in adults with intellectual disabilities.

PubMed

Hsieh, K; Murthy, S; Heller, T; Rimmer, J H; Yen, G

2018-03-01

Several risk factors for cardiovascular disease (CVD) have been identified among adults with intellectual disabilities (ID). Periodontitis has been reported to increase the risk of developing a CVD in the general population. Given that individuals with ID have been reported to have a higher prevalence of poor oral health than the general population, the purpose of this study was to determine whether adults with ID with informant reported gum disease present greater reported CVD than those who do not have reported gum disease and whether gum disease can be considered a risk factor for CVD. Using baseline data from the Longitudinal Health and Intellectual Disability Study from which informant survey data were collected, 128 participants with reported gum disease and 1252 subjects without reported gum disease were identified. A series of univariate logistic regressions was conducted to identify potential confounding factors for a multiple logistic regression. The series of univariate logistic regressions identified age, Down syndrome, hypercholesterolemia, hypertension, reported gum disease, daily consumption of fruits and vegetables and the addition of table salt as significant risk factors for reported CVD. When the significant factors from the univariate logistic regression were included in the multiple logistic analysis, reported gum disease remained as an independent risk factor for reported CVD after adjusting for the remaining risk factors. Compared with the adults with ID without reported gum disease, adults in the gum disease group demonstrated a significantly higher prevalence of reported CVD (19.5% vs. 9.7%; P = .001). After controlling for other risk factors, reported gum disease among adults with ID may be associated with a higher risk of CVD. However, further research that also includes clinical indices of periodontal disease and CVD for this population is needed to determine if there is a causal relationship between gum disease and CVD. © 2017 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Soccer and sexual health education: a promising approach for reducing adolescent births in Haiti.

PubMed

Kaplan, Kathryn C; Lewis, Judy; Gebrian, Bette; Theall, Katherine

2015-05-01

To explore the effect of an innovative, integrative program in female sexual reproductive health (SRH) and soccer (or fútbol, in Haitian Creole) in rural Haiti by measuring the rate of births among program participants 15-19 years old and their nonparticipant peers. A retrospective cohort study using 2006-2009 data from the computerized data-tracking system of the Haitian Health Foundation (HHF), a U.S.-based nongovernmental organization serving urban and rural populations in Haiti, was used to assess births among girls 15-19 years old who participated in HHF's GenNext program, a combination education-soccer program for youth, based on SRH classes HHF nurses and community workers had been conducting in Haiti for mothers, fathers, and youth; girl-centered health screenings; and an all-female summer soccer league, during 2006-2009 (n = 4 251). Bivariate and multiple logistic regression analyses were carried out to assess differences in the rate of births among program participants according to their level of participation (SRH component only ("EDU") versus both the SRH and soccer components ("SO") compared to their village peers who did not participate. Hazard ratios (HRs) of birth rates were estimated using Cox regression analysis of childbearing data for the three different groups. In the multiple logistic regression analysis, only the girls in the "EDU" group had significantly fewer births than the nonparticipants after adjusting for confounders (odds ratio = 0.535; 95% confidence interval (CI) = 0.304, 0.940). The Cox regression analysis demonstrated that those in the EDU group (HR = 0.893; 95% CI = 0.802, 0.994) and to a greater degree those in the SO group (HR = 0.631; 95% CI = 0.558, 0.714) were significantly protected against childbearing between the ages of 15 and 19 years. HHF's GenNext program demonstrates the effectiveness of utilizing nurse educators, community mobilization, and youth participation in sports, education, and structured youth groups to promote and sustain health for adolescent girls and young women.

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...

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

Personality traits and life satisfaction among online game players.

PubMed

Chen, Lily Shui-Lien; Tu, Hill Hung-Jen; Wang, Edward Shih-Tse

2008-04-01

The DFC Intelligence predicts worldwide online game revenues will reach $9.8 billion by 2009, making online gaming a mainstream recreational activity. Understanding online game player personality traits is therefore important. This study researches the relationship between personality traits and life satisfaction in online game players. Taipei, Taiwan, is the study location, with questionnaire surveys conducted in cyber cafe shops. Multiple regression analysis studies the causal relationship between personality traits and life satisfaction in online game players. The result shows that neuroticism has significant negative influence on life satisfaction. Both openness and conscientiousness have significant positive influence on life satisfaction. Finally, implications for leisure practice and further research are discussed.

Results of the 2014 AORN Salary and Compensation Survey.

PubMed

Bacon, Donald R; Stewart, Kim A

2014-12-01

AORN conducted its 12th annual compensation survey for perioperative nurses in June and July 2014. A multiple regression model was used to examine how a number of variables, including job title, education level, certification, experience, and geographic region, affect nurse compensation. Comparisons between the data from 2014 and data from previous years are presented. The effects of other forms of compensation (eg, on-call compensation, overtime, bonuses, shift differentials) on base compensation rates also are examined. Additional analyses explore the effect of the economic downturn on the perioperative work environment. Copyright © 2014 AORN, Inc. Published by Elsevier Inc. All rights reserved.

Regimen Difficulty and Medication Non-Adherence and the Interaction Effects of Gender and Age.

PubMed

Dalvi, Vidya; Mekoth, Nandakumar

2017-12-08

Medication non-adherence is a global health issue. Numerous factors predict it. This study is aimed to identify the association between regimen difficulty and medication non-adherence among patients with chronic conditions and testing the interaction effects of gender and age on the same. It was a cross-sectional study conducted among 479 outpatients from India. Convenience sampling method was used. Multiple regression analyses were performed to find the predictors of non-adherence and to test interaction effects. Regimen difficulty predicted medication non-adherence. The patient's gender and age have interaction effects on the relationship between regimen difficulty and medication non-adherence.

The Determinants of Federal and State Enforcement of Workplace Safety Regulations: OSHA Inspections 1990-2010*

PubMed Central

Jung, Juergen

2013-01-01

We explore the determinants of inspection outcomes across 1.6 million Occupational Safety and Health Agency (OSHA) audits from 1990 through 2010. We find that discretion in enforcement differs in state and federally conducted inspections. State agencies are more sensitive to local economic conditions, finding fewer standard violations and fewer serious violations as unemployment increases. Larger companies receive greater lenience in multiple dimensions. Inspector issued fines and final fines, after negotiated reductions, are both smaller during Republican presidencies. Quantile regression analysis reveals that Presidential and Congressional party affiliations have their greatest impact on the largest negotiated reductions in fines. PMID:24659856

Application of ERTS-1 data to the harvest model of the US menhaden fishery. [Gulf of Mexico

NASA Technical Reports Server (NTRS)

Maughan, P. M. (Principal Investigator); Marmelstein, A. D.

1974-01-01

The author has identified the following significant results. The project was conducted in Mississippi Sound in the north-central Gulf of Mexico. It utilized conventional surface data, obtained from fishing and other vessels, as well as aircraft and spacecraft remote data. A relationship was established between surface measured water transparency, temperature and salinity, and commercial fish-stock availability. Numerical models of the relationships were derived. A multiple regression was performed relating ERTS-1 MSS Band 5 image density to measured transparency and water depth. It is concluded that remotely acquired data can play a role in harvest decisions of commercial fisheries.

Results of the 2015 AORN Salary and Compensation Survey.

PubMed

Bacon, Donald R; Stewart, Kim A

2015-12-01

AORN conducted its 13th annual compensation survey for perioperative nurses in June and July 2015. A multiple regression model was used to examine how a number of variables, including job title, education level, certification, experience, and geographic region, affect nurse compensation. Comparisons between the 2015 data and data from previous years are presented. The effects of other forms of compensation (eg, on-call compensation, overtime, bonuses, shift differentials, benefits) on base compensation rates also are examined. Additional analyses explore the effect of the economic downturn on the perioperative work environment. Copyright © 2015 AORN, Inc. Published by Elsevier Inc. All rights reserved.

Results of the 2011 AORN Salary and Compensation Survey.

PubMed

Bacon, Donald

2011-12-01

AORN conducted its ninth annual compensation survey for perioperative nurses in June and July 2011. A multiple regression model was used to examine how a number of variables, including job title, education level, certification, experience, and geographic region, affect nurse compensation. Comparisons between the 2011 data and data from previous years are presented. The effects of other forms of compensation, such as on-call compensation, overtime, bonuses, and shift differentials, on base compensation rates also are examined. Additional analyses explore the effect of the current economic downturn on the perioperative work environment. Copyright © 2011 AORN, Inc. Published by Elsevier Inc. All rights reserved.

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.

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.

Chronic stressors and trauma: prospective influences on the course of bipolar disorder

PubMed Central

Gershon, A.; Johnson, S. L.; Miller, I.

2013-01-01

Background Exposure to life stress is known to adversely impact the course of bipolar disorder. Few studies have disentangled the effects of multiple types of stressors on the longitudinal course of bipolar I disorder. This study examines whether severity of chronic stressors and exposure to trauma are prospectively associated with course of illness among bipolar patients. Method One hundred and thirty-one participants diagnosed with bipolar I disorder were recruited through treatment centers, support groups and community advertisements. Severity of chronic stressors and exposure to trauma were assessed at study entry with in-person interviews using the Bedford College Life Event and Difficulty Schedule (LEDS). Course of illness was assessed by monthly interviews conducted over the course of 24 months (over 3000 assessments). Results Trauma exposure was related to more severe interpersonal chronic stressors. Multiple regression models provided evidence that severity of overall chronic stressors predicted depressive but not manic symptoms, accounting for 7.5% of explained variance. Conclusions Overall chronic stressors seem to be an important determinant of depressive symptoms within bipolar disorder, highlighting the importance of studying multiple forms of life stress. PMID:23419615

Chronic stressors and trauma: prospective influences on the course of bipolar disorder.

PubMed

Gershon, A; Johnson, S L; Miller, I

2013-12-01

Exposure to life stress is known to adversely impact the course of bipolar disorder. Few studies have disentangled the effects of multiple types of stressors on the longitudinal course of bipolar I disorder. This study examines whether severity of chronic stressors and exposure to trauma are prospectively associated with course of illness among bipolar patients. One hundred and thirty-one participants diagnosed with bipolar I disorder were recruited through treatment centers, support groups and community advertisements. Severity of chronic stressors and exposure to trauma were assessed at study entry with in-person interviews using the Bedford College Life Event and Difficulty Schedule (LEDS). Course of illness was assessed by monthly interviews conducted over the course of 24 months (over 3000 assessments). Trauma exposure was related to more severe interpersonal chronic stressors. Multiple regression models provided evidence that severity of overall chronic stressors predicted depressive but not manic symptoms, accounting for 7.5% of explained variance. Overall chronic stressors seem to be an important determinant of depressive symptoms within bipolar disorder, highlighting the importance of studying multiple forms of life stress.

Confounding adjustment in comparative effectiveness research conducted within distributed research networks.

PubMed

Toh, Sengwee; Gagne, Joshua J; Rassen, Jeremy A; Fireman, Bruce H; Kulldorff, Martin; Brown, Jeffrey S

2013-08-01

A distributed research network (DRN) of electronic health care databases, in which data reside behind the firewall of each data partner, can support a wide range of comparative effectiveness research (CER) activities. An essential component of a fully functional DRN is the capability to perform robust statistical analyses to produce valid, actionable evidence without compromising patient privacy, data security, or proprietary interests. We describe the strengths and limitations of different confounding adjustment approaches that can be considered in observational CER studies conducted within DRNs, and the theoretical and practical issues to consider when selecting among them in various study settings. Several methods can be used to adjust for multiple confounders simultaneously, either as individual covariates or as confounder summary scores (eg, propensity scores and disease risk scores), including: (1) centralized analysis of patient-level data, (2) case-centered logistic regression of risk set data, (3) stratified or matched analysis of aggregated data, (4) distributed regression analysis, and (5) meta-analysis of site-specific effect estimates. These methods require different granularities of information be shared across sites and afford investigators different levels of analytic flexibility. DRNs are growing in use and sharing of highly detailed patient-level information is not always feasible in DRNs. Methods that incorporate confounder summary scores allow investigators to adjust for a large number of confounding factors without the need to transfer potentially identifiable information in DRNs. They have the potential to let investigators perform many analyses traditionally conducted through a centralized dataset with detailed patient-level information.

Agreeableness and pregnancy: Relations with coping and psychiatric symptoms, a longitudinal study on Spanish pregnant women.

PubMed

Peñacoba, Cecilia; Rodríguez, Laura; Carmona, Javier; Marín, Dolores

2018-02-01

Agreeableness is associated with good mental health during pregnancy. Although different studies have indicated that agreeableness is related to adaptive coping, this relation has scarcely been studied in pregnant women. The aim of this study was to analyze the possible differences between high and low agreeableness in relation to coping strategies and psychiatric symptoms in pregnant women. We conducted a longitudinal prospective study between October 2009 and January 2013. Pregnant women (n = 285) were assessed in the first trimester of pregnancy, and 122 of them were assessed during the third. Data were collected using the Coping Strategies Questionnaire, the Symptom Check List 90-R, and the agreeableness subscale of the NEO-FFI. Using the SPSS 21 statistics package, binary logistic regression, two-way mixed analysis of variance, and multiple regression analyses and a Sobel test were conducted. Higher levels of agreeableness were associated with positive reappraisal and problem-solving, and lower levels of agreeableness were associated with overt emotional expression and negative self-focused coping. Women with low agreeableness had poorer mental health, especially in the first trimester. These findings should be taken into account to improve women's experiences during pregnancy. Nevertheless, given the scarcity of data, additional studies are needed.

Relationship between Dietary Fat Intake, Its Major Food Sources and Assisted Reproduction Parameters

PubMed Central

Kazemi, Ashraf; Ramezanzadeh, Fatemeh; Nasr-Esfahani, Mohammad Hosein

2014-01-01

Background High dietary fat consumption may alter oocyte development and embryonic development. This prospective study was conducted to determine the relation between dietary fat consumption level, its food sources and the assisted reproduction parameters. Methods A prospective study was conducted on 240 infertile women. In assisted reproduction treatment cycle, fat consumption and major food sources over the previous three months were identified. The number of retrieved oocytes, metaphase ΙΙ stage oocytes numbers, fertilization rate, embryo quality and clinical pregnancy rate were also determined. The data were analyzed using multiple regression, binary logistic regression, chi-square and t-test. The p-value of less than 0.05 was considered significant. Results Total fat intake adjusted for age, body mass index, physical activity and etiology of infertility was positively associated with the number of retrieved oocytes and inversely associated with the high embryo quality rate. An inverse association was observed between sausage and turkey ham intake and the number of retrieved oocytes. Also, oil intake level had an inverse association with good cleavage rate. Conclusion The results revealed that higher levels of fat consumption tend to increase the number of retrieved oocytes and were adversely related to embryonic development. Among food sources of fat, vegetable oil, sausage and turkey ham intake may adversely affect assisted reproduction parameters. PMID:25473630

E-cigarette Dual Users, Exclusive Users and Perceptions of Tobacco Products

PubMed Central

Cooper, Maria; Case, Kathleen R.; Loukas, Alexandra; Creamer, MeLisa R.; Perry, Cheryl L.

2016-01-01

Objectives We examined differences in the characteristics of youth non-users, cigarette-only, e-cigarette-only, and dual e-cigarette and cigarette users. Methods Using weighted, representative data, logistic regression analyses were conducted to examine differences in demographic characteristics and tobacco use behaviors across tobacco usage groups. Multiple linear regression analyses were conducted to examine differences in harm perceptions of various tobacco products and perceived peer use of e-cigarettes by tobacco usage group. Results Compared to non-users, dual users were more likely to be white, male, and high school students. Dual users had significantly higher prevalence of current use of all products (except hookah) than e-cigarette-only users, and higher prevalence of current use of snus and hookah than the cigarette-only group. Dual users had significantly lower harm perceptions for all tobacco products except for e-cigarettes and hookah as compared to e-cigarette-only users. Dual users reported higher peer use of cigarettes as compared to both exclusive user groups. Conclusion Findings highlight dual users’ higher prevalence of use of most other tobacco products, their lower harm perceptions of most tobacco products compared to e-cigarette-only users, and their higher perceived peer use of cigarettes compared to exclusive users. PMID:26685819

Development of brief versions of the Wechsler Intelligence Scale for schizophrenia: considerations of the structure and predictability of intelligence.

PubMed

Sumiyoshi, Chika; Uetsuki, Miki; Suga, Motomu; Kasai, Kiyoto; Sumiyoshi, Tomiki

2013-12-30

Short forms (SF) of the Wechsler Intelligence Scale have been developed to enhance its practicality. However, only a few studies have addressed the Wechsler Intelligence Scale Revised (WAIS-R) SFs based on data from patients with schizophrenia. The current study was conducted to develop the WAIS-R SFs for these patients based on the intelligence structure and predictability of the Full IQ (FIQ). Relations to demographic and clinical variables were also examined on selecting plausible subtests. The WAIS-R was administered to 90 Japanese patients with schizophrenia. Exploratory factor analysis (EFA) and multiple regression analysis were conducted to find potential subtests. EFA extracted two dominant factors corresponding to Verbal IQ and Performance IQ measures. Subtests with higher factor loadings on those factors were initially nominated. Regression analysis was carried out to reach the model containing all the nominated subtests. The optimality of the potential subtests included in that model was evaluated from the perspectives of the representativeness of intelligence structure, FIQ predictability, and the relation with demographic and clinical variables. Taken together, the dyad of Vocabulary and Block Design was considered to be the most optimal WAIS-R SF for patients with schizophrenia, reflecting both intelligence structure and FIQ predictability. © 2013 Elsevier Ireland Ltd. 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.

Neighborhood food environment and body mass index among Japanese older adults: results from the Aichi Gerontological Evaluation Study (AGES)

PubMed Central

2011-01-01

Background The majority of studies of the local food environment in relation to obesity risk have been conducted in the US, UK, and Australia. The evidence remains limited to western societies. The aim of this paper is to examine the association of local food environment to body mass index (BMI) in a study of older Japanese individuals. Methods The analysis was based on 12,595 respondents from cross-sectional data of the Aichi Gerontological Evaluation Study (AGES), conducted in 2006 and 2007. Using Geographic Information Systems (GIS), we mapped respondents' access to supermarkets, convenience stores, and fast food outlets, based on a street network (both the distance to the nearest stores and the number of stores within 500 m of the respondents' home). Multiple linear regression and logistic regression analyses were performed to examine the association between food environment and BMI. Results In contrast to previous reports, we found that better access to supermarkets was related to higher BMI. Better access to fast food outlets or convenience stores was also associated with higher BMI, but only among those living alone. The logistic regression analysis, using categorized BMI, showed that the access to supermarkets was only related to being overweight or obese, but not related to being underweight. Conclusions Our findings provide mixed support for the types of food environment measures previously used in western settings. Importantly, our results suggest the need to develop culture-specific approaches to characterizing neighborhood contexts when hypotheses are extrapolated across national borders. PMID:21777439

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.

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.

Communication, social capital and workplace health management as determinants of the innovative climate in German banks.

PubMed

Köhler, Thorsten; Janssen, Christian; Plath, Sven-Christoph; Reese, Jens Peter; Lay, Jann; Steinhausen, Simone; Gloede, Tristan; Kowalski, Christoph; Schulz-Nieswandt, Frank; Pfaff, Holger

2010-12-01

The present study aims to measure the determinants of the innovative climate in German banks with a focus on workplace health management (WHM). We analyze the determinants of innovative climate with multiple regressions using a dataset based on standardized telephone interviews conducted with health promotion experts from 198 randomly selected German banks. The regression analysis provided a good explanation of the variance in the dependent variable (R² = 55%). Communication climate (β = 0.55; p < 0.001), social capital (β = 0.21; p < 0.01), the establishment of a WHM program (β = 0.13; p < 0.05) as well as company size (β = 0.15; p < 0.01) were found to have a significant impact on an organization's innovative climate. In order to foster an innovation-friendly climate, organizations should establish shared values. An active step in this direction involves strengthening the organizations' social capital and communication climate through trustworthy management decisions such as the implementation of a WHM program.

Gluten-free is not enough--perception and suggestions of celiac consumers.

PubMed

do Nascimento, Amanda Bagolin; Fiates, Giovanna Medeiros Rataichesck; dos Anjos, Adilson; Teixeira, Evanilda

2014-06-01

The present study investigated the perceptions of individuals with celiac disease about gluten-free (GF) products, their consumer behavior and which product is the most desired. A survey was used to collect information. Descriptive analysis, χ² tests and Multiple Logistic Regressions were conducted. Ninety-one questionnaires were analyzed. Limited variety and availability, the high price of products and the social restrictions imposed by the diet were the factors that caused the most dissatisfaction and difficulty. A total of 71% of the participants confirmed having moderate to high difficulty finding GF products. The logistic regression identified a significant relationship between dissatisfaction, texture and variety (p < 0.05) and between variety and difficulty of finding GF products (p < 0.05). The sensory characteristics were the most important variables considered for actual purchases. Bread was the most desired product. The participants were dissatisfaction with GF products. The desire for bread with better sensory characteristics reinforces the challenge to develop higher quality baking products.

Identifying Nanoscale Structure-Function Relationships Using Multimodal Atomic Force Microscopy, Dimensionality Reduction, and Regression Techniques.

PubMed

Kong, Jessica; Giridharagopal, Rajiv; Harrison, Jeffrey S; Ginger, David S

2018-05-31

Correlating nanoscale chemical specificity with operational physics is a long-standing goal of functional scanning probe microscopy (SPM). We employ a data analytic approach combining multiple microscopy modes, using compositional information in infrared vibrational excitation maps acquired via photoinduced force microscopy (PiFM) with electrical information from conductive atomic force microscopy. We study a model polymer blend comprising insulating poly(methyl methacrylate) (PMMA) and semiconducting poly(3-hexylthiophene) (P3HT). We show that PiFM spectra are different from FTIR spectra, but can still be used to identify local composition. We use principal component analysis to extract statistically significant principal components and principal component regression to predict local current and identify local polymer composition. In doing so, we observe evidence of semiconducting P3HT within PMMA aggregates. These methods are generalizable to correlated SPM data and provide a meaningful technique for extracting complex compositional information that are impossible to measure from any one technique.

Measuring the influence of professional nursing practice on global hospital performance in an organizational context.

PubMed

Fasoli, Dijon R

2008-01-01

The purpose of this study was to measure the influence of professional nursing practice (PNP) on global hospital performance (GHP). Evidence links PNP and positive outcomes for patients and nurses, however, little is known about PNP influence on GHP measures used for patient decision-making and hospital management resource allocation decisions. A quantitative study using multiple regression analysis to predict a composite measure of GHP was conducted. Two survey instruments measuring perspectives of the PNP environment were completed by 1815 (31.3%) Registered Nurses (RN) and 28 (100%) Senior Nurse Executives (SNE) at 28 northeastern US hospitals. Secondary data provided organizational attributes. The degree of PNP was consistently reported by RNs and SNEs. When regressed with organizational factors, PNP was not a significant predictor of GHP. Better GHP was associated with lower lengths of stay, lower profitability, less admission growth, and non-health system affiliation. Further research is needed to define a nursing-sensitive GHP measure.

Genotype-phenotype association study via new multi-task learning model

PubMed Central

Huo, Zhouyuan; Shen, Dinggang

2018-01-01

Research on the associations between genetic variations and imaging phenotypes is developing with the advance in high-throughput genotype and brain image techniques. Regression analysis of single nucleotide polymorphisms (SNPs) and imaging measures as quantitative traits (QTs) has been proposed to identify the quantitative trait loci (QTL) via multi-task learning models. Recent studies consider the interlinked structures within SNPs and imaging QTs through group lasso, e.g. ℓ2,1-norm, leading to better predictive results and insights of SNPs. However, group sparsity is not enough for representing the correlation between multiple tasks and ℓ2,1-norm regularization is not robust either. In this paper, we propose a new multi-task learning model to analyze the associations between SNPs and QTs. We suppose that low-rank structure is also beneficial to uncover the correlation between genetic variations and imaging phenotypes. Finally, we conduct regression analysis of SNPs and QTs. Experimental results show that our model is more accurate in prediction than compared methods and presents new insights of SNPs. PMID:29218896

Relationship of negative self-schemas and attachment styles with appearance schemas.

PubMed

Ledoux, Tracey; Winterowd, Carrie; Richardson, Tamara; Clark, Julie Dorton

2010-06-01

The purpose was to test, among women, the relationship between negative self-schemas and styles of attachment with men and women and two types of appearance investment (Self-evaluative and Motivational Salience). Predominantly Caucasian undergraduate women (N=194) completed a modified version of the Relationship Questionnaire, the Young Schema Questionnaire-Short Form, and the Appearance Schemas Inventory-Revised. Linear multiple regression analyses were conducted with Motivational Salience and Self-evaluative Salience of appearance serving as dependent variables and relevant demographic variables, negative self-schemas, and styles of attachment to men serving as independent variables. Styles of attachment to women were not entered into these regression models because Pearson correlations indicated they were not related to either dependent variable. Self-evaluative Salience of appearance was related to impaired autonomy and performance negative self-schema and the preoccupation style of attachment with men, while Motivational Salience of appearance was related only to the preoccupation style of attachment with men. 2010 Elsevier Ltd. All rights reserved.

A Pilot Study of Reasons and Risk Factors for "No-Shows" in a Pediatric Neurology Clinic.

PubMed

Guzek, Lindsay M; Fadel, William F; Golomb, Meredith R

2015-09-01

Missed clinic appointments lead to decreased patient access, worse patient outcomes, and increased healthcare costs. The goal of this pilot study was to identify reasons for and risk factors associated with missed pediatric neurology outpatient appointments ("no-shows"). This was a prospective cohort study of patients scheduled for 1 week of clinic. Data on patient clinical and demographic information were collected by record review; data on reasons for missed appointments were collected by phone interviews. Univariate and multivariate analyses were conducted using chi-square tests and multiple logistic regression to assess risk factors for missed appointments. Fifty-nine (25%) of 236 scheduled patients were no-shows. Scheduling conflicts (25.9%) and forgetting (20.4%) were the most common reasons for missed appointments. When controlling for confounding factors in the logistic regression, Medicaid (odds ratio 2.36), distance from clinic, and time since appointment was scheduled were associated with missed appointments. Further work in this area is needed. © The Author(s) 2014.

Continuous integration for concurrent MOOSE framework and application development on GitHub

DOE PAGES

Slaughter, Andrew E.; Peterson, John W.; Gaston, Derek R.; ...

2015-11-20

For the past several years, Idaho National Laboratory’s MOOSE framework team has employed modern software engineering techniques (continuous integration, joint application/framework source code repos- itories, automated regression testing, etc.) in developing closed-source multiphysics simulation software (Gaston et al., Journal of Open Research Software vol. 2, article e10, 2014). In March 2014, the MOOSE framework was released under an open source license on GitHub, significantly expanding and diversifying the pool of current active and potential future contributors on the project. Despite this recent growth, the same philosophy of concurrent framework and application development continues to guide the project’s development roadmap. Severalmore » specific practices, including techniques for managing multiple repositories, conducting automated regression testing, and implementing a cascading build process are discussed in this short paper. Furthermore, special attention is given to describing the manner in which these practices naturally synergize with the GitHub API and GitHub-specific features such as issue tracking, Pull Requests, and project forks.« less

Continuous integration for concurrent MOOSE framework and application development on GitHub

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

Slaughter, Andrew E.; Peterson, John W.; Gaston, Derek R.

For the past several years, Idaho National Laboratory’s MOOSE framework team has employed modern software engineering techniques (continuous integration, joint application/framework source code repos- itories, automated regression testing, etc.) in developing closed-source multiphysics simulation software (Gaston et al., Journal of Open Research Software vol. 2, article e10, 2014). In March 2014, the MOOSE framework was released under an open source license on GitHub, significantly expanding and diversifying the pool of current active and potential future contributors on the project. Despite this recent growth, the same philosophy of concurrent framework and application development continues to guide the project’s development roadmap. Severalmore » specific practices, including techniques for managing multiple repositories, conducting automated regression testing, and implementing a cascading build process are discussed in this short paper. Furthermore, special attention is given to describing the manner in which these practices naturally synergize with the GitHub API and GitHub-specific features such as issue tracking, Pull Requests, and project forks.« less

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.

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.

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…

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.

Spatial analysis and land use regression of VOCs and NO(2) from school-based urban air monitoring in Detroit/Dearborn, USA.

PubMed

Mukerjee, Shaibal; Smith, Luther A; Johnson, Mary M; Neas, Lucas M; Stallings, Casson A

2009-08-01

Passive ambient air sampling for nitrogen dioxide (NO(2)) and volatile organic compounds (VOCs) was conducted at 25 school and two compliance sites in Detroit and Dearborn, Michigan, USA during the summer of 2005. Geographic Information System (GIS) data were calculated at each of 116 schools. The 25 selected schools were monitored to assess and model intra-urban gradients of air pollutants to evaluate impact of traffic and urban emissions on pollutant levels. Schools were chosen to be statistically representative of urban land use variables such as distance to major roadways, traffic intensity around the schools, distance to nearest point sources, population density, and distance to nearest border crossing. Two approaches were used to investigate spatial variability. First, Kruskal-Wallis analyses and pairwise comparisons on data from the schools examined coarse spatial differences based on city section and distance from heavily trafficked roads. Secondly, spatial variation on a finer scale and as a response to multiple factors was evaluated through land use regression (LUR) models via multiple linear regression. For weeklong exposures, VOCs did not exhibit spatial variability by city section or distance from major roads; NO(2) was significantly elevated in a section dominated by traffic and industrial influence versus a residential section. Somewhat in contrast to coarse spatial analyses, LUR results revealed spatial gradients in NO(2) and selected VOCs across the area. The process used to select spatially representative sites for air sampling and the results of coarse and fine spatial variability of air pollutants provide insights that may guide future air quality studies in assessing intra-urban gradients.

Brain networks of temporal preparation: A multiple regression analysis of neuropsychological data.

PubMed

Triviño, Mónica; Correa, Ángel; Lupiáñez, Juan; Funes, María Jesús; Catena, Andrés; He, Xun; Humphreys, Glyn W

2016-11-15

There are only a few studies on the brain networks involved in the ability to prepare in time, and most of them followed a correlational rather than a neuropsychological approach. The present neuropsychological study performed multiple regression analysis to address the relationship between both grey and white matter (measured by magnetic resonance imaging in patients with brain lesion) and different effects in temporal preparation (Temporal orienting, Foreperiod and Sequential effects). Two versions of a temporal preparation task were administered to a group of 23 patients with acquired brain injury. In one task, the cue presented (a red versus green square) to inform participants about the time of appearance (early versus late) of a target stimulus was blocked, while in the other task the cue was manipulated on a trial-by-trial basis. The duration of the cue-target time intervals (400 versus 1400ms) was always manipulated within blocks in both tasks. Regression analysis were conducted between either the grey matter lesion size or the white matter tracts disconnection and the three temporal preparation effects separately. The main finding was that each temporal preparation effect was predicted by a different network of structures, depending on cue expectancy. Specifically, the Temporal orienting effect was related to both prefrontal and temporal brain areas. The Foreperiod effect was related to right and left prefrontal structures. Sequential effects were predicted by both parietal cortex and left subcortical structures. These findings show a clear dissociation of brain circuits involved in the different ways to prepare in time, showing for the first time the involvement of temporal areas in the Temporal orienting effect, as well as the parietal cortex in the Sequential effects. Copyright © 2016 Elsevier Inc. All rights reserved.

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

Intention to Quit Smoking and Associated Factors in Smokers Newly Diagnosed with Pulmonary Tuberculosis.

PubMed

Aryanpur, Mahshid; Masjedi, Mohammad Reza; Mortaz, Esmaeil; Hosseini, Mostafa; Jamaati, Hmidreza; Tabarsi, Payam; Soori, Hamid; Heydari, Gholam Reza; Kazempour-Dizaji, Mehdi; Emami, Habib; Mozafarian, Alireza

2016-01-01

Several studies have shown that smoking, as a modifiable risk factor, can affect tuberculosis (TB) in different aspects such as enhancing development of TB infection, activation of latent TB and its related mortality. Since willingness to quit smoking is a critical stage, which may lead to quit attempts, being aware of smokers' intention to quit and the related predictors can provide considerable advantages. In this cross-sectional study, subjects were recruited via a multi-stage cluster sampling method. Sampling was performed during 2012-2014 among pulmonary TB (PTB) patients referred to health centers in Tehran implementing the directly observed treatment short course (DOTS) strategy and a TB referral center. Data analysis was conducted using SPSS version 22 and the factors influencing quit intention were assessed using bivariate regression and multiple logistic regression models. In this study 1,127 newly diagnosed PTB patients were studied; from which 284 patients (22%) were current smokers. When diagnosed with TB, 59 (23.8%) smokers quit smoking. Among the remaining 189 (76.2%) patients who continued smoking, 52.4% had intention to quit. In the final multiple logistic regression model, living in urban areas (OR=8.81, P=0.003), having an office job (OR= 7.34, P=0.001), being single (OR=4.89, P=0.016) and a one unit increase in the motivation degree (OR=2.60, P<0.001) were found to increase the intention to quit smoking. The study found that PTB patients who continued smoking had remarkable intention to quit. Thus, it is recommended that smoking cessation interventions should be started at the time of TB diagnosis. Understanding the associated factors can guide the consultants to predict patients' intention to quit and select the most proper management to facilitate smoking cessation for each patient.

Causal relationship between the AHSG gene and BMD through fetuin-A and BMI: multiple mediation analysis.

PubMed

Sritara, C; Thakkinstian, A; Ongphiphadhanakul, B; Chailurkit, L; Chanprasertyothin, S; Ratanachaiwong, W; Vathesatogkit, P; Sritara, P

2014-05-01

Using mediation analysis, a causal relationship between the AHSG gene and bone mineral density (BMD) through fetuin-A and body mass index (BMI) mediators was suggested. Fetuin-A, a multifunctional protein of hepatic origin, is associated with bone mineral density. It is unclear if this association is causal. This study aimed at clarification of this issue. A cross-sectional study was conducted among 1,741 healthy workers from the Electricity Generating Authority of Thailand (EGAT) cohort. The alpha-2-Heremans-Schmid glycoprotein (AHSG) rs2248690 gene was genotyped. Three mediation models were constructed using seemingly unrelated regression analysis. First, the ln[fetuin-A] group was regressed on the AHSG gene. Second, the BMI group was regressed on the AHSG gene and the ln[fetuin-A] group. Finally, the BMD model was constructed by fitting BMD on two mediators (ln[fetuin-A] and BMI) and the independent AHSG variable. All three analyses were adjusted for confounders. The prevalence of the minor T allele for the AHSG locus was 15.2%. The AHSG locus was highly related to serum fetuin-A levels (P < 0.001). Multiple mediation analyses showed that AHSG was significantly associated with BMD through the ln[fetuin-A] and BMI pathway, with beta coefficients of 0.0060 (95% CI 0.0038, 0.0083) and 0.0030 (95% CI 0.0020, 0.0045) at the total hip and lumbar spine, respectively. About 27.3 and 26.0% of total genetic effects on hip and spine BMD, respectively, were explained by the mediation effects of fetuin-A and BMI. Our study suggested evidence of a causal relationship between the AHSG gene and BMD through fetuin-A and BMI mediators.

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.

Using Regression Equations Built from Summary Data in the Psychological Assessment of the Individual Case: Extension to Multiple Regression

ERIC Educational Resources Information Center

Crawford, John R.; Garthwaite, Paul H.; Denham, Annie K.; Chelune, Gordon J.

2012-01-01

Regression equations have many useful roles in psychological assessment. Moreover, there is a large reservoir of published data that could be used to build regression equations; these equations could then be employed to test a wide variety of hypotheses concerning the functioning of individual cases. This resource is currently underused because…

Determinant of factors associated with child health outcomes and service utilization in Ghana: multiple indicator cluster survey conducted in 2011.

PubMed

Dwumoh, Duah; Essuman, Edward Eyipe; Afagbedzi, Seth Kwaku

2014-01-01

The effects of National Health Insurance Scheme in Ghana and its impact on child health outcome and service utilization cannot be underestimated. Despite the tremendous improvement in child health care in Ghana, there are still some challenges in relation to how National health insurance membership, socioeconomic status and other demographic factors impacts on child health outcomes. The study seeks to determine the association between NHIS membership, socio-economic status, geographic location and other relevant background factors, on child health service utilization and outcomes. Secondary data from the Multiple Indicator Cluster Survey conducted in 2011 was used. Multivariate analysis based on Binary Logistic Regression Models and Multiple linear regression techniques was applied to determine factors associated with child health outcomes and service utilization. Collection of best models was based on Hosmer-Lemeshow Goodness-Of-Fit as one criterion of fit and the Akaike Information Criterion. Controlling for confounding effect of socioeconomic status, age of the child, mothers education level and geographic location, the odds of a child developing anemia for children with National Health Insurance Scheme Membership is 65.2% [95% CI: 52.9-80.2] times less than children without National Health Insurance Scheme Membership. The odds of being fully immunized against common childhood illnesses for children with NHIS membership is 2.3[95% CI: 1.4-3.7] times higher than children without National Health Insurance Scheme Membership. There was no association between National Health Insurance Scheme Membership and stunted growth in children. National Health Insurance Scheme Membership was found to be related to child health service utilization (full immunization) of children under five a child's anemia status. Children with NHIS are more likely to be fully immunized against common childhood diseases and are less likely to develop anemia. Stunted growth of children was not associated with National Health Insurance Scheme Membership. Health Education on the registration and the use of the National Health Insurance should be made a national priority to enable the Ministry of Health achieve routine Immunization targets and to reduce to the bearers minimum prevalence of anemia.

Examining Preservice Science Teacher Understanding of Nature of Science: Discriminating Variables on the Aspects of Nature of Science

NASA Astrophysics Data System (ADS)

Jones, William I.

This study examined the understanding of nature of science among participants in their final year of a 4-year undergraduate teacher education program at a Midwest liberal arts university. The Logic Model Process was used as an integrative framework to focus the collection, organization, analysis, and interpretation of the data for the purpose of (1) describing participant understanding of NOS and (2) to identify participant characteristics and teacher education program features related to those understandings. The Views of Nature of Science Questionnaire form C (VNOS-C) was used to survey participant understanding of 7 target aspects of Nature of Science (NOS). A rubric was developed from a review of the literature to categorize and score participant understanding of the target aspects of NOS. Participants' high school and college transcripts, planning guides for their respective teacher education program majors, and science content and science teaching methods course syllabi were examined to identify and categorize participant characteristics and teacher education program features. The R software (R Project for Statistical Computing, 2010) was used to conduct an exploratory analysis to determine correlations of the antecedent and transaction predictor variables with participants' scores on the 7 target aspects of NOS. Fourteen participant characteristics and teacher education program features were moderately and significantly ( p < .01) correlated with participant scores on the target aspects of NOS. The 6 antecedent predictor variables were entered into multiple regression analyses to determine the best-fit model of antecedent predictor variables for each target NOS aspect. The transaction predictor variables were entered into separate multiple regression analyses to determine the best-fit model of transaction predictor variables for each target NOS aspect. Variables from the best-fit antecedent and best-fit transaction models for each target aspect of NOS were then combined. A regression analysis for each of the combined models was conducted to determine the relative effect of these variables on the target aspects of NOS. Findings from the multiple regression analyses revealed that each of the fourteen predictor variables was present in the best-fit model for at least 1 of the 7 target aspects of NOS. However, not all of the predictor variables were statistically significant (p < .007) in the models and their effect (beta) varied. Participants in the teacher education program who had higher ACT Math scores, completed more high school science credits, and were enrolled either in the Middle Childhood with a science concentration program major or in the Adolescent/Young Adult Science Education program major were more likely to have an informed understanding on each of the 7 target aspects of NOS. Analyses of the planning guides and the course syllabi in each teacher education program major revealed differences between the program majors that may account for the results.

Analysis of perceived risk among construction workers: a cross-cultural study and reflection on the Hofstede model.

PubMed

Martinez-Fiestas, Myriam; Rodríguez-Garzón, Ignacio; Delgado-Padial, Antonio; Lucas-Ruiz, Valeriano

2017-09-01

This article presents a cross-cultural study on perceived risk in the construction industry. Worker samples from three different countries were studied: Spain, Peru and Nicaragua. The main goal was to explain how construction workers perceive their occupational hazard and to analyze how this is related to their national culture. The model used to measure perceived risk was the psychometric paradigm. The results show three very similar profiles, indicating that risk perception is independent of nationality. A cultural analysis was conducted using the Hofstede model. The results of this analysis and the relation to perceived risk showed that risk perception in construction is independent of national culture. Finally, a multiple lineal regression analysis was conducted to determine what qualitative attributes could predict the global quantitative size of risk perception. All of the findings have important implications regarding the management of safety in the workplace.

Association of Job Stressors With Panic Attack and Panic Disorder in a Working Population in Japan: A Cross-Sectional Study.

PubMed

Asai, Yumi; Imamura, Kotaro; Kawakami, Norito

2017-06-01

This study aimed to investigate associations of job stressors with panic attack (PA) and panic disorder (PD) among Japanese workers. A cross-sectional online questionnaire survey was conducted of 2060 workers. Job strain, effort/reward imbalance, and workplace social support were measured by the job content questionnaire and effort/reward imbalance questionnaire. These variables were classified into tertiles. PA/PD were measured by self-report based on the mini international neuropsychiatric interview (MINI). Multiple logistic regression was conducted, adjusting for demographic, lifestyle, and health-related covariates. Data from 1965 participants were analyzed. Adjusted odds ratio (OR) of PA/PD was significantly greater for the group with high effort/reward imbalance compared with the group with low effort/reward imbalance (ORs, 2.64 and 2.94, respectively, both P < 0.05). This study found effort/reward imbalance was associated with having PA/PD among Japanese workers.

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

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

2016-04-01

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

Hydraulic conductivity of fly ash-sewage sludge mixes for use in landfill cover liners.

PubMed

Herrmann, Inga; Svensson, Malin; Ecke, Holger; Kumpiene, Jurate; Maurice, Christian; Andreas, Lale; Lagerkvist, Anders

2009-08-01

Secondary materials could help meeting the increasing demand of landfill cover liner materials. In this study, the effect of compaction energy, water content, ash ratio, freezing, drying and biological activity on the hydraulic conductivity of two fly ash-sewage sludge mixes was investigated using a 2(7-1) fractional factorial design. The aim was to identify the factors that influence hydraulic conductivity, to quantify their effects and to assess how a sufficiently low hydraulic conductivity can be achieved. The factors compaction energy and drying, as well as the factor interactions material x ash ratio and ash ratio x compaction energy affected hydraulic conductivity significantly (alpha=0.05). Freezing on five freeze-thaw cycles did not affect hydraulic conductivity. Water content affected hydraulic conductivity only initially. The hydraulic conductivity data were modelled using multiple linear regression. The derived models were reliable as indicated by R(adjusted)(2) values between 0.75 and 0.86. Independent on the ash ratio and the material, hydraulic conductivity was predicted to be between 1.7 x 10(-11)m s(-1) and 8.9 x 10(-10)m s(-1) if the compaction energy was 2.4 J cm(-3), the ash ratio between 20% and 75% and drying did not occur. Thus, the investigated materials met the limit value for non-hazardous waste landfills of 10(-9)m s(-1).

Elbow joint angle and elbow movement velocity estimation using NARX-multiple layer perceptron neural network model with surface EMG time domain parameters.

PubMed

Raj, Retheep; Sivanandan, K S

2017-01-01

Estimation of elbow dynamics has been the object of numerous investigations. In this work a solution is proposed for estimating elbow movement velocity and elbow joint angle from Surface Electromyography (SEMG) signals. Here the Surface Electromyography signals are acquired from the biceps brachii muscle of human hand. Two time-domain parameters, Integrated EMG (IEMG) and Zero Crossing (ZC), are extracted from the Surface Electromyography signal. The relationship between the time domain parameters, IEMG and ZC with elbow angular displacement and elbow angular velocity during extension and flexion of the elbow are studied. A multiple input-multiple output model is derived for identifying the kinematics of elbow. A Nonlinear Auto Regressive with eXogenous inputs (NARX) structure based multiple layer perceptron neural network (MLPNN) model is proposed for the estimation of elbow joint angle and elbow angular velocity. The proposed NARX MLPNN model is trained using Levenberg-marquardt based algorithm. The proposed model is estimating the elbow joint angle and elbow movement angular velocity with appreciable accuracy. The model is validated using regression coefficient value (R). The average regression coefficient value (R) obtained for elbow angular displacement prediction is 0.9641 and for the elbow anglular velocity prediction is 0.9347. The Nonlinear Auto Regressive with eXogenous inputs (NARX) structure based multiple layer perceptron neural networks (MLPNN) model can be used for the estimation of angular displacement and movement angular velocity of the elbow with good accuracy.

The relationship between perceived parental rearing behaviors and school adjustment of adolescent cancer survivors in Korea

PubMed Central

Lee, Sunhee; Kim, Dong Hee

2017-01-01

Abstract Return and adjustment to school in adolescents who have survived cancer have become of increasing interest as the numbers of childhood cancers survivors have grown due to advances in treatments. Perceived parental rearing behavior is an important factor related to school adjustment. This study examined the relationships between maternal and parental rearing practices, general characteristics, and school adjustment in adolescent cancer survivors in Korea. We conducted a descriptive, exploratory study of 84 adolescents with cancer using the Korean version of the Fragebogen zum erinnerten elterlichen Erziehungsverhalten: FEE (Recalled Parental Rearing Behavior) and a school adjustment measurement. Descriptive, Pearson correlational, and multiple regression analyses were used to investigate the data. In bivariate analysis, age (r = −0.358, P < .05), mother's emotional warmth (r = 0.549, P < .01), and father's emotional warmth (r = 0.391, P < .05) were significantly associated with school adjustment. However, the results of multiple regression analysis showed that only mother's emotional warmth (β = .720, P < .05) was significantly associated with school adjustment. Adolescent cancer survivors who reported higher mother's emotional warmth exhibited better school adjustment. This finding indicates that it is important to help parents of adolescent cancer survivors enhance their parental rearing behaviors, such as emotional warmth, to help adolescents adjust to school. PMID:28796068

Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions.

PubMed

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y; Chen, Wei

2016-02-01

Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, here we develop Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT), which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. © 2016 WILEY PERIODICALS, INC.

Cigarette smoking and its association with serum lipid/lipoprotein among Chinese nonagenarians/centenarians

PubMed Central

2012-01-01

Objective Cigarette smoking had been confirmed as an increased risk for dyslipidemia, but none of the evidence was from long-lived population. In present study, we detected relationship between cigarette smoking habits and serum lipid/lipoprotein (serum Triglyceride (TG), Total cholesterol (TC), Low-density lipoprotein (LDL) and high-density lipoprotein (HDL)) among Chinese Nonagenarians/Centenarian. Methods The present study analyzed data from the survey that was conducted on all residents aged 90 years or more in a district, there were 2,311,709 inhabitants in 2005. Unpaired Student’s t test, χ2 test, and multiple logistic regression were used to analyze datas. Results The individuals included in the statistical analysis were 216 men and 445 women. Current smokers had lower level of TC (4.05 ± 0.81 vs. 4.21 ± 0.87, t = 2.403, P = 0.017) and lower prevalence of hypercholesteremia (9.62% vs. 15.13%, χ2 = 3.018,P = 0.049) than nonsmokers. Unadjusted and adjusted multiple logistic regressions showed that cigarette smoking was not associated with risk for abnormal serum lipid/lipoprotein. Conclusions In summary, we found that among Chinese nonagenarians/centenarians, cigarette smoking habits were not associated with increased risk for dyslipidemia, which was different from the association of smoking habits with dyslipidemia in general population. PMID:22828289

Modelling of dissolved oxygen content using artificial neural networks: Danube River, North Serbia, case study.

PubMed

Antanasijević, Davor; Pocajt, Viktor; Povrenović, Dragan; Perić-Grujić, Aleksandra; Ristić, Mirjana

2013-12-01

The aims of this study are to create an artificial neural network (ANN) model using non-specific water quality parameters and to examine the accuracy of three different ANN architectures: General Regression Neural Network (GRNN), Backpropagation Neural Network (BPNN) and Recurrent Neural Network (RNN), for prediction of dissolved oxygen (DO) concentration in the Danube River. The neural network model has been developed using measured data collected from the Bezdan monitoring station on the Danube River. The input variables used for the ANN model are water flow, temperature, pH and electrical conductivity. The model was trained and validated using available data from 2004 to 2008 and tested using the data from 2009. The order of performance for the created architectures based on their comparison with the test data is RNN > GRNN > BPNN. The ANN results are compared with multiple linear regression (MLR) model using multiple statistical indicators. The comparison of the RNN model with the MLR model indicates that the RNN model performs much better, since all predictions of the RNN model for the test data were within the error of less than ± 10 %. In case of the MLR, only 55 % of predictions were within the error of less than ± 10 %. The developed RNN model can be used as a tool for the prediction of DO in river waters.

Gene-based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions

PubMed Central

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E.; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y.; Chen, Wei

2015-01-01

Summary Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, we develop here Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT) which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. PMID:26782979

Fear of cancer recurrence and psychological well-being in women with breast cancer: The role of causal cancer attributions and optimism.

PubMed

Dumalaon-Canaria, J A; Prichard, I; Hutchinson, A D; Wilson, C

2018-01-01

This study aims to examine the association between cancer causal attributions, fear of cancer recurrence (FCR) and psychological well-being and the possible moderating effect of optimism among women with a previous diagnosis of breast cancer. Participants (N = 314) completed an online self-report assessment of causal attributions for their own breast cancer, FCR, psychological well-being and optimism. Simultaneous multiple regression analyses were conducted to explore the overall contribution of causal attributions to FCR and psychological well-being separately. Hierarchical multiple regression analyses were also utilised to examine the potential moderating influence of dispositional optimism on the relationship between causal attributions and FCR and psychological well-being. Causal attributions of environmental exposures, family history and stress were significantly associated with higher FCR. The attribution of stress was also significantly associated with lower psychological well-being. Optimism did not moderate the relationship between causal attributions and FCR or well-being. The observed relationships between causal attributions for breast cancer and FCR and psychological well-being suggest that the inclusion of causal attributions in screening for FCR is potentially important. Health professionals may need to provide greater psychological support to women who attribute their cancer to non-modifiable causes and consequently continue to experience distress. © 2016 John Wiley & Sons Ltd.

Internal and external environmental factors affecting the performance of hospital-based home nursing care.

PubMed

Noh, J-W; Kwon, Y-D; Yoon, S-J; Hwang, J-I

2011-06-01

Numerous studies on HNC services have been carried out by signifying their needs, efficiency and effectiveness. However, no study has ever been performed to determine the critical factors associated with HNC's positive results despite the deluge of positive studies on the service. This study included all of the 89 training hospitals that were practising HNC service in Korea as of November 2006. The input factors affecting the performance were classified as either internal or external environmental factors. This analysis was conducted to understand the impact that the corresponding factors had on performance. Data were analysed by using multiple linear regressions. The internal and external environment variables affected the performance of HNC based on univariate analysis. The meaningful variables were internal environmental factors. Specifically, managerial resource (the number of operating beds and the outpatient/inpatient ratio) were meaningful when the multiple linear regression analysis was performed. Indeed, the importance of organizational culture (the passion of HNC nurses) was significant. This study, considering the limited market size of Korea, illustrates that the critical factor for the development of hospital-led HNC lies with internal environmental factors rather than external ones. Among the internal environmental factors, the hospitals' managerial resource-related factors (specifically, the passion of nurses) were the most important contributing element. © 2011 The Authors. International Nursing Review © 2011 International Council of Nurses.

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.

Comparison of risk factors for tooth loss between professional drivers and white-collar workers: an internet survey.

PubMed

Suzuki, Seitaro; Yoshino, Koichi; Takayanagi, Atsushi; Ishizuka, Yoichi; Satou, Ryouichi; Kamijo, Hideyuki; Sugihara, Naoki

2016-06-10

This cross-sectional study was conducted to examine tooth loss and associated factors among professional drivers and white-collar workers. The participants were recruited by applying screening procedures to a pool of Japanese registrants in an online database. The participants were asked to complete a self-reported questionnaire. A total of 592 professional drivers and 328 white-collar workers (male, aged 30 to 69 years) were analyzed. A multiple logistic regression analysis was performed to identify differences between professional drivers and white-collar workers. The results showed that professional drivers had fewer teeth than white-collar workers (odds ratio [OR], 1.74; 95% confidence interval [95% CI], 1.150-2.625). Moreover, a second multiple logistic regression analysis revealed that several factors were associated with the number of teeth among professional drivers: diabetes mellitus (OR, 2.68; 95% CI, 1.388-5.173), duration of brushing teeth (OR, 1.66; 95% CI, 1.066-2.572), frequency of eating breakfast (OR, 2.23; 95% CI, 1.416-3.513), frequency of eating out (OR, 1.70; 95% CI, 1.086-2.671) and smoking status (OR, 2.88; 95% CI, 1.388-5.964). These findings suggest that the lifestyles of professional drivers could be related to not only their general health status, but also tooth loss.

[Impacts of antiretroviral treatment on drug use and high risk sexual behaviors among HIV-positive MMT clients].

PubMed

Qian, Xiaoai; Cao, Xiaobin; Zhao, Yan; Wang, Changhe; Luo, Wei; Rou, Keming; Zhang, Bo; Min, Xiangdong; Duan, Song; Tang, Renhai; Wu, Zunyou

2015-06-01

To explore the impacts of antiretroviral treatment on drug use and high risk sexual behaviors among HIV-positive MMT clients. A cross-sectional study was conducted in patients undergoing ART (ART-experienced) and patients not undergoing ART (ART-naive) attending MMT in 5 clinics in Yunnan Honghe and Dehong prefectures in 2014. A questionnaire was designed to collect socio-demographic characteristics, ART and MMT information and sexual and drug use behaviors within 3 months before the investigation was conducted. Logistic regression analysis was conducted to identify the predictors for drug use and risky sexual behaviors. A total of 328 cases were included in the analysis, among which 202 were ART-experienced and 126 were ART-naÏve. Among 152 respondents who were sexually active, 61 (40.1%) reported having unprotected sex (UPS) with their regular partners in the prior 3 months. A total of 57.6% (189/328) of the respondents used drugs in the prior 3 months. Multiple logistic regression analysis revealed that younger than 35 years old (OR = 3.57, 95% CI: 1.23-10.37), fertility desire (OR = 4.47, 95% CI: 1.49-13.41), partner being HIV-positive (OR = 4.62, 95% CI: 1.80-11.86), length of MMT attendance less than 5 years (OR = 2.92, 95% CI: 1.14-7.53), agreed that it was necessary to use condom no matter the viral load is high or low (OR = 0.14, 95% CI: 0.04-0.51) were protective factors of UPS in the prior 3 months. Multiple logistic regression analysis revealed that being Han (OR = 0.46, 95% CI: 0.24-0.89), feeling having good health status (OR = 0.39, 95% CI: 0.18-0.85), being enrolled in ART (OR = 0.32, 95% CI: 0.17-0.60) were protective factors for drug use in the prior three months, having contact with drug using friends (OR = 4.41, 95% CI: 2.31-8.29), having experience of missing an MMT dose (OR = 3.47, 95% CI: 1.92-6.29), and not satisfied with current MMT dose (OR = 13.92, 95% CI: 3.24-59.93) were risk factors for drug use during the prior three months. ART was not associated with risky sexual behavior and drug use in the prior 3 months in this population. Future interventions should promote ART among this population, and provide education at the same time to prevent the emergence of cross infections and drug-resistant strains.

Regression Commonality Analysis: A Technique for Quantitative Theory Building

ERIC Educational Resources Information Center

Nimon, Kim; Reio, Thomas G., Jr.

2011-01-01

When it comes to multiple linear regression analysis (MLR), it is common for social and behavioral science researchers to rely predominately on beta weights when evaluating how predictors contribute to a regression model. Presenting an underutilized statistical technique, this article describes how organizational researchers can use commonality…

Precision Efficacy Analysis for Regression.

ERIC Educational Resources Information Center

Brooks, Gordon P.

When multiple linear regression is used to develop a prediction model, sample size must be large enough to ensure stable coefficients. If the derivation sample size is inadequate, the model may not predict well for future subjects. The precision efficacy analysis for regression (PEAR) method uses a cross- validity approach to select sample sizes…

Guidelines and Procedures for Computing Time-Series Suspended-Sediment Concentrations and Loads from In-Stream Turbidity-Sensor and Streamflow Data

USGS Publications Warehouse

Rasmussen, Patrick P.; Gray, John R.; Glysson, G. Douglas; Ziegler, Andrew C.

2009-01-01

In-stream continuous turbidity and streamflow data, calibrated with measured suspended-sediment concentration data, can be used to compute a time series of suspended-sediment concentration and load at a stream site. Development of a simple linear (ordinary least squares) regression model for computing suspended-sediment concentrations from instantaneous turbidity data is the first step in the computation process. If the model standard percentage error (MSPE) of the simple linear regression model meets a minimum criterion, this model should be used to compute a time series of suspended-sediment concentrations. Otherwise, a multiple linear regression model using paired instantaneous turbidity and streamflow data is developed and compared to the simple regression model. If the inclusion of the streamflow variable proves to be statistically significant and the uncertainty associated with the multiple regression model results in an improvement over that for the simple linear model, the turbidity-streamflow multiple linear regression model should be used to compute a suspended-sediment concentration time series. The computed concentration time series is subsequently used with its paired streamflow time series to compute suspended-sediment loads by standard U.S. Geological Survey techniques. Once an acceptable regression model is developed, it can be used to compute suspended-sediment concentration beyond the period of record used in model development with proper ongoing collection and analysis of calibration samples. Regression models to compute suspended-sediment concentrations are generally site specific and should never be considered static, but they represent a set period in a continually dynamic system in which additional data will help verify any change in sediment load, type, and source.

Guideline appraisal with AGREE II: Systematic review of the current evidence on how users handle the 2 overall assessments.

PubMed

Hoffmann-Eßer, Wiebke; Siering, Ulrich; Neugebauer, Edmund A M; Brockhaus, Anne Catharina; Lampert, Ulrike; Eikermann, Michaela

2017-01-01

The Appraisal of Guidelines for Research & Evaluation (AGREE) II instrument is the most commonly used guideline appraisal tool. It includes 23 appraisal criteria (items) organized within 6 domains and 2 overall assessments (1. overall guideline quality; 2. recommendation for use). The aim of this systematic review was twofold. Firstly, to investigate how often AGREE II users conduct the 2 overall assessments. Secondly, to investigate the influence of the 6 domain scores on each of the 2 overall assessments. A systematic bibliographic search was conducted for publications reporting guideline appraisals with AGREE II. The impact of the 6 domain scores on the overall assessment of guideline quality was examined using a multiple linear regression model. Their impact on the recommendation for use (possible answers: "yes", "yes, with modifications", "no") was examined using a multinomial regression model. 118 relevant publications including 1453 guidelines were identified. 77.1% of the publications reported results for at least one overall assessment, but only 32.2% reported results for both overall assessments. The results of the regression analyses showed a statistically significant influence of all domains on overall guideline quality, with Domain 3 (rigour of development) having the strongest influence. For the recommendation for use, the results showed a significant influence of Domains 3 to 5 ("yes" vs. "no") and Domains 3 and 5 ("yes, with modifications" vs. "no"). The 2 overall assessments of AGREE II are underreported by guideline assessors. Domains 3 and 5 have the strongest influence on the results of the 2 overall assessments, while the other domains have a varying influence. Within a normative approach, our findings could be used as guidance for weighting individual domains in AGREE II to make the overall assessments more objective. Alternatively, a stronger content analysis of the individual domains could clarify their importance in terms of guideline quality. Moreover, AGREE II should require users to transparently present how they conducted the assessments.

A Practical Guide to Conducting a Systematic Review and Meta-analysis of Health State Utility Values.

PubMed

Petrou, Stavros; Kwon, Joseph; Madan, Jason

2018-05-10

Economic analysts are increasingly likely to rely on systematic reviews and meta-analyses of health state utility values to inform the parameter inputs of decision-analytic modelling-based economic evaluations. Beyond the context of economic evaluation, evidence from systematic reviews and meta-analyses of health state utility values can be used to inform broader health policy decisions. This paper provides practical guidance on how to conduct a systematic review and meta-analysis of health state utility values. The paper outlines a number of stages in conducting a systematic review, including identifying the appropriate evidence, study selection, data extraction and presentation, and quality and relevance assessment. The paper outlines three broad approaches that can be used to synthesise multiple estimates of health utilities for a given health state or condition, namely fixed-effect meta-analysis, random-effects meta-analysis and mixed-effects meta-regression. Each approach is illustrated by a synthesis of utility values for a hypothetical decision problem, and software code is provided. The paper highlights a number of methodological issues pertinent to the conduct of meta-analysis or meta-regression. These include the importance of limiting synthesis to 'comparable' utility estimates, for example those derived using common utility measurement approaches and sources of valuation; the effects of reliance on limited or poorly reported published data from primary utility assessment studies; the use of aggregate outcomes within analyses; approaches to generating measures of uncertainty; handling of median utility values; challenges surrounding the disentanglement of utility estimates collected serially within the context of prospective observational studies or prospective randomised trials; challenges surrounding the disentanglement of intervention effects; and approaches to measuring model validity. Areas of methodological debate and avenues for future research are highlighted.

Prospective relations between family conflict and adolescent maladjustment: security in the family system as a mediating process.

PubMed

Cummings, E Mark; Koss, Kalsea J; Davies, Patrick T

2015-04-01

Conflict in specific family systems (e.g., interparental, parent-child) has been implicated in the development of a host of adjustment problems in adolescence, but little is known about the impact of family conflict involving multiple family systems. Furthermore, questions remain about the effects of family conflict on symptoms of specific disorders and adjustment problems and the processes mediating these effects. The present study prospectively examines the impact of family conflict and emotional security about the family system on adolescent symptoms of specific disorders and adjustment problems, including the development of symptoms of anxiety, depression, conduct problems, and peer problems. Security in the family system was examined as a mediator of these relations. Participants included 295 mother-father-adolescent families (149 girls) participating across three annual time points (grades 7-9). Including auto-regressive controls for initial levels of emotional insecurity and multiple adjustment problems (T1), higher-order emotional insecurity about the family system (T2) mediated relations between T1 family conflict and T3 peer problems, anxiety, and depressive symptoms. Further analyses supported specific patterns of emotional security/insecurity (i.e., security, disengagement, preoccupation) as mediators between family conflict and specific domains of adolescent adjustment. Family conflict was thus found to prospectively predict the development of symptoms of multiple specific adjustment problems, including symptoms of depression, anxiety, conduct problems, and peer problems, by elevating in in adolescent's emotional insecurity about the family system. The clinical implications of these findings are considered.

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.

Optimization of fixture layouts of glass laser optics using multiple kernel regression.

PubMed

Su, Jianhua; Cao, Enhua; Qiao, Hong

2014-05-10

We aim to build an integrated fixturing model to describe the structural properties and thermal properties of the support frame of glass laser optics. Therefore, (a) a near global optimal set of clamps can be computed to minimize the surface shape error of the glass laser optic based on the proposed model, and (b) a desired surface shape error can be obtained by adjusting the clamping forces under various environmental temperatures based on the model. To construct the model, we develop a new multiple kernel learning method and call it multiple kernel support vector functional regression. The proposed method uses two layer regressions to group and order the data sources by the weights of the kernels and the factors of the layers. Because of that, the influences of the clamps and the temperature can be evaluated by grouping them into different layers.

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

Comparison among methods of effective energy evaluation of corn silage for beef cattle.

PubMed

Wei, Ming; Chen, Zhiqiang; Wei, Shengjuan; Geng, Guangduo; Yan, Peishi

2018-06-01

This study was conducted to compare different methods on effective energy evaluation of corn silage for beef cattle. Twenty Wandong bulls (Chinese indigenous yellow cattle) with initial body weight of 281±15.6 kg, were assigned to 1 of 5 dietary treatments with 4 animals per treatment in a randomized complete block design. Five dietary treatments included group 1 with corn silage only diet, group 2 with corn silage-concentrate basal diet (BD) and 3 groups with 3 test diets, which were the BD partly substituted by corn silage at 10%, 30%, and 60%. The total collection digestion trial was conducted for 5 d for each block after a 10-d adaptation period, and then an open-circuit respiratory cage was used to measure the gas exchange of each animal in a consecutive 4-d period. The direct method-derived metabolizable energy and net energy of corn silage were 8.86 and 5.15 MJ/kg dry matter (DM), expressed as net energy requirement for maintenance and gain were 5.28 and 2.90 MJ/kg DM, respectively; the corresponding regression method-derived estimates were 8.96, 5.34, 5.37, and 2.98 MJ/kg DM, respectively. The direct method-derived estimates were not different (p>0.05) from those obtained using the regression method. Using substitution method, the nutrient apparent digestibility and effective energy values of corn silage varied with the increased corn silage substitution ratio (p<0.05). In addition, the corn silage estimates at the substitution ratio of 30% were similar to those estimated by direct and regression methods. In determining the energy value of corn silage using substitution method, there was a discrepancy between different substitution ratios, and the substitution ratio of 30% was more appropriate than 10% or 60% in the current study. The regression method based on multiple point substitution was more appropriate than single point substitution on energy evaluation of feedstuffs for beef cattle.

[Associations of the Employment Status during the First 2 Years Following Medical Rehabilitation and Long Term Occupational Trajectories: Implications for Outcome Measurement].

PubMed

Holstiege, J; Kaluscha, R; Jankowiak, S; Krischak, G

2017-02-01

Study Objectives: The aim was to investigate the predictive value of the employment status measured in the 6 th , 12 th , 18 th and 24 th month after medical rehabilitation for long-term employment trajectories during 4 years. Methods: A retrospective study was conducted based on a 20%-sample of all patients receiving inpatient rehabilitation funded by the German pension fund. Patients aged <62 years who were treated due to musculoskeletal, cardiovascular or psychosomatic disorders during the years 2002-2005 were included and followed for 4 consecutive years. The predictive value of the employment status in 4 predefined months after discharge (6 th , 12 th , 18 th and 24 th month), for the total number of months in employment in 4 years following rehabilitative treatment was analyzed using multiple linear regression. Per time point, separate regression analyses were conducted, including the employment status (employed vs. unemployed) at the respective point in time as explanatory variable, besides a standard set of additional prognostic variables. Results: A total of 252 591 patients were eligible for study inclusion. The level of explained variance of the regression models increased with the point in time used to measure the employment status, included as explanatory variable. Overall the R²-measure increased by 30% from the regression model that included the employment status in the 6 th month (R²=0.60) to the model that included the work status in the 24 th month (R²=0.78). Conclusion: The degree of accuracy in the prognosis of long-term employment biographies increases with the point in time used to measure employment in the first 2 years following rehabilitation. These findings should be taken into consideration for the predefinition of time points used to measure the employment status in future studies. © Georg Thieme Verlag KG Stuttgart · New York.

Weighted regression analysis and interval estimators

Treesearch

Donald W. Seegrist

1974-01-01

A method for deriving the weighted least squares estimators for the parameters of a multiple regression model. Confidence intervals for expected values, and prediction intervals for the means of future samples are given.

Estimation of premorbid general fluid intelligence using traditional Chinese reading performance in Taiwanese samples.

PubMed

Chen, Ying-Jen; Ho, Meng-Yang; Chen, Kwan-Ju; Hsu, Chia-Fen; Ryu, Shan-Jin

2009-08-01

The aims of the present study were to (i) investigate if traditional Chinese word reading ability can be used for estimating premorbid general intelligence; and (ii) to provide multiple regression equations for estimating premorbid performance on Raven's Standard Progressive Matrices (RSPM), using age, years of education and Chinese Graded Word Reading Test (CGWRT) scores as predictor variables. Four hundred and twenty-six healthy volunteers (201 male, 225 female), aged 16-93 years (mean +/- SD, 41.92 +/- 18.19 years) undertook the tests individually under supervised conditions. Seventy percent of subjects were randomly allocated to the derivation group (n = 296), and the rest to the validation group (n = 130). RSPM score was positively correlated with CGWRT score and years of education. RSPM and CGWRT scores and years of education were also inversely correlated with age, but the declining trend for RSPM performance against age was steeper than that for CGWRT performance. Separate multiple regression equations were derived for estimating RSPM scores using different combinations of age, years of education, and CGWRT score for both groups. The multiple regression coefficient of each equation ranged from 0.71 to 0.80 with the standard error of estimate between 7 and 8 RSPM points. When fitting the data of one group to the equations derived from its counterpart group, the cross-validation multiple regression coefficients ranged from 0.71 to 0.79. There were no significant differences in the 'predicted-obtained' RSPM discrepancies between any equations. The regression equations derived in the present study may provide a basis for estimating premorbid RSPM performance.

Overall Preference of Running Shoes Can Be Predicted by Suitable Perception Factors Using a Multiple Regression Model.

PubMed

Tay, Cheryl Sihui; Sterzing, Thorsten; Lim, Chen Yen; Ding, Rui; Kong, Pui Wah

2017-05-01

This study examined (a) the strength of four individual footwear perception factors to influence the overall preference of running shoes and (b) whether these perception factors satisfied the nonmulticollinear assumption in a regression model. Running footwear must fulfill multiple functional criteria to satisfy its potential users. Footwear perception factors, such as fit and cushioning, are commonly used to guide shoe design and development, but it is unclear whether running-footwear users are able to differentiate one factor from another. One hundred casual runners assessed four running shoes on a 15-cm visual analogue scale for four footwear perception factors (fit, cushioning, arch support, and stability) as well as for overall preference during a treadmill running protocol. Diagnostic tests showed an absence of multicollinearity between factors, where values for tolerance ranged from .36 to .72, corresponding to variance inflation factors of 2.8 to 1.4. The multiple regression model of these four footwear perception variables accounted for 77.7% to 81.6% of variance in overall preference, with each factor explaining a unique part of the total variance. Casual runners were able to rate each footwear perception factor separately, thus assigning each factor a true potential to improve overall preference for the users. The results also support the use of a multiple regression model of footwear perception factors to predict overall running shoe preference. Regression modeling is a useful tool for running-shoe manufacturers to more precisely evaluate how individual factors contribute to the subjective assessment of running footwear.

A population-based study on the association between rheumatoid arthritis and voice problems.

PubMed

Hah, J Hun; An, Soo-Youn; Sim, Songyong; Kim, So Young; Oh, Dong Jun; Park, Bumjung; Kim, Sung-Gyun; Choi, Hyo Geun

2016-07-01

The objective of this study was to investigate whether rheumatoid arthritis increases the frequency of organic laryngeal lesions and the subjective voice complaint rate in those with no organic laryngeal lesion. We performed a cross-sectional study using the data from 19,368 participants (418 rheumatoid arthritis patients and 18,950 controls) of the 2008-2011 Korea National Health and Nutrition Examination Survey. The associations between rheumatoid arthritis and organic laryngeal lesions/subjective voice complaints were analyzed using simple/multiple logistic regression analysis with complex sample adjusting for confounding factors, including age, sex, smoking status, stress level, and body mass index, which could provoke voice problems. Vocal nodules, vocal polyp, and vocal palsy were not associated with rheumatoid arthritis in a multiple regression analysis, and only laryngitis showed a positive association (adjusted odds ratio, 1.59; 95 % confidence interval, 1.01-2.52; P = 0.047). Rheumatoid arthritis was associated with subjective voice discomfort in a simple regression analysis, but not in a multiple regression analysis. Participants with rheumatoid arthritis were older, more often female, and had higher stress levels than those without rheumatoid arthritis. These factors were associated with subjective voice complaints in both simple and multiple regression analyses. Rheumatoid arthritis was not associated with organic laryngeal diseases except laryngitis. Rheumatoid arthritis did not increase the odds ratio for subjective voice complaints. Voice problems in participants with rheumatoid arthritis originated from the characteristics of the rheumatoid arthritis group (higher mean age, female sex, and stress level) rather than rheumatoid arthritis itself.

Predicting MHC-II binding affinity using multiple instance regression

PubMed Central

EL-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2011-01-01

Reliably predicting the ability of antigen peptides to bind to major histocompatibility complex class II (MHC-II) molecules is an essential step in developing new vaccines. Uncovering the amino acid sequence correlates of the binding affinity of MHC-II binding peptides is important for understanding pathogenesis and immune response. The task of predicting MHC-II binding peptides is complicated by the significant variability in their length. Most existing computational methods for predicting MHC-II binding peptides focus on identifying a nine amino acids core region in each binding peptide. We formulate the problems of qualitatively and quantitatively predicting flexible length MHC-II peptides as multiple instance learning and multiple instance regression problems, respectively. Based on this formulation, we introduce MHCMIR, a novel method for predicting MHC-II binding affinity using multiple instance regression. We present results of experiments using several benchmark datasets that show that MHCMIR is competitive with the state-of-the-art methods for predicting MHC-II binding peptides. An online web server that implements the MHCMIR method for MHC-II binding affinity prediction is freely accessible at http://ailab.cs.iastate.edu/mhcmir. PMID:20855923

Multiple-Shrinkage Multinomial Probit Models with Applications to Simulating Geographies in Public Use Data.

PubMed

Burgette, Lane F; Reiter, Jerome P

2013-06-01

Multinomial outcomes with many levels can be challenging to model. Information typically accrues slowly with increasing sample size, yet the parameter space expands rapidly with additional covariates. Shrinking all regression parameters towards zero, as often done in models of continuous or binary response variables, is unsatisfactory, since setting parameters equal to zero in multinomial models does not necessarily imply "no effect." We propose an approach to modeling multinomial outcomes with many levels based on a Bayesian multinomial probit (MNP) model and a multiple shrinkage prior distribution for the regression parameters. The prior distribution encourages the MNP regression parameters to shrink toward a number of learned locations, thereby substantially reducing the dimension of the parameter space. Using simulated data, we compare the predictive performance of this model against two other recently-proposed methods for big multinomial models. The results suggest that the fully Bayesian, multiple shrinkage approach can outperform these other methods. We apply the multiple shrinkage MNP to simulating replacement values for areal identifiers, e.g., census tract indicators, in order to protect data confidentiality in public use datasets.

Quality of life and functional capacity in patients with rheumatoid arthritis - Cross-sectional study.

PubMed

Rosa-Gonçalves, Diana; Bernardes, Miguel; Costa, Lúcia

2017-04-08

To analyze the Health related Quality of Life (HRQoL) and physical function in rheumatoid arthritis (RA) patients and compare it with the general population. We also intended to analyze about disease activity influence in HRQoL and functional capacity, as well as determine potential determinants for these outcomes. A cross-sectional study was conducted in RA patients from a university hospital of Portugal. We obtained Short Form 36, EuroQoL 5D, health assessment questionnaire, visual analog scale for pain and patient's assessment of disease activity. Comparisons between SF-36 and EQ-5D values with our population reference values were conducted using the Mann-Whitney test. Data were compared in different levels of disease activity, using Kruskal Wallis test and Fisher's exact test. A multiple regression analysis was conducted to identify the potential determinants of outcomes. RA sample showed significantly lower values than the portuguese general population on physical summary measure of SF-36 (median=32 vs. 50, p<0.001) and EQ-5D (median=0.620 vs. 0.758 respectively; p<0.001). Lower disease activity levels had better PROs and this was true even when compared patients achieving remission with those in low disease activity. The HAQ (r 2 =67%), VAS-P (r 2 =62%) and VAS-DA (r 2 =58%) were the variables that strongly related to SF-36. Considering HAQ, the strongest relation was found with VAS-P, VAS-DA and age (r 2 =60%, 61% and 33%, respectively). Multiple regression analysis identified HAQ, VAS-P and educational status as determinants of the HRQoL; age, female gender, employment, VAS-P and VAS-DA as determinants of physical function. Impairment of HRQoL in RA patients is enormous. We found significant differences between different levels of disease activity, showing higher HRQoL and functional capacity at lower disease activity levels. Copyright © 2017 Elsevier España, S.L.U. and Sociedad Española de Reumatología y Colegio Mexicano de Reumatología. All rights reserved.

Health-related quality of life in multiple sclerosis: role of cognitive appraisals of self, illness and treatment.

PubMed

Wilski, Maciej; Tasiemski, Tomasz

2016-07-01

Health-related quality of life (HRQoL) is considered an important measure of treatment and rehabilitation outcomes in multiple sclerosis (MS) patients. In this study, we used multivariate regression analysis to examine the role of cognitive appraisals, adjusted for clinical, socioeconomic and demographic variables, as correlates of HRQoL in MS. The cross-sectional study included 257 MS patients, who completed Multiple Sclerosis Impact Scale, Generalized Self-Efficacy Scale, Rosenberg Self-Esteem Scale, Brief Illness Perception Questionnaire, Treatment Beliefs Scale, Actually Received Support Scale (a part of Berlin Social Support Scale) and Socioeconomic Resources Scale. Demographic and clinical characteristics of the participants were collected with a self-report survey. Correlation and regression analyses were conducted to determine associations between the variables. Five variables, illness identity (β = 0.29, p ≤ 0.001), self-esteem (β = -0.22, p ≤ 0.001), general self-efficacy (β = -0.21, p ≤ 0.001), disability subgroup "EDSS" (β = 0.14, p = 0.006) and age (β = 0.12, p = 0.012), were significant correlates of HRQoL in MS. These variables explained 46 % of variance in the dependent variable. Moreover, we identified correlates of physical and psychological dimensions of HRQoL. Cognitive appraisals, such as general self-efficacy, self-esteem and illness perception, are more salient correlates of HRQoL than social support, socioeconomic resources and clinical characteristics, such as type and duration of MS. Therefore, interventions aimed at cognitive appraisals may also improve HRQoL of MS patients.

ERP correlates of word production predictors in picture naming: a trial by trial multiple regression analysis from stimulus onset to response.

PubMed

Valente, Andrea; Bürki, Audrey; Laganaro, Marina

2014-01-01

A major effort in cognitive neuroscience of language is to define the temporal and spatial characteristics of the core cognitive processes involved in word production. One approach consists in studying the effects of linguistic and pre-linguistic variables in picture naming tasks. So far, studies have analyzed event-related potentials (ERPs) during word production by examining one or two variables with factorial designs. Here we extended this approach by investigating simultaneously the effects of multiple theoretical relevant predictors in a picture naming task. High density EEG was recorded on 31 participants during overt naming of 100 pictures. ERPs were extracted on a trial by trial basis from picture onset to 100 ms before the onset of articulation. Mixed-effects regression models were conducted to examine which variables affected production latencies and the duration of periods of stable electrophysiological patterns (topographic maps). Results revealed an effect of a pre-linguistic variable, visual complexity, on an early period of stable electric field at scalp, from 140 to 180 ms after picture presentation, a result consistent with the proposal that this time period is associated with visual object recognition processes. Three other variables, word Age of Acquisition, Name Agreement, and Image Agreement influenced response latencies and modulated ERPs from ~380 ms to the end of the analyzed period. These results demonstrate that a topographic analysis fitted into the single trial ERPs and covering the entire processing period allows one to associate the cost generated by psycholinguistic variables to the duration of specific stable electrophysiological processes and to pinpoint the precise time-course of multiple word production predictors at once.

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.

Increased risk of kidney damage among Chinese adults with simple renal cyst.

PubMed

Kong, Xianglei; Ma, Xiaojing; Zhang, Chengyin; Su, Hong; Gong, Xiaojie; Xu, Dongmei

2018-05-04

The presence of simple renal cyst (SRC) has been related to hypertension, the early and long-term allograft function, and aortic disease, but the relationship with kidney damage was still controversial. Accordingly, we conducted a large sample cross-sectional study to explore the association of SRC with indicators of kidney damage among Chinese adults. A total of 42,369 adults (aged 45.8 ± 13.67 years, 70.6% males) who visited the Health Checkup Clinic were consecutively enrolled. SRC was assessed by ultrasonography according to Bosniak category. Multiple regression models were applied to explore the relationships between SRC and indicators of kidney damage [proteinuria (dipstick urine protein ≥ 1+) and decreased estimated glomerular filtration rate (DeGFR) < 60 ml/min/1.73 m 2 ]. Among all participants in the study, the prevalence of SRC was 10.5%. As a categorical outcome, participants with more 1 cyst and with 1 cyst had higher percentage of proteinuria [53 (5.3%) and 93 (2.7%) vs. 596 (1.6%), p < 0.001] and DeGFR [57 (5.7%) and 85 (2.5%) vs. 278 (0.7%), p < 0.001] compared with participants with no cyst. SRC significantly correlated with proteinuria [OR 1.59 (95% CI 1.30-1.95)] and DeGFR [OR 1.97 (95% CI 1.56-2.47)] after adjusting for potential confounders. Furthermore, the results also demonstrated that maximum diameter (per 1 cm increase), bilateral location, and multiple cysts significantly correlated with DeGFR in the multiple logistic regression analysis. The study revealed that SRC significantly correlated with kidney damage and special attention should be paid among Chinese adults with SRC.

Urinary excretion of uric acid is negatively associated with albuminuria in patients with chronic kidney disease: a cross-sectional study.

PubMed

Li, Fengqin; Guo, Hui; Zou, Jianan; Chen, Weijun; Lu, Yijun; Zhang, Xiaoli; Fu, Chensheng; Xiao, Jing; Ye, Zhibin

2018-04-24

Increasing evidence has shown that albuminuria is related to serum uric acid. Little is known about whether this association may be interrelated via renal handling of uric acid. Therefore, we aim to study urinary uric acid excretion and its association with albuminuria in patients with chronic kidney disease (CKD). A cross-sectional study of 200 Chinese CKD patients recruited from department of nephrology of Huadong hospital was conducted. Levels of 24 h urinary excretion of uric acid (24-h Uur), fractional excretion of uric acid (FEur) and uric acid clearance rate (Cur) according to gender, CKD stages, hypertension and albuminuria status were compared by a multivariate analysis. Pearson and Spearman correlation and multiple regression analyses were used to study the correlation of 24-h Uur, FEur and Cur with urinary albumin to creatinine ratio (UACR). The multivariate analysis showed that 24-h Uur and Cur were lower and FEur was higher in the hypertension group, stage 3-5 CKD and macro-albuminuria group (UACR> 30 mg/mmol) than those in the normotensive group, stage 1 CKD group and the normo-albuminuria group (UACR< 3 mg/mmol) (all P < 0.05). Moreover, males had higher 24-h Uur and lower FEur than females (both P < 0.05). Multiple linear regression analysis showed that UACR was negatively associated with 24-h Uur and Cur (P = 0.021, P = 0.007, respectively), but not with FEur (P = 0.759), after adjusting for multiple confounding factors. Our findings suggested that urinary excretion of uric acid is negatively associated with albuminuria in patients with CKD. This phenomenon may help to explain the association between albuminuria and serum uric acid.

Renal Protective Role of Xiexin Decoction with Multiple Active Ingredients Involves Inhibition of Inflammation through Downregulation of the Nuclear Factor-κB Pathway in Diabetic Rats

PubMed Central

Wu, Jia-sheng; Shi, Rong; Zhong, Jie; Lu, Xiong; Ma, Bing-liang; Wang, Tian-ming; Zan, Bin; Ma, Yue-ming; Cheng, Neng-neng; Qiu, Fu-rong

2013-01-01

In Chinese medicine, Xiexin decoction (XXD) has been used for the clinical treatment of diabetes for at least 1700 years. The present study was conducted to investigate the effective ingredients of XXD and their molecular mechanisms of antidiabetic nephropathy in rats. Rats with diabetes induced by high-fat diet and streptozotocin were treated with XXD extract for 12 weeks. XXD significantly improved the glucolipid metabolism disorder, attenuated albuminuria and renal pathological changes, reduced renal advanced glycation end-products, inhibited receptor for advanced glycation end-product and inflammation factors expression, suppressed renal nuclear factor-κB pathway activity, and downregulated renal transforming growth factor-β1. The concentrations of multiple components in plasma from XXD were determined by liquid chromatography and tandem mass spectrometry. Pharmacokinetic/pharmacodynamic analysis using partial least square regression revealed that 8 ingredients of XXD were responsible for renal protective effects via actions on multiple molecular targets. Our study suggests that the renal protective role of XXD with multiple effective ingredients involves inhibition of inflammation through downregulation of the nuclear factor-κB pathway, reducing renal advanced glycation end-products and receptor for advanced glycation end-product in diabetic rats. PMID:23935673

Quantile Regression in the Study of Developmental Sciences

ERIC Educational Resources Information Center

Petscher, Yaacov; Logan, Jessica A. R.

2014-01-01

Linear regression analysis is one of the most common techniques applied in developmental research, but only allows for an estimate of the average relations between the predictor(s) and the outcome. This study describes quantile regression, which provides estimates of the relations between the predictor(s) and outcome, but across multiple points of…

Maintenance Operations in Mission Oriented Protective Posture Level IV (MOPPIV)

DTIC Science & Technology

1987-10-01

Repair FADAC Printed Circuit Board ............. 6 3. Data Analysis Techniques ............................. 6 a. Multiple Linear Regression... ANALYSIS /DISCUSSION ............................... 12 1. Exa-ple of Regression Analysis ..................... 12 S2. Regression results for all tasks...6 * TABLE 9. Task Grouping for Analysis ........................ 7 "TABXLE 10. Remove/Replace H60A3 Power Pack................. 8 TABLE

Interactions between cadmium and decabrominated diphenyl ether on blood cells count in rats-Multiple factorial regression analysis.

PubMed

Curcic, Marijana; Buha, Aleksandra; Stankovic, Sanja; Milovanovic, Vesna; Bulat, Zorica; Đukić-Ćosić, Danijela; Antonijević, Evica; Vučinić, Slavica; Matović, Vesna; Antonijevic, Biljana

2017-02-01

The objective of this study was to assess toxicity of Cd and BDE-209 mixture on haematological parameters in subacutely exposed rats and to determine the presence and type of interactions between these two chemicals using multiple factorial regression analysis. Furthermore, for the assessment of interaction type, an isobologram based methodology was applied and compared with multiple factorial regression analysis. Chemicals were given by oral gavage to the male Wistar rats weighing 200-240g for 28days. Animals were divided in 16 groups (8/group): control vehiculum group, three groups of rats were treated with 2.5, 7.5 or 15mg Cd/kg/day. These doses were chosen on the bases of literature data and reflect relatively high Cd environmental exposure, three groups of rats were treated with 1000, 2000 or 4000mg BDE-209/kg/bw/day, doses proved to induce toxic effects in rats. Furthermore, nine groups of animals were treated with different mixtures of Cd and BDE-209 containing doses of Cd and BDE-209 stated above. Blood samples were taken at the end of experiment and red blood cells, white blood cells and platelets counts were determined. For interaction assessment multiple factorial regression analysis and fitted isobologram approach were used. In this study, we focused on multiple factorial regression analysis as a method for interaction assessment. We also investigated the interactions between Cd and BDE-209 by the derived model for the description of the obtained fitted isobologram curves. Current study indicated that co-exposure to Cd and BDE-209 can result in significant decrease in RBC count, increase in WBC count and decrease in PLT count, when compared with controls. Multiple factorial regression analysis used for the assessment of interactions type between Cd and BDE-209 indicated synergism for the effect on RBC count and no interactions i.e. additivity for the effects on WBC and PLT counts. On the other hand, isobologram based approach showed slight antagonism for the effects on RBC and WBC while no interactions were proved for the joint effect on PLT count. These results confirm that the assessment of interactions between chemicals in the mixture greatly depends on the concept or method used for this evaluation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Estimation of 1RM for knee extension based on the maximal isometric muscle strength and body composition.

PubMed

Kanada, Yoshikiyo; Sakurai, Hiroaki; Sugiura, Yoshito; Arai, Tomoaki; Koyama, Soichiro; Tanabe, Shigeo

2017-11-01

[Purpose] To create a regression formula in order to estimate 1RM for knee extensors, based on the maximal isometric muscle strength measured using a hand-held dynamometer and data regarding the body composition. [Subjects and Methods] Measurement was performed in 21 healthy males in their twenties to thirties. Single regression analysis was performed, with measurement values representing 1RM and the maximal isometric muscle strength as dependent and independent variables, respectively. Furthermore, multiple regression analysis was performed, with data regarding the body composition incorporated as another independent variable, in addition to the maximal isometric muscle strength. [Results] Through single regression analysis with the maximal isometric muscle strength as an independent variable, the following regression formula was created: 1RM (kg)=0.714 + 0.783 × maximal isometric muscle strength (kgf). On multiple regression analysis, only the total muscle mass was extracted. [Conclusion] A highly accurate regression formula to estimate 1RM was created based on both the maximal isometric muscle strength and body composition. Using a hand-held dynamometer and body composition analyzer, it was possible to measure these items in a short time, and obtain clinically useful results.

Data Mining Methods Applied to Flight Operations Quality Assurance Data: A Comparison to Standard Statistical Methods

NASA Technical Reports Server (NTRS)

Stolzer, Alan J.; Halford, Carl

2007-01-01

In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.

Parent’s Socioeconomic Status, Adolescents’ Disposable Income, and Adolescents’ Smoking Status in Massachusetts

PubMed Central

Soteriades, Elpidoforos S.; DiFranza, Joseph R.

2003-01-01

Objectives. This study examined the association between parental socioeconomic status (SES) and adolescent smoking. Methods. We conducted telephone interviews with a probability sample of 1308 Massachusetts adolescents aged 12 to 17 years. We used multiple-variable-adjusted logistic regression models. Results. The risk of adolescent smoking increased by 28% with each step down in parental education and increased by 30% for each step down in parental household income. These associations persisted after adjustment for age, sex, race/ethnicity, and adolescent disposable income. Parental smoking status was a mediator of these associations. Conclusions. Parental SES is inversely associated with adolescent smoking. Parental smoking is a mediator but does not fully explain the association. PMID:12835202

Subjective social status and readiness to quit among homeless smokers.

PubMed

Garey, Lorra; Reitzel, Lorraine R; Bakhshaie, Jafar; Kendzor, Darla E; Zvolensky, Michael J; Businelle, Michael S

2015-03-01

To explore the predictive value of subjective social status (SSS-US and SSS-Community) on readiness to quit among 245 homeless smokers. Hierarchical multiple regression analyses were conducted (stratified by sex). Higher SSS-US (p = .02) and SSS-Community (p < .001) predicted greater readiness to quit in the total sample. These relationships upheld for men (p's <. 01), but only SSS-Community predicted readiness to quit for women (p = .02). Higher SSS is associated with greater readiness to quit among homeless smokers. SSS-Community may be a more relevant index of SSS for women relative to SSS-US. Results suggest SSS may be a factor that contributes to smoking, disease, and health disparities.

Use of safety management practices for improving project performance.

PubMed

Cheng, Eddie W L; Kelly, Stephen; Ryan, Neal

2015-01-01

Although site safety has long been a key research topic in the construction field, there is a lack of literature studying safety management practices (SMPs). The current research, therefore, aims to test the effect of SMPs on project performance. An empirical study was conducted in Hong Kong and the data collected were analysed with multiple regression analysis. Results suggest that 3 of the 15 SMPs, which were 'safety committee at project/site level', 'written safety policy', and 'safety training scheme' explained the variance in project performance significantly. Discussion about the impact of these three SMPs on construction was provided. Assuring safe construction should be an integral part of a construction project plan.

[A comparative study of maintenance services using the data-mining technique].

PubMed

Cruz, Antonio M; Aguilera-Huertas, Wilmer A; Días-Mora, Darío A

2009-08-01

The main goal in this research was comparing two hospitals' maintenance service quality. One of them had a contract service; the other one had an in-house maintenance service. The authors followed the next stages when conducting this research: domain understanding, data characterisation and sample reduction, insight characterisation and building the TAT predictor. Multiple linear regression and clustering techniques were used for improving the efficiency of corrective maintenance tasks in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). The institution having an in-house maintenance service had better quality indicators than the contract maintenance service. There was lineal dependence between availability and service productivity.

Ambivalent Sexism in Close Relationships: (Hostile) Power and (Benevolent) Romance Shape Relationship Ideals

PubMed Central

Lee, Tiane L.; Fiske, Susan T.; Glick, Peter; Chen, Zhixia

2013-01-01

Gender-based structural power and heterosexual dependency produce ambivalent gender ideologies, with hostility and benevolence separately shaping close-relationship ideals. The relative importance of romanticized benevolent versus more overtly power-based hostile sexism, however, may be culturally dependent. Testing this, northeast US (N=311) and central Chinese (N=290) undergraduates rated prescriptions and proscriptions (ideals) for partners and completed Ambivalent Sexism and Ambivalence toward Men Inventories (ideologies). Multiple regressions analyses conducted on group-specific relationship ideals revealed that benevolent ideologies predicted partner ideals, in both countries, especially for US culture’s romance-oriented relationships. Hostile attitudes predicted men’s ideals, both American and Chinese, suggesting both societies’ dominant-partner advantage. PMID:23914004

Modeling Relationships Between Flight Crew Demographics and Perceptions of Interval Management

NASA Technical Reports Server (NTRS)

Remy, Benjamin; Wilson, Sara R.

2016-01-01

The Interval Management Alternative Clearances (IMAC) human-in-the-loop simulation experiment was conducted to assess interval management system performance and participants' acceptability and workload while performing three interval management clearance types. Twenty-four subject pilots and eight subject controllers flew ten high-density arrival scenarios into Denver International Airport during two weeks of data collection. This analysis examined the possible relationships between subject pilot demographics on reported perceptions of interval management in IMAC. Multiple linear regression models were created with a new software tool to predict subject pilot questionnaire item responses from demographic information. General patterns were noted across models that may indicate flight crew demographics influence perceptions of interval management.

The association between fear of falling and motor imagery abilities in older community-dwelling individuals.

PubMed

Grenier, Sébastien; Richard-Devantoy, Stéphane; Nadeau, Alexandra; Payette, Marie-Christine; Benyebdri, Fethia; Duhaime, Marie-Michelle B; Gunther, Bruno; Beauchet, Olivier

2018-04-01

We investigated the association between fear of falling (FoF) and motor imagery (MI) abilities in older people. Cross-sectional data from 3552 French older adults were used to conduct a multiple linear regression analysis looking at the association between FoF and MI abilities after controlling for several factors (e.g. gender, age, history of falls). MI abilities were significantly lower in older adults reporting a FoF compared with those without this fear. The presence of lower MI abilities, reflecting deficits in gait control, may explain why older people with a FoF are at higher risk of falling. Copyright © 2018 Elsevier B.V. All rights reserved.

Cross Validation of Selection of Variables in Multiple Regression.

DTIC Science & Technology

1979-12-01

55 vii CROSS VALIDATION OF SELECTION OF VARIABLES IN MULTIPLE REGRESSION I Introduction Background Long term DoD planning gcals...028545024 .31109000 BF * SS - .008700618 .0471961 Constant - .70977903 85.146786 55 had adequate predictive capabilities; the other two models (the...71ZCO F111D Control 54 73EGO FlIID Computer, General Purpose 55 73EPO FII1D Converter-Multiplexer 56 73HAO flllD Stabilizer Platform 57 73HCO F1ID

Quantitative Assessment of Cervical Vertebral Maturation Using Cone Beam Computed Tomography in Korean Girls

PubMed Central

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

2015-01-01

This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6–18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R 2 had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status. PMID:25878721

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.

Relationships between use of television during meals and children's food consumption patterns.

PubMed

Coon, K A; Goldberg, J; Rogers, B L; Tucker, K L

2001-01-01

We examined relationships between the presence of television during meals and children's food consumption patterns to test whether children's overall food consumption patterns, including foods not normally advertised, vary systematically with the extent to which television is part of normal mealtime routines. Ninety-one parent-child pairs from suburbs adjacent to Washington, DC, recruited via advertisements and word of mouth, participated. Children were in the fourth, fifth, or sixth grades. Socioeconomic data and information on television use were collected during survey interviews. Three nonconsecutive 24-hour dietary recalls, conducted with each child, were used to construct nutrient and food intake outcome variables. Independent sample t tests were used to compare mean food and nutrient intakes of children from families in which the television was usually on during 2 or more meals (n = 41) to those of children from families in which the television was either never on or only on during one meal (n = 50). Multiple linear regression models, controlling for socioeconomic factors and other covariates, were used to test strength of associations between television and children's consumption of food groups and nutrients. Children from families with high television use derived, on average, 6% more of their total daily energy intake from meats; 5% more from pizza, salty snacks, and soda; and nearly 5% less of their energy intake from fruits, vegetables, and juices than did children from families with low television use. Associations between television and children's consumption of food groups remained statistically significant in multiple linear regression models that controlled for socioeconomic factors and other covariates. Children from high television families derived less of their total energy from carbohydrate and consumed twice as much caffeine as children from low television families. There continued to be a significant association between television and children's consumption of caffeine when these relationships were tested in multiple linear regression models. The dietary patterns of children from families in which television viewing is a normal part of meal routines may include fewer fruits and vegetables and more pizzas, snack foods, and sodas than the dietary patterns of children from families in which television viewing and eating are separate activities.

Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

PubMed

NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

2017-08-01

Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.

Adjusted variable plots for Cox's proportional hazards regression model.

PubMed

Hall, C B; Zeger, S L; Bandeen-Roche, K J

1996-01-01

Adjusted variable plots are useful in linear regression for outlier detection and for qualitative evaluation of the fit of a model. In this paper, we extend adjusted variable plots to Cox's proportional hazards model for possibly censored survival data. We propose three different plots: a risk level adjusted variable (RLAV) plot in which each observation in each risk set appears, a subject level adjusted variable (SLAV) plot in which each subject is represented by one point, and an event level adjusted variable (ELAV) plot in which the entire risk set at each failure event is represented by a single point. The latter two plots are derived from the RLAV by combining multiple points. In each point, the regression coefficient and standard error from a Cox proportional hazards regression is obtained by a simple linear regression through the origin fit to the coordinates of the pictured points. The plots are illustrated with a reanalysis of a dataset of 65 patients with multiple myeloma.

Analysis of Binary Adherence Data in the Setting of Polypharmacy: A Comparison of Different Approaches

PubMed Central

Esserman, Denise A.; Moore, Charity G.; Roth, Mary T.

2009-01-01

Older community dwelling adults often take multiple medications for numerous chronic diseases. Non-adherence to these medications can have a large public health impact. Therefore, the measurement and modeling of medication adherence in the setting of polypharmacy is an important area of research. We apply a variety of different modeling techniques (standard linear regression; weighted linear regression; adjusted linear regression; naïve logistic regression; beta-binomial (BB) regression; generalized estimating equations (GEE)) to binary medication adherence data from a study in a North Carolina based population of older adults, where each medication an individual was taking was classified as adherent or non-adherent. In addition, through simulation we compare these different methods based on Type I error rates, bias, power, empirical 95% coverage, and goodness of fit. We find that estimation and inference using GEE is robust to a wide variety of scenarios and we recommend using this in the setting of polypharmacy when adherence is dichotomously measured for multiple medications per person. PMID:20414358

Selection of a Geostatistical Method to Interpolate Soil Properties of the State Crop Testing Fields using Attributes of a Digital Terrain Model

NASA Astrophysics Data System (ADS)

Sahabiev, I. A.; Ryazanov, S. S.; Kolcova, T. G.; Grigoryan, B. R.

2018-03-01

The three most common techniques to interpolate soil properties at a field scale—ordinary kriging (OK), regression kriging with multiple linear regression drift model (RK + MLR), and regression kriging with principal component regression drift model (RK + PCR)—were examined. The results of the performed study were compiled into an algorithm of choosing the most appropriate soil mapping technique. Relief attributes were used as the auxiliary variables. When spatial dependence of a target variable was strong, the OK method showed more accurate interpolation results, and the inclusion of the auxiliary data resulted in an insignificant improvement in prediction accuracy. According to the algorithm, the RK + PCR method effectively eliminates multicollinearity of explanatory variables. However, if the number of predictors is less than ten, the probability of multicollinearity is reduced, and application of the PCR becomes irrational. In that case, the multiple linear regression should be used instead.

Genetic Programming Transforms in Linear Regression Situations

NASA Astrophysics Data System (ADS)

Castillo, Flor; Kordon, Arthur; Villa, Carlos

The chapter summarizes the use of Genetic Programming (GP) inMultiple Linear Regression (MLR) to address multicollinearity and Lack of Fit (LOF). The basis of the proposed method is applying appropriate input transforms (model respecification) that deal with these issues while preserving the information content of the original variables. The transforms are selected from symbolic regression models with optimal trade-off between accuracy of prediction and expressional complexity, generated by multiobjective Pareto-front GP. The chapter includes a comparative study of the GP-generated transforms with Ridge Regression, a variant of ordinary Multiple Linear Regression, which has been a useful and commonly employed approach for reducing multicollinearity. The advantages of GP-generated model respecification are clearly defined and demonstrated. Some recommendations for transforms selection are given as well. The application benefits of the proposed approach are illustrated with a real industrial application in one of the broadest empirical modeling areas in manufacturing - robust inferential sensors. The chapter contributes to increasing the awareness of the potential of GP in statistical model building by MLR.

A Solution to Separation and Multicollinearity in Multiple Logistic Regression

PubMed Central

Shen, Jianzhao; Gao, Sujuan

2010-01-01

In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27–38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth’s penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study. PMID:20376286

A Solution to Separation and Multicollinearity in Multiple Logistic Regression.

PubMed

Shen, Jianzhao; Gao, Sujuan

2008-10-01

In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27-38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth's penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study.

Association between occupational exposures to pesticides with heterogeneous chemical structures and farmer health in China.

PubMed

Huang, Xusheng; Zhang, Chao; Hu, Ruifa; Li, Yifan; Yin, Yanhong; Chen, Zhaohui; Cai, Jinyang; Cui, Fang

2016-04-27

This study analyzed the associations of farmers' exposure to organophosphates (OPs), organosulfurs (OSs), organonitrogens (ONs) and pyrethroids (PYRs) with parameters of the blood complete counts (CBC), a blood chemistry panel (BCP) and the conventional nerve conduction studies among 224 farmers in China in 2012. Two health examinations and a series of follow-up field surveys were conducted. Multiple linear regression analyses were used to evaluate the associations. The results show considerable associations between multiple groups of pesticides and several CBC parameters, but it was not enough to provide evidence of hematological disorders. The short- and medium-term OPs exposures were mainly associated with liver damage and peripheral nerve impairment, respectively, while OSs exposure might induce liver damage and renal dysfunction. The neurotoxicity of ONs was second only to OPs in addition to its potential liver damage and the induced alterations in glucose. In comparison, the estimated results show that PYRs would be the least toxic in terms of the low-dose application. In conclusion, occupational exposures to pesticides with heterogeneous chemical structures are associated with farmer health in different patterns, and the association between a specific group of pesticides and farmer health also differs between the short- and medium-term exposures.

An Examination of the Likelihood of Home Discharge After General Hospitalizations Among Medicaid Recipients

PubMed Central

Mkanta, William N.; Chumbler, Neale R.; Yang, Kai; Saigal, Romesh; Abdollahi, Mohammad; Mejia de Grubb, Maria C.; Ezekekwu, Emmanuel U.

2017-01-01

Ability to predict discharge destination would be a useful way of optimizing posthospital care. We conducted a cross-sectional, multiple state study of inpatient services to assess the likelihood of home discharges in 2009 among Medicaid enrollees who were discharged following general hospitalizations. Analyses were conducted using hospitalization data from the states of California, Georgia, Michigan, and Mississippi. A total of 33 160 patients were included in the study among which 13 948 (42%) were discharged to their own homes and 19 212 (58%) were discharged to continue with institutional-based treatment. A multiple logistic regression model showed that gender, age, race, and having ambulatory care-sensitive conditions upon admission were significant predictors of home-based discharges. Females were at higher odds of home discharges in the sample (odds ratio [OR] = 1.631; 95% confidence interval [CI], 1.520-1.751), while patients with ambulatory care-sensitive conditions were less likely to get home discharges (OR = 0.739; 95% CI, 0.684-0.798). As the nation engages in the continued effort to improve the effectiveness of the health care system, cost savings are possible if providers and systems of care are able to identify admission factors with greater prospects for in-home services after discharge.

Risk of multiple myeloma following medication use and medical conditions: a case-control study in Connecticut women.

PubMed

Landgren, Ola; Zhang, Yawei; Zahm, Sheila Hoar; Inskip, Peter; Zheng, Tongzhang; Baris, Dalsu

2006-12-01

Certain commonly used drugs and medical conditions characterized by chronic immune dysfunction and/or antigen stimulation have been suggested to affect important pathways in multiple myeloma tumor cell growth and survival. We conducted a population-based case-control study to investigate the role of medical history in the etiology of multiple myeloma among Connecticut women. A total of 179 incident multiple myeloma cases (21-84 years, diagnosed 1996-2002) and 691 population-based controls was included in this study. Information on medical conditions, medications, and medical radiation was obtained by in-person interviews. We calculated odds ratios (OR) as measures of relative risks using logistic regression models. A reduced multiple myeloma risk was found among women who had used antilipid statin therapy [OR, 0.4; 95% confidence interval (95% CI), 0.2-0.8] or estrogen replacement therapy (OR, 0.6; 95% CI, 0.4-0.99) or who had a medical history of allergy (OR, 0.4; 95% CI, 0.3-0.7), scarlet fever (OR, 0.5; 95% CI, 0.2-0.9), or bursitis (OR, 0.4; 95% CI, 0.2-0.7). An increased risk of multiple myeloma was found among women who used prednisone (OR, 5.1; 95% CI, 1.8-14.4), insulin (OR, 3.1; 95% CI, 1.1-9.0), or gout medication (OR, 6.7; 95% CI, 1.2-38.0). If our results are confirmed, mechanistic studies examining how prior use of insulin, prednisone, and, perhaps, gout medication might promote increased occurrence of multiple myeloma and how antilipid statins, estrogen replacement therapy, and certain medical conditions might protect against multiple myeloma may provide insights to the as yet unknown etiology of multiple myeloma.

Squeezing observational data for better causal inference: Methods and examples for prevention research.

PubMed

Garcia-Huidobro, Diego; Michael Oakes, J

2017-04-01

Randomised controlled trials (RCTs) are typically viewed as the gold standard for causal inference. This is because effects of interest can be identified with the fewest assumptions, especially imbalance in background characteristics. Yet because conducting RCTs are expensive, time consuming and sometimes unethical, observational studies are frequently used to study causal associations. In these studies, imbalance, or confounding, is usually controlled with multiple regression, which entails strong assumptions. The purpose of this manuscript is to describe strengths and weaknesses of several methods to control for confounding in observational studies, and to demonstrate their use in cross-sectional dataset that use patient registration data from the Juan Pablo II Primary Care Clinic in La Pintana-Chile. The dataset contains responses from 5855 families who provided complete information on family socio-demographics, family functioning and health problems among their family members. We employ regression adjustment, stratification, restriction, matching, propensity score matching, standardisation and inverse probability weighting to illustrate the approaches to better causal inference in non-experimental data and compare results. By applying study design and data analysis techniques that control for confounding in different ways than regression adjustment, researchers may strengthen the scientific relevance of observational studies. © 2016 International Union of Psychological Science.

Correlation between electrical conductivity and apparent diffusion coefficient in breast cancer: effect of necrosis on magnetic resonance imaging.

PubMed

Kim, Soo-Yeon; Shin, Jaewook; Kim, Dong-Hyun; Kim, Eun-Kyung; Moon, Hee Jung; Yoon, Jung Hyun; You, Jai Kyung; Kim, Min Jung

2018-03-06

To investigate the correlation between conductivity and ADC in invasive ductal carcinoma according to the presence of necrosis on MRI. Eighty-one women with invasive ductal carcinoma ≥1 cm on T2-weighted fast spin echo sequence of preoperative MRI were included. Phase-based MR electric properties tomography was used to reconstruct conductivity. Mean ADC was measured. Necrosis was defined as an area with very high T2 signal intensity. The relationship between conductivity and ADC was examined using Spearman's correlation coefficient (r). Multiple linear regression analysis was performed to identify factors associated with conductivity or ADC. In the total group, conductivity showed negative correlation with ADC (r = -0.357, p = 0.001). This correlation was maintained in the subgroup without necrosis (n = 53, r = -0.455, p = 0.001), but not in the subgroup with necrosis (n = 28, r = -0.080, p = 0.687). The correlation between the two parameters was different according to necrosis (r = -0.455 vs -0.080, p = 0.047). HER2 enriched subtype was independently associated with conductivity (p = 0.029). Necrosis on MRI was independently associated with ADC (p = 0.027). Conductivity shows negative correlation with ADC that is abolished by the presence of necrosis on MRI. • Electric conductivity showed negative correlation with ADC • However, the correlation was abolished by the presence of necrosis on MRI • HER2-enriched subtype was independently associated with conductivity • Necrosis on MRI was independently associated with ADC.

The Role of Early Language Difficulties in the Trajectories of Conduct Problems Across Childhood.

PubMed

Yew, Shaun Goh Kok; O'Kearney, Richard

2015-11-01

This study uses latent growth curve modelling to contrast the developmental trajectories of conduct problems across childhood for children with early language difficulties (LD) and those with typical language (TL). It also examines whether the presence of early language difficulties moderates the influence of child, parent and peers factors known to be associated with the development of conduct problems. Unconditional and language status conditional latent growth curves of conduct problems were estimated for a nationally representative cohort of children, comprising of 1627 boys (280 LD) and 1609 girls (159 LD) measured at ages 4-5, 6-7, 8-9 and 10-11. Multiple regression tested interaction between language status and predictors of the level and slope of the development of conduct symptoms. On average, children's conduct problems followed a curvilinear decrease. Compared to their TL peers, LD boys and girls had trajectories of conduct problems that had the same shape but with persistently higher levels. Among boys, LD amplified the contributions of parental hostility and SES and protected against the contributions of sociability and maternal psychological distress to a high level of conduct problems. In low SES boys, LD was a vulnerability to a slower rate of decline in conduct problems. Among girls, LD amplified the contributions of low pro-social behaviour to a higher level and sociability to a slower rate of decline of conduct problems while dampening the contribution of peer problems to a higher level of problems.

Simultaneous estimation of local-scale and flow path-scale dual-domain mass transfer parameters using geoelectrical monitoring

USGS Publications Warehouse

Briggs, Martin A.; Day-Lewis, Frederick D.; Ong, John B.; Curtis, Gary P.; Lane, John W.

2013-01-01

Anomalous solute transport, modeled as rate-limited mass transfer, has an observable geoelectrical signature that can be exploited to infer the controlling parameters. Previous experiments indicate the combination of time-lapse geoelectrical and fluid conductivity measurements collected during ionic tracer experiments provides valuable insight into the exchange of solute between mobile and immobile porosity. Here, we use geoelectrical measurements to monitor tracer experiments at a former uranium mill tailings site in Naturita, Colorado. We use nonlinear regression to calibrate dual-domain mass transfer solute-transport models to field data. This method differs from previous approaches by calibrating the model simultaneously to observed fluid conductivity and geoelectrical tracer signals using two parameter scales: effective parameters for the flow path upgradient of the monitoring point and the parameters local to the monitoring point. We use regression statistics to rigorously evaluate the information content and sensitivity of fluid conductivity and geophysical data, demonstrating multiple scales of mass transfer parameters can simultaneously be estimated. Our results show, for the first time, field-scale spatial variability of mass transfer parameters (i.e., exchange-rate coefficient, porosity) between local and upgradient effective parameters; hence our approach provides insight into spatial variability and scaling behavior. Additional synthetic modeling is used to evaluate the scope of applicability of our approach, indicating greater range than earlier work using temporal moments and a Lagrangian-based Damköhler number. The introduced Eulerian-based Damköhler is useful for estimating tracer injection duration needed to evaluate mass transfer exchange rates that range over several orders of magnitude.

The psychological impact of terrorism: an epidemiologic study of posttraumatic stress disorder and associated factors in victims of the 1995-1996 bombings in France.

PubMed

Verger, Pierre; Dab, William; Lamping, Donna L; Loze, Jean-Yves; Deschaseaux-Voinet, Céline; Abenhaim, Lucien; Rouillon, Frédéric

2004-08-01

A wave of bombings struck France in 1995 and 1996, killing 12 people and injuring more than 200. The authors conducted follow-up evaluations with the victims in 1998 to determine the prevalence of and factors associated with posttraumatic stress disorder (PTSD). Victims directly exposed to the bombings (N=228) were recruited into a retrospective, cross-sectional study. Computer-assisted telephone interviews were conducted to evaluate PTSD, per DSM-IV criteria, and to assess health status before the attack, initial injury severity and perceived threat at the time of attack, and psychological symptoms, cosmetic impairment, hearing problems, and health service use at the time of the follow-up evaluation. Factors associated with PTSD were investigated with univariate logistic regression followed by multiple logistic regression analyses. A total of 196 respondents (86%) participated in the study. Of these, 19% had severe initial physical injuries (hospitalization exceeding 1 week). Problems reported at the follow-up evaluation included attack-related hearing problems (51%), cosmetic impairment (33%), and PTSD (31%) (95% confidence interval=24.5%-37.5%). Results of logistic regression analyses indicated that the risk of PTSD was significantly higher among women (odds ratio=2.54), participants age 35-54 (odds ratio=2.83), and those who had severe initial injuries (odds ratio=2.79) or cosmetic impairment (odds ratio=2.74) or who perceived substantial threat during the attack (odds ratio=3.99). The high prevalence of PTSD 2.6 years on average after a terrorist attack emphasizes the need for improved health services to address the intermediate and long-term consequences of terrorism.

Individual Participant Data Meta-Analysis of Mechanical Workplace Risk Factors and Low Back Pain

PubMed Central

Shannon, Harry S.; Wells, Richard P.; Walter, Stephen D.; Cole, Donald C.; Côté, Pierre; Frank, John; Hogg-Johnson, Sheilah; Langlois, Lacey E.

2012-01-01

Objectives. We used individual participant data from multiple studies to conduct a comprehensive meta-analysis of mechanical exposures in the workplace and low back pain. Methods. We conducted a systematic literature search and contacted an author of each study to request their individual participant data. Because outcome definitions and exposure measures were not uniform across studies, we conducted 2 substudies: (1) to identify sets of outcome definitions that could be combined in a meta-analysis and (2) to develop methods to translate mechanical exposure onto a common metric. We used generalized estimating equation regression to analyze the data. Results. The odds ratios (ORs) for posture exposures ranged from 1.1 to 2.0. Force exposure ORs ranged from 1.4 to 2.1. The magnitudes of the ORs differed according to the definition of low back pain, and heterogeneity was associated with both study-level and individual-level characteristics. Conclusions. We found small to moderate ORs for the association of mechanical exposures and low back pain, although the relationships were complex. The presence of individual-level OR modifiers in such an area can be best understood by conducting a meta-analysis of individual participant data. PMID:22390445

The influence of demographics and working conditions on self-reported injuries among Latino day laborers

PubMed Central

Fernández-Esquer, Maria Eugenia; Fernández-Espada, Natalie; Atkinson, John A; Montano, Cecilia F

2015-01-01

Background: The majority of day laborers in the USA are Latinos. They are engaged in high-risk occupations and suffer high occupational injury rates. Objectives: To describe on-the-job injuries reported by Latino day laborers, explore the extent that demographic and occupational factors predict injuries, and whether summative measures for total job types, job conditions, and personal protective equipment (PPE) predict injuries. Methods: A community survey was conducted with 327 participants at 15 corners in Houston, Texas. Hierarchical and multiple logistic regressions explored predictors of occupational injury odds in the last year. Results: Thirty-four percent of respondents reported an occupational injury in the previous year. Education, exposure to loud noises, cold temperatures, vibrating machinery, use of hard hats, total number of job conditions, and total PPE significantly predicted injury odds. Conclusion: Risk for injury among day laborers is not only the product of a specific hazard, but also the result of their exposure to multiple occupational hazards. PMID:25291983

Biopsychosocial Predictors of Fall Events among Older African Americans

PubMed Central

Nicklett, Emily Joy; Taylor, Robert Joseph; Rostant, Ola; Johnson, Kimson E.; Evans, Linnea

2016-01-01

This study identifies risk and protective factors for falls among older, community-dwelling African Americans. Drawing upon the biopsychosocial perspective (Engel, 1997), we conducted a series of sex- and age-adjusted multinomial logistic regression analyses to identify the correlates of fall events among older African Americans. Our sample consisted of 1,442 community-dwelling African Americans aged 65 and older, participating in the 2010-12 rounds of the Health and Retirement Study. Biophysical characteristics associated with greater relative risk of experiencing single and/or multiple falls included greater functional limitations, poorer self-rated health, poorer self-rated vision, chronic illnesses (high blood pressure, diabetes, cancer, lung disease, heart problems, stroke, and arthritis), greater chronic illness comorbidity, older age, and female sex. Physical activity was negatively associated with recurrent falls. Among the examined psychosocial characteristics, greater depressive symptoms were associated with greater relative risk of experiencing single and multiple fall events. Implications for clinicians and future studies are discussed. PMID:28285579

Predictors of health-related quality of life among low-income midlife women.

PubMed

Ham, Ok Kyung

2011-02-01

The purpose of this study was to determine whether any of the sociodemographic, biomedical, psychosocial, and medical-care factors independently predict health-related quality of life (HRQoL) among low-income women. Cross-sectional data were used to predict factors that determine HRQoL. A survey was conducted targeting a convenience sample of 200 midlife women. Blood samples were drawn from all participants, who also received a physical examination. Hierarchical multiple regression analysis was used to test the independent effects of each factor. The study found that sociodemographic and psychosocial factors were independently associated with HRQoL. Compared to married women, widowed or divorced women had significantly lower HRQoL, whereas those with higher levels of stress perception and those not performing regular exercise had significantly lower HRQoL (p < .01). The full model accounted for 44.7% of the variance in HRQoL. The HRQoL of low-income midlife women was associated with multiple factors, with stress perception exerting the major influence.

Serotonin transporter gene and childhood trauma--a G × E effect on anxiety sensitivity.

PubMed

Klauke, Benedikt; Deckert, Jürgen; Reif, Andreas; Pauli, Paul; Zwanzger, Peter; Baumann, Christian; Arolt, Volker; Glöckner-Rist, Angelika; Domschke, Katharina

2011-12-21

Genetic factors and environmental factors are assumed to interactively influence the pathogenesis of anxiety disorders. Thus, a gene-environment interaction (G × E) study was conducted with respect to anxiety sensitivity (AS) as a promising intermediate phenotype of anxiety disorders. Healthy subjects (N = 363) were assessed for AS, childhood maltreatment (Childhood Trauma Questionnaire), and genotyped for functional serotonin transporter gene variants (5-HTTLPR/5-HTT rs25531). The influence of genetic and environmental variables on AS and its subdimensions was determined by a step-wise hierarchical regression and a multiple indicator multiple cause (MIMIC) model. A significant G × E effect of the more active 5-HTT genotypes and childhood maltreatment on AS was observed. Furthermore, genotype (LL)-childhood trauma interaction particularly influenced somatic AS subdimensions, whereas cognitive subdimensions were affected by childhood maltreatment only. Results indicate a G × E effect of the more active 5-HTT genotypes and childhood maltreatment on AS, with particular impact on its somatic subcomponent. © 2011 Wiley Periodicals, Inc.

Cross race comparisons between SES health gradients among African-American and white women at mid-life

PubMed Central

Salsberry, Pamela J.

2014-01-01

This study explored how multiple indicators of socioeconomic status (SES) inform understanding of race differences in the magnitude of health gains associated with higher SES. The study sample, 1268 African-American women and 2066 white women, was drawn from the National Longitudinal Surveys of Youth 1979. The outcome was the Physical Components Summary from the SF-12 assessed at age 40. Ordinary least squares regressions using education, income and net worth fully interacted with race were conducted. Single measure gradients tended to be steeper for whites than African-Americans, partly because “sheepskin” effects of high school and college graduation were higher for whites and low income and low net worth whites had worse health than comparable African-Americans. Conditioning on multiple measures of SES eliminated race disparities in health benefits of education and net worth, but not income. A discussion of current public policies that affect race disparities in levels of education, income and net wealth is provided. PMID:24632052

Sex knowledge, attitudes, and high-risk sexual behaviors among unmarried youth in Hong Kong

PubMed Central

2013-01-01

Background Little is known about sex knowledge, attitudes, and high-risk sexual behaviors among unmarried youth in Hong Kong. It is of public health importance to investigate this topic to inform sex education, policymaking, and prevention and intervention programs. Methods Based on the Youth Sexuality Survey conducted by Hong Kong Family Planning Association (FPAHK) in 2011, this study explored the characteristics of sexual knowledge, attitudes, and high-risk sexual behaviors among 1,126 unmarried youth aged 18 to 27 years. Multiple logistic regressions were performed to examine factors associated with unmarried youth’s premarital sex, casual relationships, multiple sex partners, and premarital pregnancy. Results Unmarried youth in Hong Kong had adequate sex knowledge, but contraceptive knowledge was deficient. The majority of unmarried youth (63.8%) held liberal attitudes toward premarital sex and about half held liberal attitudes toward any form of sexual activity and premarital pregnancy. Around 60% held conservative attitudes toward causal sex relationships and multiple sex partners. Males tended to hold more liberal attitudes toward high-risk sex behaviors than female youth. Approximately 41.5% of unmarried youth reported having engaged in premarital sex, whereas less than 10% engaged in high-risk sexual behaviors. Males also reported higher amounts of premarital sex, casual sex relationships, and multiple sex partners. Females reported higher levels of sexual coercion. Logistic regressions indicated that being older, coming from a divorced family, out of school status and liberal attitudes toward risky sex behavior were more likely to engage in premarital sex or high-risk sex behaviors, and being female, being better educated and being immigrants were less likely to engage in premarital sex. However, being immigrants was more likely to engage in casual relationship and to have multiple partners. Conclusions Premarital sex is becoming more prevalent among unmarried youth in Hong Kong, and a small proportion of young adults are engaging in high-risk sexual behaviors. Sex education and HIV prevention programs should equip them with adequate knowledge on contraception and condom use. Intervention programs can start with their attitudes toward sex. PMID:23895326

Sex knowledge, attitudes, and high-risk sexual behaviors among unmarried youth in Hong Kong.

PubMed

Yip, Paul S F; Zhang, Huiping; Lam, Tai-Hing; Lam, Kwok Fai; Lee, Antoinette Marie; Chan, John; Fan, Susan

2013-07-29

Little is known about sex knowledge, attitudes, and high-risk sexual behaviors among unmarried youth in Hong Kong. It is of public health importance to investigate this topic to inform sex education, policymaking, and prevention and intervention programs. Based on the Youth Sexuality Survey conducted by Hong Kong Family Planning Association (FPAHK) in 2011, this study explored the characteristics of sexual knowledge, attitudes, and high-risk sexual behaviors among 1,126 unmarried youth aged 18 to 27 years. Multiple logistic regressions were performed to examine factors associated with unmarried youth's premarital sex, casual relationships, multiple sex partners, and premarital pregnancy. Unmarried youth in Hong Kong had adequate sex knowledge, but contraceptive knowledge was deficient. The majority of unmarried youth (63.8%) held liberal attitudes toward premarital sex and about half held liberal attitudes toward any form of sexual activity and premarital pregnancy. Around 60% held conservative attitudes toward causal sex relationships and multiple sex partners. Males tended to hold more liberal attitudes toward high-risk sex behaviors than female youth. Approximately 41.5% of unmarried youth reported having engaged in premarital sex, whereas less than 10% engaged in high-risk sexual behaviors. Males also reported higher amounts of premarital sex, casual sex relationships, and multiple sex partners. Females reported higher levels of sexual coercion. Logistic regressions indicated that being older, coming from a divorced family, out of school status and liberal attitudes toward risky sex behavior were more likely to engage in premarital sex or high-risk sex behaviors, and being female, being better educated and being immigrants were less likely to engage in premarital sex. However, being immigrants was more likely to engage in casual relationship and to have multiple partners. Premarital sex is becoming more prevalent among unmarried youth in Hong Kong, and a small proportion of young adults are engaging in high-risk sexual behaviors. Sex education and HIV prevention programs should equip them with adequate knowledge on contraception and condom use. Intervention programs can start with their attitudes toward sex.

RRegrs: an R package for computer-aided model selection with multiple regression models.

PubMed

Tsiliki, Georgia; Munteanu, Cristian R; Seoane, Jose A; Fernandez-Lozano, Carlos; Sarimveis, Haralambos; Willighagen, Egon L

2015-01-01

Predictive regression models can be created with many different modelling approaches. Choices need to be made for data set splitting, cross-validation methods, specific regression parameters and best model criteria, as they all affect the accuracy and efficiency of the produced predictive models, and therefore, raising model reproducibility and comparison issues. Cheminformatics and bioinformatics are extensively using predictive modelling and exhibit a need for standardization of these methodologies in order to assist model selection and speed up the process of predictive model development. A tool accessible to all users, irrespectively of their statistical knowledge, would be valuable if it tests several simple and complex regression models and validation schemes, produce unified reports, and offer the option to be integrated into more extensive studies. Additionally, such methodology should be implemented as a free programming package, in order to be continuously adapted and redistributed by others. We propose an integrated framework for creating multiple regression models, called RRegrs. The tool offers the option of ten simple and complex regression methods combined with repeated 10-fold and leave-one-out cross-validation. Methods include Multiple Linear regression, Generalized Linear Model with Stepwise Feature Selection, Partial Least Squares regression, Lasso regression, and Support Vector Machines Recursive Feature Elimination. The new framework is an automated fully validated procedure which produces standardized reports to quickly oversee the impact of choices in modelling algorithms and assess the model and cross-validation results. The methodology was implemented as an open source R package, available at https://www.github.com/enanomapper/RRegrs, by reusing and extending on the caret package. The universality of the new methodology is demonstrated using five standard data sets from different scientific fields. Its efficiency in cheminformatics and QSAR modelling is shown with three use cases: proteomics data for surface-modified gold nanoparticles, nano-metal oxides descriptor data, and molecular descriptors for acute aquatic toxicity data. The results show that for all data sets RRegrs reports models with equal or better performance for both training and test sets than those reported in the original publications. Its good performance as well as its adaptability in terms of parameter optimization could make RRegrs a popular framework to assist the initial exploration of predictive models, and with that, the design of more comprehensive in silico screening applications.Graphical abstractRRegrs is a computer-aided model selection framework for R multiple regression models; this is a fully validated procedure with application to QSAR modelling.

Ethnomathematics: The use of multiple linier regression Y = b 1 X 1 + b 2 X 2 + e in traditional house construction Saka Roras in Songan Village

NASA Astrophysics Data System (ADS)

Darmayasa, J. B.; Wahyudin; Mulyana, T.

2018-01-01

Ethnomathematics may be the connecting bridge between culture and technology and arts. Therefore, the exploration of mathematics values that intersects with cultural anthropology should be significantly conducted. One case containing such issue is the construction of Traditional House of Saka Roras in Bali. Thus, this research aimed to explore the mathematic concept adopted in the construction of such traditional Bale (house) located in Songan Village, Kintamani, Bali. Specifically, this research also aimed to investigate the selection of linear regression coefficient for the saka (pillar) in the Bale. This research applied Embedded Mix-Method Design. Meanwhile, the data collection was conducted by interview, observation and measurement of pillars of 32 Bale Saka Roras. The result of this research revealed that the connection between the width and height of pillars was stated in the formula Y = 26,3 + 18,2X, where X acted as stimulus variable. The coefficient value amounted to 18.2 showed that most preceding architects in Songan Village were more likely to use 19 as the coefficient towards the pillar width than the other coefficients such as 17, 20 and 21 as mentioned in book/palm-leaf manuscript entitled Kosala-Kosali. The last but not least, the researchers also figured out that the pillar width depended on the length of the house-owner candidate’s index finger.

Human Papillomavirus (HPV) Vaccination and Adolescent Girls' Knowledge and Sexuality in Western Uganda: A Comparative Cross-Sectional Study.

PubMed

Turiho, Andrew Kampikaho; Muhwezi, Wilson Winston; Okello, Elialilia Sarikiaeli; Tumwesigye, Nazarius Mbona; Banura, Cecil; Katahoire, Anne Ruhweza

2015-01-01

The purpose of the study was to investigate the influence of human papillomavirus (HPV) vaccination on adolescent girls' knowledge of HPV and HPV vaccine, perception of sexual risk and intentions for sexual debut. This cross-sectional comparative study was conducted in Ibanda and Mbarara districts. Data was collected using a standardized self-administered questionnaire and analyzed using the Statistical Package for the Social Sciences computer software. Univariate, bivariate, and logistic regression analyses were conducted with significance level set at p < .05. Results showed that HPV vaccination was associated with being knowledgeable (Crude OR: 5.26, CI: 2.32-11.93; p = 0.000). Vaccination against HPV did not predict perception of sexual risk. Knowledge was low (only 87/385 or 22.6% of vaccinated girls were knowledgeable), but predicted perception of a high sexual risk (Adjusted OR: 3.12, CI: 1.37-3.63; p = 0.008). HPV vaccination, knowledge and perceived sexual risk did not predict sexual behaviour intentions. High parental communication was associated with adolescent attitudes that support postponement of sexual debut in both bivariate and multiple regression analyses. In conclusion, findings of this study suggest that HPV vaccination is not likely to encourage adolescent sexual activity. Influence of knowledge on sexual behaviour intentions was not definitively explained. Prospective cohort studies were proposed to address the emerging questions.

Oral health status and the epidemiologic paradox within latino immigrant groups

PubMed Central

2012-01-01

Background According to the United States census, there are 28 categories that define “Hispanic/Latinos.” This paper compares differences in oral health status between Mexican immigrants and other Latino immigrant groups. Methods Derived from a community-based sample (N = 240) in Los Angeles, this cross-sectional study uses an interview covering demographic and behavioral measures, and an intraoral examination using NIDCR epidemiologic criteria. Descriptive, bivariate analysis, and multiple regression analysis were conducted to examine the determinants that are associated with the Oral Health Status Index (OHSI). Results Mexican immigrants had a significantly higher OHSI (p < .05) compared to other Latinos. The multilinear regression showed that both age and gender (p < .05), percentage of untreated decayed teeth (p < .001), number of replaced missing teeth (p < .001), and attachment loss (p < .001) were significant. Conclusions Compared with the other Latino immigrants in our sample, Mexican immigrants have significantly better oral health status. This confirms the epidemiologic paradox previously found in comparisons of Mexicans with whites and African Americans. In this case of oral health status the paradox also occurs between Mexicans and other Latinos. Therefore, when conducting oral health studies of Latinos, more consideration needs to be given to differences within Latino subgroups, such as their country of origin and their unique ethnic and cultural characteristics. PMID:22958726

Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS.

PubMed

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2016-11-04

Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM.

Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS

PubMed Central

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2016-01-01

Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM. PMID:28774019

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.

Assessment of the spatial scaling behaviour of floods in the United Kingdom

NASA Astrophysics Data System (ADS)

Formetta, Giuseppe; Stewart, Elizabeth; Bell, Victoria

2017-04-01

Floods are among the most dangerous natural hazards, causing loss of life and significant damage to private and public property. Regional flood-frequency analysis (FFA) methods are essential tools to assess the flood hazard and plan interventions for its mitigation. FFA methods are often based on the well-known index flood method that assumes the invariance of the coefficient of variation of floods with drainage area. This assumption is equivalent to the simple scaling or self-similarity assumption for peak floods, i.e. their spatial structure remains similar in a particular, relatively simple, way to itself over a range of scales. Spatial scaling of floods has been evaluated at national scale for different countries such as Canada, USA, and Australia. According our knowledge. Such a study has not been conducted for the United Kingdom even though the standard FFA method there is based on the index flood assumption. In this work we present an integrated approach to assess of the spatial scaling behaviour of floods in the United Kingdom using three different methods: product moments (PM), probability weighted moments (PWM), and quantile analysis (QA). We analyse both instantaneous and daily annual observed maximum floods and performed our analysis both across the entire country and in its sub-climatic regions as defined in the Flood Studies Report (NERC, 1975). To evaluate the relationship between the k-th moments or quantiles and the drainage area we used both regression with area alone and multiple regression considering other explanatory variables to account for the geomorphology, amount of rainfall, and soil type of the catchments. The latter multiple regression approach was only recently demonstrated being more robust than the traditional regression with area alone that can lead to biased estimates of scaling exponents and misinterpretation of spatial scaling behaviour. We tested our framework on almost 600 rural catchments in UK considered as entire region and split in 11 sub-regions with 50 catchments per region on average. Preliminary results from the three different spatial scaling methods are generally in agreement and indicate that: i) only some of the peak flow variability is explained by area alone (approximately 50% for the entire country and ranging between the 40% and 70% for the sub-regions); ii) this percentage increases to 90% for the entire country and ranges between 80% and 95% for the sub-regions when the multiple regression is used; iii) the simple scaling hypothesis holds in all sub-regions with the exception of weak multi-scaling found in the regions 2 (North), and 5 and 6 (South East). We hypothesize that these deviations can be explained by heterogeneity in large scale precipitation and by the influence of the soil type (predominantly chalk) on the flood formation process in regions 5 and 6.

Comparison of feed energy costs of maintenance, lean deposition, and fat deposition in three lines of mice selected for heat loss.

PubMed

Eggert, D L; Nielsen, M K

2006-02-01

Three replications of mouse selection populations for high heat loss (MH), low heat loss (ML), and a nonselected control (MC) were used to estimate the feed energy costs of maintenance and gain and to test whether selection had changed these costs. At 21 and 49 d of age, mice were weighed and subjected to dual x-ray densitometry measurement for prediction of body composition. At 21 d, mice were randomly assigned to an ad libitum, an 80% of ad libitum, or a 60% of ad libitum feeding group for 28-d collection of individual feed intake. Data were analyzed using 3 approaches. The first approach was an attempt to partition energy intake between costs for maintenance, fat deposition, and lean deposition for each replicate, sex, and line by multiple regression of feed intake on the sum of daily metabolic weight (kg(0.75)), fat gain, and lean gain. Approach II was a less restrictive attempt to partition energy intake between costs for maintenance and total gain for each replicate, sex, and line by multiple regression of feed intake on the sum of daily metabolic weight and total gain. Approach III used multiple regression on the entire data set with pooled regressions on fat and lean gains, and subclass regressions for maintenance. Contrasts were conducted to test the effect of selection (MH - ML) and asymmetry of selection [(MH + ML)/2 - MC] for the various energy costs. In approach I, there were no differences between lines for costs of maintenance, fat deposition, or protein deposition, but we question our ability to estimate these accurately. In approach II, selection changed both cost of maintenance (P = 0.03) and gain (P = 0.05); MH mice had greater per unit costs than ML mice for both. Asymmetry of the selection response was found in approach II for the cost of maintenance (P = 0.06). In approach III, the effect of selection (P < 0.01) contributed to differences in the maintenance cost, but asymmetry of selection (P > 0.17) was not evident. Sex effects were found for the cost of fat deposition (P = 0.02) in approach I and the cost of gain (P = 0.001) in approach II; females had a greater cost per unit than males. When costs per unit of fat and per unit of lean gain were assumed to be the same for both sexes (approach III), females had a somewhat greater estimate for maintenance cost (P = 0.10). We conclude that selection for heat loss has changed the costs for maintenance per unit size but probably not the costs for gain.

Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure.

PubMed

Louys, Julien; Meloro, Carlo; Elton, Sarah; Ditchfield, Peter; Bishop, Laura C

2015-01-01

We test the performance of two models that use mammalian communities to reconstruct multivariate palaeoenvironments. While both models exploit the correlation between mammal communities (defined in terms of functional groups) and arboreal heterogeneity, the first uses a multiple multivariate regression of community structure and arboreal heterogeneity, while the second uses a linear regression of the principal components of each ecospace. The success of these methods means the palaeoenvironment of a particular locality can be reconstructed in terms of the proportions of heavy, moderate, light, and absent tree canopy cover. The linear regression is less biased, and more precisely and accurately reconstructs heavy tree canopy cover than the multiple multivariate model. However, the multiple multivariate model performs better than the linear regression for all other canopy cover categories. Both models consistently perform better than randomly generated reconstructions. We apply both models to the palaeocommunity of the Upper Laetolil Beds, Tanzania. Our reconstructions indicate that there was very little heavy tree cover at this site (likely less than 10%), with the palaeo-landscape instead comprising a mixture of light and absent tree cover. These reconstructions help resolve the previous conflicting palaeoecological reconstructions made for this site. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales.

PubMed

Pratt, Bethany; Chang, Heejun

2012-03-30

The relationship among land cover, topography, built structure and stream water quality in the Portland Metro region of Oregon and Clark County, Washington areas, USA, is analyzed using ordinary least squares (OLS) and geographically weighted (GWR) multiple regression models. Two scales of analysis, a sectional watershed and a buffer, offered a local and a global investigation of the sources of stream pollutants. Model accuracy, measured by R(2) values, fluctuated according to the scale, season, and regression method used. While most wet season water quality parameters are associated with urban land covers, most dry season water quality parameters are related topographic features such as elevation and slope. GWR models, which take into consideration local relations of spatial autocorrelation, had stronger results than OLS regression models. In the multiple regression models, sectioned watershed results were consistently better than the sectioned buffer results, except for dry season pH and stream temperature parameters. This suggests that while riparian land cover does have an effect on water quality, a wider contributing area needs to be included in order to account for distant sources of pollutants. Copyright © 2012 Elsevier B.V. All rights reserved.

Regression models for estimating salinity and selenium concentrations at selected sites in the Upper Colorado River Basin, Colorado, 2009-2012

USGS Publications Warehouse

Linard, Joshua I.; Schaffrath, Keelin R.

2014-01-01

Elevated concentrations of salinity and selenium in the tributaries and main-stem reaches of the Colorado River are a water-quality concern and have been the focus of remediation efforts for many years. Land-management practices with the objective of limiting the amount of salt and selenium that reaches the stream have focused on improving the methods by which irrigation water is conveyed and distributed. Federal land managers implement improvements in accordance with the Colorado River Basin Salinity Control Act of 1974, which directs Federal land managers to enhance and protect the quality of water available in the Colorado River. In an effort to assist in evaluating and mitigating the detrimental effects of salinity and selenium, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, the Colorado River Water Resources District, and the Bureau of Land Management, analyzed salinity and selenium data collected at sites to develop regression models. The study area and sites are on the Colorado River or in one of three small basins in Western Colorado: the White River Basin, the Lower Gunnison River Basin, and the Dolores River Basin. By using data collected from water years 2009 through 2011, regression models able to estimate concentrations were developed for salinity at six sites and selenium at six sites. At a minimum, data from discrete measurement of salinity or selenium concentration, streamflow, and specific conductance at each of the sites were needed for model development. Comparison of the Adjusted R2 and standard error statistics of the two salinity models developed at each site indicated the models using specific conductance as the explanatory variable performed better than those using streamflow. The addition of multiple explanatory variables improved the ability to estimate selenium concentration at several sites compared with use of solely streamflow or specific conductance. The error associated with the log-transformed salinity and selenium estimates is consistent in log space; however, when the estimates are transformed into non-log values, the error increases as the estimates decrease. Continuous streamflow and specific conductance data collected at study sites provide the means to examine temporal variability in constituent concentration and load. The regression models can estimate continuous concentrations or loads on the basis of continuous specific conductance or streamflow data. Similar estimates are available for other sites at the USGS National Real-Time Water Quality Web page (http://nrtwq.usgs.gov) and provide water-resource managers with a means of improving their general understanding of how constituent concentration or load can change annually, seasonally, or in real time.

Young Adult and Usual Adult Body Mass Index and Multiple Myeloma Risk: A Pooled Analysis in the International Multiple Myeloma Consortium (IMMC).

PubMed

Birmann, Brenda M; Andreotti, Gabriella; De Roos, Anneclaire J; Camp, Nicola J; Chiu, Brian C H; Spinelli, John J; Becker, Nikolaus; Benhaim-Luzon, Véronique; Bhatti, Parveen; Boffetta, Paolo; Brennan, Paul; Brown, Elizabeth E; Cocco, Pierluigi; Costas, Laura; Cozen, Wendy; de Sanjosé, Silvia; Foretová, Lenka; Giles, Graham G; Maynadié, Marc; Moysich, Kirsten; Nieters, Alexandra; Staines, Anthony; Tricot, Guido; Weisenburger, Dennis; Zhang, Yawei; Baris, Dalsu; Purdue, Mark P

2017-06-01

Background: Multiple myeloma risk increases with higher adult body mass index (BMI). Emerging evidence also supports an association of young adult BMI with multiple myeloma. We undertook a pooled analysis of eight case-control studies to further evaluate anthropometric multiple myeloma risk factors, including young adult BMI. Methods: We conducted multivariable logistic regression analysis of usual adult anthropometric measures of 2,318 multiple myeloma cases and 9,609 controls, and of young adult BMI (age 25 or 30 years) for 1,164 cases and 3,629 controls. Results: In the pooled sample, multiple myeloma risk was positively associated with usual adult BMI; risk increased 9% per 5-kg/m 2 increase in BMI [OR, 1.09; 95% confidence interval (CI), 1.04-1.14; P = 0.007]. We observed significant heterogeneity by study design ( P = 0.04), noting the BMI-multiple myeloma association only for population-based studies ( P trend = 0.0003). Young adult BMI was also positively associated with multiple myeloma (per 5-kg/m 2 ; OR, 1.2; 95% CI, 1.1-1.3; P = 0.0002). Furthermore, we observed strong evidence of interaction between younger and usual adult BMI ( P interaction <0.0001); we noted statistically significant associations with multiple myeloma for persons overweight (25-<30 kg/m 2 ) or obese (30+ kg/m 2 ) in both younger and usual adulthood (vs. individuals consistently <25 kg/m 2 ), but not for those overweight or obese at only one time period. Conclusions: BMI-associated increases in multiple myeloma risk were highest for individuals who were overweight or obese throughout adulthood. Impact: These findings provide the strongest evidence to date that earlier and later adult BMI may increase multiple myeloma risk and suggest that healthy BMI maintenance throughout life may confer an added benefit of multiple myeloma prevention. Cancer Epidemiol Biomarkers Prev; 26(6); 876-85. ©2017 AACR . ©2017 American Association for Cancer Research.

Development of a Multiple Linear Regression Model to Forecast Facility Electrical Consumption at an Air Force Base.

DTIC Science & Technology

1981-09-01

corresponds to the same square footage that consumed the electrical energy. 3. The basic assumptions of multiple linear regres- sion, as enumerated in...7. Data related to the sample of bases is assumed to be representative of bases in the population. Limitations Basic limitations on this research were... Ratemaking --Overview. Rand Report R-5894, Santa Monica CA, May 1977. Chatterjee, Samprit, and Bertram Price. Regression Analysis by Example. New York: John

Behavioral and psychosocial factors associated with suicidal ideation among adolescents.

PubMed

Lee, GyuYoung; Ham, Ok Kyung

2018-04-10

Suicidal ideation poses a serious threat to the well-being of adolescents and is the strongest risk factor for suicide. Indeed, Korea ranks first among Organisation for Economic Cooperation and Development countries regarding the age-standardized suicide rates. In the present study, we examined multiple levels of factors associated with the suicidal ideation of adolescents in Korea by applying the Ecological Models of Health Behavior. A cross-sectional study was conducted with a convenience sample of 860 adolescents. The instruments included the Beck Depression Inventory and the Adolescent Mental Health and Problem Behavior Questionnaire. The data were analyzed using hierarchical multiple regression. Sixteen percent of participants reported suicidal ideation. Intrapersonal (sleep disturbance, Internet game addiction, destructive behavior, and depressive symptoms) and interpersonal factors (family conflicts and peer victimization) were associated with suicidal ideation. Because multiple factors were associated with suicidal ideation among adolescents, both intrapersonal (sleep disturbance, Internet game addiction, and depression) and interpersonal factors (family conflicts and peer problems) should be considered in the development of suicide-prevention programs. These programs could include campaigns changing the norms (permissive attitudes toward school violence) and the development of strict and rigorous school non-violence policies. © 2018 John Wiley & Sons Australia, Ltd.

Energy Analysis of a Complementary Heating System Combining Solar Energy and Coal for a Rural Residential Building in Northwest China.

PubMed

Zhen, Xiaofei; Li, Jinping; Abdalla Osman, Yassir Idris; Feng, Rong; Zhang, Xuemin; Kang, Jian

2018-01-01

In order to utilize solar energy to meet the heating demands of a rural residential building during the winter in the northwestern region of China, a hybrid heating system combining solar energy and coal was built. Multiple experiments to monitor its performance were conducted during the winter in 2014 and 2015. In this paper, we analyze the efficiency of the energy utilization of the system and describe a prototype model to determine the thermal efficiency of the coal stove in use. Multiple linear regression was adopted to present the dual function of multiple factors on the daily heat-collecting capacity of the solar water heater; the heat-loss coefficient of the storage tank was detected as well. The prototype model shows that the average thermal efficiency of the stove is 38%, which means that the energy input for the building is divided between the coal and solar energy, 39.5% and 60.5% energy, respectively. Additionally, the allocation of the radiation of solar energy projecting into the collecting area of the solar water heater was obtained which showed 49% loss with optics and 23% with the dissipation of heat, with only 28% being utilized effectively.

Multiple-trait structured antedependence model to study the relationship between litter size and birth weight in pigs and rabbits.

PubMed

David, Ingrid; Garreau, Hervé; Balmisse, Elodie; Billon, Yvon; Canario, Laurianne

2017-01-20

Some genetic studies need to take into account correlations between traits that are repeatedly measured over time. Multiple-trait random regression models are commonly used to analyze repeated traits but suffer from several major drawbacks. In the present study, we developed a multiple-trait extension of the structured antedependence model (SAD) to overcome this issue and validated its usefulness by modeling the association between litter size (LS) and average birth weight (ABW) over parities in pigs and rabbits. The single-trait SAD model assumes that a random effect at time [Formula: see text] can be explained by the previous values of the random effect (i.e. at previous times). The proposed multiple-trait extension of the SAD model consists in adding a cross-antedependence parameter to the single-trait SAD model. This model can be easily fitted using ASReml and the OWN Fortran program that we have developed. In comparison with the random regression model, we used our multiple-trait SAD model to analyze the LS and ABW of 4345 litters from 1817 Large White sows and 8706 litters from 2286 L-1777 does over a maximum of five successive parities. For both species, the multiple-trait SAD fitted the data better than the random regression model. The difference between AIC of the two models (AIC_random regression-AIC_SAD) were equal to 7 and 227 for pigs and rabbits, respectively. A similar pattern of heritability and correlation estimates was obtained for both species. Heritabilities were lower for LS (ranging from 0.09 to 0.29) than for ABW (ranging from 0.23 to 0.39). The general trend was a decrease of the genetic correlation for a given trait between more distant parities. Estimates of genetic correlations between LS and ABW were negative and ranged from -0.03 to -0.52 across parities. No correlation was observed between the permanent environmental effects, except between the permanent environmental effects of LS and ABW of the same parity, for which the estimate of the correlation was strongly negative (ranging from -0.57 to -0.67). We demonstrated that application of our multiple-trait SAD model is feasible for studying several traits with repeated measurements and showed that it provided a better fit to the data than the random regression model.

5 CFR 591.219 - How does OPM compute shelter price indexes?

Code of Federal Regulations, 2014 CFR

2014-01-01

... estimates in hedonic regressions (a type of multiple regression) to compute for each COLA survey area the price index for rental and/or rental equivalent units of comparable quality and size between the COLA...

5 CFR 591.219 - How does OPM compute shelter price indexes?

Code of Federal Regulations, 2011 CFR

2011-01-01

... estimates in hedonic regressions (a type of multiple regression) to compute for each COLA survey area the price index for rental and/or rental equivalent units of comparable quality and size between the COLA...

5 CFR 591.219 - How does OPM compute shelter price indexes?

Code of Federal Regulations, 2013 CFR

2013-01-01

... estimates in hedonic regressions (a type of multiple regression) to compute for each COLA survey area the price index for rental and/or rental equivalent units of comparable quality and size between the COLA...

5 CFR 591.219 - How does OPM compute shelter price indexes?

Code of Federal Regulations, 2012 CFR

2012-01-01

... estimates in hedonic regressions (a type of multiple regression) to compute for each COLA survey area the price index for rental and/or rental equivalent units of comparable quality and size between the COLA...

Toward customer-centric organizational science: A common language effect size indicator for multiple linear regressions and regressions with higher-order terms.

PubMed

Krasikova, Dina V; Le, Huy; Bachura, Eric

2018-06-01

To address a long-standing concern regarding a gap between organizational science and practice, scholars called for more intuitive and meaningful ways of communicating research results to users of academic research. In this article, we develop a common language effect size index (CLβ) that can help translate research results to practice. We demonstrate how CLβ can be computed and used to interpret the effects of continuous and categorical predictors in multiple linear regression models. We also elaborate on how the proposed CLβ index is computed and used to interpret interactions and nonlinear effects in regression models. In addition, we test the robustness of the proposed index to violations of normality and provide means for computing standard errors and constructing confidence intervals around its estimates. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Modeling brook trout presence and absence from landscape variables using four different analytical methods

USGS Publications Warehouse

Steen, Paul J.; Passino-Reader, Dora R.; Wiley, Michael J.

2006-01-01

As a part of the Great Lakes Regional Aquatic Gap Analysis Project, we evaluated methodologies for modeling associations between fish species and habitat characteristics at a landscape scale. To do this, we created brook trout Salvelinus fontinalis presence and absence models based on four different techniques: multiple linear regression, logistic regression, neural networks, and classification trees. The models were tested in two ways: by application to an independent validation database and cross-validation using the training data, and by visual comparison of statewide distribution maps with historically recorded occurrences from the Michigan Fish Atlas. Although differences in the accuracy of our models were slight, the logistic regression model predicted with the least error, followed by multiple regression, then classification trees, then the neural networks. These models will provide natural resource managers a way to identify habitats requiring protection for the conservation of fish species.

Schistosomiasis Breeding Environment Situation Analysis in Dongting Lake Area

NASA Astrophysics Data System (ADS)

Li, Chuanrong; Jia, Yuanyuan; Ma, Lingling; Liu, Zhaoyan; Qian, Yonggang

2013-01-01

Monitoring environmental characteristics, such as vegetation, soil moisture et al., of Oncomelania hupensis (O. hupensis)’ spatial/temporal distribution is of vital importance to the schistosomiasis prevention and control. In this study, the relationship between environmental factors derived from remotely sensed data and the density of O. hupensis was analyzed by a multiple linear regression model. Secondly, spatial analysis of the regression residual was investigated by the semi-variogram method. Thirdly, spatial analysis of the regression residual and the multiple linear regression model were both employed to estimate the spatial variation of O. hupensis density. Finally, the approach was used to monitor and predict the spatial and temporal variations of oncomelania of Dongting Lake region, China. And the areas of potential O. hupensis habitats were predicted and the influence of Three Gorges Dam (TGB)project on the density of O. hupensis was analyzed.

Modification of the USLE K factor for soil erodibility assessment on calcareous soils in Iran

NASA Astrophysics Data System (ADS)

Ostovari, Yaser; Ghorbani-Dashtaki, Shoja; Bahrami, Hossein-Ali; Naderi, Mehdi; Dematte, Jose Alexandre M.; Kerry, Ruth

2016-11-01

The measurement of soil erodibility (K) in the field is tedious, time-consuming and expensive; therefore, its prediction through pedotransfer functions (PTFs) could be far less costly and time-consuming. The aim of this study was to develop new PTFs to estimate the K factor using multiple linear regression, Mamdani fuzzy inference systems, and artificial neural networks. For this purpose, K was measured in 40 erosion plots with natural rainfall. Various soil properties including the soil particle size distribution, calcium carbonate equivalent, organic matter, permeability, and wet-aggregate stability were measured. The results showed that the mean measured K was 0.014 t h MJ- 1 mm- 1 and 2.08 times less than the estimated mean K (0.030 t h MJ- 1 mm- 1) using the USLE model. Permeability, wet-aggregate stability, very fine sand, and calcium carbonate were selected as independent variables by forward stepwise regression in order to assess the ability of multiple linear regression, Mamdani fuzzy inference systems and artificial neural networks to predict K. The calcium carbonate equivalent, which is not accounted for in the USLE model, had a significant impact on K in multiple linear regression due to its strong influence on the stability of aggregates and soil permeability. Statistical indices in validation and calibration datasets determined that the artificial neural networks method with the highest R2, lowest RMSE, and lowest ME was the best model for estimating the K factor. A strong correlation (R2 = 0.81, n = 40, p < 0.05) between the estimated K from multiple linear regression and measured K indicates that the use of calcium carbonate equivalent as a predictor variable gives a better estimation of K in areas with calcareous soils.

Analysis and prediction of flow from local source in a river basin using a Neuro-fuzzy modeling tool.

PubMed

Aqil, Muhammad; Kita, Ichiro; Yano, Akira; Nishiyama, Soichi

2007-10-01

Traditionally, the multiple linear regression technique has been one of the most widely used models in simulating hydrological time series. However, when the nonlinear phenomenon is significant, the multiple linear will fail to develop an appropriate predictive model. Recently, neuro-fuzzy systems have gained much popularity for calibrating the nonlinear relationships. This study evaluated the potential of a neuro-fuzzy system as an alternative to the traditional statistical regression technique for the purpose of predicting flow from a local source in a river basin. The effectiveness of the proposed identification technique was demonstrated through a simulation study of the river flow time series of the Citarum River in Indonesia. Furthermore, in order to provide the uncertainty associated with the estimation of river flow, a Monte Carlo simulation was performed. As a comparison, a multiple linear regression analysis that was being used by the Citarum River Authority was also examined using various statistical indices. The simulation results using 95% confidence intervals indicated that the neuro-fuzzy model consistently underestimated the magnitude of high flow while the low and medium flow magnitudes were estimated closer to the observed data. The comparison of the prediction accuracy of the neuro-fuzzy and linear regression methods indicated that the neuro-fuzzy approach was more accurate in predicting river flow dynamics. The neuro-fuzzy model was able to improve the root mean square error (RMSE) and mean absolute percentage error (MAPE) values of the multiple linear regression forecasts by about 13.52% and 10.73%, respectively. Considering its simplicity and efficiency, the neuro-fuzzy model is recommended as an alternative tool for modeling of flow dynamics in the study area.

Soil Cd, Cr, Cu, Ni, Pb and Zn sorption and retention models using SVM: Variable selection and competitive model.

PubMed

González Costa, J J; Reigosa, M J; Matías, J M; Covelo, E F

2017-09-01

The aim of this study was to model the sorption and retention of Cd, Cu, Ni, Pb and Zn in soils. To that extent, the sorption and retention of these metals were studied and the soil characterization was performed separately. Multiple stepwise regression was used to produce multivariate models with linear techniques and with support vector machines, all of which included 15 explanatory variables characterizing soils. When the R-squared values are represented, two different groups are noticed. Cr, Cu and Pb sorption and retention show a higher R-squared; the most explanatory variables being humified organic matter, Al oxides and, in some cases, cation-exchange capacity (CEC). The other group of metals (Cd, Ni and Zn) shows a lower R-squared, and clays are the most explanatory variables, including a percentage of vermiculite and slime. In some cases, quartz, plagioclase or hematite percentages also show some explanatory capacity. Support Vector Machine (SVM) regression shows that the different models are not as regular as in multiple regression in terms of number of variables, the regression for nickel adsorption being the one with the highest number of variables in its optimal model. On the other hand, there are cases where the most explanatory variables are the same for two metals, as it happens with Cd and Cr adsorption. A similar adsorption mechanism is thus postulated. These patterns of the introduction of variables in the model allow us to create explainability sequences. Those which are the most similar to the selectivity sequences obtained by Covelo (2005) are Mn oxides in multiple regression and change capacity in SVM. Among all the variables, the only one that is explanatory for all the metals after applying the maximum parsimony principle is the percentage of sand in the retention process. In the competitive model arising from the aforementioned sequences, the most intense competitiveness for the adsorption and retention of different metals appears between Cr and Cd, Cu and Zn in multiple regression; and between Cr and Cd in SVM regression. Copyright © 2017 Elsevier B.V. All rights reserved.

Quality of life among people living with hypertension in a rural Vietnam community.

PubMed

Ha, Ninh Thi; Duy, Hoa Thi; Le, Ninh Hoang; Khanal, Vishnu; Moorin, Rachael

2014-08-11

To respond to growing prevalence of hypertension in Vietnam, it is critical to have an in-depth understanding about quality of life (QOL) among people living with hypertension and related factors. This study aimed to measure QOL among hypertensive people in a rural community in Vietnam, and its association with socio-demographic characteristics and factors related to treatment. This study was conducted in a rural community located 60 km from Ho Chi Minh City. Face-to-face interviews were conducted among 275 hypertensive people aged 50 years and above using WHOQOL-BREF questionnaire. Descriptive statistics were used to examine mean scores of quality of life. Cronbach's alpha coefficient and Pearson's correlation coefficient were applied to estimate the internal consistency, and the level of agreement between different domains of WHOQOL-BREF, respectively. Independent T-test and ANOVA test followed by multiple linear regression analyses were used to measure the association between QOL domains and independent variables. Both overall WHOQOL-BREF and each domain had a good internal consistency, ranging from 0.65 to 0.88. The QOL among hypertensive patients was found moderate in all domains, except for psychological domain that was fairly low (mean = 49.4). Backward multiple linear regressions revealed that being men, married, attainment of higher education, having physical activities at moderate level, and adherence to treatment were positively associated with QOL. However, older age and presence of co-morbidity were negatively associated with QOL. WHOQOL-BREF is a reliable instrument to measure QOL among hypertensive patients. The results revealed low QOL in psychological domain and inequality in QOL across socio-demographic characteristics. Given the results, encouraging physical activities and strengthening treatment adherence should be considered to improve QOL of hypertensive people, especially for psychological aspect. Actions to improve QOL among hypertensive patients targeted towards women, lower educated and unmarried patients are needed in the setting.

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.

How Possibly Do Leisure and Social Activities Impact Mental Health of Middle-Aged Adults in Japan?: An Evidence from a National Longitudinal Survey.

PubMed

Takeda, Fumi; Noguchi, Haruko; Monma, Takafumi; Tamiya, Nanako

2015-01-01

This study aimed to investigate longitudinal relations between leisure and social activities and mental health status, considering the presence or absence of other persons in the activity as an additional variable, among middle-aged adults in Japan. This study used nationally representative data in Japan with a five-year follow-up period. This study focused on 16,642 middle-aged adults, age 50-59 at baseline, from a population-based, six-year panel survey conducted by the Japanese Ministry of Health, Labour and Welfare. To investigate the relations between two leisure activities ('hobbies or cultural activities' and 'exercise or sports') and four social activities ('community events', 'support for children', 'support for elderly individuals' and 'other social activities') at baseline and mental health status at follow-up, multiple logistic regression analysis was used. We also used multiple logistic regression analysis to investigate the association between ways of participating in these activities ('by oneself', 'with others', or 'both' (both 'by oneself' and 'with others')) at baseline and mental health status at follow-up. Involvement in both leisure activity categories, but not in social activities, was significantly and positively related to mental health status in both men and women. Furthermore, in men, both 'hobbies or cultural activities' and 'exercise or sports' were significantly related to mental health status only when conducted 'with others'. In women, the effects of 'hobbies or cultural activities' on mental health status were no differences regardless of the ways of participating, while the result of 'exercise or sports' was same as that in men. Leisure activities appear to benefit mental health status among this age group, whereas specific social activities do not. Moreover, participation in leisure activities would be effective especially if others are present. These findings should be useful for preventing the deterioration of mental health status in middle-aged adults in Japan.

Attitude towards gender roles and violence against women and girls (VAWG): baseline findings from an RCT of 1752 youths in Pakistan.

PubMed

Saeed Ali, Tazeen; Karmaliani, Rozina; Mcfarlane, Judith; Khuwaja, Hussain M A; Somani, Yasmeen; Chirwa, Esnat D; Jewkes, Rachel

2017-01-01

Violence against women is driven by gender norms that normalize and justify gender inequality and violence. Gender norms are substantially shaped during adolescence. Programs offered through schools offer an opportunity to influence gender attitudes toward gender equity if we understand these to be partly shaped by peers and the school environment. We present an analysis of the baseline research conducted for a randomized controlled trial with 1752 grade 6 boys and girls and their attitudes toward gender roles, VAWG, and associated factors. We used baseline data from a  cluster randomised control study. Interviews were conducted in 40 public schools in Hyderabad, with 25-65 children per school. Questions were asked about attitudes toward gender roles, peer-to-peer perpetration, and victimization experiences, and family life, including father- or in-law-to- mother violence and food security. Multiple regression models were built of factors associated with gender attitudes for boys and girls. Our result have shown youth attitudes endorsing patriarchal gender beliefs were higher for boys, compared to girls. The multiple regression model showed that for boys, patriarchal gender attitudes were positively associated with hunger, depression, being promised already in marriage, and being a victim and/or perpetrator of peer violence. For girls gender attitudes were associated with hunger, experiencing corporal punishment at home, and being a perpetrator (for some, and victim) of peer violence. Youth patriarchal attitudes are closely related to their experience of violence at school and for girl's physical punishment, at home and for boys being promised in early marriage. We suggest that these variables are indicators of gender norms among peers and in the family. The significance of peer norms is that it provides the possibility that school-based interventions which work with school peers have the potential to positively impact youth patriarchal gender attitudes and foster attitudes of gender equality and respect, and potentially to decrease youth victimization and perpetration.

Multiple tobacco product use among US adolescents and young adults

PubMed Central

Soneji, Samir; Sargent, James; Tanski, Susanne

2016-01-01

Objective To assess the extent to which multiple tobacco product use among adolescents and young adults falls outside current Food and Drug Administration (FDA) regulatory authority. Methods We conducted a web-based survey of 1596 16–26-year-olds to assess use of 11 types of tobacco products. We ascertained current (past 30 days) tobacco product use among 927 respondents who ever used tobacco. Combustible tobacco products included cigarettes, cigars (little filtered, cigarillos, premium) and hookah; non-combustible tobacco products included chew, dip, dissolvables, e-cigarettes, snuff and snus. We then fitted an ordinal logistic regression model to assess demographic and behavioural associations with higher levels of current tobacco product use (single, dual and multiple product use). Results Among 448 current tobacco users, 54% were single product users, 25% dual users and 21% multiple users. The largest single use category was cigarettes (49%), followed by hookah (23%), little filtered cigars (17%) and e-cigarettes (5%). Most dual and multiple product users smoked cigarettes, along with little filtered cigars, hookah and e-cigarettes. Forty-six per cent of current single, 84% of dual and 85% of multiple tobacco product users consumed a tobacco product outside FDA regulatory authority. In multivariable analysis, the adjusted risk of multiple tobacco use was higher for males, first use of a non-combustible tobacco product, high sensation seeking respondents and declined for each additional year of age that tobacco initiation was delayed. Conclusions Nearly half of current adolescent and young adult tobacco users in this study engaged in dual and multiple tobacco product use; the majority of them used products that fall outside current FDA regulatory authority. This study supports FDA deeming of these products and their incorporation into the national media campaign to address youth tobacco use. PMID:25361744

Older age, higher perceived disability and depressive symptoms predict the amount and severity of work-related difficulties in persons with multiple sclerosis.

PubMed

Raggi, Alberto; Giovannetti, Ambra Mara; Schiavolin, Silvia; Brambilla, Laura; Brenna, Greta; Confalonieri, Paolo Agostino; Cortese, Francesca; Frangiamore, Rita; Leonardi, Matilde; Mantegazza, Renato Emilio; Moscatelli, Marco; Ponzio, Michela; Torri Clerici, Valentina; Zaratin, Paola; De Torres, Laura

2018-04-16

This cross-sectional study aims to identify the predictors of work-related difficulties in a sample of employed persons with multiple sclerosis as addressed with the Multiple Sclerosis Questionnaire for Job Difficulties. Hierarchical linear regression analysis was conducted to identify predictors of work difficulties: predictors included demographic variables (age, formal education), disease duration and severity, perceived disability and psychological variables (cognitive dysfunction, depression and anxiety). The targets were the questionnaire's overall score and its six subscales. A total of 177 participants (108 females, aged 21-63) were recruited. Age, perceived disability and depression were direct and significant predictors of the questionnaire total score, and the final model explained 43.7% of its variation. The models built on the questionnaire's subscales show that perceived disability and depression were direct and significant predictors of most of its subscales. Our results show that, among patients with multiple sclerosis, those who were older, with higher perceived disability and higher depression symptoms have more and more severe work-related difficulties. The Multiple Sclerosis Questionnaire for Job Difficulties can be fruitfully exploited to plan tailored actions to limit the likelihood of near-future job loss in persons of working age with multiple sclerosis. Implications for rehabilitation Difficulties with work are common among people with multiple sclerosis and are usually addressed in terms of unemployment or job loss. The Multiple Sclerosis Questionnaire for Job Difficulties is a disease-specific questionnaire developed to address the amount and severity of work-related difficulties. We found that work-related difficulties were associated to older age, higher perceived disability and depressive symptoms. Mental health issues and perceived disability should be consistently included in future research targeting work-related difficulties.

Neural network and multiple linear regression to predict school children dimensions for ergonomic school furniture design.

PubMed

Agha, Salah R; Alnahhal, Mohammed J

2012-11-01

The current study investigates the possibility of obtaining the anthropometric dimensions, critical to school furniture design, without measuring all of them. The study first selects some anthropometric dimensions that are easy to measure. Two methods are then used to check if these easy-to-measure dimensions can predict the dimensions critical to the furniture design. These methods are multiple linear regression and neural networks. Each dimension that is deemed necessary to ergonomically design school furniture is expressed as a function of some other measured anthropometric dimensions. Results show that out of the five dimensions needed for chair design, four can be related to other dimensions that can be measured while children are standing. Therefore, the method suggested here would definitely save time and effort and avoid the difficulty of dealing with students while measuring these dimensions. In general, it was found that neural networks perform better than multiple linear regression in the current study. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

A Modified Double Multiple Nonlinear Regression Constitutive Equation for Modeling and Prediction of High Temperature Flow Behavior of BFe10-1-2 Alloy

NASA Astrophysics Data System (ADS)

Cai, Jun; Wang, Kuaishe; Shi, Jiamin; Wang, Wen; Liu, Yingying

2018-01-01

Constitutive analysis for hot working of BFe10-1-2 alloy was carried out by using experimental stress-strain data from isothermal hot compression tests, in a wide range of temperature of 1,023 1,273 K, and strain rate range of 0.001 10 s-1. A constitutive equation based on modified double multiple nonlinear regression was proposed considering the independent effects of strain, strain rate, temperature and their interrelation. The predicted flow stress data calculated from the developed equation was compared with the experimental data. Correlation coefficient (R), average absolute relative error (AARE) and relative errors were introduced to verify the validity of the developed constitutive equation. Subsequently, a comparative study was made on the capability of strain-compensated Arrhenius-type constitutive model. The results showed that the developed constitutive equation based on modified double multiple nonlinear regression could predict flow stress of BFe10-1-2 alloy with good correlation and generalization.

Evaluation of physico-mechanical properties of clayey soils using electrical resistivity imaging technique

NASA Astrophysics Data System (ADS)

Kibria, Golam

Resistivity imaging (RI) is a promising approach to obtaining continuous profile of soil subsurface. This method offers simple technique to identify moisture variation and heterogeneity of the investigated area. However, at present, only qualitative information of subsurface can be obtained using RI. A study on the quantification of geotechnical properties has become important for rigorous use of this method in the evaluation of geohazard potential and construction quality control of landfill liner system. Several studies have been performed to describe electrical resistivity of soil as a function of pore fluid conductivity and surface conductance. However, characterization tests on pore water and surface charge are not typically performed in a conventional geotechnical investigation. The overall objective of this study is to develop correlations between geotechnical parameters and electrical resistivity of soil, which would provide a mean to estimate geotechnical properties from RI. As a part of the study, multiple regression analyses were conducted to develop practically applicable models correlating resistivity with influential geotechnical parameters. The soil samples considered in this study were classified as highly plastic clay (CH) and low plasticity clay (CL) according to Unified Soil Classification System (USCS). Based on the physical tests, scanning electron microscope (SEM), and energy dispersive X-ray spectroscopy (EDS) analysis, kaolinite was identified as the dominant mineral with some traces of magnesium, calcium, potassium, and iron. Electrical resistivity tests were conducted on compacted clays and undisturbed samples under varied geotechnical conditions. The experimental results indicated that the degree of saturation substantially influenced electrical resistivity. Electrical resistivity decreased as much as 11 times from initial value for the increase of degree of saturation from 23 to 100% in the laboratory tests on compacted clays. In case of undisturbed soil samples, resistivity decreased as much as sixteen fold (49.4 to 3.2 Ohm-m) for an increase of saturation from 31 to 100%. Furthermore, the resistivity results were different for the specimens at a specific degree of saturation because of varied surface activity and isomorphous substitution of clayey soils. In addition to physical properties, compressibility of clays was correlated with electrical conductivity. Based on the investigation, it was determined that the electrical conductivity vs. pressure curves followed similar trends as e vs. logp curves. Multiple linear regression (MLR) models were developed for compacted and undisturbed samples using statistical analysis software SAS (2009). During model development, degree of saturation and CEC were selected as independent variables. The proposed models were validated using experimental results on a different set of samples. Moreover, the applicability of the models in the determination of degrees of saturation was evaluated using field RI tests.

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.

The relationship between children's oral health-related behaviors and their caregiver's social support.

PubMed

Qiu, Rong Min; Tao, Ye; Zhou, Yan; Zhi, Qing Hui; Lin, Huan Cai

2016-09-01

Social support might play a role in helping people adopt healthy behaviors and improve their health. Stronger social support from mothers has been found to be positively related to higher tooth brushing frequency in 1- to 3-year-old children. However, little is known regarding the relationship between the caregiver's social support and the oral health-related behaviors of 5-year-old children in China. This study aimed to investigate this relationship. A cross-sectional study was conducted among 1332 5-year-old children and their caregivers in Guangzhou, southern China. Data were collected using questionnaires that were completed by the caregivers and the children's caries status were examined. The caregivers' social support was measured using the Social Support Rating Scale. The measurements of the children's oral health-related behaviors included the frequencies of sugary snack intake and tooth brushing, utilization of dental services, and patterns of dental visits. Univariate and multiple logistic regression analyses were used to analyze the relationships between the variables. No association was found between the caregiver's social support and the child's oral health-related behaviors in a multiple logistic regression analysis. However, other factors, particularly the oral health-related behaviors of the caregiver, were found to be significantly linked to the child's oral health-related behaviors. The oral health-related behaviors of 5-year-old children in Guangzhou are unrelated to the caregiver's social support but are related to other specific factors, particularly the caregiver's oral health-related behaviors.

[Patients' reaction to pharmacists wearing a mask during their consultations].

PubMed

Tamura, Eri; Kishimoto, Keiko; Fukushima, Noriko

2013-01-01

  This study sought to determine the effect of pharmacists wearing a mask on the consultation intention of patients who do not have a trusting relationship with the pharmacists. We conducted a questionnaire survey of customers at a Tokyo drugstore in August 2012. Subjects answered a questionnaire after watching two medical teaching videos, one in which the pharmacist was wearing a mask and the other in which the pharmacist was not wearing a mask. Data analysis was performed using a paired t-test and multiple logistic regression. The paired t-test revealed a significant difference in 'Maintenance Problem' between the two pharmacist situations. After excluding factors not associated with wearing a mask, multiple logistic regression analysis identified three independent variables with a significant effect on participants not wanting to consult with a pharmacist wearing a mask. Positive factors were 'active-inactive' and 'frequency mask use', a negative factor was 'age'. Our study has shown that pharmacists wearing a mask may be a factor that prevents patients from consulting with pharmacist. Those patients whose intention to consult might be affected by the pharmacists wearing a mask tended to be younger, to have no habit of wearing masks preventively themselves, and to form a negative opinion of such pharmacists. Therefore, it was estimated that pharmacists who wear masks need to provide medical education by asking questions more positively than when they do not wear a mask in order to prevent the patient worrying about oneself.

Variability in in vitro fertilization outcomes of prepubertal goat oocytes explained by basic semen analyses.

PubMed

Palomo, M J; Quintanilla, R; Izquierdo, M D; Mogas, T; Paramio, M T

2016-12-01

This work analyses the changes that caprine spermatozoa undergo during in vitro fertilization (IVF) of in vitro matured prepubertal goat oocytes and their relationship with IVF outcome, in order to obtain an effective model that allows prediction of in vitro fertility on the basis of semen assessment. The evolution of several sperm parameters (motility, viability and acrosomal integrity) during IVF and their relationship with three IVF outcome criteria (total penetration, normal penetration and cleavage rates) were studied in a total of 56 IVF replicates. Moderate correlation coefficients between some sperm parameters and IVF outcome were observed. In addition, stepwise multiple regression analyses were conducted that considered three grouping of sperm parameters as potential explanatory variables of the three IVF outcome criteria. The proportion of IVF outcome variation that can be explained by the fitted models ranged from 0.62 to 0.86, depending upon the trait analysed and the variables considered. Seven out of 32 sperm parameters were selected as partial covariates in at least one of the nine multiple regression models. Among these, progressive sperm motility assessed immediately after swim-up, the percentage of dead sperm with intact acrosome and the incidence of acrosome reaction both determined just before the gamete co-culture, and finally the proportion of viable spermatozoa at 17 h post-insemination were the most frequently selected sperm parameters. Nevertheless, the predictive ability of these models must be confirmed in a larger sample size experiment.

Association between osteoporosis and periodontal disease among postmenopausal Indian women.

PubMed

Richa; R, Yashoda; Puranik, Manjunath P; Shrivastava, Amit

2017-08-01

The aim of the present study was to determine the association between osteoporosis and periodontal disease among postmenopausal Indian women. A cross-sectional comparative study was conducted among postmenopausal women aged 45-65 years attending various hospitals in Bangalore, India. The examination was performed using the plaque index, gingival index, modified sulcus bleeding index, and community periodontal index. The women then underwent a bone mineral density (BMD) test using an ultrasonometer. Based on the BMD scores, participants were divided into osteoporotic and non-osteoporotic groups. For the statistical analysis, χ 2 -test, Student's t-test, and multiple regression analysis were applied. The mean plaque, gingival, and bleeding scores were significantly higher among osteoporotic women (1.83 ± 0.47, 1.73 ± 0.49, 1.82 ± 0.52) compared to the non-osteoporotic women (1.31 ± 0.40, 1.09 ± 0.52, 1.25 ± 0.50). The mean number of sextants affected for codes 3 and 4 of the community periodontal index and codes 1, 2, and 3 of loss of attachment were significantly higher among osteoporotic group compared to the non-osteoporotic group. Multiple logistic regression tests confirmed the statistically-significant association between osteoporosis and menopause duration, loss of attachment, bleeding, and gingivitis scores. Skeletal BMD is related to clinical attachment loss, bleeding, and gingivitis, which suggests that there is an association between osteoporosis and periodontal diseases. © 2016 John Wiley & Sons Australia, Ltd.

The Relationship between Structure-Related Food Parenting Practices and Children's Heightened Levels of Self-Regulation in Eating.

PubMed

Frankel, Leslie A; Powell, Elisabeth; Jansen, Elena

Food parenting practices influence children's eating behaviors and weight status. Food parenting practices also influence children's self-regulatory abilities around eating, which has important implications for children's eating behaviors. The purpose of the following study is to examine use of structure-related food parenting practices and the potential impact on children's ability to self-regulate energy intake. Parents (n = 379) of preschool age children (M = 4.10 years, SD = 0.92) were mostly mothers (68.6%), Non-White (54.5%), and overweight/obese (50.1%). Hierarchical Multiple Regression was conducted to predict child self-regulation in eating from structure-related food parenting practices (structured meal setting, structured meal timing, family meal setting), while accounting for child weight status, parent age, gender, BMI, race, and yearly income. Hierarchical Multiple Regression results indicated that structure-related feeding practices (structured meal setting and family meal setting, but not structured meal timing) are associated with children's heightened levels of self-regulation in eating. Models examining the relationship within children who were normal weight and overweight/obese indicated the following: a relationship between structured meal setting and heightened self-regulation in eating for normal-weight children and a relationship between family meal setting and heightened self-regulation in eating for overweight/obese children. Researchers should further investigate these potentially modifiable parent feeding behaviors as a protective parenting technique, which possibly contributes to a healthy weight development by enhancing self-regulation in eating.

Job stress, achievement motivation and occupational burnout among male nurses.

PubMed

Hsu, Hsiu-Yueh; Chen, Sheng-Hwang; Yu, Hsing-Yi; Lou, Jiunn-Horng

2010-07-01

This paper is a report of an exploration of job stress, achievement motivation and occupational burnout in male nurses and to identify predictors of occupational burnout. Since the Nightingale era, the nursing profession has been recognized as 'women's work'. The data indicate that there are more female nurses than male nurses in Taiwan. However, the turnover rate for male nurses is twice that of female nurses. Understanding the factors that affect occupational burnout of male nurses may help researchers find ways to reduce the likelihood that they will quit. A survey was conducted in Taiwan in 2008 using a cross-sectional design. A total of 121 male nurses participated in the study. Mailed questionnaires were used to collect data, which were analysed using descriptive statistics and stepwise multiple regression. The job stress of male nurses was strongly correlated with occupational burnout (r = 0.64, P < 0.001). Stepwise multiple regression analyses indicated that job stress was the only factor to have a statistically significant direct influence on occupational burnout, accounting for 45.8% of the variance in this. Job stress was comprised of three dimensions, of which role conflict accounted for 40.8% of the variance in occupational burnout. The contribution of job stress to occupational burnout of male nurses was confirmed. As occupational burnout may influence the quality of care by these nurses, nurse managers should strive to decrease male nurses' job stress as this should lead to a reduction of negative outcomes of occupational burnout.

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.

Impulsivity, attention, memory, and decision-making among adolescent marijuana users.

PubMed

Dougherty, Donald M; Mathias, Charles W; Dawes, Michael A; Furr, R Michael; Charles, Nora E; Liguori, Anthony; Shannon, Erin E; Acheson, Ashley

2013-03-01

Marijuana is a popular drug of abuse among adolescents, and they may be uniquely vulnerable to resulting cognitive and behavioral impairments. Previous studies have found impairments among adolescent marijuana users. However, the majority of this research has examined measures individually rather than multiple domains in a single cohesive analysis. This study used a logistic regression model that combines performance on a range of tasks to identify which measures were most altered among adolescent marijuana users. The purpose of this research was to determine unique associations between adolescent marijuana use and performances on multiple cognitive and behavioral domains (attention, memory, decision-making, and impulsivity) in 14- to 17-year-olds while simultaneously controlling for performances across the measures to determine which measures most strongly distinguish marijuana users from nonusers. Marijuana-using adolescents (n = 45) and controls (n = 48) were tested. Logistic regression analyses were conducted to test for: (1) differences between marijuana users and nonusers on each measure, (2) associations between marijuana use and each measure after controlling for the other measures, and (3) the degree to which (1) and (2) together elucidated differences among marijuana users and nonusers. Of all the cognitive and behavioral domains tested, impaired short-term recall memory and consequence sensitivity impulsivity were associated with marijuana use after controlling for performances across all measures. This study extends previous findings by identifying cognitive and behavioral impairments most strongly associated with adolescent marijuana users. These specific deficits are potential targets of intervention for this at-risk population.

The Moderating Role of Power Distance on the Relationship between Employee Participation and Outcome Variables.

PubMed

Rafiei, Sima; Pourreza, Abolghasem

2013-06-01

Many organisations have realised the importance of human resource for their competitive advantage. Empowering employees is therefore essential for organisational effectiveness. This study aimed to investigate the relationship between employee participation with outcome variables such as organisational commitment, job satisfaction, perception of justice in an organisation and readiness to accept job responsibilities. It further examined the impact of power distance on the relationship between participation and four outcome variables. This was a cross sectional study with a descriptive research design conducted among employees and managers of hospitals affiliated with Tehran University of Medical Sciences, Tehran, Iran. A questionnaire as a main procedure to gather data was developed, distributed and collected. Descriptive statistics, Pearson correlation coefficient and moderated multiple regression were used to analyse the study data. Findings of the study showed that the level of power distance perceived by employees had a significant relationship with employee participation, organisational commitment, job satisfaction, perception of justice and readiness to accept job responsibilities. There was also a significant relationship between employee participation and four outcome variables. The moderated multiple regression results supported the hypothesis that power distance had a significant effect on the relationship between employee participation and four outcome variables. Organisations in which employee empowerment is practiced through diverse means such as participating them in decision making related to their field of work, appear to have more committed and satisfied employees with positive perception toward justice in the organisational interactions and readiness to accept job responsibilities.

Relationship between betel quid chewing and radiographic alveolar bone loss among Taiwanese aboriginals: a retrospective study.

PubMed

Hsiao, Chun-Nan; Ting, Chun-Chan; Shieh, Tien-Yu; Ko, Edward Chengchuan

2014-11-04

Betel quid chewing is associated with the periodontal status; however, results of epidemiological studies are inconsistent. To the best of our knowledge, no study has reported radiographic alveolar bone loss (RABL) associated with betel quid chewing. This survey was conducted in an aboriginal community in Taiwan because almost all betel quid chewers were city-dwelling cigarette smokers. In total, 114 subjects, aged 30-60 years, were included. Full-mouth intraoral RABL was retrospectively measured and adjusted for age, gender, and plaque index (PI). Multiple regression analysis was used to assess the relationship between RABL and potential risk factors. Age-, gender-, and PI-adjusted mean RABL was significantly higher in chewers with or without cigarette smoking than in controls. Multiple regression analysis showed that the RABL for consumption of 100,000 pieces betel quid for the chewer group was 0.40 mm. Full-mouth plotted curves for adjusted mean RABL in the maxilla were similar between the chewer and control groups, suggesting that chemical effects were not the main factors affecting the association between betel quid chewing and the periodontal status. Betel quid chewing significantly increases RABL. The main contributory factors are age and oral hygiene; however, the major mechanism underlying this process may not be a chemical mechanism. Regular dental visits, maintenance of good oral hygiene, and reduction in the consumption of betel quid, additives, and cigarettes are highly recommended to improve the periodontal status.

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.

Serum uric acid concentrations are directly associated with the presence of benign multiple sclerosis.

PubMed

Simental-Mendía, Esteban; Simental-Mendía, Luis E; Guerrero-Romero, Fernando

2017-09-01

It has been reported that patients with multiple sclerosis (MS) exhibit lower serum uric acid levels; however, the association between uric acid concentrations and benign MS (BMS) has not been assessed. Hence, the objective of the present study was to determine whether the serum concentrations of uric acid are associated with the presence of BMS. Men and non-pregnant women over 16 years of age with diagnosis of MS were enrolled in a cross-sectional study. Expanded Disability Status Scale score < 3, progression of disease ≤10 years, diabetes, renal or hepatic diseases, gout, malignancy, alcohol intake, and treatment with thiazide diuretics and/or acetylsalicylic acid were exclusion criteria. According to subtype of disease, the eligible patients were allocated into groups with BMS and other varieties of MS. A logistic regression analysis was conducted in order to evaluate the association between serum concentrations of uric acid and BMS. A total of 106 patients were included, 39 in the group with BMS and 67 in the group with other varieties of MS. The logistic regression analysis adjusted by age, sex, and disease duration showed that increased concentrations of uric acid, indeed within the physiological levels, are significantly associated with the presence of BMS (OR = 2.60; 95% CI: 1.55-4.38, p < 0.001). The results of the present study suggest that elevated concentrations of uric acid, indeed within the physiological range, are likely linked to the presence of BMS.

Application of WHOQOL-BREF in Measuring Quality of Life in Health-Care Staff.

PubMed

Gholami, Ali; Jahromi, Leila Moosavi; Zarei, Esmail; Dehghan, Azizallah

2013-07-01

The objective of this study was to evaluate the quality of life of Neyshabur health-care staff and some factors associated with it with use of WHOQOL-BREF scale. This cross-sectional study was conducted on 522 staff of Neyshabur health-care centers from May to July 2011. Cronbach's alpha coefficient was applied to examine the internal consistency of WHOQOL-BREF scale; Pearson's correlation coefficient was used to determine the level of agreement between different domains of WHOQOL-BREF. Paired t-test was used to compare difference between score means of different domains. T-independent test was performed for group analysis and Multiple Linear Regression was used to control confounding effects. In this study, a good internal consistency (α = 0.925) for WHOQOL-BREF and its four domains was observed. The highest and the lowest mean scores of WHOQOL-BREF domains was found for physical health domain (Mean = 15.26) and environmental health domain (Mean = 13.09) respectively. Backward multiple linear regression revealed that existence chronic disease in staff was significantly associated with four domains of WHOQOL-BREF, education years was associated with two domains (Psychological and Environmental) and sex was associated with psychological domain (P < 0.05). The findings from this study confirm that the WHOQOL-BREF questionnaire is a reliable instrument to measure quality of life in health-care staff. From the data, it appears that Neyshabur health-care staff has WHOQOL-BREF scores that might be considered to indicate a relatively moderate quality of life.

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.

Functional recovery differences after stroke rehabilitation in patients with uni- or bilateral hemiparesis

PubMed Central

Bindawas, Saad M.; Mawajdeh, Hussam M.; Vennu, Vishal S.; Alhaidary, Hisham M.

2017-01-01

Objective: To examine the functional recovery differences after stroke rehabilitation in patients with uni- or bilateral hemiparesis. Methods: In this retrospective study, we included data from the medical record of all 383 patients with uni- or bilateral hemiparesis after stroke who were admitted to King Fahad Medical City-Rehabilitation Hospital between 2008 and 2014 in Riyadh, Kingdom of Saudi Arabia. According to the site of hemiparesis, we classified patients into 3 groups: right hemiparesis (n=208), left hemiparesis (n=157), and bilateral hemipareses (n=18). The patients (n=49) who did not have either site of hemiparesis were excluded. The Functional Independence Measures (FIM) instrument was used to assess the score at admission and discharge. A post hoc test was conducted to examine the functional recovery differences between groups. Multiple regression analyses were used to confirm the findings. Results: Amongst the three groups, there were significant (p<0.05) differences in the total-FIM score as well as motor- and cognitive-FIM sub-scores between admission and discharge of stroke rehabilitation. The differences were significantly greater in the bilateral hemipareses group than in either unilateral hemiparesis group. Multiple regression analyses also confirmed that the site of hemiparesis significantly (p<0.05) differs in the total-FIM score as well as motor-FIM and cognitive-FIM sub-scores. Conclusion: Our results demonstrate that differences in functional recovery after stroke rehabilitation may be influenced by the site of hemiparesis after stroke. PMID:28678212

Factors Predicting a Good Symptomatic Outcome After Prostate Artery Embolisation (PAE).

PubMed

Maclean, D; Harris, M; Drake, T; Maher, B; Modi, S; Dyer, J; Somani, B; Hacking, N; Bryant, T

2018-02-26

As prostate artery embolisation (PAE) becomes an established treatment for benign prostatic obstruction, factors predicting good symptomatic outcome remain unclear. Pre-embolisation prostate size as a predictor is controversial with a handful of papers coming to conflicting conclusions. We aimed to investigate if an association existed in our patient cohort between prostate size and clinical benefit, in addition to evaluating percentage volume reduction as a predictor of symptomatic outcome following PAE. Prospective follow-up of 86 PAE patients at a single institution between June 2012 and January 2016 was conducted (mean age 64.9 years, range 54-80 years). Multiple linear regression analysis was performed to assess strength of association between clinical improvement (change in IPSS) and other variables, of any statistical correlation, through Pearson's bivariate analysis. No major procedural complications were identified and clinical success was achieved in 72.1% (n = 62) at 12 months. Initial prostate size and percentage reduction were found to have a significant association with clinical improvement. Multiple linear regression analysis (r 2  = 0.48) demonstrated that percentage volume reduction at 3 months (r = 0.68, p < 0.001) had the strongest correlation with good symptomatic improvement at 12 months after adjusting for confounding factors. Both the initial prostate size and percentage volume reduction at 3 months predict good symptomatic outcome at 12 months. These findings therefore aid patient selection and counselling to achieve optimal outcomes for men undergoing prostate artery embolisation.

The vestibular evoked myogenic potentials (VEMP) score: a promising tool for evaluation of brainstem involvement in multiple sclerosis.

PubMed

Gabelić, T; Krbot Skorić, M; Adamec, I; Barun, B; Zadro, I; Habek, M

2015-02-01

Concerning the great importance of brainstem involvement in multiple sclerosis (MS), the aim of this study was to explore the role of the newly developed vestibular evoked myogenic potentials (VEMP) score as a possible marker of brainstem involvement in MS patients. This was a prospective case-control study which included 100 MS patients divided into two groups (without and with clinical signs of brainstem involvement) and 50 healthy controls. Ocular VEMP (oVEMP) and cervical VEMP (cVEMP) measurements were performed in all participants and analyzed for latencies, conduction block and amplitude asymmetry ratio. Based on this the VEMP score was calculated and compared with Expanded Disability Status Scale (EDSS), disease duration and magnetic resonance imaging data. Multiple sclerosis patients with clinical signs of brainstem involvement (group 2) had a statistically significant higher percentage of VEMP conduction blocks compared with patients without clinical signs of brainstem involvement (group 1) and healthy controls (P = 0.027 and P < 0.0001, respectively). Similarly, the VEMP score was significantly higher in group 2 compared with group 1 (P = 0.018) and correlated with EDSS and disease duration (P = 0.011 and P = 0.032, respectively). Multivariate linear regression analysis showed that the VEMP score has a statistically significant influence on the EDSS score (P < 0.001, R(2) = 0.239). Interpretation of the oVEMP and cVEMP results in the form of the VEMP score enables better evaluation of brainstem involvement than either of these evoked potentials alone and correlates well with disability. © 2014 EAN.