Employment barriers, skills, and aspirations among unemployed job seekers with and without social anxiety disorder.

PubMed

Himle, Joseph A; Weaver, Addie; Bybee, Deborah; O'Donnell, Lisa; Vlnka, Sarah; Laviolette, Wayne; Steinberger, Edward; Golenberg, Zipora; Levine, Debra Siegel

2014-07-01

The literature has consistently demonstrated that social anxiety disorder has substantial negative impacts on occupational functioning. However, to date, no empirical work has focused on understanding the specific nature of vocational problems among persons with social anxiety disorder. This study examined the association between perceived barriers to employment, employment skills, and job aspirations and social anxiety among adults seeking vocational rehabilitation services. Data from intake assessments (June 2010-December 2011) of 265 low-income, unemployed adults who initiated vocational rehabilitation services in urban Michigan were examined to assess perceived barriers to employment, employment skills, job aspirations, and demographic characteristics among participants who did or did not screen positive for social anxiety disorder. Bivariate and multiple logistic regression analyses were performed. After adjustment for other factors, the multiple logistic regression analysis revealed that perceiving more employment barriers involving experience and skills, reporting fewer skills related to occupations requiring social skills, and having less education were significantly associated with social anxiety disorder. Participants who screened positive for social anxiety disorder were significantly less likely to aspire to social jobs. Employment-related characteristics that were likely to have an impact on occupational functioning were significantly different between persons with and without social anxiety problems. Identifying these differences in employment barriers, skills, and job aspirations revealed important information for designing psychosocial interventions for treatment of social anxiety disorder. The findings underscored the need for vocational services professionals to assess and address social anxiety among their clients.

Latent profile analysis of regression-based norms demonstrates relationship of compounding MS symptom burden and negative work events.

PubMed

Frndak, Seth E; Smerbeck, Audrey M; Irwin, Lauren N; Drake, Allison S; Kordovski, Victoria M; Kunker, Katrina A; Khan, Anjum L; Benedict, Ralph H B

2016-10-01

We endeavored to clarify how distinct co-occurring symptoms relate to the presence of negative work events in employed multiple sclerosis (MS) patients. Latent profile analysis (LPA) was utilized to elucidate common disability patterns by isolating patient subpopulations. Samples of 272 employed MS patients and 209 healthy controls (HC) were administered neuroperformance tests of ambulation, hand dexterity, processing speed, and memory. Regression-based norms were created from the HC sample. LPA identified latent profiles using the regression-based z-scores. Finally, multinomial logistic regression tested for negative work event differences among the latent profiles. Four profiles were identified via LPA: a common profile (55%) characterized by slightly below average performance in all domains, a broadly low-performing profile (18%), a poor motor abilities profile with average cognition (17%), and a generally high-functioning profile (9%). Multinomial regression analysis revealed that the uniformly low-performing profile demonstrated a higher likelihood of reported negative work events. Employed MS patients with co-occurring motor, memory and processing speed impairments were most likely to report a negative work event, classifying them as uniquely at risk for job loss.

Job characteristics in relation to the prevalence of myocardial infarction in the US Health Examination Survey (HES) and the Health and Nutrition Examination Survey (HANES).

PubMed

Karasek, R A; Theorell, T; Schwartz, J E; Schnall, P L; Pieper, C F; Michela, J L

1988-08-01

Associations between psychosocial job characteristics and past myocardial infarction (MI) prevalence for employed males were tested with the Health Examination Survey (HES) 1960-61, N = 2,409, and the Health and Nutrition Examination Survey (HANES) 1971-75, N = 2,424. A new estimation method is used which imputes to census occupation codes, job characteristic information from national surveys of job characteristics (US Department of Labor, Quality of Employment Surveys). Controlling for age, we find that employed males with jobs which are simultaneously low in decision latitude and high in psychological work load (a multiplicative product term isolating 20 per cent of the population) have a higher prevalence of myocardial infarction in both data bases. In a logistic regression analysis, using job measures adjusted for demographic factors and controlling for age, race, education, systolic blood pressure, serum cholesterol, smoking (HANES only), and physical exertion, we find a low decision latitude/high psychological demand multiplicative product term associated with MI in both data bases. Additional multiple logistic regressions show that low decision latitude is associated with increased prevalence of MI in both the HES and the HANES. Psychological workload and physical exertion are significant only in the HANES.

Job characteristics in relation to the prevalence of myocardial infarction in the US Health Examination Survey (HES) and the Health and Nutrition Examination Survey (HANES).

PubMed Central

Karasek, R A; Theorell, T; Schwartz, J E; Schnall, P L; Pieper, C F; Michela, J L

1988-01-01

Associations between psychosocial job characteristics and past myocardial infarction (MI) prevalence for employed males were tested with the Health Examination Survey (HES) 1960-61, N = 2,409, and the Health and Nutrition Examination Survey (HANES) 1971-75, N = 2,424. A new estimation method is used which imputes to census occupation codes, job characteristic information from national surveys of job characteristics (US Department of Labor, Quality of Employment Surveys). Controlling for age, we find that employed males with jobs which are simultaneously low in decision latitude and high in psychological work load (a multiplicative product term isolating 20 per cent of the population) have a higher prevalence of myocardial infarction in both data bases. In a logistic regression analysis, using job measures adjusted for demographic factors and controlling for age, race, education, systolic blood pressure, serum cholesterol, smoking (HANES only), and physical exertion, we find a low decision latitude/high psychological demand multiplicative product term associated with MI in both data bases. Additional multiple logistic regressions show that low decision latitude is associated with increased prevalence of MI in both the HES and the HANES. Psychological workload and physical exertion are significant only in the HANES. PMID:3389427

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.

ESTER HYDROLYSIS RATE CONSTANT PREDICTION FROM INFRARED INTERFEROGRAMS

EPA Science Inventory

A method for predicting reactivity parameters of organic chemicals from spectroscopic data is being developed to assist in assessing the environmental fate of pollutants. he prototype system, which employs multiple linear regression analysis using selected points from the Fourier...

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.

A comparison of unemployed job-seekers with and without social anxiety

PubMed Central

Himle, Joseph A; Weaver, Addie; Bybee, Deborah; O'Donnell, Lisa; Vlnka, Sarah; Laviolette, Wayne; Steinberger, Edward; Zipora, Golenberg; Levine, Debra Siegel

2014-01-01

Objective Literature consistently demonstrates that social anxiety disorder has substantial negative impacts on occupational functioning. However, to date, no identified empirical work has focused on understanding the specific nature of vocational problems among persons with social anxiety disorder. This study examines the association between employment-related factors (i.e., barriers to employment; skills related to employment; and job aspirations) and social anxiety among a sample of adults seeking vocational rehabilitation services. Methods Data from intake assessments, including a screen for social anxiety disorder, of 265 low-income, unemployed adults who initiated vocational rehabilitation services in urban Michigan was examined to assess differences in barriers to employment, employment skills, job aspirations, and demographic characteristics among participants who screened positive for social anxiety disorder compared to those who did not. Bivariate and multiple logistic regression analyses were performed. Results Multiple logistic regression analysis revealed that greater perceived experience and skill barriers to employment, fewer skills related to social-type occupations, and less education were significantly associated with social anxiety, after adjusting for other factors. Bivariate analysis also suggested that participants who screened positive for social anxiety disorder were significantly less likely to aspire to social jobs. Conclusions Employment-related factors likely impacting occupational functioning were significantly different between persons with and without social anxiety problems. Identifying these differences in employment barriers, skills, and job aspirations offer potentially important functional targets for psychosocial interventions aimed at social anxiety disorder and suggest the need for vocational service professionals to assess and address social anxiety among their clients. PMID:24733524

Internal Accountability and District Achievement: How Superintendents Affect Student Learning

ERIC Educational Resources Information Center

Hough, Kimberly L.

2014-01-01

This quantitative survey study was designed to determine whether superintendent accountability behaviors or agreement about accountability behaviors between superintendents and their subordinate central office administrators predicted district student achievement. Hierarchical multiple regression and analyses of covariance were employed,…

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.

Positive correlation of employment and psychological well-being for veterans with major abdominal surgery.

PubMed

Horner, David J; Wendel, Christopher S; Skeps, Raymond; Rawl, Susan M; Grant, Marcia; Schmidt, C Max; Ko, Clifford Y; Krouse, Robert S

2010-11-01

Intestinal stomas (ostomies) have been associated negatively with multiple aspects of health-related quality of life. This article examines the relationship between employment status and psychological well-being (PWB) in veterans who underwent major bowel procedures with or without ostomy. Veterans from 3 Veterans Affairs (VA) medical centers were surveyed using the City of Hope ostomy-specific questionnaire and the Short Form 36 item Veteran's version (SF-36V). Response rate was 48% (511 of 1,063). Employment and PWB relationship was assessed using multiple regression with age, income, SF-36V physical component summary (PCS), and employment status as independent variables. Employed veterans reported higher PWB compared with unemployed veterans (P = .003). Full-time workers also reported higher PWB than part-time or unemployed workers (P = .001). Ostomy was not an independent predictor of PWB. Employment among veterans after major abdominal surgery may have intrinsic value for PWB. Patients should be encouraged to return to work, or do volunteer work after recovery. Published by Elsevier Inc.

[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.

An Exploratory Study of Religion and Trust in Ghana

ERIC Educational Resources Information Center

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

2013-01-01

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

Musculoskeletal pain and re-employment among unemployed job seekers: a three-year follow-up study.

PubMed

Nwaru, Chioma A; Nygård, Clas-Håkan; Virtanen, Pekka

2016-07-08

Poor health is a potential risk factor for not finding employment among unemployed individuals. We investigated the associations between localized and multiple-site musculoskeletal pain and re-employment in a three-year follow-up of unemployed job seekers. Unemployed people (n = 539) from six localities in southern Finland who participated in various active labour market policy measures at baseline in 2002/2003 were recruited into a three-year health service intervention trial. A questionnaire was used to collect data on musculoskeletal health and background characteristics at baseline and on employment status at the end of the follow-up. We conducted a complete case (n = 284) and multiple imputation analyses using logistic regression to investigate the association between baseline musculoskeletal pain and re-employment after three years. Participants with severe pain in the lower back were less likely to become re-employed. This was independent of potential confounding variables. Pain in the hands/upper extremities, neck/shoulders, lower extremities, as well as multiple site were not determinants of re-employment. Our findings lend some support to the hypothesis that poor health can potentially cause health selection into employment. There is the need to disentangle health problems in order to clearly appreciate their putative impact on employment. This will allow for more targeted interventions for the unemployed.

Posttraumatic Stress Disorder Symptoms and Social and Occupational Functioning of People with Schizophrenia

PubMed Central

Ng, Lauren C.; Petruzzi, Liana J.; Greene, M. Claire; Mueser, Kim T.; Borba, Christina P.C.; Henderson, David C.

2016-01-01

This study sought to clarify the contribution of PTSD to interpersonal and occupational functioning in people with schizophrenia. Self-report questionnaires and semi-structured interviews were employed to evaluate PTSD and brain injury, positive symptoms, depression, substance abuse, occupational and social functioning, and intelligence. Multiple regressions assessed the relationship between predictors and functional impairment. PTSD symptoms were present in 76% of participants, with 12% of participants meeting diagnostic criteria for PTSD. Participants with PTSD had higher rates of depression and more severe positive symptoms. Results of multiple regressions indicated that PTSD symptoms were the only significant predictor of patient-rated interpersonal and occupational functioning. PTSD symptoms were not associated with interviewer-rated interpersonal or occupational functioning or employment. While more research is needed, screening and treatment for exposure to traumatic events and PTSD symptoms might be indicated for individuals with schizophrenia. Availability of PTSD assessment and evidence-based treatments for people with schizophrenia is a crucial and often unmet health service need. PMID:27105458

Contributions of sociodemographic factors to criminal behavior

PubMed Central

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

2016-01-01

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

Employment characteristics and socioeconomic factors associated with disparities in smoking abstinence and former smoking among U.S. workers.

PubMed

Fagan, Pebbles; Shavers, Vickie L; Lawrence, Deirdre; Gibson, James Todd; O'Connell, Mary E

2007-11-01

This study examines the associations among employment and socioeconomic factors and the outcomes, current smoking, cigarette abstinence and former smoking among adult U.S. workers ages 18-64 (n=288,813). Multivariate logistic regression was used to examine the associations among the variables using cross-sectional data from the 1998-1999 and 2001-2002 Tobacco Use Supplements to the Current Population Survey. Lower odds of current smoking was observed among part-time workers compared to those working variable hours and multiple job holders compared to persons holding one job. The self-employed, part-time workers and multiple job holders had higher odds of former smoking than comparison groups. Employment factors were not associated with short-term abstinence or 12-month abstinence from smoking, but income, education, marital status, and duration of smoking were associated with 12-month abstinence. These data suggest that while employment factors are associated with current and former smoking, socioeconomic factors are associated with long-term quitting.

Epidemiologic programs for computers and calculators. A microcomputer program for multiple logistic regression by unconditional and conditional maximum likelihood methods.

PubMed

Campos-Filho, N; Franco, E L

1989-02-01

A frequent procedure in matched case-control studies is to report results from the multivariate unmatched analyses if they do not differ substantially from the ones obtained after conditioning on the matching variables. Although conceptually simple, this rule requires that an extensive series of logistic regression models be evaluated by both the conditional and unconditional maximum likelihood methods. Most computer programs for logistic regression employ only one maximum likelihood method, which requires that the analyses be performed in separate steps. This paper describes a Pascal microcomputer (IBM PC) program that performs multiple logistic regression by both maximum likelihood estimation methods, which obviates the need for switching between programs to obtain relative risk estimates from both matched and unmatched analyses. The program calculates most standard statistics and allows factoring of categorical or continuous variables by two distinct methods of contrast. A built-in, descriptive statistics option allows the user to inspect the distribution of cases and controls across categories of any given variable.

The influence of coping styles on long-term employment in multiple sclerosis: A prospective study.

PubMed

Grytten, Nina; Skår, Anne Br; Aarseth, Jan Harald; Assmus, Jorg; Farbu, Elisabeth; Lode, Kirsten; Nyland, Harald I; Smedal, Tori; Myhr, Kjell Morten

2017-06-01

The aim was to investigate predictive values of coping styles, clinical and demographic factors on time to unemployment in patients diagnosed with multiple sclerosis (MS) during 1998-2002 in Norway. All patients ( N = 108) diagnosed with MS 1998-2002 in Hordaland and Rogaland counties, Western Norway, were invited to participate in the long-term follow-up study in 2002. Baseline recordings included disability scoring (Expanded Disability Status Scale (EDSS)), fatigue (Fatigue Severity Scale (FSS)), depression (Beck Depression Inventory (BDI)), and questionnaire assessing coping (the Dispositional Coping Styles Scale (COPE)). Logistic regression analysis was used to identify factors associated with unemployed at baseline, and Cox regression analysis to identify factors at baseline associated with time to unemployment during follow-up. In all, 41 (44%) were employed at baseline. After 13 years follow-up in 2015, mean disease duration of 22 years, 16 (17%) were still employed. Median time from baseline to unemployment was 6 years (±5). Older age at diagnosis, female gender, and depression were associated with patients being unemployed at baseline. Female gender, long disease duration, and denial as avoidant coping strategy at baseline predicted shorter time to unemployment. Avoidant coping style, female gender, and longer disease duration were associated with shorter time to unemployment. These factors should be considered when advising patients on MS and future employment.

On the relation between personality and job performance of airline pilots.

PubMed

Hormann, H J; Maschke, P

1996-01-01

The validity of a personality questionnaire for the prediction of job success of airline pilots is compared to validities of a simulator checkflight and of flying experience data. During selection, 274 pilots applying for employment with a European charter airline were examined with a multidimensional personality questionnaire (Temperature Structure Scales; TSS). Additionally, the applicants were graded in a simulator checkflight. On the basis of training records, the pilots were classified as performing at standard or below standard after about 3 years of employment in the hiring company. In a multiple-regression model, this dichotomous criterion for job success can be predicted with 73.8% accuracy through the simulator checkflight and flying experience prior to employment. By adding the personality questionnaire to the regression equation, the number of correct classifications increases to 79.3%. On average, successful pilots score substantially higher on interpersonal scales and lower on emotional scales of the TSS.

Computer Simulation of Human Behavior: Assessment of Creativity.

ERIC Educational Resources Information Center

Greene, John F.

The major purpose of this study is to further the development of procedures which minimize current limitations of creativity instruments, thus yielding a reliable and functional means for assessing creativity. Computerized content analysis and multiple regression are employed to simulate the creativity ratings of trained judges. The computerized…

Exploring Race Differences in Correlates of Seniors' Satisfaction with Undergraduate Education

ERIC Educational Resources Information Center

Einarson, Marne K.; Matier, Michael W.

2005-01-01

This study employed multiple linear regression and decision tree analysis to examine the correlates of overall satisfaction with undergraduate education for white, Asian American, Latino and African American seniors enrolled at 17 doctoral/research universities. Satisfaction with the overall quality of instruction and social involvement were the…

Exploring Race Differences in Correlates of Seniors' Satisfaction with Undergraduate Education

ERIC Educational Resources Information Center

Einarson, Marne K.; Matier, Michael W.

2004-01-01

This study employed multiple linear regression and decision tree analysis to examine the correlates of overall satisfaction with undergraduate education for white, Asian American, Hispanic and African American seniors enrolled at 17 research-extensive universities. Satisfaction with the overall quality of instruction and social involvement were…

Assessing Family Economic Status From Teacher Reports.

ERIC Educational Resources Information Center

Moskowitz, Joel M.; Hoepfner, Ralph

The utility of employing teacher reports about characteristics of students and their parents to assess family economic status was investigated using multiple regression analyses. The accuracy of teacher reports about parents' educational background was also explored, in addition to the effect of replacing missing data with logical, mean, or modal…

Rate and Predictors of Employment among Formerly Polysubstance Dependent Urban Individuals in Recovery

PubMed Central

Laudet, Alexandre B

2012-01-01

Employment is a key functioning index in addiction services and consistently emerges as a goal among persons in recovery. Research on employment in the addictions has focused on treatment populations and/or welfare recipients; little is known of employment rates or their predictors among persons in recovery. This study seeks to fill this gap, capitalizing on a sample (N = 311) of urban individuals at various stages of recovery. Fewer than half (44.5%) were employed; in logistic regressions, male gender and Caucasian race enhanced the odds of employment whereas having a comorbid chronic physical and/or mental health condition halved the odds. Implications center on the need to identify effective strategies to enhance employability among women and minorities, and for integrated care for persons with multiple chronic conditions. PMID:22873190

The Impact of School Community Partnerships on the Success of Elementary Schools

ERIC Educational Resources Information Center

Grady, Kevin Richard

2010-01-01

This study employed multiple regression modeling to examine the success of 63 California elementary schools in terms of (a) school-community social capital, (b) student academic performance, (c) student behavioral incident rate, and (d) teacher turnover rate with respect to the extent of school-community partnership programs. Also of interest to…

Ethnicity and Economic Well-Being: The Case of Ghana

ERIC Educational Resources Information Center

Addai, Isaac; Pokimica, Jelena

2010-01-01

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

Modeling Success: Using Preenrollment Data to Identify Academically At-Risk Students

ERIC Educational Resources Information Center

Gansemer-Topf, Ann M.; Compton, Jonathan; Wohlgemuth, Darin; Forbes, Greg; Ralston, Ekaterina

2015-01-01

Improving student success and degree completion is one of the core principles of strategic enrollment management. To address this principle, institutional data were used to develop a statistical model to identify academically at-risk students. The model employs multiple linear regression techniques to predict students at risk of earning below a…

Exact Interval Estimation, Power Calculation, and Sample Size Determination in Normal Correlation Analysis

ERIC Educational Resources Information Center

Shieh, Gwowen

2006-01-01

This paper considers the problem of analysis of correlation coefficients from a multivariate normal population. A unified theorem is derived for the regression model with normally distributed explanatory variables and the general results are employed to provide useful expressions for the distributions of simple, multiple, and partial-multiple…

Profiles of Supportive Alumni: Donors, Volunteers, and Those Who "Do It All"

ERIC Educational Resources Information Center

Weerts, David J.; Ronca, Justin M.

2007-01-01

In the competitive marketplace of higher education, college and university alumni are increasingly called on to support their institutions in multiple ways: political advocacy, volunteerism, and charitable giving. Drawing on alumni survey data gathered from a large research extensive university, we employ a multinomial logistic regression model to…

On the Misconception of Multicollinearity in Detection of Moderating Effects: Multicollinearity Is Not Always Detrimental

ERIC Educational Resources Information Center

Shieh, Gwowen

2010-01-01

Due to its extensive applicability and computational ease, moderated multiple regression (MMR) has been widely employed to analyze interaction effects between 2 continuous predictor variables. Accordingly, considerable attention has been drawn toward the supposed multicollinearity problem between predictor variables and their cross-product term.…

Sexual practices in Malaysia: determinants of sexual intercourse among unmarried youths.

PubMed

Zulkifli, S N; Low, W Y

2000-10-01

This paper describes findings on selected determinants of sexual intercourse among 468 unmarried adolescents from a survey in Malaysia. Data on respondents' background, sexual experience, contraceptive use, and sexual attitudes are provided. Based on multiple logistic regressions, factors significantly predictive of sexual experience are gender, employment, and sexual attitudes.

Students with Intellectual Disabilities: Predictors of Transition Outcomes

ERIC Educational Resources Information Center

Baer, Robert M.; Daviso, Alfred W., III; Flexer, Robert W.; Queen, Rachel McMahan; Meindl, Richard S.

2011-01-01

This study examined the outcomes of 409 students with mental retardation or multiple disabilities from 177 school districts in a Great Lakes state. These students with intellectual disabilities were interviewed at exit and 1 year following graduation. The authors developed and tested three regression models--two to predict full-time employment and…

The Prediction of Achievement and Time Spent in Instruction in a Self-Paced Individualized Course.

ERIC Educational Resources Information Center

Franklin, Thomas E.

Multiple linear regressions were employed to determine the relative contributions of cognitive and affective variables accounting for variance in college students' achievement and amount of time taken to complete a self-paced, individualized course. Study habits and attitudes (SSHA) made greater relative contributions to explaining total course…

Electronic Resource Expenditure and the Decline in Reference Transaction Statistics in Academic Libraries

ERIC Educational Resources Information Center

Dubnjakovic, Ana

2012-01-01

The current study investigates factors influencing increase in reference transactions in a typical week in academic libraries across the United States of America. Employing multiple regression analysis and general linear modeling, variables of interest from the "Academic Library Survey (ALS) 2006" survey (sample size 3960 academic libraries) were…

Modelling Student Satisfaction and Motivation in the Integrated Educational Environment: An Empirical study

ERIC Educational Resources Information Center

Stukalina, Yulia

2016-01-01

Purpose: The purpose of this paper is to explore some issues related to enhancing the quality of educational services provided by a university in the agenda of integrating quality assurance activities and strategic management procedures. Design/methodology/approach: Employing multiple regression analysis the author has examined some factors that…

A CNN Regression Approach for Real-Time 2D/3D Registration.

PubMed

Shun Miao; Wang, Z Jane; Rui Liao

2016-05-01

In this paper, we present a Convolutional Neural Network (CNN) regression approach to address the two major limitations of existing intensity-based 2-D/3-D registration technology: 1) slow computation and 2) small capture range. Different from optimization-based methods, which iteratively optimize the transformation parameters over a scalar-valued metric function representing the quality of the registration, the proposed method exploits the information embedded in the appearances of the digitally reconstructed radiograph and X-ray images, and employs CNN regressors to directly estimate the transformation parameters. An automatic feature extraction step is introduced to calculate 3-D pose-indexed features that are sensitive to the variables to be regressed while robust to other factors. The CNN regressors are then trained for local zones and applied in a hierarchical manner to break down the complex regression task into multiple simpler sub-tasks that can be learned separately. Weight sharing is furthermore employed in the CNN regression model to reduce the memory footprint. The proposed approach has been quantitatively evaluated on 3 potential clinical applications, demonstrating its significant advantage in providing highly accurate real-time 2-D/3-D registration with a significantly enlarged capture range when compared to intensity-based methods.

Rate and predictors of employment among formerly polysubstance dependent urban individuals in recovery.

PubMed

Laudet, Alexandre B

2012-01-01

Employment is a key functioning index in addiction services and consistently emerges as a goal among individuals in recovery. Research on the employment status in the addiction field has focused on treatment populations or welfare recipients; little is known of employment rates or their predictors among individuals in recovery. This study seeks to fill this gap, capitalizing on a sample (N = 311) of urban individuals at various stages of recovery. Fewer than half (44.5%) of participants were employed; in logistic regressions, male gender and Caucasian race enhanced the odds of employment, whereas having a comorbid chronic physical or mental health condition decreased the odds by half. Implications center on the need to identify effective strategies to enhance employability among women and minorities and for integrated care for individuals with multiple chronic conditions.

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 Prediction Model for Community Colleges Using Graduation Rate as the Performance Indicator

ERIC Educational Resources Information Center

Moosai, Susan

2010-01-01

In this thesis a prediction model using graduation rate as the performance indicator is obtained for community colleges for three cohort years, 2003, 2004, and 2005 in the states of California, Florida, and Michigan. Multiple Regression analysis, using an aggregate of seven predictor variables, was employed in determining this prediction model.…

The Counseling Opportunity Structure: Examining Correlates of Four-Year College-Going Rates

ERIC Educational Resources Information Center

Engberg, Mark E.; Gilbert, Aliza J.

2014-01-01

This study examines the relationships between the normative and resource dimensions of a high school counseling department and four-year college-going rates. Utilizing data from the High School Longitudinal Study of 2009 (HSLS: 09), we employ multiple regression and latent class analysis to identify salient factors related to the college-going…

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

ERIC Educational Resources Information Center

Maholchic-Nelson, Suzy

2010-01-01

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

Knowledge Systems and Value Chain Integration: The Case of Linseed Production in Ethiopia

ERIC Educational Resources Information Center

Chagwiza, Clarietta; Muradian, Roldan; Ruben, Ruerd

2017-01-01

Purpose: This study uses data from a sample of 150 oilseed farming households from Arsi Robe, Ethiopia, to assess the impact of different knowledge bases (education, training and experience) and their interactions on linseed productivity. Methodology: A multiple regression analysis was employed to assess the combined effect of the knowledge bases,…

Caring, employment, and quality of life: comparison of employed and nonemployed mothers of adults with intellectual disability.

PubMed

Chou, Yueh-Ching; Pu, Cheng-Yun; Kröger, Teppo; Fu, Li-yeh

2010-09-01

The effects of caregiving on mothers of adults with intellectual disability was examined by determining whether there are differences in quality of life and related factors between mothers with different employment status. Study participants were 302 working-age mothers who had adult children with intellectual disability based on the 2008 census survey on intellectual disability carried out in Hsinchu, City, Taiwan. Results revealed that nonemployed mothers are more likely to have a lower level of health status, including the WHOQOL Physical Health domain, than are mothers employed fulltime. Multiple regression analysis showed that mothers' quality of life was significantly determined by the availability of a person with whom they could share care work, family income, social support, and employment status.

[Predictors of employment intention for mentally disabled persons].

PubMed

Han, Sang-Sook; Han, Jeong Hye; Yun, Eun Kyoung

2008-08-01

This study was conducted to determine the predictors of employment intention for mentally disabled persons. Mentally disabled persons who had participated in rehabilitation programs in one of 16 mental health centers and 9 community rehabilitation centers located in Seoul and Kyunggi province were recruited for this study. A random sampling method was used and 414 respondents were used for final analysis. Data was analyzed by Pearson's correlation, and stepwise multiple regression using the SPSS Win 14.0. The predictors influencing employment intention of the mentally disabled person were observed as employment desire (beta=.48), guardian's expectation (beta=.26), professional's support (beta=.23), financial management (beta=.10), eating habits (beta=.07), and quality of life (beta=-.01). Six factors explained 61.1% of employment intention of mentally disabled persons. The employment intention of a mentally disabled person was influenced by employment desire, diet self-efficacy, guardian's expectation, professional's support, quality of life, financial management and eating habits.

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

PubMed

Moon, C

1987-07-01

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

Should I stay or should I go? A prospective investigation examining individual factors impacting employment status among individuals with multiple sclerosis (MS).

PubMed

Strober, Lauren B; Chiaravalloti, Nancy; DeLuca, John

2018-01-01

Rates of unemployment among individuals with multiple sclerosis (MS) are as high as 80%. While several factors for such high rates of unemployment have been identified, they do not account for the majority of the variance. This study examines person-specific factors such as personality and coping, which may better account for individuals leaving the workforce. Forty individuals with MS (20 considering reducing work hours or leaving the workforce and 20 remaining employed) were matched on age, gender, education, disease duration, and disease course, and administered a comprehensive survey of factors purported to be related to employment status. Based on multiple, logistic regression analyses certain disease factors and person-specific factors differentiate those who are considering leaving work or reducing work hours and those staying employed. In particular, those expressing the need to reduce work hours or leaving the workforce reported more fatigue, anxiety, depression, and use of behavioral disengagement as a means of coping. In contrast, those staying employed reported greater levels of extraversion, self-efficacy, and use of humor as a means of coping. Together, fatigue, use of humor, and use of behavioral disengagement as a means of coping were the most significant factors, accounting for 44% of the variance. Findings suggest that greater consideration be given to these factors and that interventions tailored to address these factors may assist individuals with MS staying employed and/or making appropriate accommodations.

[Impact of the labour market on vocational retraining centre participants' return to work: a study on employment agencies level].

PubMed

Hetzel, C; Flach, T; Schmidt, C

2012-08-01

This paper is aimed at identifying labour market factors impacting vocational retraining centre participants' return to work on Employment Agencies level and at comparing results to unemployed people's return to work (Social Code Book III). Databases are regional return to work rates of 2006 graduates, selected labour market indicators 2007, and the 2007 labour market classification of the Institute for Employment Research (IAB). The n = 75 Employment Agency districts where 74.5 % of the participants followed-up lived were analyzed using analyses of variance and multiple loglinear regression. Compared to the unemployment context (Social Code Book III), the impact of the labour market is much lower and less complex. In the multiple model, the regional unemployment rate and the regional tertiarization rate (size of the service sector) are found to be significant and superior to the IAB-classification. Hence, participants' return to work is less dependent on labour market conditions than unemployed people's return to work (Social Code Book III). © Georg Thieme Verlag KG Stuttgart · New York.

Factors Affecting Conservation Practice Behavior of CRP Participants in Alabama

Treesearch

Okwudili Onianwa; Gerald Wheelock; Shannon Hendrix

1999-01-01

This study examines the factors that affect conservation practice choices of CRP farmers in Alabama. From over 9,000 contracts enrolled in the state between 1986 and 1995, 594 were randomly selected for the study. A multiple-regression analysis was employed to analyze the data. Results indicate that education, ratio ofcropland in CRP, farm size, gender, prior crop...

Using regression equations built from summary data in the psychological assessment of the individual case: extension to multiple regression.

PubMed

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

2012-12-01

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 (a) not all psychologists are aware that regression equations can be built not only from raw data but also using only basic summary data for a sample, and (b) the computations involved are tedious and prone to error. In an attempt to overcome these barriers, Crawford and Garthwaite (2007) provided methods to build and apply simple linear regression models using summary statistics as data. In the present study, we extend this work to set out the steps required to build multiple regression models from sample summary statistics and the further steps required to compute the associated statistics for drawing inferences concerning an individual case. We also develop, describe, and make available a computer program that implements these methods. Although there are caveats associated with the use of the methods, these need to be balanced against pragmatic considerations and against the alternative of either entirely ignoring a pertinent data set or using it informally to provide a clinical "guesstimate." Upgraded versions of earlier programs for regression in the single case are also provided; these add the point and interval estimates of effect size developed in the present article.

Incentives and other factors associated with employee participation in health risk assessments.

PubMed

Taitel, Michael S; Haufle, Vincent; Heck, Debi; Loeppke, Ronald; Fetterolf, Donald

2008-08-01

Investigate factors associated with employee participation rates in health risk assessments. This cross-sectional study using multiple regression analyzed data from 124 employers with 882,275 eligible employees who completed 344,825 health and productivity assessments (HPAs). Incentive value and Communications and Organizational Commitment Level (Com/Org Level) were the strongest predictors of HPA completion rates. Employer size and a Gateway Model were also significant predictors. In addition, a correlation of variables showed other important relationships. To achieve a 50% HPA completion rate, employers with a low Com/Org Level will need an incentive value of approximately $120 whereas employers with a high Com/Org Level only need approximately $40--a difference of $80 dollars. This applied study offers empirical evidence to help employers increase their employees' participation in health risk assessments.

Multiple Traumatic Events and Psychological Distress : The South Africa Stress and Health Study

PubMed Central

Williams, Stacey L.; Williams, David R.; Stein, Dan J.; Seedat, Soraya; Jackson, Pamela B.; Moomal, Hashim

2011-01-01

Using nationally representative data from South Africa, we examine lifetime prevalence of traumas and multiple traumas (number of events). Employing multiple regression analysis, we study sociodemographic risk of trauma, and the association between trauma and distress. Results indicate most South Africans experience at least one traumatic event during their lives, with the majority reporting multiple. Consistent variation in risk is evident for gender and marital status but not other sociodemographics. Trauma is positively related to high distress, and findings also support a cumulative effect of trauma exposure. Individuals with the most traumas (6+) appear at five- times greater risk of high distress. This study highlights the importance of considering traumatic events in the context of other traumas in South Africa. PMID:17955545

Multiple traumatic events and psychological distress: the South Africa stress and health study.

PubMed

Williams, Stacey L; Williams, David R; Stein, Dan J; Seedat, Soraya; Jackson, Pamela B; Moomal, Hashim

2007-10-01

Using nationally representative data from South Africa, we examine lifetime prevalence of traumas and multiple traumas (number of events). Employing multiple regression analysis, the authors study the sociodemographic risk of trauma, and the association between trauma and distress. Results indicate most South Africans experience at least one traumatic event during their lives, with the majority reporting multiple. Consistent variation in risk is evident for gender and marital status, but not other sociodemographics. Trauma is positively related to high distress, and findings also support a cumulative effect of trauma exposure. Individuals with the most traumas (6+) appear at 5 times greater risk of high distress. This study highlights the importance of considering traumatic events in the context of other traumas in South Africa.

Employment program for patients with severe mental illness in Malaysia: a 3-month outcome.

PubMed

Wan Kasim, Syarifah Hafizah; Midin, Marhani; Abu Bakar, Abdul Kadir; Sidi, Hatta; Nik Jaafar, Nik Ruzyanei; Das, Srijit

2014-01-01

This study aimed to examine the rate and predictive factors of successful employment at 3 months upon enrolment into an employment program among patients with severe mental illness (SMI). A cross-sectional study using universal sampling technique was conducted on patients with SMI who completed a 3-month period of being employed at Hospital Permai, Malaysia. A total of 147 patients were approached and 126 were finally included in the statistical analyses. Successful employment was defined as the ability to work 40 or more hours per month. Factors significantly associated with successful employment from bivariate analyses were entered into a multiple logistic regression analysis to identify predictors of successful employment. The rate of successful employment at 3 months was 68.3% (n=81). Significant factors associated with successful employment from bivariate analyses were having past history of working, good family support, less number of psychiatric admissions, good compliance to medicine, good interest in work, living in hostel, being motivated to work, satisfied with the job or salary, getting a preferred job, being in competitive or supported employment and having higher than median scores of PANNS on the positive, negative and general psychopathology. Significant predictors of employment, from a logistic regression model were having good past history of working (p<0.021; OR 6.12; [95% CI 2.1-11.9]) and getting a preferred job (p<0.032; [OR 4.021; 95% CI 1.83-12.1]). Results showed a high employment rate among patients with SMI. Good past history of working and getting a preferred job were significant predictors of successful employment. Copyright © 2014 Elsevier Inc. All rights reserved.

Regression analysis for LED color detection of visual-MIMO system

NASA Astrophysics Data System (ADS)

Banik, Partha Pratim; Saha, Rappy; Kim, Ki-Doo

2018-04-01

Color detection from a light emitting diode (LED) array using a smartphone camera is very difficult in a visual multiple-input multiple-output (visual-MIMO) system. In this paper, we propose a method to determine the LED color using a smartphone camera by applying regression analysis. We employ a multivariate regression model to identify the LED color. After taking a picture of an LED array, we select the LED array region, and detect the LED using an image processing algorithm. We then apply the k-means clustering algorithm to determine the number of potential colors for feature extraction of each LED. Finally, we apply the multivariate regression model to predict the color of the transmitted LEDs. In this paper, we show our results for three types of environmental light condition: room environmental light, low environmental light (560 lux), and strong environmental light (2450 lux). We compare the results of our proposed algorithm from the analysis of training and test R-Square (%) values, percentage of closeness of transmitted and predicted colors, and we also mention about the number of distorted test data points from the analysis of distortion bar graph in CIE1931 color space.

A Study of the Effect of the Front-End Styling of Sport Utility Vehicles on Pedestrian Head Injuries

PubMed Central

Qin, Qin; Chen, Zheng; Bai, Zhonghao; Cao, Libo

2018-01-01

Background The number of sport utility vehicles (SUVs) on China market is continuously increasing. It is necessary to investigate the relationships between the front-end styling features of SUVs and head injuries at the styling design stage for improving the pedestrian protection performance and product development efficiency. Methods Styling feature parameters were extracted from the SUV side contour line. And simplified finite element models were established based on the 78 SUV side contour lines. Pedestrian headform impact simulations were performed and validated. The head injury criterion of 15 ms (HIC15) at four wrap-around distances was obtained. A multiple linear regression analysis method was employed to describe the relationships between the styling feature parameters and the HIC15 at each impact point. Results The relationship between the selected styling features and the HIC15 showed reasonable correlations, and the regression models and the selected independent variables showed statistical significance. Conclusions The regression equations obtained by multiple linear regression can be used to assess the performance of SUV styling in protecting pedestrians' heads and provide styling designers with technical guidance regarding their artistic creations.

Fishing in the Amazonian forest: a gendered social network puzzle

PubMed Central

Díaz-Reviriego, I.; Fernández-Llamazares, Á.; Howard, P.L; Molina, JL; Reyes-García, V

2016-01-01

We employ social network analysis (SNA) to describe the structure of subsistence fishing social networks and to explore the relation between fishers’ emic perceptions of fishing expertise and their position in networks. Participant observation and quantitative methods were employed among the Tsimane’ Amerindians of the Bolivian Amazonia. A multiple regression quadratic assignment procedure was used to explore the extent to which gender, kinship, and age homophilies influence the formation of fishing networks. Logistic regressions were performed to determine the association between the fishers’ expertise, their socio-demographic identities, and network centrality. We found that fishing networks are gendered and that there is a positive association between fishers’ expertise and centrality in networks, an association that is more striking for women than for men. We propose that a social network perspective broadens understanding of the relations that shape the intracultural distribution of fishing expertise as well as natural resource access and use. PMID:28479670

Fishing in the Amazonian forest: a gendered social network puzzle.

PubMed

Díaz-Reviriego, I; Fernández-Llamazares, Á; Howard, P L; Molina, J L; Reyes-García, V

2017-01-01

We employ social network analysis (SNA) to describe the structure of subsistence fishing social networks and to explore the relation between fishers' emic perceptions of fishing expertise and their position in networks. Participant observation and quantitative methods were employed among the Tsimane' Amerindians of the Bolivian Amazonia. A multiple regression quadratic assignment procedure was used to explore the extent to which gender, kinship, and age homophilies influence the formation of fishing networks. Logistic regressions were performed to determine the association between the fishers' expertise, their socio-demographic identities, and network centrality. We found that fishing networks are gendered and that there is a positive association between fishers' expertise and centrality in networks, an association that is more striking for women than for men. We propose that a social network perspective broadens understanding of the relations that shape the intracultural distribution of fishing expertise as well as natural resource access and use.

Application of third molar development and eruption models in estimating dental age in Malay sub-adults.

PubMed

Mohd Yusof, Mohd Yusmiaidil Putera; Cauwels, Rita; Deschepper, Ellen; Martens, Luc

2015-08-01

The third molar development (TMD) has been widely utilized as one of the radiographic method for dental age estimation. By using the same radiograph of the same individual, third molar eruption (TME) information can be incorporated to the TMD regression model. This study aims to evaluate the performance of dental age estimation in individual method models and the combined model (TMD and TME) based on the classic regressions of multiple linear and principal component analysis. A sample of 705 digital panoramic radiographs of Malay sub-adults aged between 14.1 and 23.8 years was collected. The techniques described by Gleiser and Hunt (modified by Kohler) and Olze were employed to stage the TMD and TME, respectively. The data was divided to develop three respective models based on the two regressions of multiple linear and principal component analysis. The trained models were then validated on the test sample and the accuracy of age prediction was compared between each model. The coefficient of determination (R²) and root mean square error (RMSE) were calculated. In both genders, adjusted R² yielded an increment in the linear regressions of combined model as compared to the individual models. The overall decrease in RMSE was detected in combined model as compared to TMD (0.03-0.06) and TME (0.2-0.8). In principal component regression, low value of adjusted R(2) and high RMSE except in male were exhibited in combined model. Dental age estimation is better predicted using combined model in multiple linear regression models. Copyright © 2015 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Factors Influencing the Completion of the GED in a Federal Correctional Setting a Multiple Regression Correlation-Predictive Study

ERIC Educational Resources Information Center

Akers, Kimberly

2013-01-01

Correctional education's primary goal is to reduce recidivism and increase employment among ex-offenders. The Bureau of Prison's practical goal in its mandatory GED program is to maximize the number of inmates obtaining the GED in a given time period. The purpose of this research is to model the number of instructional hours an inmate requires to…

Influences of Disciplinary Classroom Climate on High School Student Self-Efficacy and Mathematics Achievement: A Look at Gender and Racial-Ethnic Differences

ERIC Educational Resources Information Center

Cheema, Jehanzeb R.; Kitsantas, Anastasia

2014-01-01

The present study investigated the role of disciplinary climate in the classroom and student math self-efficacy on math achievement. The student part of the Program for International Student Assessment (PISA) 2003 survey containing 4,199 U.S. observations was employed in a weighted least squares nested multiple regression framework to predict math…

Workplace bullying a risk for permanent employees.

PubMed

Keuskamp, Dominic; Ziersch, Anna M; Baum, Fran E; Lamontagne, Anthony D

2012-04-01

We tested the hypothesis that the risk of experiencing workplace bullying was greater for those employed on casual contracts compared to permanent or ongoing employees. A cross-sectional population-based telephone survey was conducted in South Australia in 2009. Employment arrangements were classified by self-report into four categories: permanent, casual, fixed-term and self-employed. Self-report of workplace bullying was modelled using multiple logistic regression in relation to employment arrangement, controlling for sex, age, working hours, years in job, occupational skill level, marital status and a proxy for socioeconomic status. Workplace bullying was reported by 174 respondents (15.2%). Risk of workplace bullying was higher for being in a professional occupation, having a university education and being separated, divorced or widowed, but did not vary significantly by sex, age or job tenure. In adjusted multivariate logistic regression models, casual workers were significantly less likely than workers on permanent or fixed-term contracts to report bullying. Those separated, divorced or widowed had higher odds of reporting bullying than married, de facto or never-married workers. Contrary to expectation, workplace bullying was more often reported by permanent than casual employees. It may represent an exposure pathway not previously linked with the more idealised permanent employment arrangement. A finer understanding of psycho-social hazards across all employment arrangements is needed, with equal attention to the hazards associated with permanent as well as casual employment. © 2012 The Authors. ANZJPH © 2012 Public Health Association of Australia.

Attendance rates in a workplace predict subsequent outcome of employment-based reinforcement of cocaine abstinence in methadone patients.

PubMed

Donlin, Wendy D; Knealing, Todd W; Needham, Mick; Wong, Conrad J; Silverman, Kenneth

2008-01-01

This study assessed whether attendance rates in a workplace predicted subsequent outcome of employment-based reinforcement of cocaine abstinence. Unemployed adults in Baltimore methadone programs who used cocaine (N=111) could work in a workplace for 4 hr every weekday and earn $10.00 per hour in vouchers for 26 weeks. During an induction period, participants provided urine samples but could work independent of their urinalysis results. After the induction period, participants had to provide urinalysis evidence of cocaine abstinence to work and maintain maximum pay. A multiple regression analysis showed that induction period attendance was independently associated with urinalysis evidence of cocaine abstinence under the employment-based abstinence reinforcement contingency. Induction period attendance may measure the reinforcing value of employment and could be used to guide the improvement of employment-based abstinence reinforcement.

Optimized multiple linear mappings for single image super-resolution

NASA Astrophysics Data System (ADS)

Zhang, Kaibing; Li, Jie; Xiong, Zenggang; Liu, Xiuping; Gao, Xinbo

2017-12-01

Learning piecewise linear regression has been recognized as an effective way for example learning-based single image super-resolution (SR) in literature. In this paper, we employ an expectation-maximization (EM) algorithm to further improve the SR performance of our previous multiple linear mappings (MLM) based SR method. In the training stage, the proposed method starts with a set of linear regressors obtained by the MLM-based method, and then jointly optimizes the clustering results and the low- and high-resolution subdictionary pairs for regression functions by using the metric of the reconstruction errors. In the test stage, we select the optimal regressor for SR reconstruction by accumulating the reconstruction errors of m-nearest neighbors in the training set. Thorough experimental results carried on six publicly available datasets demonstrate that the proposed SR method can yield high-quality images with finer details and sharper edges in terms of both quantitative and perceptual image quality assessments.

Employment and absenteeism in working-age persons with multiple sclerosis.

PubMed

Salter, Amber; Thomas, Nina; Tyry, Tuula; Cutter, Gary; Marrie, Ruth Ann

2017-05-01

To better understand the impact of the clinical course of multiple sclerosis (MS) and disability on employment, absenteeism, and related factors. This study included respondents to the North American Research Committee on Multiple Sclerosis Registry spring 2015 update survey who were US or Canadian residents, aged 18-65 years and reported having relapsing-remitting MS (RRMS), secondary progressive MS (SPMS), or primary progressive MS (PPMS). The RRMS and SPMS participants were combined to form the relapsing-onset MS (RMS) group and compared with the PPMS group regarding employment status, absenteeism, and disability. Multivariable logistic regression was used to examine the relationship between employment-related outcomes and factors that may affect these relationships. Of the 8004 survey respondents, 5887 (73.6%) were 18-65 years of age. The PPMS group (n = 344) had a higher proportion of males and older mean age at the time of the survey and at time of diagnosis than the RMS group (n = 4829). Female sex, age, age at diagnosis, cognitive and hand function impairment, fatigue, higher disability levels, ≥3 comorbidities, and a diagnosis of PPMS were associated with not working. After adjustment for disability, the employed PPMS sub-group reported similar levels of absenteeism to the employed RMS sub-group. Limitations of the study include self-report of information and the possibility that participants may not fully represent the working-age MS population. In MS, employment status and absenteeism are negatively affected by disability, cognitive impairment, and fatigue. These findings underscore the need for therapies that prevent disability progression and other symptoms that negatively affect productivity in persons with MS to enable them to persist in the workforce.

The extraction of simple relationships in growth factor-specific multiple-input and multiple-output systems in cell-fate decisions by backward elimination PLS regression.

PubMed

Akimoto, Yuki; Yugi, Katsuyuki; Uda, Shinsuke; Kudo, Takamasa; Komori, Yasunori; Kubota, Hiroyuki; Kuroda, Shinya

2013-01-01

Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multiple-outputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells.

Socioeconomic status, labour market connection, and self-rated psychological health: the role of social capital and economic stress.

PubMed

Lindström, Martin; Ali, Sadiq M; Rosvall, Maria

2012-02-01

To investigate the association between socioeconomic status, unemployment and self-rated psychological health, taking economic stress and horizontal trust into account. The 2008 public health survey in Skåne is a cross-sectional postal questionnaire study with a 55% participation rate. A random sample was invited and 28,198 persons aged 18-80 participated. Logistic regression models were used to investigate associations between socioeconomic status by occupation (SES), labour market connection and self-rated psychological health (GHQ12). The multiple regression analyses included age, country of birth, education, economic stress and generalized (horizontal) trust. 13.8% of the men and 18.2% of the women had poor psychological health. Poor psychological health was more common among the young, among those born abroad, among those with lower education, with economic stress, and low horizontal trust. There were no significant differences between the employed and self-employed groups. However, the people who had retired early, the unemployed and those on long-term sick leave had significantly higher odds ratios of poor psychological health than higher non-manual employees throughout the analyses. There were no differences in psychological health between non-manual employees in higher positions and other employed and self-employed SES groups among men or women. In contrast, the early retired, the unemployed and the category on long-term sick leave had significantly higher odds ratios of poor psychological health among both men and women throughout the multiple analyses. Both economic stress and trust affected this association (i.e., lowered the odds ratios of poor psychological health), but affected by economic stress to a somewhat higher extent.

Employment of persons with spinal cord lesions injured more than 20 years ago.

PubMed

Lidal, Ingeborg Beate; Hjeltnes, Nils; Røislien, Jo; Stanghelle, Johan Kvalvik; Biering-Sørensen, Fin

2009-01-01

The primary objective was to study factors influencing post-injury employment and withdrawal from work in persons who sustained traumatic spinal cord injury (SCI) more than 20 years ago. A secondary objective was to study life satisfaction in the same patients. A cross-sectional study with retrospective data of 165 SCI-patients admitted to Sunnaas Rehabilitation Hospital 1961-1982. Multiple logistic regression was used to identify predictors for obtaining work post-injury. A Cox proportional hazards regression model was used to study factors influencing early withdrawal from work, i.e. time from injury until discontinuing employment. Sixty-five percent of the participants were employed at some point after the injury. Thirty-five percent still had work at the time of the survey. The odds of obtaining work after injury were higher in persons of younger age at injury, higher in males versus females, higher for persons with paraplegia versus tetraplegia, and for persons classified as Frankel D-E compared to a more severe SCI. Factors associated with shorter time from injury until discontinuing employment were higher age at injury, incidence of injury after 1975 versus before, and a history of pre-injury medical condition(s). Life satisfaction was better for currently employed participants. The study indicates a low employment-rate in persons with SCI, even several years after injury. From the results, we suggest more support, especially to persons of older age at injury and/or with a history of pre-injury medical condition(s), to help them to obtain work and sustain employed for more years after injury.

Disclosure of disease status among employed multiple sclerosis patients: association with negative work events and accommodations.

PubMed

Frndak, Seth E; Kordovski, Victoria M; Cookfair, Diane; Rodgers, Jonathan D; Weinstock-Guttman, Bianca; Benedict, Ralph H B

2015-02-01

Unemployment is common in multiple sclerosis (MS) and detrimental to quality of life. Studies suggest disclosure of diagnosis is an adaptive strategy for patients. However, the role of cognitive deficits and psychiatric symptoms in disclosure are not well studied. The goals of this paper were to (a) determine clinical factors most predictive of disclosure, and (b) measure the effects of disclosure on workplace problems and accommodations in employed patients. We studied two overlapping cohorts: a cross-sectional sample (n = 143) to determine outcomes associated with disclosure, and a longitudinal sample (n = 103) compared at four time points over one year on reported problems and accommodations. A case study of six patients, disclosing during monitoring, was also included. Disclosure was associated with greater physical disability but not cognitive impairment. Logistic regression predicting disclosure status retained physical disability, accommodations and years of employment (p < 0.0001). Disclosed patients reported more work problems and accommodations over time. The case study revealed that reasons for disclosing are multifaceted, including connection to employer, decreased mobility and problems at work. Although cognitive impairment is linked to unemployment, it does not appear to inform disclosure decisions. Early disclosure may help maintain employment if followed by appropriate accommodations. © The Author(s), 2014.

Simple to complex modeling of breathing volume using a motion sensor.

PubMed

John, Dinesh; Staudenmayer, John; Freedson, Patty

2013-06-01

To compare simple and complex modeling techniques to estimate categories of low, medium, and high ventilation (VE) from ActiGraph™ activity counts. Vertical axis ActiGraph™ GT1M activity counts, oxygen consumption and VE were measured during treadmill walking and running, sports, household chores and labor-intensive employment activities. Categories of low (<19.3 l/min), medium (19.3 to 35.4 l/min) and high (>35.4 l/min) VEs were derived from activity intensity classifications (light <2.9 METs, moderate 3.0 to 5.9 METs and vigorous >6.0 METs). We examined the accuracy of two simple techniques (multiple regression and activity count cut-point analyses) and one complex (random forest technique) modeling technique in predicting VE from activity counts. Prediction accuracy of the complex random forest technique was marginally better than the simple multiple regression method. Both techniques accurately predicted VE categories almost 80% of the time. The multiple regression and random forest techniques were more accurate (85 to 88%) in predicting medium VE. Both techniques predicted the high VE (70 to 73%) with greater accuracy than low VE (57 to 60%). Actigraph™ cut-points for light, medium and high VEs were <1381, 1381 to 3660 and >3660 cpm. There were minor differences in prediction accuracy between the multiple regression and the random forest technique. This study provides methods to objectively estimate VE categories using activity monitors that can easily be deployed in the field. Objective estimates of VE should provide a better understanding of the dose-response relationship between internal exposure to pollutants and disease. Copyright © 2013 Elsevier B.V. All rights reserved.

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

USGS Publications Warehouse

Lee, L.; Helsel, D.

2005-01-01

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

Factors associated with active commuting to work among women.

PubMed

Bopp, Melissa; Child, Stephanie; Campbell, Matthew

2014-01-01

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

Contribution of neurocognition to 18-month employment outcomes in first-episode psychosis.

PubMed

Karambelas, George J; Cotton, Sue M; Farhall, John; Killackey, Eóin; Allott, Kelly A

2017-10-27

To examine whether baseline neurocognition predicts vocational outcomes over 18 months in patients with first-episode psychosis enrolled in a randomized controlled trial of Individual Placement and Support or treatment as usual. One-hundred and thirty-four first-episode psychosis participants completed an extensive neurocognitive battery. Principal axis factor analysis using PROMAX rotation was used to determine the underlying structure of the battery. Setwise (hierarchical) multiple linear and logistic regressions were used to examine predictors of (1) total hours employed over 18 months and (2) employment status, respectively. Neurocognition factors were entered in the models after accounting for age, gender, premorbid IQ, negative symptoms, treatment group allocation and employment status at baseline. Five neurocognitive factors were extracted: (1) processing speed, (2) verbal learning and memory, (3) knowledge and reasoning, (4) attention and working memory and (5) visual organization and memory. Employment status over 18 months was not significantly predicted by any of the predictors in the final model. Total hours employed over 18 months were significantly predicted by gender (P = .027), negative symptoms (P = .032) and verbal learning and memory (P = .040). Every step of the regression model was a significant predictor of total hours worked overall (final model: P = .013). Verbal learning and memory, negative symptoms and gender were implicated in duration of employment in first-episode psychosis. The other neurocognitive domains did not significantly contribute to the prediction of vocational outcomes over 18 months. Interventions targeting verbal memory may improve vocational outcomes in early psychosis. © 2017 John Wiley & Sons Australia, Ltd.

Measurements of respiratory illness among construction painters.

PubMed

White, M C; Baker, E L

1988-08-01

The prevalence of different measurements of respiratory illness among construction painters was examined and the relation between respiratory illness and employment as a painter assessed in a cross sectional study of current male members of two local affiliates of a large international union of painters. Respiratory illness was measured by questionnaire and spirometry. Longer employment as a painter was associated with increased prevalence of chronic obstructive disease and an interactive effect was observed for smoking and duration of employment as a painter. Multiple regression analysis showed a significant association between years worked as a painter and a decrement in FEV1 equal to about 11 ml for each year worked. This association was larger among painters who had smoked. The prevalence of chronic bronchitis was significantly associated with increased use of spray application methods.

[A Correlational Study of the Recovery Process in Patients With Mental Illness].

PubMed

Huang, Yao-Hui; Lin, Yao-Yu; Lee, Shih-Kai; Lee, Ming-Feng; Lin, Ching-Lan Esther

2018-04-01

The ideology of recovery addresses the autonomy of patients with mental illness and their ability to reconstruct a normal life. Empirical knowledge of this process of recovery and related factors remains unclear. To assess the process of recovery and related factors in patients with mental illness. This cross-sectional, correlational study was conducted on a convenience sample in a psychiatric hospital. Two-hundred and fifty patients with mental illness were recruited and were assessed using 3 instruments: Questionnaire about the Process of Recovery (QPR), Perceived Psychiatric Stigma Scale (PPSS), and Personal and Social Performance Scale (PSP). Data were analyzed using descriptive statistics, χ 2 , analysis of variance, and multiple linear regression analysis. Most of the participants were male, middle-aged, unmarried, educated to the senior high school level, employed, receiving home-care treatment, and diagnosed with schizophrenia. Those who were unemployed, living in a community rehabilitative house, and living in the community, respectively, earned relatively higher recovery scores (p < .05). The total scores of QPR and the 3 subscales were negatively correlated with PPSS (p < .01) and positively correlated with PSPS (p < .01; p < .05). Multiple regression analysis indicated that the factors of education, employment, having received community rehabilitative models, and stigma, respectively, significantly explained the recovery capacity of patients with mental illness. Community psychiatric nurses should provide care to help employed patients adapt to stresses in the workplace, strengthen their stigma-coping strategies, and promote public awareness of mental health issues by increasing public knowledge and acceptance of mental illness in order to minimize patient-perceived stigma and facilitate their recovery.

Genetic and Environmental Etiologies of Reading Difficulties: DeFries-Fulker Analysis of Reading Performance Data from Twin Pairs and Their Non-Twin Siblings

ERIC Educational Resources Information Center

Astrom, Raven L.; Wadsworth, Sally J.; Olson, Richard K.; Willcutt, Erik G.; DeFries, John C.

2012-01-01

Reading performance data from 254 pairs of identical (MZ) and 420 pairs of fraternal (DZ) twins, 8.0 to 20.0 years of age, were subjected to multiple regression analyses. An extension of the DeFries-Fulker (DF) analysis (DeFries & Fulker, 1985, 1988) that facilitated inclusion of data from 303 of their nontwin siblings was employed. In addition to…

Markov chains and semi-Markov models in time-to-event analysis.

PubMed

Abner, Erin L; Charnigo, Richard J; Kryscio, Richard J

2013-10-25

A variety of statistical methods are available to investigators for analysis of time-to-event data, often referred to as survival analysis. Kaplan-Meier estimation and Cox proportional hazards regression are commonly employed tools but are not appropriate for all studies, particularly in the presence of competing risks and when multiple or recurrent outcomes are of interest. Markov chain models can accommodate censored data, competing risks (informative censoring), multiple outcomes, recurrent outcomes, frailty, and non-constant survival probabilities. Markov chain models, though often overlooked by investigators in time-to-event analysis, have long been used in clinical studies and have widespread application in other fields.

Markov chains and semi-Markov models in time-to-event analysis

PubMed Central

Abner, Erin L.; Charnigo, Richard J.; Kryscio, Richard J.

2014-01-01

A variety of statistical methods are available to investigators for analysis of time-to-event data, often referred to as survival analysis. Kaplan-Meier estimation and Cox proportional hazards regression are commonly employed tools but are not appropriate for all studies, particularly in the presence of competing risks and when multiple or recurrent outcomes are of interest. Markov chain models can accommodate censored data, competing risks (informative censoring), multiple outcomes, recurrent outcomes, frailty, and non-constant survival probabilities. Markov chain models, though often overlooked by investigators in time-to-event analysis, have long been used in clinical studies and have widespread application in other fields. PMID:24818062

Obsessional personality features in employed Japanese adults with a lifetime history of depression: assessment by the Munich Personality Test (MPT).

PubMed

Sakado, K; Sakado, M; Seki, T; Kuwabara, H; Kojima, M; Sato, T; Someya, T

2001-06-01

Although a number of studies have reported on the association between obsessional personality features as measured by the Munich Personality Test (MPT) "Rigidity" scale and depression, there has been no examination of these relationships in a non-clinical sample. The dimensional scores on the MPT were compared between subjects with and without lifetime depression, using a sample of employed Japanese adults. The odds ratio for suffering from lifetime depression was estimated by multiple logistic regression analysis. To diagnose a lifetime history of depression, the Inventory to Diagnose Depression, Lifetime version (IDDL) was used. The subjects with lifetime depression scored significantly higher on the "Rigidity" scale than the subjects without lifetime depression. In our logistic regression analysis, three risk factors were identified as each independently increasing a person's risk for suffering from lifetime depression: higher levels of "Rigidity", being of the female gender, and suffering from current depressive symptoms. The MPT "Rigidity" scale is a sensitive measure of personality features that occur with depression.

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

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

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

Estimating standard errors in feature network models.

PubMed

Frank, Laurence E; Heiser, Willem J

2007-05-01

Feature network models are graphical structures that represent proximity data in a discrete space while using the same formalism that is the basis of least squares methods employed in multidimensional scaling. Existing methods to derive a network model from empirical data only give the best-fitting network and yield no standard errors for the parameter estimates. The additivity properties of networks make it possible to consider the model as a univariate (multiple) linear regression problem with positivity restrictions on the parameters. In the present study, both theoretical and empirical standard errors are obtained for the constrained regression parameters of a network model with known features. The performance of both types of standard error is evaluated using Monte Carlo techniques.

Digital literacy of youth and young adults with intellectual disability predicted by support needs and social maturity.

PubMed

Seok, Soonhwa; DaCosta, Boaventura

2017-01-01

This study investigated relationships between digital propensity and support needs as well as predictors of digital propensity in the context of support intensity, age, gender, and social maturity. A total of 118 special education teachers rated the support intensity, digital propensity, and social maturity of 352 students with intellectual disability. Leveraging the Digital Propensity Index, Supports Intensity Scale, and the Social Maturity Scale, descriptive statistics, correlations, multiple regressions, and regression analyses were employed. The findings revealed significant relationships between digital propensity and support needs. In addition, significant predictors of digital propensity were found with regard to support intensity, age, gender, and social maturity.

Brain MRI lesions and atrophy are associated with employment status in patients with multiple sclerosis.

PubMed

Tauhid, Shahamat; Chu, Renxin; Sasane, Rahul; Glanz, Bonnie I; Neema, Mohit; Miller, Jennifer R; Kim, Gloria; Signorovitch, James E; Healy, Brian C; Chitnis, Tanuja; Weiner, Howard L; Bakshi, Rohit

2015-11-01

Multiple sclerosis (MS) commonly affects occupational function. We investigated the link between brain MRI and employment status. Patients with MS (n = 100) completed a Work Productivity and Activity Impairment (WPAI) (general health version) survey measuring employment status, absenteeism, presenteeism, and overall work and daily activity impairment. Patients "working for pay" were considered employed; "temporarily not working but looking for work," "not working or looking for work due to age," and "not working or looking for work due to disability" were considered not employed. Brain MRI T1 hypointense (T1LV) and T2 hyperintense (T2LV) lesion volumes were quantified. To assess lesional destructive capability, we calculated each subject's ratio of T1LV to T2LV (T1/T2). Normalized brain parenchymal volume (BPV) assessed brain atrophy. The mean (SD) age was 45.5 (9.7) years; disease duration was 12.1 (8.1) years; 75 % were women, 76 % were relapsing-remitting, and 76 % were employed. T1LV, T1/T2, Expanded Disability Status Scale (EDSS) scores, and activity impairment were lower and BPV was higher in the employed vs. not employed group (Wilcoxon tests, p < 0.05). Age, disease duration, MS clinical subtype, and T2LV did not differ between groups (p > 0.05). In multivariable logistic regression modeling, adjusting for age, sex, and disease duration, higher T1LV predicted a lower chance of employment (p < 0.05). Pearson correlations showed that EDSS was associated with activity impairment (p < 0.05). Disease duration, age, and MRI measures were not correlated with activity impairment or other WPAI outcomes (p > 0.05). We report a link between brain atrophy and lesions, particularly lesions with destructive potential, to MS employment status.

Epidemiologic Evaluation of Measurement Data in the Presence of Detection Limits

PubMed Central

Lubin, Jay H.; Colt, Joanne S.; Camann, David; Davis, Scott; Cerhan, James R.; Severson, Richard K.; Bernstein, Leslie; Hartge, Patricia

2004-01-01

Quantitative measurements of environmental factors greatly improve the quality of epidemiologic studies but can pose challenges because of the presence of upper or lower detection limits or interfering compounds, which do not allow for precise measured values. We consider the regression of an environmental measurement (dependent variable) on several covariates (independent variables). Various strategies are commonly employed to impute values for interval-measured data, including assignment of one-half the detection limit to nondetected values or of “fill-in” values randomly selected from an appropriate distribution. On the basis of a limited simulation study, we found that the former approach can be biased unless the percentage of measurements below detection limits is small (5–10%). The fill-in approach generally produces unbiased parameter estimates but may produce biased variance estimates and thereby distort inference when 30% or more of the data are below detection limits. Truncated data methods (e.g., Tobit regression) and multiple imputation offer two unbiased approaches for analyzing measurement data with detection limits. If interest resides solely on regression parameters, then Tobit regression can be used. If individualized values for measurements below detection limits are needed for additional analysis, such as relative risk regression or graphical display, then multiple imputation produces unbiased estimates and nominal confidence intervals unless the proportion of missing data is extreme. We illustrate various approaches using measurements of pesticide residues in carpet dust in control subjects from a case–control study of non-Hodgkin lymphoma. PMID:15579415

Logistic Stick-Breaking Process

PubMed Central

Ren, Lu; Du, Lan; Carin, Lawrence; Dunson, David B.

2013-01-01

A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are more likely to be clustered together. The sticks in the LSBP are realized via multiple logistic regression functions, with shrinkage priors employed to favor contiguous and spatially localized segments. The LSBP is also extended for the simultaneous processing of multiple data sets, yielding a hierarchical logistic stick-breaking process (H-LSBP). The model parameters (atoms) within the H-LSBP are shared across the multiple learning tasks. Efficient variational Bayesian inference is derived, and comparisons are made to related techniques in the literature. Experimental analysis is performed for audio waveforms and images, and it is demonstrated that for segmentation applications the LSBP yields generally homogeneous segments with sharp boundaries. PMID:25258593

An Application of Robust Method in Multiple Linear Regression Model toward Credit Card Debt

NASA Astrophysics Data System (ADS)

Amira Azmi, Nur; Saifullah Rusiman, Mohd; Khalid, Kamil; Roslan, Rozaini; Sufahani, Suliadi; Mohamad, Mahathir; Salleh, Rohayu Mohd; Hamzah, Nur Shamsidah Amir

2018-04-01

Credit card is a convenient alternative replaced cash or cheque, and it is essential component for electronic and internet commerce. In this study, the researchers attempt to determine the relationship and significance variables between credit card debt and demographic variables such as age, household income, education level, years with current employer, years at current address, debt to income ratio and other debt. The provided data covers 850 customers information. There are three methods that applied to the credit card debt data which are multiple linear regression (MLR) models, MLR models with least quartile difference (LQD) method and MLR models with mean absolute deviation method. After comparing among three methods, it is found that MLR model with LQD method became the best model with the lowest value of mean square error (MSE). According to the final model, it shows that the years with current employer, years at current address, household income in thousands and debt to income ratio are positively associated with the amount of credit debt. Meanwhile variables for age, level of education and other debt are negatively associated with amount of credit debt. This study may serve as a reference for the bank company by using robust methods, so that they could better understand their options and choice that is best aligned with their goals for inference regarding to the credit card debt.

The Clinical and Occupational Correlates of Work Productivity Loss Among Employed Patients With Depression

PubMed Central

Lerner, Debra; Adler, David A.; Chang, Hong; Berndt, Ernst R.; Irish, Julie T.; Lapitsky, Leueen; Hood, Maggie Y.; Reed, John; Rogers, William H.

2014-01-01

Employers who are developing strategies to reduce health-related productivity loss may benefit from aiming their interventions at the employees who need them most. We determined whether depression’s negative productivity impact varied with the type of work employees performed. Subjects (246 with depression and 143 controls) answered the Work Limitations Questionnaire and additional work questions. Occupational requirements were measured objectively. In multiple regression analyses, productivity was most influenced by depression severity (P < 0.01 in 5/5 models). However, certain occupations also significantly increased employee vulnerability to productivity loss. Losses increased when employees had occupations requiring proficiency in decision-making and communication and/or frequent customer contact (P < 0.05 in 3/5 models). The Work Limitations Questionnaire can help employers to reduce productivity loss by identifying health and productivity improvement priorities. PMID:15194895

Partial Least Squares with Structured Output for Modelling the Metabolomics Data Obtained from Complex Experimental Designs: A Study into the Y-Block Coding.

PubMed

Xu, Yun; Muhamadali, Howbeer; Sayqal, Ali; Dixon, Neil; Goodacre, Royston

2016-10-28

Partial least squares (PLS) is one of the most commonly used supervised modelling approaches for analysing multivariate metabolomics data. PLS is typically employed as either a regression model (PLS-R) or a classification model (PLS-DA). However, in metabolomics studies it is common to investigate multiple, potentially interacting, factors simultaneously following a specific experimental design. Such data often cannot be considered as a "pure" regression or a classification problem. Nevertheless, these data have often still been treated as a regression or classification problem and this could lead to ambiguous results. In this study, we investigated the feasibility of designing a hybrid target matrix Y that better reflects the experimental design than simple regression or binary class membership coding commonly used in PLS modelling. The new design of Y coding was based on the same principle used by structural modelling in machine learning techniques. Two real metabolomics datasets were used as examples to illustrate how the new Y coding can improve the interpretability of the PLS model compared to classic regression/classification coding.

Predictive value of grade point average (GPA), Medical College Admission Test (MCAT), internal examinations (Block) and National Board of Medical Examiners (NBME) scores on Medical Council of Canada qualifying examination part I (MCCQE-1) scores.

PubMed

Roy, Banibrata; Ripstein, Ira; Perry, Kyle; Cohen, Barry

2016-01-01

To determine whether the pre-medical Grade Point Average (GPA), Medical College Admission Test (MCAT), Internal examinations (Block) and National Board of Medical Examiners (NBME) scores are correlated with and predict the Medical Council of Canada Qualifying Examination Part I (MCCQE-1) scores. Data from 392 admitted students in the graduating classes of 2010-2013 at University of Manitoba (UofM), College of Medicine was considered. Pearson's correlation to assess the strength of the relationship, multiple linear regression to estimate MCCQE-1 score and stepwise linear regression to investigate the amount of variance were employed. Complete data from 367 (94%) students were studied. The MCCQE-1 had a moderate-to-large positive correlation with NBME scores and Block scores but a low correlation with GPA and MCAT scores. The multiple linear regression model gives a good estimate of the MCCQE-1 (R2 =0.604). Stepwise regression analysis demonstrated that 59.2% of the variation in the MCCQE-1 was accounted for by the NBME, but only 1.9% by the Block exams, and negligible variation came from the GPA and the MCAT. Amongst all the examinations used at UofM, the NBME is most closely correlated with MCCQE-1.

[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.

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

PubMed Central

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

2014-01-01

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

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

PubMed

Beckstead, Jason W

2012-03-30

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 strategy to isolate, examine, and remove suppression effects has been offered. In this article such an approach, rooted in confirmatory factor analysis theory and employing matrix algebra, is developed. Suppression is viewed as the result of criterion-irrelevant variance operating among predictors. Decomposition of predictor variables into criterion-relevant and criterion-irrelevant components using structural equation modeling permits derivation of regression weights with the effects of criterion-irrelevant variance omitted. Three examples with data from applied research are used to illustrate the approach: the first assesses child and parent characteristics to explain why some parents of children with obsessive-compulsive disorder accommodate their child's compulsions more so than do others, the second examines various dimensions of personal health to explain individual differences in global quality of life among patients following heart surgery, and the third deals with quantifying the relative importance of various aptitudes for explaining academic performance in a sample of nursing students. The approach is offered as an analytic tool for investigators interested in understanding predictor-criterion relationships when complex patterns of intercorrelation among predictors are present and is shown to augment dominance analysis.

Adolescent gambling and impulsivity: Does employment during high school moderate the association?

PubMed

Canale, Natale; Scacchi, Luca; Griffiths, Mark D

2016-09-01

The aim of the present study was to examine the potential moderating relationships between adolescent gambling and impulsivity traits (negative urgency, positive urgency, lack of premeditation, lack of perseverance and sensation seeking) with employment status. High-school students (N=400; 69% male; mean age=18.35years; SD=1.16; past year gamblers) were surveyed to provide data on impulsivity and employment. Multiple linear regression analysis was applied to examine associations with gambling and related problems. Positive urgency was associated with stronger scores of both gambling frequency and problem gambling. Students in employment had substantially higher frequency of gambling and greater problem gambling. Moreover, the combination of having a job and low perseverance was associated with a particularly high frequency on gambling. These findings further support the importance of positive urgency and employment status in adolescent gambling. The study highlights unique moderating relationship between gambling and lack of perseverance with employment status. Youth with a low perseverance and having a job may have particular need for interventions to reduce gambling. Copyright © 2016 Elsevier Ltd. All rights reserved.

Psychological distress in Canada: the role of employment and reasons of non-employment.

PubMed

Marchand, Alain; Drapeau, Aline; Beaulieu-Prévost, Dominic

2012-11-01

This study investigated variations in psychological distress in a large sample of the Canadian population according to employment status, occupation, work organization conditions, reasons for non-employment, stress and support outside the work environment, family situation and individual characteristics. Data came from cycle 4 (2000-1) of the Canadian National Population Health Survey conducted by Statistics Canada. Multiple regression analyses, adjusted for the family situation, the level of support from the social network and the individual characteristics, were carried out on a sample of 7258 individuals aged from 18 to 65 years. Occupation, social support at work, age, self-esteem, presence of children aged five and under and social support outside of the workplace were associated with lower levels of psychological distress, while permanent and temporary disability, psychological demands in the workplace, job insecurity, female gender, and stressful financial, marital and parental situations were related to higher levels of psychological distress. Findings from this study suggest that, in terms of psychological distress, having a job is not always better than non-employment, and that specific non-employment situations associate differently with psychological distress.

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.

Workplace Congruence and Occupational Outcomes among Social Service Workers.

PubMed

Graham, John R; Shier, Micheal L; Nicholas, David

2016-06-01

Workplace expectations reflect an important consideration in employee experience. A higher prevalence of workplace congruence between worker and employer expectations has been associated with higher levels of productivity and overall workplace satisfaction across multiple occupational groups. Little research has investigated the relationship between workplace congruence and occupational health outcomes among social service workers. This study sought to better understand the extent to which occupational congruence contributes to occupational outcomes by surveying unionised social service workers ( n = 674) employed with the Government of Alberta, Canada. Multiple regression analysis shows that greater congruence between workplace and worker expectations around workloads, workplace values and the quality of the work environment significantly: (i) decreases symptoms related to distress and secondary traumatic stress; (ii) decreases intentions to leave; and (iii) increases overall life satisfaction. The findings provide some evidence of areas within the workplace of large government run social welfare programmes that can be better aligned to worker expectations to improve occupational outcomes among social service workers.

Workplace Congruence and Occupational Outcomes among Social Service Workers

PubMed Central

Graham, John R.; Shier, Micheal L.; Nicholas, David

2016-01-01

Workplace expectations reflect an important consideration in employee experience. A higher prevalence of workplace congruence between worker and employer expectations has been associated with higher levels of productivity and overall workplace satisfaction across multiple occupational groups. Little research has investigated the relationship between workplace congruence and occupational health outcomes among social service workers. This study sought to better understand the extent to which occupational congruence contributes to occupational outcomes by surveying unionised social service workers (n = 674) employed with the Government of Alberta, Canada. Multiple regression analysis shows that greater congruence between workplace and worker expectations around workloads, workplace values and the quality of the work environment significantly: (i) decreases symptoms related to distress and secondary traumatic stress; (ii) decreases intentions to leave; and (iii) increases overall life satisfaction. The findings provide some evidence of areas within the workplace of large government run social welfare programmes that can be better aligned to worker expectations to improve occupational outcomes among social service workers. PMID:27559216

Remote-sensing data processing with the multivariate regression analysis method for iron mineral resource potential mapping: a case study in the Sarvian area, central Iran

NASA Astrophysics Data System (ADS)

Mansouri, Edris; Feizi, Faranak; Jafari Rad, Alireza; Arian, Mehran

2018-03-01

This paper uses multivariate regression to create a mathematical model for iron skarn exploration in the Sarvian area, central Iran, using multivariate regression for mineral prospectivity mapping (MPM). The main target of this paper is to apply multivariate regression analysis (as an MPM method) to map iron outcrops in the northeastern part of the study area in order to discover new iron deposits in other parts of the study area. Two types of multivariate regression models using two linear equations were employed to discover new mineral deposits. This method is one of the reliable methods for processing satellite images. ASTER satellite images (14 bands) were used as unique independent variables (UIVs), and iron outcrops were mapped as dependent variables for MPM. According to the results of the probability value (p value), coefficient of determination value (R2) and adjusted determination coefficient (Radj2), the second regression model (which consistent of multiple UIVs) fitted better than other models. The accuracy of the model was confirmed by iron outcrops map and geological observation. Based on field observation, iron mineralization occurs at the contact of limestone and intrusive rocks (skarn type).

GLOBALLY ADAPTIVE QUANTILE REGRESSION WITH ULTRA-HIGH DIMENSIONAL DATA

PubMed Central

Zheng, Qi; Peng, Limin; He, Xuming

2015-01-01

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

[Multiple roles and health among Korean women].

PubMed

Cho, Su-Jin; Jang, Soong-Nang; Cho, Sung-Il

2008-09-01

Most studies about multiple roles and women's health suggested that combining with paid job, being married and having children was more likely to improve health status than in case of single or traditional roles. We investigated whether there was better health outcome in multiple roles among Korean women coinciding with previous studies of other nations. Data were from the 2005 Korea National Health & Nutritional Examination Survey, a subsample of women aged 25-59 years (N=2,943). Health status was assessed for self-rated poor health, perceived stress and depression, respectively based on one questionnaire item. The age-standardized prevalence of all health outcomes were calculated by role categories and socioeconomic status. Multiple logistic regression was used to assess the association of self rated health, perceived stress, and depression with multiple roles adjusted for age, education, household income, number of children and age of children. Having multiple roles with working role was not associated with better health and psychological wellbeing. Compared to those with traditional roles, employed women more frequently experienced perceived stress, with marital and/or parental roles. Non-working single mothers suffered depression more often than women with traditional roles or other role occupancy. Socioeconomic status indicators were potent independent correlates of self-rated health and perceived stress. Employment of women with other roles did not confer additional health benefit to traditional family responsibility. Juggling of work and family responsibility appeared more stressful than traditional unemployed parental and marital role in Korean women.

Parenting styles and alcohol consumption among Brazilian adolescents.

PubMed

Paiva, Fernando Santana; Bastos, Ronaldo Rocha; Ronzani, Telmo Mota

2012-10-01

This study evaluates the correlation between alcohol consumption in adolescence and parenting styles of socialization among Brazilian adolescents. The sample was composed of 273 adolescents, 58% whom were males. Instruments were: 1) Sociodemographic Questionnaire; 2) Demand and Responsiveness Scales; 3) Drug Use Screening Inventory (DUSI). Study analyses employed multiple correspondence analysis and logistic regression. Maternal, but not paternal, authoritative and authoritarian parenting styles were directly related to adolescent alcohol intake. The style that mothers use to interact with their children may influence uptake of high-risk behaviors.

Return-to-work of sick-listed workers without an employment contract--what works?

PubMed

Vermeulen, Sylvia J; Tamminga, Sietske J; Schellart, Antonius Jm; Ybema, Jan Fekke; Anema, Johannes R

2009-07-14

In the past decade flexible labour market arrangements have emerged as a significant change in the European Union labour market. Studies suggest that these new types of labour arrangements may be linked to ill health, an increased risk for work disability, and inadequate vocational rehabilitation. Therefore, the objectives of this study were: 1. to examine demographic characteristics of workers without an employment contract sick-listed for at least 13 weeks, 2. to describe the content and frequency of occupational health care (OHC) interventions for these sick-listed workers, and 3. to examine OHC interventions as possible determinants for return-to-work (RTW) of these workers. A cohort of 1077 sick-listed workers without an employment contract were included at baseline, i.e. 13 weeks after reporting sick. Demographic variables were available at baseline. Measurement of cross-sectional data took place 4-6 months after inclusion. Primary outcome measures were: frequency of OHC interventions and RTW-rates. Measured confounding variables were: gender, age, type of worker (temporary agency worker, unemployed worker, or remaining worker without employment contract), level of education, reason for absenteeism (diagnosis), and perceived health. The association between OHC interventions and RTW was analysed with a logistic multiple regression analysis. At 7-9 months after the first day of reporting sick only 19% of the workers had (partially or completely) returned to work, and most workers perceived their health as fairly poor or poor. The most frequently reported (49%) intervention was 'the OHC professional discussed RTW'. However, the intervention 'OHC professional made and discussed a RTW action plan' was reported by only 19% of the respondents. The logistic multiple regression analysis showed a significant positive association between RTW and the interventions: 'OHC professional discussed RTW'; and 'OHC professional made and discussed a RTW action plan'. The intervention 'OHC professional referred sick-listed worker to a vocational rehabilitation agency' was significantly associated with no RTW. This is the first time that characteristics of a large cohort of sick-listed workers without an employment contract were examined. An experimental or prospective study is needed to explore the causal nature of the associations found between OHC interventions and RTW.

Self-Efficacy as a Predictor of Self-Reported Physical, Cognitive and Social Functioning in Multiple Sclerosis

PubMed Central

Schmitt, Margaret M.; Goverover, Yael; DeLuca, John; Chiaravalloti, Nancy

2014-01-01

Objective Investigate whether self-efficacy is associated with physical, cognitive and social functioning in individuals with Multiple Sclerosis (MS) when controlling for disease-related characteristics and depressive symptomatology. Participants 81 individuals between the ages of 29 and 67 with a diagnosis of clinically definite MS. Method Hierarchical regression analysis was employed to examine the relationships between self-efficacy and self-reported physical, cognitive, and social functioning. Results Self-efficacy is a significant predictor of self-reported physical, cognitive and social functioning in MS after controlling for variance due to disease related factors and depressive symptomatology. Conclusions Self-efficacy plays a significant role in individual adjustment to MS across multiple areas of functional outcome, beyond that which is accounted for by disease related variables and symptoms of depression. PMID:24320946

Gis-Based Spatial Statistical Analysis of College Graduates Employment

NASA Astrophysics Data System (ADS)

Tang, R.

2012-07-01

It is urgently necessary to be aware of the distribution and employment status of college graduates for proper allocation of human resources and overall arrangement of strategic industry. This study provides empirical evidence regarding the use of geocoding and spatial analysis in distribution and employment status of college graduates based on the data from 2004-2008 Wuhan Municipal Human Resources and Social Security Bureau, China. Spatio-temporal distribution of employment unit were analyzed with geocoding using ArcGIS software, and the stepwise multiple linear regression method via SPSS software was used to predict the employment and to identify spatially associated enterprise and professionals demand in the future. The results show that the enterprises in Wuhan east lake high and new technology development zone increased dramatically from 2004 to 2008, and tended to distributed southeastward. Furthermore, the models built by statistical analysis suggest that the specialty of graduates major in has an important impact on the number of the employment and the number of graduates engaging in pillar industries. In conclusion, the combination of GIS and statistical analysis which helps to simulate the spatial distribution of the employment status is a potential tool for human resource development research.

Socioeconomic factors and home allergen exposure in children with asthma.

PubMed

Ungar, Wendy J; Cope, Shannon F; Kozyrskyj, Anita; Paterson, J Michael

2010-01-01

The objective of this study was to determine the association between sociodemographic factors and the elimination of allergen sources from homes of asthmatic children. In a cross-sectional analysis of data from 845 asthmatic children, multiple linear regression investigated the association between socioeconomic factors and failure to reduce allergen sources (i.e., stuffed toys, pets, carpeting, curtains, and cushions); failure to use linen covers; and not laundering linens weekly in hot water. Logistic regression assessed the relationship between socioeconomic status and exposure to environmental tobacco smoke. Mother's employment status was significantly associated with the quality of the home environment (P = .0002). Homemakers demonstrated fewer poor practices (3.1) compared with full-time or part-time employed mothers (3.6). Children whose mothers reported no post-secondary education were more likely to have environmental tobacco smoke exposure compared with those who had a post-secondary CE education or higher (OR 2.4, 95% CI 1.7, 3.5). Children whose mothers worked at home and were better educated were at reduced risk for exposure to sources of indoor allergens.

Time to career: Science and engineering education to career trajectories

NASA Astrophysics Data System (ADS)

Choi, Angie Nim

Two waves of data from the 2006 and 2008 Survey of Earned Doctorates and Survey of Doctorate Recipients were used in this study to investigate time to doctorate (TTD) and time to career (TTC) for science and engineering PhDs. Three-way factorial ANOVAs were conducted, and TTD results indicated main effects for gender, US citizenship, and Biglan classification, and interaction effects for gender and US citizenship. US citizen PhDs progressed to their career approximately one mean year faster than foreign PhDs. For TTC, PhDs who held postdocs progressed to their careers in 14 and 15 years for females and males respectively compared to 19 years for those without postdoctoral appointments. PhDs working in academe also had shorter TTC rates than those working in industry or government settings. TTC rates were lowest for PhDs from engineering fields and highest for those from health sciences. A multiple linear regression based upon the 2006 data was also used to determine the best predictors of TTC based upon individual, academic, and employer characteristics, and the model was cross-validated with an independent sample from the 2008 data. The regression solution was significant, F (20, 11000) = 97.06, p < .001, and significant predictors were gender, US citizen, children ages 2-5, married or married-like relationship, TTD, teaching assistantship, research assistantship, student loans, salary, postdoc, government employer, and business/industry employer. The regression solution for predicting TTC had a medium effect size (R2 = .14), and the cross-validated model had a slightly higher effect (R2 = .28).

Employment among patients with multiple sclerosis-a population study.

PubMed

Bøe Lunde, Hanne Marie; Telstad, Wenche; Grytten, Nina; Kyte, Lars; Aarseth, Jan; Myhr, Kjell-Morten; Bø, Lars

2014-01-01

To investigate demographic and clinical factors associated with employment in MS. The study included 213 (89.9%) of all MS patients in Sogn and Fjordane County, Western Norway at December 31st 2010. The patients underwent clinical evaluation, structured interviews and completed self-reported questionnaires. Demographic and clinical factors were compared between patients being employed versus patients being unemployed and according to disease course of MS. Logistic regression analysis was used to identify factors independently associated with current employment. After a mean disease duration of almost 19 years, 45% of the population was currently full-time or part- time employed. Patients with relapsing -remitting MS (RRMS) had higher employment rate than patients with secondary (SPMS) and primary progressive (PPMS). Higher educated MS patients with lower age at onset, shorter disease duration, less severe disability and less fatigue were most likely to be employed. Nearly half of all MS patients were still employed after almost two decades of having MS. Lower age at onset, shorter disease duration, higher education, less fatigue and less disability were independently associated with current employment. These key clinical and demographic factors are important to understand the reasons to work ability in MS. The findings highlight the need for environmental adjustments at the workplace to accommodate individual 's needs in order to improve working ability among MS patients.

The relationship between employment status and self-rated health among wage workers in South Korea: the moderating role of household income.

PubMed

Lim, Hyejin; Kimm, Heejin; Song, In Han

2015-02-01

The purpose of the study reported in this article was to investigate the relationship between employment status and self-rated health (SRH) and the moderating effect of household income among wage workers in South Korea. This research analyzed the Korean Labor and Income Panel Study, 2005 to 2008. Of the 10,494 respondents participating in the survey during the period, a total of 1,548 people whose employment status had remained either precarious or nonprecarious were selected. A moderated multiple regression model was used to examine the main effect of employment status on SRH and the moderating effect of total household income on the relationship between employment status and SRH. Among 343 precarious workers and 1,205 nonprecarious workers, after controlling for gender, age, education, smoking, and drinking, employment status was associated with SRH of wage workers, and household income was found to have a moderating effect on SRH in that higher income buffers the link between unstable employment status and low SRH. Unstable employment, combined with low income, was significantly related to precarious wage workers' perceived health. To promote public health, efforts may be needed to secure not only people's employment, but also their income.

Multiple Sclerosis impact on employment and income in New Zealand.

PubMed

Pearson, J F; Alla, S; Clarke, G; Mason, D F; Anderson, T; Richardson, A; Miller, D H; Sabel, C E; Abernethy, D A; Willoughby, E W; Taylor, B V

2017-09-01

We investigated the demographic, social and clinical characteristics associated with employment status and income for people with multiple sclerosis (MS) in New Zealand (NZ). The NZ National MS Prevalence study included all persons resident in NZ on census day 2006 diagnosed with MS (96.7% coverage). Factors associated with employment and income status among the working age population (25-64 years) were identified by linear regression. Over 90% of working age people with MS (n=1727) had a work history, but 54% were not working. Work loss occurred early in the disease course, and at low disability (P<.001). Advancing age, progressive disease, longer disease duration, higher disability levels, partner loss and lower education were associated with work loss (P<.001). Working age people with MS had lower income than the NZ population (P<.0001). Higher qualifications yielded no additional income for MS females and about half the additional income for MS males (P<.0001). MS profoundly reduces employment and income early in the disease course, and at low levels of disability, however, unemployment is not entirely accounted for by clinical, social and demographic factors. These findings suggest social supports should be explored early in the disease course to reduce loss of income and unemployment for people with MS. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Outcome and Life Satisfaction of Adults with Myelomeningocele

PubMed Central

Cope, Heidi; McMahon, Kelly; Heise, Elizabeth; Eubanks, Sonja; Garrett, Melanie; Gregory, Simon; Ashley-Koch, Allison

2013-01-01

Background Myelomeningocele (MMC) commonly causes impairments in body structure and functions as well as cognitive disabilities that can have an adverse effect on adult life. Improved medical care has resulted in increased numbers of individuals with MMC surviving to adulthood, however little is known about the impact of MMC on the lives of adults age 25 years or older. Objective To gain a better understanding of outcomes in education, employment, relationships, reproduction and life satisfaction of adults with MMC. Methods A primarily quantitative multiple-choice questionnaire designed to capture outcomes in education, employment, relationships and reproduction, along with a previously validated life satisfaction checklist (LiSat-11), was completed by adults with MMC. Relationships between demographic variables, outcomes and life satisfaction were determined using cross tabulation analysis, logistic regression and linear regression. Results Ninety adults with MMC, age 25 to 85 years (median age 32), reported a diverse range of outcomes in education, employment, relationships and reproduction. The most consistent variable associated with difficulty attaining adult milestones was hydrocephalus, the presence of which reduced the likelihood of living independently (p=<0.001), having a partner (p=0.003) and reproducing (p=<0.001), but did not contribute to reduced life satisfaction. Conclusions Adults with MMC, especially those without hydrocephalus, can obtain gainful employment, live independently, form partner relationships and have children, and these achievements contribute to life satisfaction. While MMC does not affect overall reported life satisfaction for adults, attention should be paid to specific domains with less reported satisfaction. PMID:23769483

Vocational outcome following spinal cord injury.

PubMed

Conroy, L; McKenna, K

1999-09-01

Non-experimental (ex post facto) survey research design involving the use of a fixed alternative format questionnaire. To investigate variables influencing vocational outcome, to identify barriers to gaining and sustaining employment and to identify the effects of variables on the type of work engaged in following spinal cord injury. The two sets of independent variables considered were, individual and injury-related factors (age at onset of injury, time since injury, extent/level of injury, highest educational qualification achieved pre-injury, and pre-injury occupation) and circumstantial factors (means of transport, access difficulties, perceived workplace discrimination, financial disincentives to work and perceived level of skill). The Princess Alexandra Hospital Spinal Injuries Unit, Queensland, Australia. Data on the variables and the vocational outcomes of having ever worked or studied post-injury, current employment status and post-injury occupation were obtained from survey responses. Demographical and medical data were gathered from medical records. Forward stepwise logistic regression revealed that having ever worked or studied post-injury was associated with all individual and injury-related factors except pre-injury occupation, and two circumstantial factors, namely means of transport and access difficulties. Current employment was associated with all circumstantial factors as well as age at injury and pre-injury occupation. Standard multiple regression analyses revealed that post-injury occupation was correlated with all individual and injury-related factors as well as means of transport and perceived workplace discrimination. Tailored rehabilitation programs for individuals with characteristics associated with less successful vocational outcomes may facilitate their employment status after injury.

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

PubMed

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

2014-07-15

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

Using Classification and Regression Trees (CART) and random forests to analyze attrition: Results from two simulations.

PubMed

Hayes, Timothy; Usami, Satoshi; Jacobucci, Ross; McArdle, John J

2015-12-01

In this article, we describe a recent development in the analysis of attrition: using classification and regression trees (CART) and random forest methods to generate inverse sampling weights. These flexible machine learning techniques have the potential to capture complex nonlinear, interactive selection models, yet to our knowledge, their performance in the missing data analysis context has never been evaluated. To assess the potential benefits of these methods, we compare their performance with commonly employed multiple imputation and complete case techniques in 2 simulations. These initial results suggest that weights computed from pruned CART analyses performed well in terms of both bias and efficiency when compared with other methods. We discuss the implications of these findings for applied researchers. (c) 2015 APA, all rights reserved).

Using Classification and Regression Trees (CART) and Random Forests to Analyze Attrition: Results From Two Simulations

PubMed Central

Hayes, Timothy; Usami, Satoshi; Jacobucci, Ross; McArdle, John J.

2016-01-01

In this article, we describe a recent development in the analysis of attrition: using classification and regression trees (CART) and random forest methods to generate inverse sampling weights. These flexible machine learning techniques have the potential to capture complex nonlinear, interactive selection models, yet to our knowledge, their performance in the missing data analysis context has never been evaluated. To assess the potential benefits of these methods, we compare their performance with commonly employed multiple imputation and complete case techniques in 2 simulations. These initial results suggest that weights computed from pruned CART analyses performed well in terms of both bias and efficiency when compared with other methods. We discuss the implications of these findings for applied researchers. PMID:26389526

How does employment quality relate to health and job satisfaction in Europe? A typological approach.

PubMed

Van Aerden, Karen; Puig-Barrachina, Vanessa; Bosmans, Kim; Vanroelen, Christophe

2016-06-01

The changing nature of employment in recent decades, due to an increased emphasis on flexibility and competitiveness in European labour markets, compels the need to assess the consequences of contemporary employment situations for workers. This article aims to study the relation between the quality of employment and the health and well-being of European workers, using data from the 2010 European Working Conditions Survey. A typology of employment arrangements, mapping out employment quality in the European labour force, is constructed by means of a Latent Class Cluster Analysis. This innovative approach shows that it is possible to condense multiple factors characterising the employment situation into five job types: Standard Employment Relationship-like (SER-like), instrumental, precarious unsustainable, precarious intensive and portfolio jobs. Binary logistic regression analyses show that, controlling for other work quality characteristics, this employment quality typology is related to self-perceived job satisfaction, general health and mental health. Precarious intensive jobs are associated with the worst and SER-like jobs with the best health and well-being situation. The findings presented in this study indicate that, among European wage workers, flexible and de-standardised employment tends to be related to lower job satisfaction, general health and mental health. The quality of employment is thus identified as an important social determinant of health (inequalities) in Europe. Copyright © 2016 Elsevier Ltd. All rights reserved.

Improving Lidar-based Aboveground Biomass Estimation with Site Productivity for Central Hardwood Forests, USA

NASA Astrophysics Data System (ADS)

Shao, G.; Gallion, J.; Fei, S.

2016-12-01

Sound forest aboveground biomass estimation is required to monitor diverse forest ecosystems and their impacts on the changing climate. Lidar-based regression models provided promised biomass estimations in most forest ecosystems. However, considerable uncertainties of biomass estimations have been reported in the temperate hardwood and hardwood-dominated mixed forests. Varied site productivities in temperate hardwood forests largely diversified height and diameter growth rates, which significantly reduced the correlation between tree height and diameter at breast height (DBH) in mature and complex forests. It is, therefore, difficult to utilize height-based lidar metrics to predict DBH-based field-measured biomass through a simple regression model regardless the variation of site productivity. In this study, we established a multi-dimension nonlinear regression model incorporating lidar metrics and site productivity classes derived from soil features. In the regression model, lidar metrics provided horizontal and vertical structural information and productivity classes differentiated good and poor forest sites. The selection and combination of lidar metrics were discussed. Multiple regression models were employed and compared. Uncertainty analysis was applied to the best fit model. The effects of site productivity on the lidar-based biomass model were addressed.

Use of AMMI and linear regression models to analyze genotype-environment interaction in durum wheat.

PubMed

Nachit, M M; Nachit, G; Ketata, H; Gauch, H G; Zobel, R W

1992-03-01

The joint durum wheat (Triticum turgidum L var 'durum') breeding program of the International Maize and Wheat Improvement Center (CIMMYT) and the International Center for Agricultural Research in the Dry Areas (ICARDA) for the Mediterranean region employs extensive multilocation testing. Multilocation testing produces significant genotype-environment (GE) interaction that reduces the accuracy for estimating yield and selecting appropriate germ plasm. The sum of squares (SS) of GE interaction was partitioned by linear regression techniques into joint, genotypic, and environmental regressions, and by Additive Main effects and the Multiplicative Interactions (AMMI) model into five significant Interaction Principal Component Axes (IPCA). The AMMI model was more effective in partitioning the interaction SS than the linear regression technique. The SS contained in the AMMI model was 6 times higher than the SS for all three regressions. Postdictive assessment recommended the use of the first five IPCA axes, while predictive assessment AMMI1 (main effects plus IPCA1). After elimination of random variation, AMMI1 estimates for genotypic yields within sites were more precise than unadjusted means. This increased precision was equivalent to increasing the number of replications by a factor of 3.7.

Person factors and work environments of workers who use mobility devices.

PubMed

Gray, David B; Morgan, Kerri A; Gottlieb, Meghan; Hollingsworth, Holly H

2014-01-01

Nearly 25% of people with mobility impairments and limitations who are of working age are employed, yet few studies have examined their perspectives on their jobs or work environments required to complete job tasks. The purpose of this study was to describe the factors that contribute to successful employment for those who use mobility devices. A convenience sample of 132 workers who use power wheelchairs, manual wheelchairs, canes, crutches or walkers. Participants completed an online version of the Mobility Device User Work Survey (MWS). A multivariate analysis and a two-step multiple linear regression analysis were used. Study participants had few secondary health conditions that influenced their work. Employee satisfactoriness to their employers was high. Accessibility of worksites was high. Assistive technologies were inexpensive, and personal assistance was used infrequently and usually was unpaid. Co-worker communications were very positive. Flexible work rules and supportive managers were highly valued. Job satisfaction positively correlated with accessibility, work tasks, co-worker communication and work support. The description of work environments of successfully employed mobility device users can provide some useful guidance to employers, vocational rehabilitation (VR) counselors and unemployed mobility device users to balance employee abilities and preferences with the needs of employers.

Multiple Sclerosis and Catastrophic Health Expenditure in Iran.

PubMed

Juyani, Yaser; Hamedi, Dorsa; Hosseini Jebeli, Seyede Sedighe; Qasham, Maryam

2016-09-01

There are many disabling medical conditions which can result in catastrophic health expenditure. Multiple Sclerosis is one of the most costly medical conditions through the world which encounter families to the catastrophic health expenditures. This study aims to investigate on what extent Multiple sclerosis patients face catastrophic costs. This study was carried out in Ahvaz, Iran (2014). The study population included households that at least one of their members suffers from MS. To analyze data, Logit regression model was employed by using the default software STATA12. 3.37% of families were encountered with catastrophic costs. Important variables including brand of drug, housing, income and health insurance were significantly correlated with catastrophic expenditure. This study suggests that although a small proportion of MS patients met the catastrophic health expenditure, mechanisms that pool risk and cost (e.g. health insurance) are required to protect them and improve financial and access equity in health care.

Multiple role adaptation among women who have children and re-enter nursing school in Taiwan.

PubMed

Lin, Li-Ling

2005-03-01

This study assessed multiple role adaptation within maternal and student roles among female RNs who had children and returned to school for baccalaureate degrees in Taiwan. Using Roy's Adaptation Model as the theoretical framework, relationships were explored among demographic (number of children, age of youngest child, employment status), physical (sleep quality, health perception, activity), and psychosocial factors (self-identity, role expectation, role involvement, social support) and multiple role adaptation (role accumulation). The sample included 118 mother-students who had at least one child younger than age 18 and who were studying in nursing programs in Taiwan. The highest correlation was found between activity and role accumulation followed by significant correlations between sleep quality, health perception, maternal role expectation, and age of youngest child and role accumulation. In regression analyses, the complete model explained 46% of the variance in role accumulation. Implications for education and future research are identified.

Types of employment and their associations with work characteristics and health in Swedish women and men.

PubMed

Samuelsson, Åsa; Houkes, Inge; Verdonk, Petra; Hammarström, Anne

2012-03-01

To investigate whether type of employment was related to work characteristics and health status at age 42 adjusted for health status at age 30 and whether gender moderates the associations. Questionnaire data was used from a 27-year follow-up study of school-leavers carried out in Luleå in the north of Sweden (response rate 94%). The study population consisted of 877 (47.8% women) working respondents. Data were analysed by means of t-tests, ANOVAs, and multiple linear regression analyses. Men were more often self-employed, while more women had temporary types of employment. Moreover, men reported more control over work and less emotional exhaustion than women. Compared to permanently employed, self-employed (men and women) perceived more control over work and better health status (p<0.01). Self-employed men also reported more demands and social support (p<0.05). People in temporary types of employment, however, reported less job control, as well as lower health status (only men) (p<0.01). Poor self-reported health and emotional exhaustion were significantly (p<0.05) associated with poor work characteristics (more demands, lower job control, and lower support). No direct associations between type of employment and health were found for women and men. However we find indications of an influence of type of employment on work and thereupon health, with job control playing an important role.

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.

DFT study on oxidation of HS(CH2) m SH ( m = 1-8) in oxidative desulfurization

NASA Astrophysics Data System (ADS)

Song, Y. Z.; Song, J. J.; Zhao, T. T.; Chen, C. Y.; He, M.; Du, J.

2016-06-01

Density functional theory was employed for calculation of HS(CH2) m SH ( m = 1-8) and its derivatives at B3LYP method at 6-31++g ( d, p) level. Using eigenvalues of LUMO and HOMO for HS(CH2) m SH, the standard electrode potentials were estimated by a stepwise multiple regression techniques (MLR), and obtained as E° = 1.500 + 7.167 × 10-3 HOMO-0.229 LUMO with high correlation coefficients of 0.973 and F values of 43.973.

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.

Fuzzy regression modeling for tool performance prediction and degradation detection.

PubMed

Li, X; Er, M J; Lim, B S; Zhou, J H; Gan, O P; Rutkowski, L

2010-10-01

In this paper, the viability of using Fuzzy-Rule-Based Regression Modeling (FRM) algorithm for tool performance and degradation detection is investigated. The FRM is developed based on a multi-layered fuzzy-rule-based hybrid system with Multiple Regression Models (MRM) embedded into a fuzzy logic inference engine that employs Self Organizing Maps (SOM) for clustering. The FRM converts a complex nonlinear problem to a simplified linear format in order to further increase the accuracy in prediction and rate of convergence. The efficacy of the proposed FRM is tested through a case study - namely to predict the remaining useful life of a ball nose milling cutter during a dry machining process of hardened tool steel with a hardness of 52-54 HRc. A comparative study is further made between four predictive models using the same set of experimental data. It is shown that the FRM is superior as compared with conventional MRM, Back Propagation Neural Networks (BPNN) and Radial Basis Function Networks (RBFN) in terms of prediction accuracy and learning speed.

Adulteration of Argentinean milk fats with animal fats: Detection by fatty acids analysis and multivariate regression techniques.

PubMed

Rebechi, S R; Vélez, M A; Vaira, S; Perotti, M C

2016-02-01

The aims of the present study were to test the accuracy of the fatty acid ratios established by the Argentinean Legislation to detect adulterations of milk fat with animal fats and to propose a regression model suitable to evaluate these adulterations. For this purpose, 70 milk fat, 10 tallow and 7 lard fat samples were collected and analyzed by gas chromatography. Data was utilized to simulate arithmetically adulterated milk fat samples at 0%, 2%, 5%, 10% and 15%, for both animal fats. The fatty acids ratios failed to distinguish adulterated milk fats containing less than 15% of tallow or lard. For each adulterant, Multiple Linear Regression (MLR) was applied, and a model was chosen and validated. For that, calibration and validation matrices were constructed employing genuine and adulterated milk fat samples. The models were able to detect adulterations of milk fat at levels greater than 10% for tallow and 5% for lard. Copyright © 2015 Elsevier Ltd. All rights reserved.

Employer retention strategies and their effect on nurses' job satisfaction and intent to stay.

PubMed

Ellenbecker, Carol Hall; Samia, Linda; Cushman, Margaret J; Porell, Frank W

2007-01-01

Faced with a nursing shortage and anticipated increase in demand, home care agencies are implementing retention strategies with little knowledge of their effectiveness. The purpose of this study is to describe the strategies implemented and their effect on nurse job satisfaction and intention to leave. Data were collected from a random sample of 123 New England agencies during in-person interviews. Most agencies reported implementing multiple recruitment and retention strategies. Regression results suggest that the effects of employer retention strategy on nurses' intent to stay are the indirect result of its effects on job satisfaction. The only retention intervention that made a statistically significant difference in job satisfaction was shared governance, and no retention strategy directly affected nurses' intention to stay in their jobs.

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

PubMed

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

2016-02-01

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

Employment status among the Singapore elderly and its correlates.

PubMed

Tan, Min-En; Sagayadevan, Vathsala; Abdin, Edimansyah; Picco, Louisa; Vaingankar, Janhavi; Chong, Siow Ann; Subramaniam, Mythily

2017-05-01

It has been hypothesized that working beyond retirement age may have a protective effect on various aspects of well-being in the elderly. This paper aims to examine the relationship between employment status of elderly Singaporeans and indicators of well-being. As part of the Well-being of the Singapore Elderly study, data relating to sociodemographics, social networks, medical history, physical activity, cognitive function, and disability were collected from 2534 participants aged 60 years and older. Participants included full-time workers (n = 483), part-time workers (n = 205), the unemployed (n = 32), homemakers (n = 808), and retirees (n = 1006). The data were analyzed by multiple logistic regression. Likelihood of being employed decreased with age, and employment was higher among men. Paid workers had significantly higher levels of physical activity, more extensive social networks, better cognitive function, less disability, and lower risk of dementia than retirees and homemakers. Paid workers had significantly lower chronic disease burden than retirees and rated their health to be better than retirees and the unemployed. These findings show that meaningful employment is associated with better psychological and physiological well-being among the elderly, highlighting the importance of studying likely protective effects of employment and creating employment opportunities for elderly Singaporeans. © 2016 The Authors. Psychogeriatrics © 2016 Japanese Psychogeriatric Society.

Employment among Patients with Multiple Sclerosis-A Population Study

PubMed Central

Bøe Lunde, Hanne Marie; Telstad, Wenche; Grytten, Nina; Kyte, Lars; Aarseth, Jan; Myhr, Kjell-Morten; Bø, Lars

2014-01-01

Objective To investigate demographic and clinical factors associated with employment in MS. Methods The study included 213 (89.9%) of all MS patients in Sogn and Fjordane County, Western Norway at December 31st 2010. The patients underwent clinical evaluation, structured interviews and completed self-reported questionnaires. Demographic and clinical factors were compared between patients being employed versus patients being unemployed and according to disease course of MS. Logistic regression analysis was used to identify factors independently associated with current employment. Results After a mean disease duration of almost 19 years, 45% of the population was currently full-time or part- time employed. Patients with relapsing –remitting MS (RRMS) had higher employment rate than patients with secondary (SPMS) and primary progressive (PPMS). Higher educated MS patients with lower age at onset, shorter disease duration, less severe disability and less fatigue were most likely to be employed. Conclusions Nearly half of all MS patients were still employed after almost two decades of having MS. Lower age at onset, shorter disease duration, higher education, less fatigue and less disability were independently associated with current employment. These key clinical and demographic factors are important to understand the reasons to work ability in MS. The findings highlight the need for environmental adjustments at the workplace to accommodate individual ’s needs in order to improve working ability among MS patients. PMID:25054972

Polychlorinated dibenzo-p-dioxin and dibenzofuran concentrations in serum samples of workers at intermittently burning municipal waste incinerators in Japan

PubMed Central

Kumagai, S; Koda, S; Miyakita, T; Ueno, M

2002-01-01

Objectives: To find whether or not incinerator workers employed at intermittently burning municipal incineration plants are exposed to high concentrations of polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs). Methods: 20 Workers employed at three municipal waste incineration plants (incinerator workers) and 20 controls were studied. The previous job, dietary, smoking, and body weight and height were obtained from a questionnaire survey. Concentrations of PCDDs and PCDFs were measured in serum samples of the workers and the deposited dust of the plants. The influence of occupational exposure on concentrations of PCDDs and PCDFs in serum samples was examined by multiple regression analysis. Results: Dust analysis showed that dominant constituents were octachlorodibenzo-p-dioxin (OCDD) and 1,2,3,4,6,7,8-heptachlorodibenzo-p-dioxin (HpCDD) among the PCDDs, and 1,2,3,4,6,7,8-heptachlorodibenzofuran (HpCDF) and octachlorodibenzofuran (OCDF) among the PCDFs. The toxicity equivalents (TEQs) of summed PCDDs and PCDFs in the deposited dust were 0.91, 33, and 11 ng TEQ/g, respectively, for plants I, II, and III. The means of TEQ in serum samples of summed PCDDs and PCDFs in the incinerator workers and controls were 22.8 and 16.4 pg TEQ/g lipid for area I, 29.4 and 19.3 pg TEQ/g lipid for area II, and 22.8 and 24.9 pg TEQ/g lipid for area III, which were almost the same as for the general population of Japan. No significant differences in the TEQ of PCDDs and TEQ of PCDDs and PCDDs were found between the incinerator workers and the controls. However, the TEQ of PCDFs was significantly higher among the incinerator workers in areas I and II, and the 1,2,3,4,6,7,8-HpCDF concentration was also significantly higher for all three areas. When the occupational exposure index for each constituent of PCDDs and PCDFs was defined as the product of the duration of employment at the incineration plant and the concentration of the constituent in the deposited dust, multiple regression analysis showed that the concentrations of HxCDF, HpCDF, and TEQ of PCDFs in serum samples increased with the occupational exposure index. The multiple regression analysis also suggested that significant factors affecting the concentrations in serum samples were area for HxCDD, age for TCDD, PeCDD, PeCDF, TEQ of PCDDs, TEQ of PCDFs, and TEQ of summed PCDDs and PCDFs, and BMI for HxCDD, HpCDD, and OCDD. Conclusion: This study showed that incinerator workers employed at intermittently burning incineration plants were not necessarily exposed to high concentrations of PCDDs and PCDFs. However, the increases in the concentrations in serum of HxCDF, HpCDF and TEQ of PCDFs with the occupational exposure index suggest that the incinerator workers had inhaled dust containing PCDDs and PCDFs during their work. PMID:12040109

The effect of social deprivation on local authority sickness absence rates.

PubMed

Wynn, P; Low, A

2008-06-01

There is an extensive body of research relating to the association between ergonomic and psychosocial factors on sickness absence rates. The impact of deprivation on health indices has also been extensively investigated. However, published research has not investigated the extent of any association between standard measures of deprivation and sickness absence and ill-health retirement rates. To establish if a relationship exists between standard measures of deprivation, used by the UK central government to determine regional health and social welfare funding, and sickness absence and ill-health early retirement rates in English local government employers. Local authority sickness absence rates for 2001-02 were regressed against the 2004 Indices of Multiple Deprivation in a multiple regression model that also included size and type of organization as independent variables. A second model using ill-health retirement as the dependent variable was also estimated. In the full regression models, organization size was not significant and reduced models with deprivation and organization type (depending on whether teachers were employed by the organization or not) were estimated. For the sickness absence model, the adjusted R(2) was 0.20, with 17% of the variation in sickness absence rates being explained by deprivation rank. Ill-health retirement showed a similar relationship with deprivation. In both models, the deprivation coefficients were highly significant: for sickness absence [t = -7.85 (P = 0.00)] and for ill-health retirement [t = -4.79 (P = 0.00)]. A significant proportion of variation in sickness absence and ill-health retirement rates in local government in England are associated with local measures of deprivation. Recognition of the impact of deprivation on sickness absence has implications for a number of different areas of work. These include target setting for Local Government Best Value Performance Indicators, history taking in sickness absence consultations and the role of deprivation as a confounding factor in sickness absence intervention studies.

Multiple regression based imputation for individualizing template human model from a small number of measured dimensions.

PubMed

Nohara, Ryuki; Endo, Yui; Murai, Akihiko; Takemura, Hiroshi; Kouchi, Makiko; Tada, Mitsunori

2016-08-01

Individual human models are usually created by direct 3D scanning or deforming a template model according to the measured dimensions. In this paper, we propose a method to estimate all the necessary dimensions (full set) for the human model individualization from a small number of measured dimensions (subset) and human dimension database. For this purpose, we solved multiple regression equation from the dimension database given full set dimensions as the objective variable and subset dimensions as the explanatory variables. Thus, the full set dimensions are obtained by simply multiplying the subset dimensions to the coefficient matrix of the regression equation. We verified the accuracy of our method by imputing hand, foot, and whole body dimensions from their dimension database. The leave-one-out cross validation is employed in this evaluation. The mean absolute errors (MAE) between the measured and the estimated dimensions computed from 4 dimensions (hand length, breadth, middle finger breadth at proximal, and middle finger depth at proximal) in the hand, 2 dimensions (foot length, breadth, and lateral malleolus height) in the foot, and 1 dimension (height) and weight in the whole body are computed. The average MAE of non-measured dimensions were 4.58% in the hand, 4.42% in the foot, and 3.54% in the whole body, while that of measured dimensions were 0.00%.

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

PubMed

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

2007-12-01

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

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.

Enhancing the estimation of blood pressure using pulse arrival time and two confounding factors.

PubMed

Baek, Hyun Jae; Kim, Ko Keun; Kim, Jung Soo; Lee, Boreom; Park, Kwang Suk

2010-02-01

A new method of blood pressure (BP) estimation using multiple regression with pulse arrival time (PAT) and two confounding factors was evaluated in clinical and unconstrained monitoring situations. For the first analysis with clinical data, electrocardiogram (ECG), photoplethysmogram (PPG) and invasive BP signals were obtained by a conventional patient monitoring device during surgery. In the second analysis, ECG, PPG and non-invasive BP were measured using systems developed to obtain data under conditions in which the subject was not constrained. To enhance the performance of BP estimation methods, heart rate (HR) and arterial stiffness were considered as confounding factors in regression analysis. The PAT and HR were easily extracted from ECG and PPG signals. For arterial stiffness, the duration from the maximum derivative point to the maximum of the dicrotic notch in the PPG signal, a parameter called TDB, was employed. In two experiments that normally cause BP variation, the correlation between measured BP and the estimated BP was investigated. Multiple-regression analysis with the two confounding factors improved correlation coefficients for diastolic blood pressure and systolic blood pressure to acceptable confidence levels, compared to existing methods that consider PAT only. In addition, reproducibility for the proposed method was determined using constructed test sets. Our results demonstrate that non-invasive, non-intrusive BP estimation can be obtained using methods that can be applied in both clinical and daily healthcare situations.

Simultaneous determination of hydroquinone, resorcinol, phenol, m-cresol and p-cresol in untreated air samples using spectrofluorimetry and a custom multiple linear regression-successive projection algorithm.

PubMed

Pistonesi, Marcelo F; Di Nezio, María S; Centurión, María E; Lista, Adriana G; Fragoso, Wallace D; Pontes, Márcio J C; Araújo, Mário C U; Band, Beatriz S Fernández

2010-12-15

In this study, a novel, simple, and efficient spectrofluorimetric method to determine directly and simultaneously five phenolic compounds (hydroquinone, resorcinol, phenol, m-cresol and p-cresol) in air samples is presented. For this purpose, variable selection by the successive projections algorithm (SPA) is used in order to obtain simple multiple linear regression (MLR) models based on a small subset of wavelengths. For comparison, partial least square (PLS) regression is also employed in full-spectrum. The concentrations of the calibration matrix ranged from 0.02 to 0.2 mg L(-1) for hydroquinone, from 0.05 to 0.6 mg L(-1) for resorcinol, and from 0.05 to 0.4 mg L(-1) for phenol, m-cresol and p-cresol; incidentally, such ranges are in accordance with the Argentinean environmental legislation. To verify the accuracy of the proposed method a recovery study on real air samples of smoking environment was carried out with satisfactory results (94-104%). The advantage of the proposed method is that it requires only spectrofluorimetric measurements of samples and chemometric modeling for simultaneous determination of five phenols. With it, air is simply sampled and no pre-treatment sample is needed (i.e., separation steps and derivatization reagents are avoided) that means a great saving of time. Copyright © 2010 Elsevier B.V. All rights reserved.

Ecological validity of neuropsychological assessment and perceived employability.

PubMed

Wen, Johnny H; Boone, Kyle; Kim, Kevin

2006-11-01

Ecological validity studies that have examined the relationship between cognitive abilities and employment in psychiatric and medical populations have found that a wide range of cognitive domains predict employability, although memory and executive skills appear to be the most important. However, no information is available regarding a patient's self-perceived work attributes and objective neuropsychological performance, and whether the same cognitive domains associated with successful employment are also related to a patient's self-perception of work competence. In the present study, 73 medical and psychiatric patients underwent comprehensive neuropsychological assessment. Step-wise multiple regression analyses revealed that the visual-spatial domain was the only significant predictor of self-perceived work attributes and work competence as measured by the Working Inventory (WI) and the Work Adjustment Inventory (WAI), accounting for 7% to 10% of inventory score variability. The results raise the intriguing possibility that targeting of visual spatial skills for remediation and development might play a separate and unique role in the vocational rehabilitation of a lower SES population, specifically, by leading to enhanced self-perception of work competence as these individuals attempt to enter the job market.

Socioeconomic determinants of childhood overweight and obesity in China: the long arm of institutional power

PubMed Central

Fu, Qiang; George, Linda K.

2018-01-01

Abstract Previous studies have widely reported that the association between socioeconomic status (SES) and childhood overweight and obesity in China is significant and positive, which lends little support to the fundamental-cause perspective. Using multiple waves (1997, 2000, 2004 and 2006) of the China Health and Nutrition Survey (CHNS) (N = 2,556, 2,063, 1,431 and 1,242, respectively) and continuous BMI cut-points obtained from a polynomial method, (mixed-effect) logistic regression analyses show that parental state-sector employment, an important, yet overlooked, indicator of political power during the market transformation has changed from a risk factor for childhood overweight/obesity in 1997 to a protective factor for childhood overweight/obesity in 2006. Results from quantile regression analyses generate the same conclusions and demonstrate that the protective effect of parental state sector employment at high percentiles of BMI is robust under different estimation strategies. By bridging the fundamental causes perspective and theories of market transformation, this research not only documents the effect of political power on childhood overweight/obesity but also calls for the use of multifaceted, culturally-relevant stratification measures in testing the fundamental cause perspective across time and space. PMID:26178452

Relationship between Leadership among Peers and Burnout in Sports Teams.

PubMed

Torrado, Julio; Arce, Constantino; Vales-Vázquez, Ángel; Areces, Alberto; Iglesias, Gabriel; Valle, Iván; Patiño, Gabriel

2017-04-03

This study has been conducted with the aim of ascertaining the relationship between peer leaders in sport teams and the levels of burnout experienced by their team-mates. A total of 219 Spanish athletes involved in football and basketball participated in the study. To measure leadership among peers, we employed the Sports Peer Leadership Scale, which comprises 24 items, grouped into 6 primary factors: empathy, influence on decision making, sports values, social support, training orientation and competition orientation. And to measure burnout, we employed the Athlete Burnout Questionnaire, which comprises 15 items which are indicators of physical and emotional exhaustion, devaluation and reduced sense of accomplishment among athletes. The results led to the conclusion that there is a statistically significant negative relationship between perceived leadership capacity and the levels of burnout experience by a team. The greater the level of leadership capacity perceived, the lower the levels of burnout will be. A multiple regression analysis with total burnout as dependent variable and social and task orientations of the leader as predictors showed standardized regression coefficients of -.241 (p = .010) and -.076 (p = .413), respectively for social and task orientation, being the effect size equal to .089.

Time-Frequency Analysis of Non-Stationary Biological Signals with Sparse Linear Regression Based Fourier Linear Combiner.

PubMed

Wang, Yubo; Veluvolu, Kalyana C

2017-06-14

It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC). In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976) ratio and outperforms existing methods such as short-time Fourier transfrom (STFT), continuous Wavelet transform (CWT) and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.

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.

Relating Factors for Depression in Korean Working Women: Secondary Analysis of the Fifth Korean National Health and Nutrition Examination Survey (KNHANES V).

PubMed

Lee, Kyung-Jae; Kim, Jeung-Im

2015-09-01

The purpose of this study was to investigate the health behaviors and risk factors for self-reported depression in Korean working women. This study adopted a secondary analysis from the fifth Korean National Health and Nutrition Examination Survey (KNHANES-V) for the Health Examination Survey and Health Behavior Survey, using stratified, multi-stage, cluster-sampling design to obtain a nationally representative sample. Data were gathered on extensive information including sociodemographic, occupational characteristics, health behaviors and depression. Multiple logistic regression analysis was employed to compute the odds ratio (OR) between health behaviors and depression to identify the health behaviors and the risk factors for depression with adjustment for the complex sample design of the survey. The prevalence rate of depression was 15.5% among working women. Depression was more common in older female workers and in those with part-time job. Current smokers were significantly more likely to be depression-positive. In a multiple logistic regression analysis, significant variables of depression were marital status (OR = 2.02; 95% CI [1.05, 3.89]), smoking status (OR = 1.55; 95% CI [1.01, 2.38]), stress (OR = 0.20; 95% CI [0.15, 0.26]), employment condition (OR = 1.77; 95% CI [1.34, 2.33]) and health status (OR = 2.10; 95% CI [1.53, 2.87]). Based on the study, factors leading to depression were marital status, current smoking, stress, employment condition and self-reported health status. Further studies are expected to unravel the characteristics of stress. Health care providers for women need to evaluate underreported depression and change their associated health behaviors. Also it is necessary to establish preventive strategies for female workers to control the negative effect of depression in the workplace. Copyright © 2015. Published by Elsevier B.V.

Return-to-work of sick-listed workers without an employment contract – what works?

PubMed Central

Vermeulen, Sylvia J; Tamminga, Sietske J; Schellart, Antonius JM; Ybema, Jan Fekke; Anema, Johannes R

2009-01-01

Background In the past decade flexible labour market arrangements have emerged as a significant change in the European Union labour market. Studies suggest that these new types of labour arrangements may be linked to ill health, an increased risk for work disability, and inadequate vocational rehabilitation. Therefore, the objectives of this study were: 1. to examine demographic characteristics of workers without an employment contract sick-listed for at least 13 weeks, 2. to describe the content and frequency of occupational health care (OHC) interventions for these sick-listed workers, and 3. to examine OHC interventions as possible determinants for return-to-work (RTW) of these workers. Methods A cohort of 1077 sick-listed workers without an employment contract were included at baseline, i.e. 13 weeks after reporting sick. Demographic variables were available at baseline. Measurement of cross-sectional data took place 4–6 months after inclusion. Primary outcome measures were: frequency of OHC interventions and RTW-rates. Measured confounding variables were: gender, age, type of worker (temporary agency worker, unemployed worker, or remaining worker without employment contract), level of education, reason for absenteeism (diagnosis), and perceived health. The association between OHC interventions and RTW was analysed with a logistic multiple regression analysis. Results At 7–9 months after the first day of reporting sick only 19% of the workers had (partially or completely) returned to work, and most workers perceived their health as fairly poor or poor. The most frequently reported (49%) intervention was 'the OHC professional discussed RTW'. However, the intervention 'OHC professional made and discussed a RTW action plan' was reported by only 19% of the respondents. The logistic multiple regression analysis showed a significant positive association between RTW and the interventions: 'OHC professional discussed RTW'; and 'OHC professional made and discussed a RTW action plan'. The intervention 'OHC professional referred sick-listed worker to a vocational rehabilitation agency' was significantly associated with no RTW. Conclusion This is the first time that characteristics of a large cohort of sick-listed workers without an employment contract were examined. An experimental or prospective study is needed to explore the causal nature of the associations found between OHC interventions and RTW. PMID:19602219

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

USGS Publications Warehouse

Sophocleous, M.

2000-01-01

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

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)

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)

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

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

MultiDK: A Multiple Descriptor Multiple Kernel Approach for Molecular Discovery and Its Application to Organic Flow Battery Electrolytes.

PubMed

Kim, Sungjin; Jinich, Adrián; Aspuru-Guzik, Alán

2017-04-24

We propose a multiple descriptor multiple kernel (MultiDK) method for efficient molecular discovery using machine learning. We show that the MultiDK method improves both the speed and accuracy of molecular property prediction. We apply the method to the discovery of electrolyte molecules for aqueous redox flow batteries. Using multiple-type-as opposed to single-type-descriptors, we obtain more relevant features for machine learning. Following the principle of "wisdom of the crowds", the combination of multiple-type descriptors significantly boosts prediction performance. Moreover, by employing multiple kernels-more than one kernel function for a set of the input descriptors-MultiDK exploits nonlinear relations between molecular structure and properties better than a linear regression approach. The multiple kernels consist of a Tanimoto similarity kernel and a linear kernel for a set of binary descriptors and a set of nonbinary descriptors, respectively. Using MultiDK, we achieve an average performance of r 2 = 0.92 with a test set of molecules for solubility prediction. We also extend MultiDK to predict pH-dependent solubility and apply it to a set of quinone molecules with different ionizable functional groups to assess their performance as flow battery electrolytes.

Does improvement of cognitive functioning by cognitive remediation therapy effect work outcomes in severe mental illness? A secondary analysis of a randomized controlled trial.

PubMed

Ikebuchi, Emi; Sato, Sayaka; Yamaguchi, Sosei; Shimodaira, Michiyo; Taneda, Ayano; Hatsuse, Norifumi; Watanabe, Yukako; Sakata, Masuhiro; Satake, Naoko; Nishio, Masaaki; Ito, Jun-Ichiro

2017-05-01

The aim of this study was to clarify whether improvement of cognitive functioning by cognitive remediation therapy can improve work outcome in schizophrenia and other severe mental illnesses when combined with supported employment. The subjects of this study were persons with severe mental illness diagnosed with schizophrenia, major depression, or bipolar disorder (ICD-10) and cognitive dysfunction who participated in both cognitive remediation using the Thinking Skills for Work program and a supported employment program in a multisite, randomized controlled study. Logistic and multiple linear regression analyses were performed to clarify the influence of cognitive functioning on vocational outcomes, adjusting for demographic and clinical variables. Improvement of cognitive functioning with cognitive remediation significantly contributed to the total days employed and total earnings of competitive employment in supported employment service during the study period. Any baseline demographic and clinical variables did not significantly contribute to the work-related outcomes. A cognitive remediation program transferring learning skills into the real world is useful to increase the quality of working life in supported employment services for persons with severe mental illness and cognitive dysfunction who want to work competitively. © 2016 The Authors. Psychiatry and Clinical Neurosciences © 2016 Japanese Society of Psychiatry and Neurology.

Behavioral Intervention in the Overweight and Obese Employee: The Challenge of Promoting Weight Loss and Physical Activity

PubMed Central

Maniwa, Rumi; Iwamoto, Mamiko; Nogi, Akiko; Yamasaki, Masayuki; Yang, Jian-jun; Hanaoka, Hideaki; Shiwaku, Kuninori

2012-01-01

Effects of gender and employment situation on weight loss and lifestyle modification were assessed in a 3-month intervention study done for overweight and obesity. A total of 384 individuals in Izumo City Japan, participated from 2000 to 2006. Lifestyle modifications were quantitatively evaluated by calculating calories of energy intake and expenditure. Eleven men and 15 women failed to complete the intervention; they were significantly younger in both genders, and the women had a higher rate of employment than the completing group (91 men and 267 women). Intervention induced a weight loss of 1.9 kg for men and 1.6 kg for women, with no significant differences by gender. Significant differences were found in changes in energy intake and expenditure in both genders, but these disappeared after adjusting for weight. There were significant decreases in weight (1.6 kg in unemployed, 2.5 kg in employed) in men. Increases in walking and exercise for the employed were smaller than those for the unemployed. The relationship between changes in weight and energy balance by employment status was independently significant using multiple regression analysis. Employment is associated with difficulty in losing weight due to limited exercise time in behavioral intervention. PMID:25648082

Trapped between the two cultures: Urban college students' attitudes toward science

NASA Astrophysics Data System (ADS)

Dawson, Roy Edward

Most Americans agree that science plays an important part in maintaining our leadership role in economics, health, and security. Yet when it comes to science and math we appear to be baffled. Only 25% of Americans understand the process of science well enough to make informed judgment about scientific research reported in the media (National Science Foundation, 1998). What is it that turns Americans away from science? Is it our culture, schools, families, or friends? This study investigates urban college students' attitudes toward science to determine what changes might promote increased participation in the questions, ethical implications and culture of science. Volunteers completed a science questionnaire which included multiple-choice and open-answer questions. The questions were divided into the categories of individual characteristics, home/family, peers, and school/teachers. The multiple-choice questions were analyzed with quantitative statistical techniques. The open-answer questions were used to rate each student's attitude toward science and then analyzed with qualitative methods. Thirteen factors were significant in predicting science attitude but none of them, by itself, explained a large amount of variation. A multiple regression model indicated that the significant factors (in order of importance) were watching science television with your family, having a father not employed in science, having friends who like science, and imagining yourself to be a successful student. A hierarchical multiple regression analysis indicated that the categories of individual characteristics, family, and peers were all significant contributors to the model's prediction of science attitude. School environment/teachers did not add significant predictive power to the model. The qualitative results indicated that the factors of (1) a student's previous experience in science classes and (2) the curriculum philosophy which his or her science teachers employed appeared to be the most important factors in determining a student's feelings toward science. Outliers to the science attitude profile were interviewed to determine how they maintained a positive attitude toward science when the profile predicted a negative attitude. These students appeared to be resilient and it is not clear if resiliency is a way of defeating the profile, or if resilient students incorrectly identified themselves as outliers to the profile.

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.

Predictive Utility of Marketed Volumetric Software Tools in Subjects at Risk for Alzheimer's: Do Regions Outside the Hippocampus Matter?

PubMed Central

Tanpitukpongse, Teerath P.; Mazurowski, Maciej A.; Ikhena, John; Petrella, Jeffrey R.

2016-01-01

Background and Purpose To assess prognostic efficacy of individual versus combined regional volumetrics in two commercially-available brain volumetric software packages for predicting conversion of patients with mild cognitive impairment to Alzheimer's disease. Materials and Methods Data was obtained through the Alzheimer's Disease Neuroimaging Initiative. 192 subjects (mean age 74.8 years, 39% female) diagnosed with mild cognitive impairment at baseline were studied. All had T1WI MRI sequences at baseline and 3-year clinical follow-up. Analysis was performed with NeuroQuant® and Neuroreader™. Receiver operating characteristic curves assessing the prognostic efficacy of each software package were generated using a univariable approach employing individual regional brain volumes, as well as two multivariable approaches (multiple regression and random forest), combining multiple volumes. Results On univariable analysis of 11 NeuroQuant® and 11 Neuroreader™ regional volumes, hippocampal volume had the highest area under the curve for both software packages (0.69 NeuroQuant®, 0.68 Neuroreader™), and was not significantly different (p > 0.05) between packages. Multivariable analysis did not increase the area under the curve for either package (0.63 logistic regression, 0.60 random forest NeuroQuant®; 0.65 logistic regression, 0.62 random forest Neuroreader™). Conclusion Of the multiple regional volume measures available in FDA-cleared brain volumetric software packages, hippocampal volume remains the best single predictor of conversion of mild cognitive impairment to Alzheimer's disease at 3-year follow-up. Combining volumetrics did not add additional prognostic efficacy. Therefore, future prognostic studies in MCI, combining such tools with demographic and other biomarker measures, are justified in using hippocampal volume as the only volumetric biomarker. PMID:28057634

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.

Application of Multiple Regression and Design of Experiments for Modelling the Effect of Monoethylene Glycol in the Calcium Carbonate Scaling Process.

PubMed

Kartnaller, Vinicius; Venâncio, Fabrício; F do Rosário, Francisca; Cajaiba, João

2018-04-10

To avoid gas hydrate formation during oil and gas production, companies usually employ thermodynamic inhibitors consisting of hydroxyl compounds, such as monoethylene glycol (MEG). However, these inhibitors may cause other types of fouling during production such as inorganic salt deposits (scale). Calcium carbonate is one of the main scaling salts and is a great concern, especially for the new pre-salt wells being explored in Brazil. Hence, it is important to understand how using inhibitors to control gas hydrate formation may be interacting with the scale formation process. Multiple regression and design of experiments were used to mathematically model the calcium carbonate scaling process and its evolution in the presence of MEG. It was seen that MEG, although inducing the precipitation by increasing the supersaturation ratio, actually works as a scale inhibitor for calcium carbonate in concentrations over 40%. This effect was not due to changes in the viscosity, as suggested in the literature, but possibly to the binding of MEG to the CaCO₃ particles' surface. The interaction of the MEG inhibition effect with the system's variables was also assessed, when temperature' and calcium concentration were more relevant.

Limb-darkening and the structure of the Jovian atmosphere

NASA Technical Reports Server (NTRS)

Newman, W. I.; Sagan, C.

1978-01-01

By observing the transit of various cloud features across the Jovian disk, limb-darkening curves were constructed for three regions in the 4.6 to 5.1 mu cm band. Several models currently employed in describing the radiative or dynamical properties of planetary atmospheres are here examined to understand their implications for limb-darkening. The statistical problem of fitting these models to the observed data is reviewed and methods for applying multiple regression analysis are discussed. Analysis of variance techniques are introduced to test the viability of a given physical process as a cause of the observed limb-darkening.

Sequence analysis to assess labour market participation following vocational rehabilitation: an observational study among patients sick-listed with low back pain from a randomised clinical trial in Denmark.

PubMed

Lindholdt, Louise; Labriola, Merete; Nielsen, Claus Vinther; Horsbøl, Trine Allerslev; Lund, Thomas

2017-07-20

The return-to-work (RTW) process after long-term sickness absence is often complex and long and implies multiple shifts between different labour market states for the absentee. Standard methods for examining RTW research typically rely on the analysis of one outcome measure at a time, which will not capture the many possible states and transitions the absentee can go through. The purpose of this study was to explore the potential added value of sequence analysis in supplement to standard regression analysis of a multidisciplinary RTW intervention among patients with low back pain (LBP). The study population consisted of 160 patients randomly allocated to either a hospital-based brief or a multidisciplinary intervention. Data on labour market participation following intervention were obtained from a national register and analysed in two ways: as a binary outcome expressed as active or passive relief at a 1-year follow-up and as four different categories for labour market participation. Logistic regression and sequence analysis were performed. The logistic regression analysis showed no difference in labour market participation for patients in the two groups after 1 year. Applying sequence analysis showed differences in subsequent labour market participation after 2 years after baseline in favour of the brief intervention group versus the multidisciplinary intervention group. The study indicated that sequence analysis could provide added analytical value as a supplement to traditional regression analysis in prospective studies of RTW among patients with LBP. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Unwanted sexual advances at work: variations by employment arrangement in a sample of working Australians.

PubMed

Lamontagne, Anthony D; Smith, Peter M; Louie, Amber M; Quinlan, Michael; Shoveller, Jean; Ostry, Aleck S

2009-04-01

We tested the hypothesis that the risk of experiencing unwanted sexual advances at work (UWSA) is greater for precariously-employed workers in comparison to those in permanent or continuing employment. A cross-sectional population-based telephone survey was conducted in Victoria (66% response rate, N=1,101). Employment arrangements were analysed using eight differentiated categories, as well as a four-category collapsed measure to address small cell sizes. Self-report of unwanted sexual advances at work was modelled using multiple logistic regression in relation to employment arrangement, controlling for gender, age, and occupational skill level. Forty-seven respondents reported UWSA in our sample (4.3%), mainly among women (37 of 47). Risk of UWSA was higher for younger respondents, but did not vary significantly by occupational skill level or education. In comparison to Permanent Full-Time, three employment arrangements were strongly associated with UWSA after adjustment for age, gender, and occupational skill level: Casual Full-Time OR = 7.2 (95% Confidence Interval 1.7-30.2); Fixed-Term Contract OR = 11.4 (95% CI 3.4-38.8); and Own-Account Self-Employed OR = 3.8 (95% CI 1.2-11.7). In analyses of females only, the magnitude of these associations was further increased. Respondents employed in precarious arrangements were more likely to report being exposed to UWSA, even after adjustment for age and gender. Greater protections from UWSA are likely needed for precariously employed workers.

Employment insecurity and mental health during the economic recession: An analysis of the young adult labour force in Italy.

PubMed

Fiori, Francesca; Rinesi, Francesca; Spizzichino, Daniele; Di Giorgio, Ginevra

2016-03-01

A growing body of scientific literature highlights the negative consequences of employment insecurity on several life domains. This study focuses on the young adult labour force in Italy, investigating the relationship between employment insecurity and mental health and whether this has changed after years of economic downturn. It enhances understanding by addressing differences in mental health according to several employment characteristics; and by exploring the role of respondents' economic situation and educational level. Data from a large-scale, nationally representative health survey are used to estimate the relationship between employment insecurity and the Mental Health Inventory (MHI), by means of multiple linear regressions. The study demonstrates that employment insecurity is associated with poorer mental health. Moreover, neither temporary workers nor unemployed individuals are a homogeneous group. Previous job experience is important in differentiating the mental health risks of unemployed individuals; and the effects on mental health vary according to occupational status and to the amount of time spent in a condition of insecurity. Further, the experience of financial difficulties partly explains the relationship between employment insecurity and mental health; and different mental health outcomes depend on respondents' educational level. Lastly, the risks of reporting poorer mental health were higher in 2013 than in 2005. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

The Impact of Work and Volunteer Hours on the Health of Undergraduate Students.

PubMed

Lederer, Alyssa M; Autry, Dana M; Day, Carol R T; Oswalt, Sara B

2015-01-01

To examine the impact of work and volunteer hours on 4 health issues among undergraduate college students. Full-time undergraduate students (N = 70,068) enrolled at 129 institutions who participated in the Spring 2011 American College Health Association-National College Health Assessment II survey. Multiple linear regression and binary logistic regression were used to examine work and volunteer hour impact on depression, feelings of being overwhelmed, sleep, and physical activity. The impact of work and volunteer hours was inconsistent among the health outcomes. Increased work hours tended to negatively affect sleep and increase feelings of being overwhelmed. Students who volunteered were more likely to meet physical activity guidelines, and those who volunteered 1 to 9 hours per week reported less depression. College health professionals should consider integrating discussion of students' employment and volunteering and their intersection with health outcomes into clinical visits, programming, and other services.

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

USGS Publications Warehouse

Koltun, G.F.

1985-01-01

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

Multitasking in multiple sclerosis: can it inform vocational functioning?

PubMed

Morse, Chelsea L; Schultheis, Maria T; McKeever, Joshua D; Leist, Thomas

2013-12-01

To examine associations between multitasking ability defined by performance on a complex task integrating multiple cognitive domains and vocational functioning in multiple sclerosis (MS). Survey data collection. Laboratory with referrals from an outpatient clinic. Community-dwelling individuals with MS (N=30) referred between October 2011 and June 2012. Not applicable. The modified Six Elements Test (SET) to measure multitasking ability, Fatigue Severity Scale to measure fatigue, several neuropsychological measures of executive functioning, and vocational status. Among the sample, 60% of individuals have reduced their work hours because of MS symptoms (cutback employment group) and 40% had maintained their work hours. Among both groups, SET performance was significantly associated with performance on several measures of neuropsychological functioning. Individuals in the cutback employment group demonstrated significantly worse overall performance on the SET (P=.041). Logistic regression was used to evaluate associations between SET performance and vocational status, while accounting for neuropsychological performance and fatigue. The overall model was significant (χ(2)3=8.65, P=.032), with fatigue [Exp(B)=.83, P=.01] and multitasking ability [Exp(B)=.60, P=.043] retained as significant predictors. Multitasking ability may play an important role in performance at work for individuals with MS. Given that multitasking was associated with vocational functioning, future efforts should assess the usefulness of incorporating multitasking ability into rehabilitation planning. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Predictors of transitions from single to multiple job holding: Results of a longitudinal study among employees aged 45-64 in the Netherlands.

PubMed

Bouwhuis, Stef; Geuskens, Goedele A; Boot, Cécile R L; Bongers, Paulien M; van der Beek, Allard J

2017-08-01

To construct prediction models for transitions to combination multiple job holding (MJH) (multiple jobs as an employee) and hybrid MJH (being an employee and self-employed), among employees aged 45-64. A total of 5187 employees in the Netherlands completed online questionnaires annually between 2010 and 2013. We applied logistic regression analyses with a backward elimination strategy to construct prediction models. Transitions to combination MJH and hybrid MJH were best predicted by a combination of factors including: demographics, health and mastery, work characteristics, work history, skills and knowledge, social factors, and financial factors. Not having a permanent contract and a poor household financial situation predicted both transitions. Some predictors only predicted combination MJH, e.g., working part-time, or hybrid MJH, e.g., work-home interference. A wide variety of factors predict combination MJH and/or hybrid MJH. The prediction model approach allowed for the identification of predictors that have not been previously studied. © 2017 Wiley Periodicals, Inc.

Employment status, working conditions and depressive symptoms among German employees born in 1959 and 1965.

PubMed

Burr, Hermann; Rauch, Angela; Rose, Uwe; Tisch, Anita; Tophoven, Silke

2015-08-01

We investigated whether (1) current employment status (regular full-time, regular part-time and marginal employment) is associated with depressive symptoms and (2) whether these associations are mediated by current working conditions and previous employment history. Two cohorts of German employees aged 46 and 52 years were selected from administrative data of the German Federal Employment Agency and answered questions about depressive symptoms (we use an applied version of BDI-V) and their current working conditions. In addition, the participants gave written consent to link register data regarding their employment histories (n = 4,207). Multiple linear regression analyses were conducted. Men experienced elevated depressive symptoms when working regular part-time; women experienced such symptoms when engaged in marginal employment. These associations decreased when we adjusted for job insecurity and rose slightly when we adjusted for leadership quality. Men and women who reported a low level of influence at work showed a higher risk of depressive symptoms. For women, the association between current employment position and depressive symptoms could be partly explained by low levels of influence at work. For men, the association between depressive symptoms and current regular part-time employment decreased when we adjusted for previous part-time employment. Conversely, for women, the association with depressive symptoms increased in current regular part-time and marginal employment when we adjusted for employment history. In both genders, the observed associations between depressive symptoms and current employment status were mediated by both current psychosocial conditions and employment history. Employees not having a regular full-time job differed from full-time employees with respect to both their current working conditions and their employment history.

20 CFR 345.403 - Multiple base year employers.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 20 Employees' Benefits 1 2013-04-01 2012-04-01 true Multiple base year employers. 345.403 Section... INSURANCE ACT EMPLOYERS' CONTRIBUTIONS AND CONTRIBUTION REPORTS Benefit Charging § 345.403 Multiple base... than one base year employer shall be charged to the cumulative benefit balances of such employers, as...

20 CFR 345.403 - Multiple base year employers.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 20 Employees' Benefits 1 2011-04-01 2011-04-01 false Multiple base year employers. 345.403 Section... INSURANCE ACT EMPLOYERS' CONTRIBUTIONS AND CONTRIBUTION REPORTS Benefit Charging § 345.403 Multiple base... than one base year employer shall be charged to the cumulative benefit balances of such employers, as...

20 CFR 345.403 - Multiple base year employers.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 20 Employees' Benefits 1 2012-04-01 2012-04-01 false Multiple base year employers. 345.403 Section... INSURANCE ACT EMPLOYERS' CONTRIBUTIONS AND CONTRIBUTION REPORTS Benefit Charging § 345.403 Multiple base... than one base year employer shall be charged to the cumulative benefit balances of such employers, as...

20 CFR 345.403 - Multiple base year employers.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Multiple base year employers. 345.403 Section... INSURANCE ACT EMPLOYERS' CONTRIBUTIONS AND CONTRIBUTION REPORTS Benefit Charging § 345.403 Multiple base... than one base year employer shall be charged to the cumulative benefit balances of such employers, as...

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.

Health Status of Older US Workers and Nonworkers, National Health Interview Survey, 1997-2011.

PubMed

Kachan, Diana; Fleming, Lora E; Christ, Sharon; Muennig, Peter; Prado, Guillermo; Tannenbaum, Stacey L; Yang, Xuan; Caban-Martinez, Alberto J; Lee, David J

2015-09-24

Many US workers are increasingly delaying retirement from work, which may be leading to an increase in chronic disease at the workplace. We examined the association of older adults' health status with their employment/occupation and other characteristics. National Health Interview Survey data from 1997 through 2011 were pooled for adults aged 65 or older (n = 83,338; mean age, 74.6 y). Multivariable logistic regression modeling was used to estimate the association of socioeconomic factors and health behaviors with 4 health status measures: 1) self-rated health (fair/poor vs good/very good/excellent); 2) multimorbidity (≤1 vs ≥2 chronic conditions); 3) multiple functional limitations (≤1 vs ≥2); and 4) Health and Activities Limitation Index (HALex) (below vs above 20th percentile). Analyses were stratified by sex and age (young-old vs old-old) where interactions with occupation were significant. Employed older adults had better health outcomes than unemployed older adults. Physically demanding occupations had the lowest risk of poor health outcomes, suggesting a stronger healthy worker effect: service workers were at lowest risk of multiple functional limitations (odds ratio [OR], 0.82; 95% confidence interval [CI], 0.71-0.95); and blue-collar workers were at lowest risk of multimorbidity (OR, 0.84; 95% CI, 0.74-0.97) and multiple functional limitation (OR, 0.84; 95% CI, 0.72-0.98). Hispanics were more likely than non-Hispanic whites to report fair/poor health (OR, 1.62; 95% CI, 1.52-1.73) and lowest HALex quintile (OR, 1.21; 95% CI, 1.13-1.30); however, they were less likely to report multimorbidity (OR, 0.78; 95% CI, 0.73-0.83) or multiple functional limitations (OR, 0.82; 95% CI, 0.77-0.88). A strong association exists between employment and health status in older adults beyond what can be explained by socioeconomic factors (eg, education, income) or health behaviors (eg, smoking). Disability accommodations in the workplace could encourage employment among older adults with limitations.

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…

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

PubMed

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

2014-01-01

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

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)

Determination of biodiesel content in biodiesel/diesel blends using NIR and visible spectroscopy with variable selection.

PubMed

Fernandes, David Douglas Sousa; Gomes, Adriano A; Costa, Gean Bezerra da; Silva, Gildo William B da; Véras, Germano

2011-12-15

This work is concerned of evaluate the use of visible and near-infrared (NIR) range, separately and combined, to determine the biodiesel content in biodiesel/diesel blends using Multiple Linear Regression (MLR) and variable selection by Successive Projections Algorithm (SPA). Full spectrum models employing Partial Least Squares (PLS) and variables selection by Stepwise (SW) regression coupled with Multiple Linear Regression (MLR) and PLS models also with variable selection by Jack-Knife (Jk) were compared the proposed methodology. Several preprocessing were evaluated, being chosen derivative Savitzky-Golay with second-order polynomial and 17-point window for NIR and visible-NIR range, with offset correction. A total of 100 blends with biodiesel content between 5 and 50% (v/v) prepared starting from ten sample of biodiesel. In the NIR and visible region the best model was the SPA-MLR using only two and eight wavelengths with RMSEP of 0.6439% (v/v) and 0.5741 respectively, while in the visible-NIR region the best model was the SW-MLR using five wavelengths and RMSEP of 0.9533% (v/v). Results indicate that both spectral ranges evaluated showed potential for developing a rapid and nondestructive method to quantify biodiesel in blends with mineral diesel. Finally, one can still mention that the improvement in terms of prediction error obtained with the procedure for variables selection was significant. Copyright © 2011 Elsevier B.V. All rights reserved.

Multiple Ordinal Regression by Maximizing the Sum of Margins

PubMed Central

Hamsici, Onur C.; Martinez, Aleix M.

2016-01-01

Human preferences are usually measured using ordinal variables. A system whose goal is to estimate the preferences of humans and their underlying decision mechanisms requires to learn the ordering of any given sample set. We consider the solution of this ordinal regression problem using a Support Vector Machine algorithm. Specifically, the goal is to learn a set of classifiers with common direction vectors and different biases correctly separating the ordered classes. Current algorithms are either required to solve a quadratic optimization problem, which is computationally expensive, or are based on maximizing the minimum margin (i.e., a fixed margin strategy) between a set of hyperplanes, which biases the solution to the closest margin. Another drawback of these strategies is that they are limited to order the classes using a single ranking variable (e.g., perceived length). In this paper, we define a multiple ordinal regression algorithm based on maximizing the sum of the margins between every consecutive class with respect to one or more rankings (e.g., perceived length and weight). We provide derivations of an efficient, easy-to-implement iterative solution using a Sequential Minimal Optimization procedure. We demonstrate the accuracy of our solutions in several datasets. In addition, we provide a key application of our algorithms in estimating human subjects’ ordinal classification of attribute associations to object categories. We show that these ordinal associations perform better than the binary one typically employed in the literature. PMID:26529784

The Association between Job-Related Psychosocial Factors and Prolonged Fatigue among Industrial Employees in Taiwan

PubMed Central

Tang, Feng-Cheng; Li, Ren-Hau; Huang, Shu-Ling

2016-01-01

Background and Objectives Prolonged fatigue is common among employees, but the relationship between prolonged fatigue and job-related psychosocial factors is seldom studied. This study aimed (1) to assess the individual relations of physical condition, psychological condition, and job-related psychosocial factors to prolonged fatigue among employees, and (2) to clarify the associations between job-related psychosocial factors and prolonged fatigue using hierarchical regression when demographic characteristics, physical condition, and psychological condition were controlled. Methods A cross-sectional study was employed. A questionnaire was used to obtain information pertaining to demographic characteristics, physical condition (perceived physical health and exercise routine), psychological condition (perceived mental health and psychological distress), job-related psychosocial factors (job demand, job control, and workplace social support), and prolonged fatigue. Results A total of 3,109 employees were recruited. Using multiple regression with controlled demographic characteristics, psychological condition explained 52.0% of the variance in prolonged fatigue. Physical condition and job-related psychosocial factors had an adjusted R2 of 0.370 and 0.251, respectively. Hierarchical multiple regression revealed that, among job-related psychosocial factors, job demand and job control showed significant associations with fatigue. Conclusion Our findings highlight the role of job demand and job control, in addition to the role of perceived physical health, perceived mental health, and psychological distress, in workers’ prolonged fatigue. However, more research is required to verify the causation among all the variables. PMID:26930064

Parental restriction reduces the harmful effects of in-bedroom electronic devices.

PubMed

Fu, King-Wa; Ho, Frederick Ka Wing; Rao, Nirmala; Jiang, Fan; Li, Sophia Ling; Lee, Tatia Mei-Chun; Chan, Sophelia Hoi-Shan; Yung, Ada Wing-Yan; Young, Mary Eming; Ip, Patrick

2017-12-01

To investigate whether school readiness could be affected by placing electronic devices (EDs) in children's bedroom and whether the relationship was moderated by parental restriction and family socioeconomic status (SES). This is a cross-sectional study with bedroom ED placement and parental restriction reported by parents. Multiple linear regressions were used to test the relationship between school readiness and ED placement. Multiple regression with interaction terms were used to test whether the effect was consistent with and without parental restriction. Kindergartens randomly selected from two districts of different socioeconomic backgrounds in Hong Kong, China. 556 young children attending the third year of kindergarten. Children's school readiness was rated by teachers using the Chinese Early Development Instrument. 556 preschoolers (mean age 5.46; 51.8% girls) from 20 kindergartens participated in this study. About 30% of parents placed at least one ED in their children's bedroom. After controlling for sex and SES, the placement of television in the bedroom was associated with lower overall school readiness (β -1.11, 95% CI -1.80 to -0.42) and the placement of game console was associated with lower social competence (β-0.94, 95% CI -1.74 to -0.15). Such harmful effect was more prominent among lower SES families and could be partially alleviated with parental restriction. ED placement in children's bedroom was associated with lower school readiness, particularly among lower SES families. Parental restriction might help to alleviate the harm. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Multiscale characterization and prediction of monsoon rainfall in India using Hilbert-Huang transform and time-dependent intrinsic correlation analysis

NASA Astrophysics Data System (ADS)

Adarsh, S.; Reddy, M. Janga

2017-07-01

In this paper, the Hilbert-Huang transform (HHT) approach is used for the multiscale characterization of All India Summer Monsoon Rainfall (AISMR) time series and monsoon rainfall time series from five homogeneous regions in India. The study employs the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for multiscale decomposition of monsoon rainfall in India and uses the Normalized Hilbert Transform and Direct Quadrature (NHT-DQ) scheme for the time-frequency characterization. The cross-correlation analysis between orthogonal modes of All India monthly monsoon rainfall time series and that of five climate indices such as Quasi Biennial Oscillation (QBO), El Niño Southern Oscillation (ENSO), Sunspot Number (SN), Atlantic Multi Decadal Oscillation (AMO), and Equatorial Indian Ocean Oscillation (EQUINOO) in the time domain showed that the links of different climate indices with monsoon rainfall are expressed well only for few low-frequency modes and for the trend component. Furthermore, this paper investigated the hydro-climatic teleconnection of ISMR in multiple time scales using the HHT-based running correlation analysis technique called time-dependent intrinsic correlation (TDIC). The results showed that both the strength and nature of association between different climate indices and ISMR vary with time scale. Stemming from this finding, a methodology employing Multivariate extension of EMD and Stepwise Linear Regression (MEMD-SLR) is proposed for prediction of monsoon rainfall in India. The proposed MEMD-SLR method clearly exhibited superior performance over the IMD operational forecast, M5 Model Tree (MT), and multiple linear regression methods in ISMR predictions and displayed excellent predictive skill during 1989-2012 including the four extreme events that have occurred during this period.

Education and health and well-being: direct and indirect effects with multiple mediators and interactions with multiple imputed data in Stata.

PubMed

Sheikh, Mashhood Ahmed; Abelsen, Birgit; Olsen, Jan Abel

2017-11-01

Previous methods for assessing mediation assume no multiplicative interactions. The inverse odds weighting (IOW) approach has been presented as a method that can be used even when interactions exist. The substantive aim of this study was to assess the indirect effect of education on health and well-being via four indicators of adult socioeconomic status (SES): income, management position, occupational hierarchy position and subjective social status. 8516 men and women from the Tromsø Study (Norway) were followed for 17 years. Education was measured at age 25-74 years, while SES and health and well-being were measured at age 42-91 years. Natural direct and indirect effects (NIE) were estimated using weighted Poisson regression models with IOW. Stata code is provided that makes it easy to assess mediation in any multiple imputed dataset with multiple mediators and interactions. Low education was associated with lower SES. Consequently, low SES was associated with being unhealthy and having a low level of well-being. The effect (NIE) of education on health and well-being is mediated by income, management position, occupational hierarchy position and subjective social status. This study contributes to the literature on mediation analysis, as well as the literature on the importance of education for health-related quality of life and subjective well-being. The influence of education on health and well-being had different pathways in this Norwegian sample. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Job quality and inequality: parents' jobs and children's emotional and behavioural difficulties.

PubMed

Strazdins, Lyndall; Shipley, Megan; Clements, Mark; Obrien, Léan V; Broom, Dorothy H

2010-06-01

In the context of high and rising rates of parental employment in Australia, we investigated whether poor quality jobs (without security, control, flexibility or paid family leave) could pose a health risk to employed parents' children. We examined the extent to which both mothers' and fathers' jobs matter, and whether disadvantaged children are more vulnerable than others. Multiple regression modelling was used to analyse cross-sectional data for 2004 from the Growing Up in Australia study, a nationally representative sample of 4-5 year old children and their families (N = 2373 employed mothers; 3026 employed fathers). Results revealed that when parents held poor quality jobs their children showed more emotional and behavioural difficulties. The associations with child difficulties were independent of income, parent education, family structure and work hours, and were evident for both mothers' and fathers' jobs. Further, the associations tended to be stronger for children in low-income households and lone-mother families. Thus job quality may be another mechanism underlying the intergenerational transmission of health inequality. Our findings also support the argument that a truly family-friendly job must not erode children's health. Copyright 2010 Elsevier Ltd. All rights reserved.

Social Networks of Lesbian, Gay, Bisexual, and Transgender Older Adults

PubMed Central

Erosheva, Elena A.; Kim, Hyun-Jun; Emlet, Charles; Fredriksen-Goldsen, Karen I.

2015-01-01

Purpose This study examines global social networks—including friendship, support, and acquaintance networks—of lesbian, gay, bisexual, and transgender (LGBT) older adults. Design and Methods Utilizing data from a large community-based study, we employ multiple regression analyses to examine correlates of social network size and diversity. Results Controlling for background characteristics, network size was positively associated with being female, transgender identity, employment, higher income, having a partner or a child, identity disclosure to a neighbor, engagement in religious activities, and service use. Controlling in addition for network size, network diversity was positively associated with younger age, being female, transgender identity, identity disclosure to a friend, religious activity, and service use. Implications According to social capital theory, social networks provide a vehicle for social resources that can be beneficial for successful aging and well-being. This study is a first step at understanding the correlates of social network size and diversity among LGBT older adults. PMID:25882129

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.

Reexamining the arthritis-employment interface: perceptions of arthritis-work spillover among employed adults.

PubMed

Gignac, Monique A M; Sutton, Deborah; Badley, Elizabeth M

2006-04-15

To examine employed individuals' perceptions of arthritis-work spillover (AWS), the reciprocal influence of arthritis on work and work on arthritis, and the demographic, illness, and work context factors associated with AWS. The study group comprised 492 employed individuals with osteoarthritis or inflammatory arthritis. Participants completed an interview-administered, structured questionnaire assessing AWS, demographic (e.g., age, sex), illness (e.g., disease type, pain, activity limitations), and work context (e.g., workplace control, hours of work) variables. Principal components analysis, reliability analysis, and multiple linear regression were used to analyze the data. A single factor solution emerged for AWS. The scale had an internal reliability of 0.88. Respondents were more likely to report that work interfered with caring for their arthritis than they were to report that their disease affected their work performance. Younger respondents, those with more fatigue and workplace activity limitations, and those working in trades and transportation reported more AWS. Individuals with more control over their work schedules reported less AWS. The results of this study extend research on arthritis by reexamining the interface between arthritis and employment. This study introduces a new measure of AWS that enhances the range of tools available to researchers and clinicians examining the impact of arthritis in individuals' lives.

Development of a noise prediction model based on advanced fuzzy approaches in typical industrial workrooms.

PubMed

Aliabadi, Mohsen; Golmohammadi, Rostam; Khotanlou, Hassan; Mansoorizadeh, Muharram; Salarpour, Amir

2014-01-01

Noise prediction is considered to be the best method for evaluating cost-preventative noise controls in industrial workrooms. One of the most important issues is the development of accurate models for analysis of the complex relationships among acoustic features affecting noise level in workrooms. In this study, advanced fuzzy approaches were employed to develop relatively accurate models for predicting noise in noisy industrial workrooms. The data were collected from 60 industrial embroidery workrooms in the Khorasan Province, East of Iran. The main acoustic and embroidery process features that influence the noise were used to develop prediction models using MATLAB software. Multiple regression technique was also employed and its results were compared with those of fuzzy approaches. Prediction errors of all prediction models based on fuzzy approaches were within the acceptable level (lower than one dB). However, Neuro-fuzzy model (RMSE=0.53dB and R2=0.88) could slightly improve the accuracy of noise prediction compared with generate fuzzy model. Moreover, fuzzy approaches provided more accurate predictions than did regression technique. The developed models based on fuzzy approaches as useful prediction tools give professionals the opportunity to have an optimum decision about the effectiveness of acoustic treatment scenarios in embroidery workrooms.

Socioeconomic determinants of childhood overweight and obesity in China: the long arm of institutional power.

PubMed

Fu, Qiang; George, Linda K

2015-07-01

Previous studies have widely reported that the association between socioeconomic status (SES) and childhood overweight and obesity in China is significant and positive, which lends little support to the fundamental-cause perspective. Using multiple waves (1997, 2000, 2004 and 2006) of the China Health and Nutrition Survey (CHNS) (N = 2,556, 2,063, 1,431 and 1,242, respectively) and continuous BMI cut-points obtained from a polynomial method, (mixed-effect) logistic regression analyses show that parental state-sector employment, an important, yet overlooked, indicator of political power during the market transformation has changed from a risk factor for childhood overweight/obesity in 1997 to a protective factor for childhood overweight/obesity in 2006. Results from quantile regression analyses generate the same conclusions and demonstrate that the protective effect of parental state sector employment at high percentiles of BMI is robust under different estimation strategies. By bridging the fundamental causes perspective and theories of market transformation, this research not only documents the effect of political power on childhood overweight/obesity but also calls for the use of multifaceted, culturally-relevant stratification measures in testing the fundamental cause perspective across time and space. © 2015 Foundation for the Sociology of Health & Illness.

Worklife expectancies of fixed-term Finnish employees in 1997-2006.

PubMed

Nurminen, Markku

2008-04-01

Fixed-term employment is prevalent in the Finnish labor force. This form of employment contract is marked by fragmentary work periods, demands for flexibility in workhours, and concern for multiple insecurities. A nonpermanent employee may also incur adverse health consequences. Yet there exist no exact statistics on the duration of fixed-term employment. This paper estimated the future duration of the time that a Finn is expected to be engaged in irregular work. Multistate regression modeling and stochastic analysis were applied to aggregated data from surveys conducted among the labor force by Statistics Finland in 1997-2006. In 2006, a Finnish male was expected to work a total of 3.8 years in fixed-term employment, combined over consecutive or separate time spans; this time amounts to 8% of his remaining work career from entry into the work force until final retirement. For a woman the expectancy was greater, 6.5 years or 13%. For the age interval 20-29 years, the total was 16% for men and 23% for women. The type and duration of employment is influenced by security factors and economic cycles, both of which affect men and women differently. Over the past decade, fixed-term employment increased consistently in the female labor contingent, and it was more pronounced during economic slowdowns. This labor market development calls for standards for flexibility and guarantees for security in the fragmented future worklives of fixed-term employees.

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

Across-Platform Imputation of DNA Methylation Levels Incorporating Nonlocal Information Using Penalized Functional Regression.

PubMed

Zhang, Guosheng; Huang, Kuan-Chieh; Xu, Zheng; Tzeng, Jung-Ying; Conneely, Karen N; Guan, Weihua; Kang, Jian; Li, Yun

2016-05-01

DNA methylation is a key epigenetic mark involved in both normal development and disease progression. Recent advances in high-throughput technologies have enabled genome-wide profiling of DNA methylation. However, DNA methylation profiling often employs different designs and platforms with varying resolution, which hinders joint analysis of methylation data from multiple platforms. In this study, we propose a penalized functional regression model to impute missing methylation data. By incorporating functional predictors, our model utilizes information from nonlocal probes to improve imputation quality. Here, we compared the performance of our functional model to linear regression and the best single probe surrogate in real data and via simulations. Specifically, we applied different imputation approaches to an acute myeloid leukemia dataset consisting of 194 samples and our method showed higher imputation accuracy, manifested, for example, by a 94% relative increase in information content and up to 86% more CpG sites passing post-imputation filtering. Our simulated association study further demonstrated that our method substantially improves the statistical power to identify trait-associated methylation loci. These findings indicate that the penalized functional regression model is a convenient and valuable imputation tool for methylation data, and it can boost statistical power in downstream epigenome-wide association study (EWAS). © 2016 WILEY PERIODICALS, INC.

How to address data gaps in life cycle inventories: a case study on estimating CO2 emissions from coal-fired electricity plants on a global scale.

PubMed

Steinmann, Zoran J N; Venkatesh, Aranya; Hauck, Mara; Schipper, Aafke M; Karuppiah, Ramkumar; Laurenzi, Ian J; Huijbregts, Mark A J

2014-05-06

One of the major challenges in life cycle assessment (LCA) is the availability and quality of data used to develop models and to make appropriate recommendations. Approximations and assumptions are often made if appropriate data are not readily available. However, these proxies may introduce uncertainty into the results. A regression model framework may be employed to assess missing data in LCAs of products and processes. In this study, we develop such a regression-based framework to estimate CO2 emission factors associated with coal power plants in the absence of reported data. Our framework hypothesizes that emissions from coal power plants can be explained by plant-specific factors (predictors) that include steam pressure, total capacity, plant age, fuel type, and gross domestic product (GDP) per capita of the resident nations of those plants. Using reported emission data for 444 plants worldwide, plant level CO2 emission factors were fitted to the selected predictors by a multiple linear regression model and a local linear regression model. The validated models were then applied to 764 coal power plants worldwide, for which no reported data were available. Cumulatively, available reported data and our predictions together account for 74% of the total world's coal-fired power generation capacity.

The More, the Better?! Multiple vs. Single Jobholders’ Job Satisfaction as a Matter of Lacked Information

PubMed Central

Kottwitz, Maria U.; Hünefeld, Lena; Frank, Benjamin P.; Otto, Kathleen

2017-01-01

In recent decades, the working world has changed dramatically and rising demands on flexibility make the coordination of personal and professional life more difficult. Therefore, it is important that the incumbents are in possession of all necessary information concerning their job. This might be a key issue to remain satisfied. Simultaneously, atypical forms of employment have substantially increased in the labor market; one such form is holding more than one job. While the motives might differ from needing an additional income to broadening job opportunities, practicing several jobs requires coordination and thus, being informed. Building on research regarding organizational constraints and role ambiguity, we hypothesize that the paucity of information is negatively related to (dimensions of) job satisfaction. This effect should be stronger for multiple as compared to single jobbers; specifically when considering the job satisfaction with the social climate, given that being informed by others is an important factor in the coordination of several jobs. Data taken from the BiBB/BAuA-Employment-Survey provide a sample of 17,782 German employees (54% women), including 1,084 multiple jobbers (59% women). Job satisfaction was measured as employees global satisfaction and their satisfaction with facets dimensions: the social climate, structural working conditions, personal growth opportunities, and material incentives they receive for their work. Paucity of information was measured by the frequency of lacked information. Our study indicated that paucity of information was negatively related to both, global and all facets dimensions of job satisfaction. Multiple regression analyses further revealed interaction effects of paucity of information and form of employment. Specifically, the negative correlation of paucity of information with global as well as satisfaction with the social climate was stronger for employees’ holding more than one job. These results were independent of age, gender, organizational tenure, working hours, socioeconomic occupational status, as well as important working conditions (workload and autonomy). Incumbents with less paucity of necessary job-related information are more satisfied, especially when they hold multiple jobs. Supervisors and colleagues are advised to provide all necessary information and to ensure that employees retain it. PMID:28798709

The More, the Better?! Multiple vs. Single Jobholders' Job Satisfaction as a Matter of Lacked Information.

PubMed

Kottwitz, Maria U; Hünefeld, Lena; Frank, Benjamin P; Otto, Kathleen

2017-01-01

In recent decades, the working world has changed dramatically and rising demands on flexibility make the coordination of personal and professional life more difficult. Therefore, it is important that the incumbents are in possession of all necessary information concerning their job. This might be a key issue to remain satisfied. Simultaneously, atypical forms of employment have substantially increased in the labor market; one such form is holding more than one job. While the motives might differ from needing an additional income to broadening job opportunities, practicing several jobs requires coordination and thus, being informed. Building on research regarding organizational constraints and role ambiguity, we hypothesize that the paucity of information is negatively related to (dimensions of) job satisfaction. This effect should be stronger for multiple as compared to single jobbers; specifically when considering the job satisfaction with the social climate, given that being informed by others is an important factor in the coordination of several jobs. Data taken from the BiBB/BAuA-Employment-Survey provide a sample of 17,782 German employees (54% women), including 1,084 multiple jobbers (59% women). Job satisfaction was measured as employees global satisfaction and their satisfaction with facets dimensions: the social climate, structural working conditions, personal growth opportunities, and material incentives they receive for their work. Paucity of information was measured by the frequency of lacked information. Our study indicated that paucity of information was negatively related to both, global and all facets dimensions of job satisfaction. Multiple regression analyses further revealed interaction effects of paucity of information and form of employment. Specifically, the negative correlation of paucity of information with global as well as satisfaction with the social climate was stronger for employees' holding more than one job. These results were independent of age, gender, organizational tenure, working hours, socioeconomic occupational status, as well as important working conditions (workload and autonomy). Incumbents with less paucity of necessary job-related information are more satisfied, especially when they hold multiple jobs. Supervisors and colleagues are advised to provide all necessary information and to ensure that employees retain it.

Comparison of the Relationship between Women' Empowerment and Fertility between Single-child and Multi-child Families

PubMed Central

Saberi, Tahereh; Ehsanpour, Soheila; Mahaki, Behzad; Kohan, Shahnaz

2018-01-01

Background: The reduction in fertility and increase in the number of single-child families in Iran will result in an increased risk of population aging. One of the factors affecting fertility is women's empowerment. This study aimed to evaluate the relationship between women's empowerment and fertility in single-child and multi-child families. Materials and Methods: This case-control study was conducted among 350 women (120 who had only 1 child as case group and 230 who had 2 or more children as control group) of 15–49 years of age in Isfahan, Iran, in 2016. For data collection, a 2-part questionnaire was designed. Data were analyzed using independent t-test, Chi-square test, and logistic regression analysis. Results: The difference between average scores of women's empowerment in the case group 54.08 (9.88) and control group 51.47 (8.57) was significant (p = 0.002). Simple logistic regression analysis showed that under diploma education, compared to postgraduate education, (OR = 0.21, p = 0.001) and being a housewife, compared to being employed, (OR = 0.45, p = 0.004) decreased the odds of having only 1 child. Multiple logistic regression results showed that the relationship between women's empowerment and fertility was not significant (p = 0.265). Conclusions: Although women in single-child families were more empowered, this was not the main reason for their preference to have only 1 child. In fact, educated and employed women postpone marriage and childbearing and limit fertility to only 1 child despite their desire. PMID:29628961

Characterization of the spatial variability of soil available zinc at various sampling densities using grouped soil type information.

PubMed

Song, Xiao-Dong; Zhang, Gan-Lin; Liu, Feng; Li, De-Cheng; Zhao, Yu-Guo

2016-11-01

The influence of anthropogenic activities and natural processes involved high uncertainties to the spatial variation modeling of soil available zinc (AZn) in plain river network regions. Four datasets with different sampling densities were split over the Qiaocheng district of Bozhou City, China. The difference of AZn concentrations regarding soil types was analyzed by the principal component analysis (PCA). Since the stationarity was not indicated and effective ranges of four datasets were larger than the sampling extent (about 400 m), two investigation tools, namely F3 test and stationarity index (SI), were employed to test the local non-stationarity. Geographically weighted regression (GWR) technique was performed to describe the spatial heterogeneity of AZn concentrations under the non-stationarity assumption. GWR based on grouped soil type information (GWRG for short) was proposed so as to benefit the local modeling of soil AZn within each soil-landscape unit. For reference, the multiple linear regression (MLR) model, a global regression technique, was also employed and incorporated the same predictors as in the GWR models. Validation results based on 100 times realization demonstrated that GWRG outperformed MLR and can produce similar or better accuracy than the GWR approach. Nevertheless, GWRG can generate better soil maps than GWR for limit soil data. Two-sample t test of produced soil maps also confirmed significantly different means. Variogram analysis of the model residuals exhibited weak spatial correlation, rejecting the use of hybrid kriging techniques. As a heuristically statistical method, the GWRG was beneficial in this study and potentially for other soil properties.

Stress and coping as predictors of children's divorce-related ruminations.

PubMed

Weyer, M; Sandler, I N

1998-03-01

Examined stress and coping variables as predictors of divorce-related ruminations in children whose parents had recently divorced. Simultaneous multiple regression was used to analyze the cross-sectional data of 351 children of divorce. Divorce-related stressful events and threat appraisal were positively related to children's ruminations. A prospective longitudinal design was employed to predict rumination at Time 2 (T2) controlling for Time 1 (T1) rumination. Efficacy of coping was negatively related to T2 rumination after controlling for T1 rumination and all other predictors. This study also provided descriptive data on the frequency of children's divorce-related ruminations.

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.

[The importance of handprint morphometry for determining the human body length].

PubMed

Grigor'eva, M A

2018-01-01

Handprint morphometry for the purpose of personality identification still remains a relatively novel approach. The methods employed for the measurements are not infrequently difficult to reproduce and therefore cause controversy. The objective of the present study was to introduce the system of methods for the measurement of handprints suitable for the reliable determination of the human body length. The study included the measurement of the size of 40 handprints left by124 adult subjects (52 men and 72 women). Two methods of the regression analysis, stepwise and forced inclusion, were applied to the combined group of handprints to select the equations with the high (R>0.800) coefficients of multiple correlation with the body length. 13 equations of multiple regression were obtained and analyzed. The standard error of estimating (SEE) varied from 4.30 to 5.19 cm. The best results were obtained with the equations constructed from the sizes I, II, and III of the rays without their distal phalanges. It was shown that the body length can be successfully reconstructed within the height range from 168 to 183 cm for men and from 157 to 176 cm for women. The examples of the use of the equations for the purpose of expertise of illegible and incomplete handprints are presented.

Response of dissolved trace metals to land use/land cover and their source apportionment using a receptor model in a subtropic river, China.

PubMed

Li, Siyue; Zhang, Quanfa

2011-06-15

Water samples were collected for determination of dissolved trace metals in 56 sampling sites throughout the upper Han River, China. Multivariate statistical analyses including correlation analysis, stepwise multiple linear regression models, and principal component and factor analysis (PCA/FA) were employed to examine the land use influences on trace metals, and a receptor model of factor analysis-multiple linear regression (FA-MLR) was used for source identification/apportionment of anthropogenic heavy metals in the surface water of the River. Our results revealed that land use was an important factor in water metals in the snow melt flow period and land use in the riparian zone was not a better predictor of metals than land use away from the river. Urbanization in a watershed and vegetation along river networks could better explain metals, and agriculture, regardless of its relative location, however slightly explained metal variables in the upper Han River. FA-MLR analysis identified five source types of metals, and mining, fossil fuel combustion, and vehicle exhaust were the dominant pollutions in the surface waters. The results demonstrated great impacts of human activities on metal concentrations in the subtropical river of China. Copyright © 2011 Elsevier B.V. All rights reserved.

Association between the Type of Workplace and Lung Function in Copper Miners

PubMed Central

Gruszczyński, Leszek; Wojakowska, Anna; Ścieszka, Marek; Turczyn, Barbara; Schmidt, Edward

2016-01-01

The aim of the analysis was to retrospectively assess changes in lung function in copper miners depending on the type of workplace. In the groups of 225 operators, 188 welders, and 475 representatives of other jobs, spirometry was performed at the start of employment and subsequently after 10, 20, and 25 years of work. Spirometry Longitudinal Data Analysis software was used to estimate changes in group means for FEV1 and FVC. Multiple linear regression analysis was used to assess an association between workplace and lung function. Lung function assessed on the basis of calculation of longitudinal FEV1 (FVC) decline was similar in all studied groups. However, multiple linear regression model used in cross-sectional analysis revealed an association between workplace and lung function. In the group of welders, FEF75 was lower in comparison to operators and other miners as early as after 10 years of work. Simultaneously, in smoking welders, the FEV1/FVC ratio was lower than in nonsmokers (p < 0,05). The interactions between type of workplace and smoking (p < 0,05) in their effect on FVC, FEV1, PEF, and FEF50 were shown. Among underground working copper miners, the group of smoking welders is especially threatened by impairment of lung ventilatory function. PMID:27274987

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…

Determining the in-hospital cost of bleeding in patients undergoing percutaneous coronary intervention.

PubMed

Ewen, Edward F; Zhao, Liping; Kolm, Paul; Jurkovitz, Claudine; Fidan, Dogan; White, Harvey D; Gallo, Richard; Weintraub, William S

2009-06-01

The economic impact of bleeding in the setting of nonemergent percutaneous coronary intervention (PCI) is poorly understood and complicated by the variety of bleeding definitions currently employed. This retrospective analysis examines and contrasts the in-hospital cost of bleeding associated with this procedure using six bleeding definitions employed in recent clinical trials. All nonemergent PCI cases at Christiana Care Health System not requiring a subsequent coronary artery bypass were identified between January 2003 and March 2006. Bleeding events were identified by chart review, registry, laboratory, and administrative data. A microcosting strategy was applied utilizing hospital charges converted to costs using departmental level direct cost-to-charge ratios. The independent contributions of bleeding, both major and minor, to cost were determined by multiple regression. Bootstrap methods were employed to obtain estimates of regression parameters and their standard errors. A total of 6,008 cases were evaluated. By GUSTO definitions there were 65 (1.1%) severe, 52 (0.9%) moderate, and 321 (5.3%) mild bleeding episodes with estimated bleeding costs of $14,006; $6,980; and $4,037, respectively. When applying TIMI definitions there were 91 (1.5%) major and 178 (3.0%) minor bleeding episodes with estimated costs of $8,794 and $4,310, respectively. In general, the four additional trial-specific definitions identified more bleeding events, provided lower estimates of major bleeding cost, and similar estimates of minor bleeding costs. Bleeding is associated with considerable cost over and above interventional procedures; however, the choice of bleeding definition impacts significantly on both the incidence and economic consequences of these events.

Predicting quality of life in multiple sclerosis: accounting for physical disability, fatigue, cognition, mood disorder, personality, and behavior change.

PubMed

Benedict, Ralph H B; Wahlig, Elizabeth; Bakshi, Rohit; Fishman, Inna; Munschauer, Frederick; Zivadinov, Robert; Weinstock-Guttman, Bianca

2005-04-15

Health-related quality of life (HQOL) is poor in multiple sclerosis (MS) but the clinical precipitants of the problem are not well understood. Previous correlative studies demonstrated relationships between various clinical parameters and diminished HQOL in MS. Unfortunately, these studies failed to account for multiple predictors in the same analysis. We endeavored to determine what clinical parameters account for most variance in predicting HQOL, and employability, while accounting for disease course, physical disability, fatigue, cognition, mood disorder, personality, and behavior disorder. In 120 MS patients, we measured HQOL (MS Quality of Life-54) and vocational status (employed vs. disabled) and then conducted detailed clinical testing. Data were analyzed by linear and logistic regression methods. MS patients reported lower HQOL (p<0.001) and were more likely to be disabled (45% of patients vs. 0 controls). Physical HQOL was predicted by fatigue, depression, and physical disability. Mental HQOL was associated with only depression and fatigue. In contrast, vocational status was predicted by three cognitive tests, conscientiousness, and disease duration (p<0.05). Thus, for the first time, we predicted HQOL in MS while accounting for measures from these many clinical domains. We conclude that self-report HQOL indices are most strongly predicted by measures of depression, whereas vocational status is predicted primarily by objective measures of cognitive function. The findings highlight core clinical problems that merit early identification and further research regarding the development of effective treatment.

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)

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.

4D-LQTA-QSAR and docking study on potent Gram-negative specific LpxC inhibitors: a comparison to CoMFA modeling.

PubMed

Ghasemi, Jahan B; Safavi-Sohi, Reihaneh; Barbosa, Euzébio G

2012-02-01

A quasi 4D-QSAR has been carried out on a series of potent Gram-negative LpxC inhibitors. This approach makes use of the molecular dynamics (MD) trajectories and topology information retrieved from the GROMACS package. This new methodology is based on the generation of a conformational ensemble profile, CEP, for each compound instead of only one conformation, followed by the calculation intermolecular interaction energies at each grid point considering probes and all aligned conformations resulting from MD simulations. These interaction energies are independent variables employed in a QSAR analysis. The comparison of the proposed methodology to comparative molecular field analysis (CoMFA) formalism was performed. This methodology explores jointly the main features of CoMFA and 4D-QSAR models. Step-wise multiple linear regression was used for the selection of the most informative variables. After variable selection, multiple linear regression (MLR) and partial least squares (PLS) methods used for building the regression models. Leave-N-out cross-validation (LNO), and Y-randomization were performed in order to confirm the robustness of the model in addition to analysis of the independent test set. Best models provided the following statistics: [Formula in text] (PLS) and [Formula in text] (MLR). Docking study was applied to investigate the major interactions in protein-ligand complex with CDOCKER algorithm. Visualization of the descriptors of the best model helps us to interpret the model from the chemical point of view, supporting the applicability of this new approach in rational drug design.

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.

Evaluating construct validity of the second version of the Copenhagen Psychosocial Questionnaire through analysis of differential item functioning and differential item effect.

PubMed

Bjorner, Jakob Bue; Pejtersen, Jan Hyld

2010-02-01

To evaluate the construct validity of the Copenhagen Psychosocial Questionnaire II (COPSOQ II) by means of tests for differential item functioning (DIF) and differential item effect (DIE). We used a Danish general population postal survey (n = 4,732 with 3,517 wage earners) with a one-year register based follow up for long-term sickness absence. DIF was evaluated against age, gender, education, social class, public/private sector employment, and job type using ordinal logistic regression. DIE was evaluated against job satisfaction and self-rated health (using ordinal logistic regression), against depressive symptoms, burnout, and stress (using multiple linear regression), and against long-term sick leave (using a proportional hazards model). We used a cross-validation approach to counter the risk of significant results due to multiple testing. Out of 1,052 tests, we found 599 significant instances of DIF/DIE, 69 of which showed both practical and statistical significance across two independent samples. Most DIF occurred for job type (in 20 cases), while we found little DIF for age, gender, education, social class and sector. DIE seemed to pertain to particular items, which showed DIE in the same direction for several outcome variables. The results allowed a preliminary identification of items that have a positive impact on construct validity and items that have negative impact on construct validity. These results can be used to develop better shortform measures and to improve the conceptual framework, items and scales of the COPSOQ II. We conclude that tests of DIF and DIE are useful for evaluating construct validity.

Association between being employed in a smoke-free workplace and living in a smoke-free home: evidence from 15 low and middle income countries.

PubMed

Nazar, Gaurang P; Lee, John Tayu; Glantz, Stanton A; Arora, Monika; Pearce, Neil; Millett, Christopher

2014-02-01

To assess whether being employed in a smoke-free workplace is associated with living in a smoke-free home in 15 low and middle income countries (LMICs). Country-specific individual level analyses of cross-sectional Global Adult Tobacco Survey data (2008-2011) from 15 LMICs was conducted using multiple logistic regression. The dependent variable was living in a smoke-free home; the independent variable was being employed in a smoke-free workplace. Analyses were adjusted for age, gender, residence, region, education, occupation, current smoking, current smokeless tobacco use and number of household members. Individual country results were combined in a random effects meta-analysis. In each country, the percentage of participants employed in a smoke-free workplace who reported living in a smoke-free home was higher than those employed in a workplace not smoke-free. The adjusted odds ratios (AORs) of living in a smoke-free home among participants employed in a smoke-free workplace (vs. those employed where smoking occurred) were statistically significant in 13 of the 15 countries, ranging from 1.12 [95% CI 0.79-1.58] in Uruguay to 2.29 [1.37-3.83] in China. The pooled AOR was 1.61 [1.46-1.79]. In LMICs, employment in a smoke-free workplace is associated with living in a smoke-free home. Accelerated implementation of comprehensive smoke-free policies is likely to result in substantial population health benefits in these settings. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Association between being employed in a smoke-free workplace and living in a smoke-free home: Evidence from 15 low and middle income countries☆

PubMed Central

Nazar, Gaurang P.; Lee, John Tayu; Glantz, Stanton A.; Arora, Monika; Pearce, Neil; Millett, Christopher

2014-01-01

Objective To assess whether being employed in a smoke-free workplace is associated with living in a smoke-free home in 15 low and middle income countries (LMICs). Methods Country-specific individual level analyses of cross-sectional Global Adult Tobacco Survey data (2008–2011) from 15 LMICs was conducted using multiple logistic regression. The dependent variable was living in a smoke-free home; the independent variable was being employed in a smoke-free workplace. Analyses were adjusted for age, gender, residence, region, education, occupation, current smoking, current smokeless tobacco use and number of household members. Individual country results were combined in a random effects meta-analysis. Results In each country, the percentage of participants employed in a smoke-free workplace who reported living in a smoke-free home was higher than those employed in a workplace not smoke-free. The adjusted odds ratios (AORs) of living in a smoke-free home among participants employed in a smoke-free workplace (vs. those employed where smoking occurred) were statistically significant in 13 of the 15 countries, ranging from 1.12 [95% CI 0.79–1.58] in Uruguay to 2.29 [1.37–3.83] in China. The pooled AOR was 1.61 [1.46–1.79]. Conclusion In LMICs, employment in a smoke-free workplace is associated with living in a smoke-free home. Accelerated implementation of comprehensive smoke-free policies is likely to result in substantial population health benefits in these settings. PMID:24287123

Measures and predictors of community-based employment and earnings of persons with schizophrenia in a multisite study.

PubMed

Salkever, David S; Karakus, Mustafa C; Slade, Eric P; Harding, Courtenay M; Hough, Richard L; Rosenheck, Robert A; Swartz, Marvin S; Barrio, Concepcion; Yamada, Anne Marie

2007-03-01

Data from a national study of persons with schizophrenia-related disorders were examined to determine clinical factors and labor-market conditions related to employment outcomes. Data were obtained from the U.S. Schizophrenia Care and Assessment Program, a naturalistic study of more than 2,300 persons from organized care systems in six U.S. regions. Data were collected via surveys and from medical records and clinical assessments at baseline and for three years. Outcome measures included any community-based (nonsheltered) employment, 40 or more hours of work in the past month, employment at or above the federal minimum wage, days and hours of work, and earnings. Bivariate and multiple regression analyses of data from more than 7,000 assessments tested relationships between outcomes and sociodemographic, clinical, and local labor market characteristics. The employment rate was 17.2%; only 57.1% of participants who worked reported 40 or more hours of past-month employment. The mean hourly wage was $7.05, and mean monthly earnings were $494.20. Employment rates and number of hours worked were substantially below those found in household surveys or in baseline data from trials of employment programs but substantially higher than those found in a recent large clinical trial. Strong positive relationships were found between clinical factors and work outcomes, but evidence of a relationship between local unemployment rates and outcomes was weak. Work attachment and earnings were substantially lower than in previous survey data, not very sensitive to labor market conditions, and strongly related to clinical status.

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…

Regression assumptions in clinical psychology research practice-a systematic review of common misconceptions.

PubMed

Ernst, Anja F; Albers, Casper J

2017-01-01

Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated employment and reporting of assumption checks in twelve clinical psychology journals. Findings indicate that normality of the variables themselves, rather than of the errors, was wrongfully held for a necessary assumption in 4% of papers that use regression. Furthermore, 92% of all papers using linear regression were unclear about their assumption checks, violating APA-recommendations. This paper appeals for a heightened awareness for and increased transparency in the reporting of statistical assumption checking.

Regression assumptions in clinical psychology research practice—a systematic review of common misconceptions

PubMed Central

Ernst, Anja F.

2017-01-01

Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated employment and reporting of assumption checks in twelve clinical psychology journals. Findings indicate that normality of the variables themselves, rather than of the errors, was wrongfully held for a necessary assumption in 4% of papers that use regression. Furthermore, 92% of all papers using linear regression were unclear about their assumption checks, violating APA-recommendations. This paper appeals for a heightened awareness for and increased transparency in the reporting of statistical assumption checking. PMID:28533971

Impact of multiple sclerosis on employment and use of job-retention strategies: The situation in France in 2015.

PubMed

Fantoni-Quinton, Sophie; Kwiatkowski, Arnaud; Vermersch, Patrick; Roux, Bastien; Hautecoeur, Patrick; Leroyer, Ariane

2016-06-13

The main objective of this survey of persons with multiple sclerosis was to describe their employment situation. Secondary objectives were to ascertain when and how multiple sclerosis symptoms first impact employment per se and what strategies persons with multiple sclerosis use to cope with their employment problems. A retrospective survey was conducted to collect data from persons with multiple sclerosis aged 18 years and over, using a computer-assisted web tool. A total of 941 respondents were working at the time of multiple sclerosis diagnosis or had worked subsequently. Median time since diagnosis was 10 years. Multiple sclerosis had an impact on employment for 74.3% of respondents. The overall employment rate at the time of the survey was 68.1%; 27.2% had discontinued their occupational activity for a multiple sclerosis-related reason. Median time from diagnosis to multiple sclerosis-related cessation of occupational activity was 24.0 years (95% confidence interval (CI) 21.7-26.3 years). Respondents were poorly aware of available tools designed to assist them in retaining employment. This study highlights the importance of early intervention by the occupational medicine physician in order to favour job retention and use of available tools by all workers with MS and not only those with a recognized status as a disabled worker.

Sequential Monte Carlo tracking of the marginal artery by multiple cue fusion and random forest regression.

PubMed

Cherry, Kevin M; Peplinski, Brandon; Kim, Lauren; Wang, Shijun; Lu, Le; Zhang, Weidong; Liu, Jianfei; Wei, Zhuoshi; Summers, Ronald M

2015-01-01

Given the potential importance of marginal artery localization in automated registration in computed tomography colonography (CTC), we have devised a semi-automated method of marginal vessel detection employing sequential Monte Carlo tracking (also known as particle filtering tracking) by multiple cue fusion based on intensity, vesselness, organ detection, and minimum spanning tree information for poorly enhanced vessel segments. We then employed a random forest algorithm for intelligent cue fusion and decision making which achieved high sensitivity and robustness. After applying a vessel pruning procedure to the tracking results, we achieved statistically significantly improved precision compared to a baseline Hessian detection method (2.7% versus 75.2%, p<0.001). This method also showed statistically significantly improved recall rate compared to a 2-cue baseline method using fewer vessel cues (30.7% versus 67.7%, p<0.001). These results demonstrate that marginal artery localization on CTC is feasible by combining a discriminative classifier (i.e., random forest) with a sequential Monte Carlo tracking mechanism. In so doing, we present the effective application of an anatomical probability map to vessel pruning as well as a supplementary spatial coordinate system for colonic segmentation and registration when this task has been confounded by colon lumen collapse. Published by Elsevier B.V.

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.

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…

Characteristics of Venture Capital Network and Its Correlation with Regional Economy: Evidence from China.

PubMed

Jin, Yonghong; Zhang, Qi; Shan, Lifei; Li, Sai-Ping

2015-01-01

Financial networks have been extensively studied as examples of real world complex networks. In this paper, we establish and study the network of venture capital (VC) firms in China. We compute and analyze the statistical properties of the network, including parameters such as degrees, mean lengths of the shortest paths, clustering coefficient and robustness. We further study the topology of the network and find that it has small-world behavior. A multiple linear regression model is introduced to study the relation between network parameters and major regional economic indices in China. From the result of regression, we find that, economic aggregate (including the total GDP, investment, consumption and net export), upgrade of industrial structure, employment and remuneration of a region are all positively correlated with the degree and the clustering coefficient of the VC sub-network of the region, which suggests that the development of the VC industry has substantial effects on regional economy in China.

Characteristics of Venture Capital Network and Its Correlation with Regional Economy: Evidence from China

PubMed Central

Jin, Yonghong; Zhang, Qi; Shan, Lifei; Li, Sai-Ping

2015-01-01

Financial networks have been extensively studied as examples of real world complex networks. In this paper, we establish and study the network of venture capital (VC) firms in China. We compute and analyze the statistical properties of the network, including parameters such as degrees, mean lengths of the shortest paths, clustering coefficient and robustness. We further study the topology of the network and find that it has small-world behavior. A multiple linear regression model is introduced to study the relation between network parameters and major regional economic indices in China. From the result of regression, we find that, economic aggregate (including the total GDP, investment, consumption and net export), upgrade of industrial structure, employment and remuneration of a region are all positively correlated with the degree and the clustering coefficient of the VC sub-network of the region, which suggests that the development of the VC industry has substantial effects on regional economy in China. PMID:26340555

Gendered Cultural Identities: The Influences of Family and Privacy Boundaries, Subjective Norms, and Stigma Beliefs on Family Health History Communication.

PubMed

Hong, Soo Jung

2018-08-01

This study investigates the effects of cultural norms on family health history (FHH) communication in the American, Chinese, and Korean cultures. More particularly, this study focuses on perceived family boundaries, subjective norms, stigma beliefs, and privacy boundaries, including age and gender, that affect people's FHH communication. For data analyses, hierarchical multiple regression and logistic regression methods were employed. The results indicate that participants' subjective norms, stigma beliefs, and perceived family/privacy boundaries were positively associated with current FHH communication. Age- and gender-related privacy boundaries were negatively related to perceived privacy boundaries, however. Finally, the results show that gendered cultural identities have three-way interaction effects on two associations: (1) between perceived family boundaries and perceived privacy boundaries and (2) between perceived privacy boundaries and current FHH communication. The findings have meaningful implications for future cross-cultural studies on the roles of family systems, subjective norms, and stigma beliefs in FHH communication.

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator)

1979-01-01

The spatial characteristics of the data were evaluated. A program was developed to reduce the spatial distortions resulting from variable viewing distance, and geometrically adjusted data sets were generated. The potential need for some level of radiometric adjustment was evidenced by an along track band of high reflectance across different cover types in the Varian imagery. A multiple regression analysis was employed to explore the viewing angle effect on measured reflectance. Areas in the data set which appeared to have no across track stratification of cover type were identified. A program was developed which computed the average reflectance by column for each channel, over all of the scan lines in the designated areas. A regression analysis was then run using the first, second, and third degree polynomials, for each channel. An atmospheric effect as a component of the viewing angle source of variance is discussed. Cover type maps were completed and training and test field selection was initiated.

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.

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

Optimization by response surface methodology of lutein recovery from paprika leaves using accelerated solvent extraction.

PubMed

Kang, Jae-Hyun; Kim, Suna; Moon, BoKyung

2016-08-15

In this study, we used response surface methodology (RSM) to optimize the extraction conditions for recovering lutein from paprika leaves using accelerated solvent extraction (ASE). The lutein content was quantitatively analyzed using a UPLC equipped with a BEH C18 column. A central composite design (CCD) was employed for experimental design to obtain the optimized combination of extraction temperature (°C), static time (min), and solvent (EtOH, %). The experimental data obtained from a twenty sample set were fitted to a second-order polynomial equation using multiple regression analysis. The adjusted coefficient of determination (R(2)) for the lutein extraction model was 0.9518, and the probability value (p=0.0000) demonstrated a high significance for the regression model. The optimum extraction conditions for lutein were temperature: 93.26°C, static time: 5 min, and solvent: 79.63% EtOH. Under these conditions, the predicted extraction yield of lutein was 232.60 μg/g. Copyright © 2016 Elsevier Ltd. All rights reserved.

Relationship between college success and employer competency ratings for graduates of a baccalaureate nursing program.

PubMed

Bolin, S E; Hogle, E L

1984-01-01

This expost facto correlational study sought to determine which measures of academic success in one class of BSN graduates predicted their competence as employees one year after graduation, as judged by their employers. The relationship between pre-entrance test scores, clinical experience grades, GPA, State Board Test Pool examination scores, and employer competency ratings were also determined. In keeping with the literature in fields other than nursing, the findings suggest that there may be little relationship between academic performance in a nursing program and subsequent job performance as a nurse, even though verbal ability may be predictive of success in school. While significant positive correlations were found between pre-entrance test data and final grade point averages, as well as pre-entrance test scores and State Board Test Pool examination scores, there was little evidence that pre-entrance test scores were predictive of nursing abilities. Isolated correlations were found between the clinical components of some nursing courses and specific nursing abilities. Using multiple regression analysis, no clinical course grade was found to be a significant predictor of the mean employer competency rating. Significant predictors were found for only four of the individual nursing abilities, with the clinical component of Leadership in Nursing being the most frequent and best predictor.

Prevalence and socio-demographic correlates of obesity in the British Army.

PubMed

Sanderson, Paul W; Clemes, Stacy A; Biddle, Stuart J H

2014-01-01

The trend of escalating obesity has prompted some armed forces to employ comprehensive health surveys to report obesity trends and prevalence, the findings of which suggest that obesity is a growing concern in these specific populations. To provide an appraisal of obesity prevalence and risk to obesity-related diseases in the British Army in relation to age, gender, military rank and employment. An observational cohort study (n = 50 635) consisting of 47 173 men and 3462 women was drawn from a study sample hosted on the Fitness Information Software System (FISS) (n = 54 854). Multiple logistic regression techniques were employed separately for men and women. According to BMI, 56.7% of the study population were overweight and of those individuals 12% were obese. Whilst a higher percentage of males were obese (12.2% and 8.6%, respectively), when waist circumference data were added to the BMI data, the results indicate that females displayed a higher percentage of risk to obesity-related diseases than males (30.4% and 24%, respectively). Armed service personnel should be made aware of the implications of obesity in regards to health and occupation. Specific focus should be given to those older individuals employed in managerial positions undertaking low levels of occupational physical activity.

An Effect Size for Regression Predictors in Meta-Analysis

ERIC Educational Resources Information Center

Aloe, Ariel M.; Becker, Betsy Jane

2012-01-01

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

Regression Analysis: Legal Applications in Institutional Research

ERIC Educational Resources Information Center

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

2008-01-01

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

RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,

DTIC Science & Technology

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

Incremental Net Effects in Multiple Regression

ERIC Educational Resources Information Center

Lipovetsky, Stan; Conklin, Michael

2005-01-01

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

Floating Data and the Problem with Illustrating Multiple Regression.

ERIC Educational Resources Information Center

Sachau, Daniel A.

2000-01-01

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

Validity and reliability of dental age estimation of teeth root translucency based on digital luminance determination.

PubMed

Ramsthaler, Frank; Kettner, Mattias; Verhoff, Marcel A

2014-01-01

In forensic anthropological casework, estimating age-at-death is key to profiling unknown skeletal remains. The aim of this study was to examine the reliability of a new, simple, fast, and inexpensive digital odontological method for age-at-death estimation. The method is based on the original Lamendin method, which is a widely used technique in the repertoire of odontological aging methods in forensic anthropology. We examined 129 single root teeth employing a digital camera and imaging software for the measurement of the luminance of the teeth's translucent root zone. Variability in luminance detection was evaluated using statistical technical error of measurement analysis. The method revealed stable values largely unrelated to observer experience, whereas requisite formulas proved to be camera-specific and should therefore be generated for an individual recording setting based on samples of known chronological age. Multiple regression analysis showed a highly significant influence of the coefficients of the variables "arithmetic mean" and "standard deviation" of luminance for the regression formula. For the use of this primer multivariate equation for age-at-death estimation in casework, a standard error of the estimate of 6.51 years was calculated. Step-by-step reduction of the number of embedded variables to linear regression analysis employing the best contributor "arithmetic mean" of luminance yielded a regression equation with a standard error of 6.72 years (p < 0.001). The results of this study not only support the premise of root translucency as an age-related phenomenon, but also demonstrate that translucency reflects a number of other influencing factors in addition to age. This new digital measuring technique of the zone of dental root luminance can broaden the array of methods available for estimating chronological age, and furthermore facilitate measurement and age classification due to its low dependence on observer experience.

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

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

PubMed

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

2018-04-09

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

Temporally-Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer’s Disease

PubMed Central

Jie, Biao; Liu, Mingxia; Liu, Jun

2016-01-01

Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer’s disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). However, most existing sparse learning-based studies only adopt cross-sectional analysis methods, where the sparse model is learned using data from a single time-point. Actually, multiple time-points of data are often available in brain imaging applications, which can be used in some longitudinal analysis methods to better uncover the disease progression patterns. Accordingly, in this paper we propose a novel temporally-constrained group sparse learning method aiming for longitudinal analysis with multiple time-points of data. Specifically, we learn a sparse linear regression model by using the imaging data from multiple time-points, where a group regularization term is first employed to group the weights for the same brain region across different time-points together. Furthermore, to reflect the smooth changes between data derived from adjacent time-points, we incorporate two smoothness regularization terms into the objective function, i.e., one fused smoothness term which requires that the differences between two successive weight vectors from adjacent time-points should be small, and another output smoothness term which requires the differences between outputs of two successive models from adjacent time-points should also be small. We develop an efficient optimization algorithm to solve the proposed objective function. Experimental results on ADNI database demonstrate that, compared with conventional sparse learning-based methods, our proposed method can achieve improved regression performance and also help in discovering disease-related biomarkers. PMID:27093313

Relationships among perceived career support, affective commitment, and work engagement.

PubMed

Poon, June M L

2013-01-01

This study sought to test the predictive effects of perceived career support and affective commitment on work engagement. It was hypothesized that perceived career support would relate positively to work engagement and this relationship would be transmitted through affective commitment. Survey data were collected from 115 full-time employees enrolled as part-time graduate students in a large public university in Malaysia. Multiple regression analysis yielded results indicating that the relationship between perceived career support and work engagement was mediated by affective commitment. This finding suggests that employers can promote employee work engagement by ensuring employees perceive their organization to be supportive of their career and increasing employees' level of affective commitment.

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.

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.

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…

Korean Youth Risk Behavior Surveillance Survey: Association Between Part-time Employment and Suicide Attempts.

PubMed

Jo, Sun-Jin; Yim, Hyeon Woo; Lee, Myung-Soo; Jeong, Hyunsuk; Lee, Won-Chul

2015-04-01

This study investigated the association between in-school students' part-time work and 1-year suicide attempts in Korea. The authors analyzed Korean Youth Risk Behavior Surveillance data (2008), which included 75 238 samples that represent Korean middle and high school students. Multiple logistic regression analysis was performed to investigate the association between part-time work and suicide attempt during the past 1 year, controlled by sociodemographic, school-related, lifestyle, and psychological factors. Among high school students, there was no association between part-time work and suicide attempts. However, part-time work was associated with suicide attempts significantly among middle school students (odds ratio = 1.59; 95% confidence interval = 1.37-1.83). Despite the limitation that details of the part-time work were not included in this study, it was found that middle school students' part-time work may increase suicide attempts, and the circumstances of Korean adolescents' employment, especially that of younger adolescents, would need to be reconsidered to prevent their suicide attempts. © 2014 APJPH.

A novel application of artificial neural network for wind speed estimation

NASA Astrophysics Data System (ADS)

Fang, Da; Wang, Jianzhou

2017-05-01

Providing accurate multi-steps wind speed estimation models has increasing significance, because of the important technical and economic impacts of wind speed on power grid security and environment benefits. In this study, the combined strategies for wind speed forecasting are proposed based on an intelligent data processing system using artificial neural network (ANN). Generalized regression neural network and Elman neural network are employed to form two hybrid models. The approach employs one of ANN to model the samples achieving data denoising and assimilation and apply the other to predict wind speed using the pre-processed samples. The proposed method is demonstrated in terms of the predicting improvements of the hybrid models compared with single ANN and the typical forecasting method. To give sufficient cases for the study, four observation sites with monthly average wind speed of four given years in Western China were used to test the models. Multiple evaluation methods demonstrated that the proposed method provides a promising alternative technique in monthly average wind speed estimation.

Arthritis symptoms, the work environment, and the future: measuring perceived job strain among employed persons with arthritis.

PubMed

Gignac, Monique A M; Sutton, Deborah; Badley, Elizabeth M

2007-06-15

To develop a measure of job strain related to differing aspects of working with arthritis and to examine the demographic, illness, work context, and psychosocial variables associated with it. Study participants were 292 employed individuals with osteoarthritis or inflammatory arthritis. Participants were from wave 3 of a 4-wave longitudinal study examining coping and adaptation efforts used to remain employed. Participants completed an interview-administered structured questionnaire, including a Chronic Illness Job Strain Scale (CIJSS) and questions on demographic (e.g., age, sex), illness and disability (e.g., disease type, pain, activity limitations), work context (e.g., job type, job control), and psychosocial variables (e.g., arthritis-work spillover, coworker/managerial support, job perceptions). Principal component analysis and multiple linear regression were used to analyze the data. A single factor solution emerged for the CIJSS. The scale had an internal reliability of 0.95. Greater job strain was reported for future uncertainty, balancing multiple roles, and difficulties accepting the disease than for current workplace conditions. Participants with inflammatory arthritis, more frequent severe pain, greater workplace activity limitations, fewer hours of work, less coworker support, and greater arthritis-work spillover reported greater job strain. The findings underscore the diverse areas that contribute to perceptions of job strain and suggest that existing models of job strain do not adequately capture the stress experienced by individuals working with chronic illnesses or the factors associated with job strain. Measures similar to the CIJSS can enhance the tools researchers and clinicians have available to examine the impact of arthritis in individuals' lives.

Predictors for Employment Status in People With Multiple Sclerosis: A 10-Year Longitudinal Observational Study.

PubMed

Forslin, Mia; Fink, Katharina; Hammar, Ulf; von Koch, Lena; Johansson, Sverker

2018-01-31

To identify predictors for employment status after 10 years in a cohort of people with multiple sclerosis (MS), with the aim to increase knowledge concerning factors present at an early stage that are important for working life and work-life balance. A 10-year longitudinal observational cohort study. University hospital. A consecutive sample of people with MS (N=154) of working age were included at baseline, of which a total of 116 people participated in the 10-year follow-up; 27 people declined participation and 11 were deceased. Not applicable. Baseline data on personal factors and functioning were used as independent variables. Employment status 10 years after baseline, categorized as full-time work, part-time work, and no work, was used as the dependent variable. A generalized ordinal logistic regression was used to analyze the predictive value of the independent variables. Predictors for full- or part-time work after 10 years were young age (P=.002), low perceived physical impact of MS (P=.02), fatigue (P=.03), full-time work (P=.001), and high frequency of social/lifestyle activities (P=.001) at baseline. Low perceived physical impact of MS (P=.02) at baseline also predicted full-time work after 10 years. This study underlines the complexity of working life for people with MS, and indicates that it may be valuable to give more attention to the balance between working and private life, both in clinical practice and future research, to achieve a sustainable working life over time. Copyright © 2018 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2017-05-01

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

Quality by Design approach to spray drying processing of crystalline nanosuspensions.

PubMed

Kumar, Sumit; Gokhale, Rajeev; Burgess, Diane J

2014-04-10

Quality by Design (QbD) principles were explored to understand spray drying process for the conversion of liquid nanosuspensions into solid nano-crystalline dry powders using indomethacin as a model drug. The effects of critical process variables: inlet temperature, flow and aspiration rates on critical quality attributes (CQAs): particle size, moisture content, percent yield and crystallinity were investigated employing a full factorial design. A central cubic design was employed to generate the response surface for particle size and percent yield. Multiple linear regression analysis and ANOVA were employed to identify and estimate the effect of critical parameters, establish their relationship with CQAs, create design space and model the spray drying process. Inlet temperature was identified as the only significant factor (p value <0.05) to affect dry powder particle size. Higher inlet temperatures caused drug surface melting and hence aggregation of the dried nano-crystalline powders. Aspiration and flow rates were identified as significant factors affecting yield (p value <0.05). Higher yields were obtained at higher aspiration and lower flow rates. All formulations had less than 3% (w/w) moisture content. Formulations dried at higher inlet temperatures had lower moisture compared to those dried at lower inlet temperatures. Published by Elsevier B.V.

Workplace, psychosocial factors, and depressive symptoms among working people with arthritis: a longitudinal study.

PubMed

Li, Xin; Gignac, Monique A M; Anis, Aslam H

2006-09-01

To examine the role of demographic, illness-related, workplace support, workplace activity limitations, arthritis-related work changes, and psychosocial factors in predicting subsequent depressive symptoms among employed people with arthritis. In a prospective study, 366 employed individuals with arthritis were recruited from Toronto, Canada. Respondents completed a structured questionnaire assessing demographic, disease-related factors, workplace support, and employment-related transitions, as well as psychosocial variables at 2 timepoints 18 months apart. Depression was assessed using the Center for Epidemiologic Studies Depression Scale. Hierarchical multiple regression was used for analyses. Individuals with greater education reported significantly less depression. Lower workplace support and greater workplace activity limitations were significantly associated with future depressive symptoms. No relationship was found between work transitions and later depression, but more work changes were strongly associated with concurrent depressive symptoms. An association was also found between greater pain catastrophizing and future depressive symptoms. Our results highlight the need to assess the influence of work-related changes, workplace support, and psychosocial variables on depressive symptoms among people with arthritis. These findings suggest that workplace interventions should address not only ways to reduce workplace activity limitations, but also ways to better manage emotional distress related to working with arthritis.

Predictive factors for cosmetic surgery: a hospital-based investigation.

PubMed

Li, Jun; Li, Qian; Zhou, Bei; Gao, Yanli; Ma, Jiehua; Li, Jingyun

2016-01-01

Cosmetic surgery is becoming increasingly popular in China. However, reports on the predictive factors for cosmetic surgery in Chinese individuals are scarce in the literature. We retrospectively analyzed 4550 cosmetic surgeries performed from January 2010 to December 2014 at a single center in China. Data collection included patient demographics and type of cosmetic surgery. Predictive factors were age, sex, marital status, occupational status, educational degree, and having had children. Predictive factors for the three major cosmetic surgeries were determined using a logistic regression analysis. Patients aged 19-34 years accounted for the most popular surgical procedures (76.9 %). The most commonly requested procedures were eye surgery, Botox injection, and nevus removal. Logistic regression analysis showed that higher education level (college, P = 0.01, OR 1.21) was predictive for eye surgery. Age (19-34 years, P = 0.00, OR 33.39; 35-50, P = 0.00, OR 31.34; ≥51, P = 0.00, OR 16.42), female sex (P = 0.00, OR 9.19), employment (service occupations, P = 0.00, OR 2.31; non-service occupations, P = 0.00, OR 1.76), and higher education level (college, P = 0.00, OR 1.39) were independent predictive factors for Botox injection. Married status (P = 0.00, OR 1.57), employment (non-service occupations, P = 0.00, OR 1.50), higher education level (masters, P = 0.00, OR 6.61), and having children (P = 0.00, OR 1.45) were independent predictive factors for nevus removal. The principal three cosmetic surgeries (eye surgery, Botox injection, and nevus removal) were associated with multiple variables. Patients employed in non-service occupations were more inclined to undergo Botox injection and nevus removal. Cohort study, Level III.

Dental age estimation employing CBCT scans enhanced with Mimics software: Comparison of two different approaches using pulp/tooth volumetric analysis.

PubMed

Asif, Muhammad Khan; Nambiar, Phrabhakaran; Mani, Shani Ann; Ibrahim, Norliza Binti; Khan, Iqra Muhammad; Sukumaran, Prema

2018-02-01

The methods of dental age estimation and identification of unknown deceased individuals are evolving with the introduction of advanced innovative imaging technologies in forensic investigations. However, assessing small structures like root canal volumes can be challenging in spite of using highly advanced technology. The aim of the study was to investigate which amongst the two methods of volumetric analysis of maxillary central incisors displayed higher strength of correlation between chronological age and pulp/tooth volume ratio for Malaysian adults. Volumetric analysis of pulp cavity/tooth ratio was employed in Method 1 and pulp chamber/crown ratio (up to cemento-enamel junction) was analysed in Method 2. The images were acquired employing CBCT scans and enhanced by manipulating them with the Mimics software. These scans belonged to 56 males and 54 females and their ages ranged from 16 to 65 years. Pearson correlation and regression analysis indicated that both methods used for volumetric measurements had strong correlation between chronological age and pulp/tooth volume ratio. However, Method 2 gave higher coefficient of determination value (R2 = 0.78) when compared to Method 1 (R2 = 0.64). Moreover, manipulation in Method 2 was less time consuming and revealed higher inter-examiner reliability (0.982) as no manual intervention during 'multiple slice editing phase' of the software was required. In conclusion, this study showed that volumetric analysis of pulp cavity/tooth ratio is a valuable gender independent technique and the Method 2 regression equation should be recommended for dental age estimation. Copyright © 2018 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Factors Associated with Dental Caries in Primary Dentition in a Non-Fluoridated Rural Community of New South Wales, Australia

PubMed Central

Arora, Amit; Manohar, Narendar

2017-01-01

Dental caries persists as one of the most prevalent chronic diseases among children worldwide. This study aims to determine factors that influence dental caries in primary dentition among primary school children residing in the rural non-fluoridated community of Lithgow, New South Wales, Australia. A total of 495 children aged 5–10 years old from all the six primary schools in Lithgow were approached to participate in a cross-sectional survey prior to implementation of water fluoridation in 2014. Following parental consent, children were clinically examined for caries in their primary teeth, and parents were requested to complete a questionnaire on previous fluoride exposure, diet and relevant socio-demographic characteristics that influence oral health. Multiple logistic regression analysis was employed to examine the independent risk factors of primary dentition caries. Overall, 51 percent of children had dental caries in one or more teeth. In the multiple logistic regression analysis, child’s age (Adjusted Odd’s Ratio (AOR) = 1.30, 95% CI: 1.14–1.49) and mother’s extraction history (AOR = 2.05, 95% CI: 1.40–3.00) were significantly associated with caries experience in the child’s primary teeth. In addition, each serve of chocolate consumption was associated with 52 percent higher odds (AOR = 1.52, 95% CI: 1.19–1.93) of primary dentition caries. PMID:29168780

Volunteering predicts happiness among older Māori and non-Māori in the New Zealand health, work, and retirement longitudinal study.

PubMed

Dulin, Patrick L; Gavala, Jhanitra; Stephens, Christine; Kostick, Marylynne; McDonald, Jennifer

2012-01-01

This study sought to understand the relationship between volunteer activity and happiness among a sample of older adult New Zealanders. It specifically sought to determine if ethnicity (Māori vs. non-Māori) and economic living standards (ELS) functioned as moderators of the relationship between volunteering and happiness. Data were garnered from the 2008 administration of the New Zealand Health, Work, and Retirement Longitudinal Study. Correlational and multiple regression procedures were employed to examine study hypotheses. Results from multiple regression analyses showed that the amount of volunteering per week was a unique predictor of the overall level of happiness. Moderation analyses indicated that ethnicity did not function as a moderator of the relationship between volunteering and happiness, but ELS did. Those with low ELS evidenced a stronger relationship between volunteering and happiness than those with high ELS. Results also indicated that Maori and those with low ELS volunteered more frequently than non-Māori and those with high ELS. This study provides evidence that volunteering is related to increased happiness, irrespective of ethnicity. It also provides further evidence that the relationship between volunteering and happiness is moderated by economic resources. Older individuals at the low end of the economic spectrum are likely to benefit more from volunteering than those at the high end.

Associations of health behaviors on depressive symptoms among employed men in Japan.

PubMed

Wada, Koji; Satoh, Toshihiko; Tsunoda, Masashi; Aizawa, Yoshiharu

2006-07-01

The associations between health behaviors and depressive symptoms have been demonstrated in many studies. However, job strain has also been associated with health behaviors. The aim of this study was to analyze whether health behaviors such as physical activity, sleeping, smoking and alcohol intake are associated with depressive symptoms after adjusting for job strain. Workers were recruited from nine companies and factories located in east and central areas of Japan. The Center for Epidemiologic Studies Depression (CES-D) Scale was used to assess depressive symptoms. Psychological demand and control (decision-latitude) at work were measured with the Job Content Questionnaire. Multiple logistic regression analysis was used to determine the independent contribution of each health behavior to depressive symptoms. Among the total participants, 3,748 (22.7%) had depressive symptoms, which was defined as scoring 16 or higher on the CES-D scale. Using the multiple logistic regression analysis, depressive symptoms were significantly associated with physical activity less than once a week (adjusted relative risk [ARR] = 1.18, 95% confidence interval [CI], 1.14 to 1.25) and daily hours of sleep of 6 h or less (ARR, 1.25; 95% CI, 1.14 to 1.35). Smoking and frequency of alcohol intake were not significantly associated with depressive symptoms. This study suggests some health behaviors such as physical activity or daily hours of sleep are associated with depressive symptoms after adjusting for job strain.

Factors Associated with Dental Caries in Primary Dentition in a Non-Fluoridated Rural Community of New South Wales, Australia.

PubMed

Arora, Amit; Manohar, Narendar; John, James Rufus

2017-11-23

Dental caries persists as one of the most prevalent chronic diseases among children worldwide. This study aims to determine factors that influence dental caries in primary dentition among primary school children residing in the rural non-fluoridated community of Lithgow, New South Wales, Australia. A total of 495 children aged 5-10 years old from all the six primary schools in Lithgow were approached to participate in a cross-sectional survey prior to implementation of water fluoridation in 2014. Following parental consent, children were clinically examined for caries in their primary teeth, and parents were requested to complete a questionnaire on previous fluoride exposure, diet and relevant socio-demographic characteristics that influence oral health. Multiple logistic regression analysis was employed to examine the independent risk factors of primary dentition caries. Overall, 51 percent of children had dental caries in one or more teeth. In the multiple logistic regression analysis, child's age (Adjusted Odd's Ratio (AOR) = 1.30, 95% CI: 1.14-1.49) and mother's extraction history (AOR = 2.05, 95% CI: 1.40-3.00) were significantly associated with caries experience in the child's primary teeth. In addition, each serve of chocolate consumption was associated with 52 percent higher odds (AOR = 1.52, 95% CI: 1.19-1.93) of primary dentition caries.

Predictors of dental visits among primary school children in the rural Australian community of Lithgow.

PubMed

John, James Rufus; Mannan, Haider; Nargundkar, Subrat; D'Souza, Mario; Do, Loc Giang; Arora, Amit

2017-04-11

Regular dental attendance is significant in maintaining and improving children's oral health and well-being. This study aims to determine the factors that predict and influence dental visits in primary school children residing in the rural community of Lithgow, New South Wales (NSW), Australia. All six primary schools of Lithgow were approached to participate in a cross-sectional survey prior to implementing water fluoridation in 2014. Children aged 6-13 years (n = 667) were clinically examined for their oral health status and parents were requested to complete a questionnaire on fluoride history, diet, last dental visit, and socio-demographic characteristics. Multiple logistic regression analyses were employed to examine the independent predictors of a 6-monthly and a yearly dental visit. Overall, 53% of children visited a dentist within six months and 77% within twelve months. In multiple logistic regression analyses, age of the child and private health insurance coverage were significantly associated with both 6-monthly and twelve-month dental visits. In addition, each serve of chocolate consumption was significantly associated with a 27% higher odds (OR = 1.27, 95% CI: 1.05-1.54) of a 6-monthly dental visit. It is imperative that the socio-demographic and dietary factors that influence child oral health must be effectively addressed when developing the oral health promotion policies to ensure better oral health outcomes.

Vasomotor and physical menopausal symptoms are associated with sleep quality.

PubMed

Kim, Min-Ju; Yim, Gyeyoon; Park, Hyun-Young

2018-01-01

Sleep disturbance is one of the common complaints in menopause. This study investigated the relationship between menopausal symptoms and sleep quality in middle-aged women. This cross-sectional observational study involved 634 women aged 44-56 years attending a healthcare center at Kangbuk Samsung Hospitals. Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI).Multiple linear regression analysis was performed to assess the associations between Menopause-specific Quality of Life (MENQOL) scores and PSQI scores and Menopause-specific Quality of Life (MENQOL)scores. The mean PSQI score was 3.6±2.3, and the rates of poor sleep quality(PSQI score > 5) in premenopausal, perimenopausal, and postmenopausal women were 14.4%, 18.2%, and 30.2%, respectively. Total PSQI score, specifically the sleep latency, habitual sleep efficiency and sleep disturbances scores, were significantly increased in postmenopausal women. Multiple linear regression analysis adjusted for age, BMI, hypertension, diabetes, smoking, marital status, family income, education, employment status, parity, physical activity, depression symptoms, perceived stress and menopausal status showed that higher PSQI score was positively correlated with higher vasomotor(ß = 0.240, P = 0.020)and physical(ß = 0.572, P<0.001) scores. Vasomotor and physical menopause symptoms was related to poor sleep quality. Effective management strategies aimed at reducing menopausal symptoms may improve sleep quality among women around the time of menopause.

Self-reported physical activity correlates in Swedish adults with multiple sclerosis: a cross-sectional study.

PubMed

Anens, Elisabeth; Zetterberg, Lena; Urell, Charlotte; Emtner, Margareta; Hellström, Karin

2017-12-01

The benefits of physical activity in persons with Multiple Sclerosis (MS) are considerable. Knowledge about factors that correlate to physical activity is helpful in order to develop successful strategies to increase physical activity in persons with MS. Previous studies have focused on correlates to physical activity in MS, however falls self-efficacy, social support and enjoyment of physical activity are not much studied, as well as if the correlates differ with regard to disease severity. The aim of the study was to examine associations between physical activity and age, gender, employment, having children living at home, education, disease type, disease severity, fatigue, self-efficacy for physical activity, falls self-efficacy, social support and enjoyment of physical activity in a sample of persons with MS and in subgroups with regard to disease severity. This is a cross-sectional survey study including Swedish community living adults with MS, 287 persons, response rate 58.2%. The survey included standardized self-reported scales measuring physical activity, disease severity, fatigue, self-efficacy for physical activity, falls self-efficacy, and social support. Physical activity was measured by the Physical Activity Disability Survey - Revised. Multiple regression analyzes showed that 59% (F(6,3) = 64.9, p = 0.000) of the variation in physical activity was explained by having less severe disease (β = -0.30), being employed (β = 0.26), having high falls self-efficacy (β = 0.20), having high self-efficacy for physical activity (β = 0.17), and enjoying physical activity (β = 0.11). In persons with moderate/severe MS, self-efficacy for physical activity explained physical activity. Consistent with previous research in persons with MS in other countries this study shows that disease severity, employment and self-efficacy for physical activity are important for physical activity. Additional important factors were falls self-efficacy and enjoyment. More research is needed to confirm this and the subgroup differences.

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…

Association between overuse of mobile phones on quality of sleep and general health among occupational health and safety students.

PubMed

Eyvazlou, Meysam; Zarei, Esmaeil; Rahimi, Azin; Abazari, Malek

2016-01-01

Concerns about health problems due to the increasing use of mobile phones are growing. Excessive use of mobile phones can affect the quality of sleep as one of the important issues in the health literature and general health of people. Therefore, this study investigated the relationship between the excessive use of mobile phones and general health and quality of sleep on 450 Occupational Health and Safety (OH&S) students in five universities of medical sciences in the North East of Iran in 2014. To achieve this objective, special questionnaires that included Cell Phone Overuse Scale, Pittsburgh's Sleep Quality Index (PSQI) and General Health Questionnaire (GHQ) were used, respectively. In addition to descriptive statistical methods, independent t-test, Pearson correlation, analysis of variance (ANOVA) and multiple regression tests were performed. The results revealed that half of the students had a poor level of sleep quality and most of them were considered unhealthy. The Pearson correlation co-efficient indicated a significant association between the excessive use of mobile phones and the total score of general health and the quality of sleep. In addition, the results of the multiple regression showed that the excessive use of mobile phones has a significant relationship between each of the four subscales of general health and the quality of sleep. Furthermore, the results of the multivariate regression indicated that the quality of sleep has a simultaneous effect on each of the four scales of the general health. Overall, a simultaneous study of the effects of the mobile phones on the quality of sleep and the general health could be considered as a trigger to employ some intervention programs to improve their general health status, quality of sleep and consequently educational performance.

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.

Impact of wearing fixed orthodontic appliances on quality of life among adolescents: Case-control study.

PubMed

Costa, Andréa A; Serra-Negra, Júnia M; Bendo, Cristiane B; Pordeus, Isabela A; Paiva, Saul M

2016-01-01

To investigate the impact of wearing a fixed orthodontic appliance on oral health-related quality of life (OHRQoL) among adolescents. A case-control study (1 ∶ 2) was carried out with a population-based randomized sample of 327 adolescents aged 11 to 14 years enrolled at public and private schools in the City of Brumadinho, southeast of Brazil. The case group (n  =  109) was made up of adolescents with a high negative impact on OHRQoL, and the control group (n  =  218) was made up of adolescents with a low negative impact. The outcome variable was the impact on OHRQoL measured by the Brazilian version of the Child Perceptions Questionnaire (CPQ 11-14) - Impact Short Form (ISF:16). The main independent variable was wearing fixed orthodontic appliances. Malocclusion and the type of school were identified as possible confounding variables. Bivariate and multiple conditional logistic regressions were employed in the statistical analysis. A multiple conditional logistic regression model demonstrated that adolescents wearing fixed orthodontic appliances had a 4.88-fold greater chance of presenting high negative impact on OHRQoL (95% CI: 2.93-8.13; P < .001) than those who did not wear fixed orthodontic appliances. A bivariate conditional logistic regression demonstrated that malocclusion was significantly associated with OHRQoL (P  =  .017), whereas no statistically significant association was found between the type of school and OHRQoL (P  =  .108). Adolescents who wore fixed orthodontic appliances had a greater chance of reporting a negative impact on OHRQoL than those who did not wear such appliances.

Socio-economic factors associated with infant mortality in Italy: an ecological study.

PubMed

Dallolio, Laura; Di Gregori, Valentina; Lenzi, Jacopo; Franchino, Giuseppe; Calugi, Simona; Domenighetti, Gianfranco; Fantini, Maria Pia

2012-08-16

One issue that continues to attract the attention of public health researchers is the possible relationship in high-income countries between income, income inequality and infant mortality (IM). The aim of this study was to assess the associations between IM and major socio-economic determinants in Italy. Associations between infant mortality rates in the 20 Italian regions (2006-2008) and the Gini index of income inequality, mean household income, percentage of women with at least 8 years of education, and percentage of unemployed aged 15-64 years were assessed using Pearson correlation coefficients. Univariate linear regression and multiple stepwise linear regression analyses were performed to determine the magnitude and direction of the effect of the four socio-economic variables on IM. The Gini index and the total unemployment rate showed a positive strong correlation with IM (r = 0.70; p < 0.001 and r = 0.84; p < 0.001 respectively), mean household income showed a strong negative correlation (r = -0.78; p < 0.001), while female educational attainment presented a weak negative correlation (r = -0.45; p < 0.05). Using a multiple stepwise linear regression model, only unemployment rate was independently associated with IM (b = 0.15, p < 0.001). In Italy, a high-income country where health care is universally available, variations in IM were strongly associated with relative and absolute income and unemployment rate. These results suggest that in Italy IM is not only related to income distribution, as demonstrated for other developed countries, but also to economic factors such as absolute income and unemployment. In order to reduce IM and the existing inequalities, the challenge for Italian decision makers is to promote economic growth and enhance employment levels.

Estimating Dbh of Trees Employing Multiple Linear Regression of the best Lidar-Derived Parameter Combination Automated in Python in a Natural Broadleaf Forest in the Philippines

NASA Astrophysics Data System (ADS)

Ibanez, C. A. G.; Carcellar, B. G., III; Paringit, E. C.; Argamosa, R. J. L.; Faelga, R. A. G.; Posilero, M. A. V.; Zaragosa, G. P.; Dimayacyac, N. A.

2016-06-01

Diameter-at-Breast-Height Estimation is a prerequisite in various allometric equations estimating important forestry indices like stem volume, basal area, biomass and carbon stock. LiDAR Technology has a means of directly obtaining different forest parameters, except DBH, from the behavior and characteristics of point cloud unique in different forest classes. Extensive tree inventory was done on a two-hectare established sample plot in Mt. Makiling, Laguna for a natural growth forest. Coordinates, height, and canopy cover were measured and types of species were identified to compare to LiDAR derivatives. Multiple linear regression was used to get LiDAR-derived DBH by integrating field-derived DBH and 27 LiDAR-derived parameters at 20m, 10m, and 5m grid resolutions. To know the best combination of parameters in DBH Estimation, all possible combinations of parameters were generated and automated using python scripts and additional regression related libraries such as Numpy, Scipy, and Scikit learn were used. The combination that yields the highest r-squared or coefficient of determination and lowest AIC (Akaike's Information Criterion) and BIC (Bayesian Information Criterion) was determined to be the best equation. The equation is at its best using 11 parameters at 10mgrid size and at of 0.604 r-squared, 154.04 AIC and 175.08 BIC. Combination of parameters may differ among forest classes for further studies. Additional statistical tests can be supplemented to help determine the correlation among parameters such as Kaiser- Meyer-Olkin (KMO) Coefficient and the Barlett's Test for Spherecity (BTS).

Developmental sensitivity to cannabis use patterns and risk for major depressive disorder in mid-life: findings from 40 years of follow-up.

PubMed

Schoeler, Tabea; Theobald, Delphine; Pingault, Jean-Baptiste; Farrington, David P; Coid, Jeremy W; Bhattacharyya, Sagnik

2018-04-02

Evidence regarding the association between cannabis use and depression remain conflicting, especially as studies have not typically adopted a longitudinal design with a follow-up period that was long enough to adequately cover the risk period for onset of depression. Males from the Cambridge Study in Delinquent Development (CSDD) (N = 285) were assessed seven times from age 8 to 48 years to prospectively investigate the association between cannabis use and risk of major depressive disorder (MDD). A combination of multiple analyses (logistic regression, Cox regression, fixed-effects analysis) was employed to explore the strength and direction of effect within different developmental stages. Multiple regression analyses revealed that early-onset cannabis use (before age 18) but not late-onset cannabis use (after age 27) was associated with a higher risk and shorter time until a subsequent MDD diagnosis. This effect was present in high-frequency [(odds ratio (OR) 8.83, 95% confidence interval (CI) 1.29-70.79]; [hazard ratio (HR) 8.69, 95% CI 2.07-36.52)] and low-frequency early-onset users (OR 2.41, 95% CI 1.22-4.76; HR 2.09, 95% CI 1.16-3.74). Effect of increased frequency of cannabis use on increased risk of subsequent MDD was observed only for use during adolescence (age 14-18) but not at later life stages, while controlling for observed and non-unobserved time-invariant factors. Conversely, MDD in adulthood (age 18-32) was linked to a reduction in subsequent cannabis use (age 32-48). The present findings provide evidence implicating frequent cannabis use during adolescence as a risk factor for later life depression. Future studies should further examine causality of effects in larger samples.

Time and motion studies of National Health Service cataract theatre lists to determine strategies to improve efficiency.

PubMed

Roberts, Harry W; Myerscough, James; Borsci, Simone; Ni, Melody; O'Brart, David P S

2017-11-24

To provide a quantitative assessment of cataract theatre lists focusing on productivity and staffing levels/tasks using time and motion studies. National Health Service (NHS) cataract theatre lists were prospectively observed in five different institutions (four NHS hospitals and one private hospital). Individual tasks and their timings of every member of staff were recorded. Multiple linear regression analyses were performed to investigate possible associations between individual timings and tasks. 140 operations were studied over 18 theatre sessions. The median number of scheduled cataract operations was 7 (range: 5-14). The average duration of an operation was 10.3 min±(SD 4.11 min). The average time to complete one case including patient turnaround was 19.97 min (SD 8.77 min). The proportion of the surgeons' time occupied on total duties or operating ranged from 65.2% to 76.1% and from 42.4% to 56.7%, respectively. The correlations of the surgical time to patient time in theatre was R 2 =0.95. A multiple linear regression model found a significant association (F(3,111)=32.86, P<0.001) with R 2 =0.47 between the duration of one operation and the number of allied healthcare professionals (AHPs), the number of AHP key tasks and the time taken to perform these key tasks by the AHPs. Significant variability in the number of cases performed and the efficiency of patient flow were found between different institutions. Time and motion studies identified requirements for high-volume models and factors relating to performance. Supporting the surgeon with sufficient AHPs and tasks performed by AHPs could improve surgical efficiency up to approximately double productivity over conventional theatre models. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

The relationship between intention to leave the hospital and coping methods of emergency nurses after workplace violence.

PubMed

Jeong, In-Young; Kim, Ji-Soo

2018-04-01

To identify the relationship between emergency nurses' intention to leave the hospital and their coping methods following workplace violence. Emergency departments report a high prevalence of workplace violence, with nurses being at particular risk of violence from patients and patients' relatives. Violence negatively influences nurses' personal and professional lives and increases their turnover. This is a cross-sectional, descriptive survey study. Participants were nurses (n = 214) with over one year of experience of working in an emergency department. We measured workplace violence, coping after workplace violence experiences and job satisfaction using scales validated through a preliminary survey. Questionnaires were distributed to all nurses who signed informed consent forms. Multiple logistic regression analysis was used to identify the relationships between nurses' intention to leave the hospital and their coping methods after workplace violence. Verbal abuse was the most frequent violence experience and more often originated from patients' relatives than from patients. Of the nurses who experienced violence, 61.0% considered leaving the hospital. As for coping, nurses who employed problem-focused coping most frequently sought to identify the problems that cause violence, while nurses who employed emotion-focused coping primarily attempted to endure the situation. The multiple logistic regression analysis revealed that female sex, emotion-focused coping and job satisfaction were significantly related to emergency nurses' intention to leave. Emotion-focused coping seems to have a stronger effect on intention to leave after experiencing violence than does job satisfaction. Nurse managers should begin providing emergency nurses with useful information to guide their management of violence experiences. Nurse managers should also encourage nurses to report violent experiences to the administrative department rather than resorting to emotion-focused coping. Nurses should be provided with the opportunity to communicate their feelings to their colleagues. © 2017 John Wiley & Sons Ltd.

Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China.

PubMed

Yang, Haiou; Chen, Wenbo; Liang, Zhaofeng

2017-04-26

Fine particulate matter (PM 2.5 ) pollution has become one of the greatest urban issues in China. Studies have shown that PM 2.5 pollution is strongly related to the land use pattern at the micro-scale and optimizing the land use pattern has been suggested as an approach to mitigate PM 2.5 pollution. However, there are only a few researches analyzing the effect of land use on PM 2.5 pollution. This paper employed land use regression (LUR) models and statistical analysis to explore the effect of land use on PM 2.5 pollution in urban areas. Nanchang city, China, was taken as the study area. The LUR models were used to simulate the spatial variations of PM 2.5 concentrations. Analysis of variance and multiple comparisons were employed to study the PM 2.5 concentration variances among five different types of urban functional zones. Multiple linear regression was applied to explore the PM 2.5 concentration variances among the same type of urban functional zone. The results indicate that the dominant factor affecting PM 2.5 pollution in the Nanchang urban area was the traffic conditions. Significant variances of PM 2.5 concentrations among different urban functional zones throughout the year suggest that land use types generated a significant impact on PM 2.5 concentrations and the impact did not change as the seasons changed. Land use intensity indexes including the building volume rate, building density, and green coverage rate presented an insignificant or counter-intuitive impact on PM 2.5 concentrations when studied at the spatial scale of urban functional zones. Our study demonstrates that land use can greatly affect the PM 2.5 levels. Additionally, the urban functional zone was an appropriate spatial scale to investigate the impact of land use type on PM 2.5 pollution in urban areas.

Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China

PubMed Central

Yang, Haiou; Chen, Wenbo; Liang, Zhaofeng

2017-01-01

Fine particulate matter (PM2.5) pollution has become one of the greatest urban issues in China. Studies have shown that PM2.5 pollution is strongly related to the land use pattern at the micro-scale and optimizing the land use pattern has been suggested as an approach to mitigate PM2.5 pollution. However, there are only a few researches analyzing the effect of land use on PM2.5 pollution. This paper employed land use regression (LUR) models and statistical analysis to explore the effect of land use on PM2.5 pollution in urban areas. Nanchang city, China, was taken as the study area. The LUR models were used to simulate the spatial variations of PM2.5 concentrations. Analysis of variance and multiple comparisons were employed to study the PM2.5 concentration variances among five different types of urban functional zones. Multiple linear regression was applied to explore the PM2.5 concentration variances among the same type of urban functional zone. The results indicate that the dominant factor affecting PM2.5 pollution in the Nanchang urban area was the traffic conditions. Significant variances of PM2.5 concentrations among different urban functional zones throughout the year suggest that land use types generated a significant impact on PM2.5 concentrations and the impact did not change as the seasons changed. Land use intensity indexes including the building volume rate, building density, and green coverage rate presented an insignificant or counter-intuitive impact on PM2.5 concentrations when studied at the spatial scale of urban functional zones. Our study demonstrates that land use can greatly affect the PM2.5 levels. Additionally, the urban functional zone was an appropriate spatial scale to investigate the impact of land use type on PM2.5 pollution in urban areas. PMID:28445430

A study of the relationship between characteristic traits and Employee Engagement (A case study of nurses across Kermanshah, Iran in 2015).

PubMed

Ziapour, A; Kianipour, N

2015-01-01

Staff Engagement is an individual's interest and enthusiasm to accomplish the specified duties, all together with his sustained profession with organizations. Accordingly, the current research aimed to delve into the relationship between the characteristical traits and Staff Engag ement among nurses employed in Kermanshah-based hospitals in 2015. In this descriptive-correlational study, 322 nurses of public hospitals in Kermanshah were picked in 2015. For information gathering, Schaufeli & Bakker's Utrecht Staff Engagement scale and NEO Five-Factor Inventory (NEO-FFI) were used. Information was examined through descriptive analytics (Frequency, Rate, Average, and Standard Deviation) and inferential analytics (Pearson Correlation Test and Multiple Regression Analysis). Also, the 21st version of SPSS software was applied for information investigation. The results demonstrated that the greatest and smallest means of characteristical traits among nurses related to acceptance to experience (3.75 ± 0.63) and neuroticism (2.82 ± 0.55). Also, the highest and lowest means of Staff Engagement related to absorption (5.41 ± 0.76) and vigor (5.04 ± 0.86). Moreover, the outcomes of the Pearson correlation examination showed that there were important connections between the two dimensions of personality traits, i.e. neuroticism (P<0.001, r=0.172) and extraversion (P<0.001, r=0.038), and job engagement. Moreover, neuroticism had the most meaningful relationship with Staff Engagement (P<0.001, r=0.172). On the other hand, the outcomes of multiple regression analysis revealed that dutifulness and agreeableness were good predictors for job engagement. Given that the two scopes of personality traits, i.e. dutifulness and agreeableness, were closely related to work engagement, it was suggested that these dimensions were given a careful consideration in the event of employing workforce, especially nurses, with the aim of boosting the organizational productivity.

A study of the relationship between characteristic traits and Employee Engagement (A case study of nurses across Kermanshah, Iran in 2015)

PubMed Central

Ziapour, A; Kianipour, N

2015-01-01

Staff Engagement is an individual’s interest and enthusiasm to accomplish the specified duties, all together with his sustained profession with organizations. Accordingly, the current research aimed to delve into the relationship between the characteristical traits and Staff Engag ement among nurses employed in Kermanshah-based hospitals in 2015. In this descriptive-correlational study, 322 nurses of public hospitals in Kermanshah were picked in 2015. For information gathering, Schaufeli & Bakker’s Utrecht Staff Engagement scale and NEO Five-Factor Inventory (NEO-FFI) were used. Information was examined through descriptive analytics (Frequency, Rate, Average, and Standard Deviation) and inferential analytics (Pearson Correlation Test and Multiple Regression Analysis). Also, the 21st version of SPSS software was applied for information investigation. The results demonstrated that the greatest and smallest means of characteristical traits among nurses related to acceptance to experience (3.75 ± 0.63) and neuroticism (2.82 ± 0.55). Also, the highest and lowest means of Staff Engagement related to absorption (5.41 ± 0.76) and vigor (5.04 ± 0.86). Moreover, the outcomes of the Pearson correlation examination showed that there were important connections between the two dimensions of personality traits, i.e. neuroticism (P<0.001, r=0.172) and extraversion (P<0.001, r=0.038), and job engagement. Moreover, neuroticism had the most meaningful relationship with Staff Engagement (P<0.001, r=0.172). On the other hand, the outcomes of multiple regression analysis revealed that dutifulness and agreeableness were good predictors for job engagement. Given that the two scopes of personality traits, i.e. dutifulness and agreeableness, were closely related to work engagement, it was suggested that these dimensions were given a careful consideration in the event of employing workforce, especially nurses, with the aim of boosting the organizational productivity. PMID:28316680

Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

PubMed Central

Wang, Ke-Sheng; Liu, Xuefeng; Ategbole, Muyiwa; Xie, Xin; Liu, Ying; Xu, Chun; Xie, Changchun; Sha, Zhanxin

2017-01-01

Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (p<0.0001) and residence groups had significant interactions with gender, age group, education level, and employment status (p<0.05). Multiple logistic regression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p<0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions. PMID:28952708

Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

PubMed

Wang, Ke-Sheng; Liu, Xuefeng; Ategbole, Muyiwa; Xie, Xin; Liu, Ying; Xu, Chun; Xie, Changchun; Sha, Zhanxin

2017-09-27

Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (p<0.0001) and residence groups had significant interactions with gender, age group, education level, and employment status (p<0.05). Multiple logistic regression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p<0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions. Creative Commons Attribution License

Bayesian Estimation of Multivariate Latent Regression Models: Gauss versus Laplace

ERIC Educational Resources Information Center

Culpepper, Steven Andrew; Park, Trevor

2017-01-01

A latent multivariate regression model is developed that employs a generalized asymmetric Laplace (GAL) prior distribution for regression coefficients. The model is designed for high-dimensional applications where an approximate sparsity condition is satisfied, such that many regression coefficients are near zero after accounting for all the model…

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.

Body mass index, blood pressure, and glucose and lipid metabolism among permanent and fixed-term workers in the manufacturing industry: a cross-sectional study.

PubMed

Inoue, Mariko; Minami, Masahide; Yano, Eiji

2014-02-27

Temporary employment, a precarious form of employment, is recognized as social determinant of poor health. However, evidence supporting precarious employment as a risk factor for health is mainly obtained from subjective data. Studies using objective clinical measurement data in the assessment of health status are limited. This study compared body mass index (BMI), lipid and glucose metabolism, and health-related lifestyle factors between permanent workers and fixed-term workers employed in the manufacturing industry. Data of 1,701 male manufacturing industry workers <50 years old in Japan were collected and analyzed. Anthropometric data were BMI, calculated using measured height and weight of study participants, and blood pressure. For lipid metabolism, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglyceride levels were determined. For glucose metabolism, fasting plasma glucose and hemoglobin A1c (HbA1c) levels were measured. Multiple regression analysis adjusted for age and lifestyle factors was performed. BMI was significantly higher in permanent workers (22.9 kg/m2) compared with fixed-term workers (22.4 kg/m2). The leaner population (BMI < 18.5) was greater among fixed-term workers (8.3%) compared with permanent workers (4.0%), whereas the overweight population (BMI ≥ 25.0) was greater among permanent workers (21.4%) compared with fixed-term workers (18.1%). Although fixed-term workers tended not to be overweight, regression analysis adjusted for age and lifestyle factors suggested that fixed-term employment was significantly associated with higher blood pressure (systolic β = 2.120, diastolic β = 2.793), triglyceride (β = 11.147), fasting blood glucose (β = 2.218), and HbA1c (β = 0.107) compared with permanent workers (all p < 0.01). Fixed-term workers showed more health risks, such as poorer blood pressure and lipid and glucose metabolism, even when adjusted for age and lifestyle variables, although BMI of fixed-term workers were lower than permanent workers. Precarious work might contribute to a deteriorating health status even among less overweight populations.

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.

Assessing the Effectiveness of E-learning Integration in College Physics in the Alamo Community Colleges District

NASA Astrophysics Data System (ADS)

Zhou, Qiaoying

Academic achievement and student participation in physics are lower than desired. Research has shown that there is a shortage of college students entering science and technology fields such as physics. E-learning may provide the technology-oriented Net Generation learner an option for taking courses such as physics in a course modality with which they are most comfortable thus garnering more participation and higher academic achievement. A quantitative ex-post facto study was performed to compare face-to-face and E-learning modalities on course completion and physics achievement for an entire introductory physics course. The theoretical framework for this study was based on the constructivist theory of education that implies a student-centered learning process. The sample consisted of 116 students enrolled in introductory physics courses at four 2-year community colleges in Texas. Course completion, SAT scores, Force Concept Inventory examination scores, as well as demographic information and employment information were examined. Linear and ordinal multiple regression analysis were used to determine if course modality is predictive of physics achievement while controlling for general scholastic aptitude, current employment, the presence of children in the home, and teacher evaluations. The results showed that students in the E-learning course performed better on the Force Concept Inventory than those in the traditional course both in the multiple regression analysis, beta = .61, p < .001, and in the ordinal regression analysis, Wald(1) = 18.83, p < .001. A chi-square test was used to determine if course completion rates differ between students in the two course modalities. The results showed no difference in course completion rates between students in the two course modalities, chi 2(1, n = 116) = 1.02, p = .312. It was concluded that students in an E-learning course modality had higher physics achievement but were no more likely to complete the introductory physics course than students were in a face-to-face modality. It was recommended that other colleges and universities should develop and test E-learning courses for introductory physics, that larger sample sizes should be used in future studies, and that additional outcome variables including the likelihood that a student chooses physics as a major or the likelihood that a student completes a physics degree should be examined.

The relationship between coping with stress and employment in patients receiving maintenance hemodialysis.

PubMed

Takaki, Jiro; Yano, Eiji

2006-07-01

The goal of this study was to assess the relationship between emotion- and task-oriented coping (EOC/TOC) with stress and employment in patients undergoing maintenance hemodialysis. Individuals aged 18 to 64 yr who had uremia and had been undergoing hemodialysis regularly for at least three months were evaluated according to sociodemographic and clinical factors. Work status was defined using the most recent International Labour Organization definitions. Patients were requested to complete the following questionnaires: the Japanese version of the Coping Inventory for Stressful Situations, the Short Form-36 Health Survey, an item on itchiness, the Self-Efficacy on Health-Related Behavior Scale, the Japanese version of the Health Locus of Control Scale, the Social Support Scale, and the Japanese version of the Hospital Anxiety and Depression Scale. A total of 317 individuals participated in this study. Among men, age, physical functioning, EOC, and depression differed significantly (p<0.05) depending on employment. Among women, marital status, household composition, EOC, depression, and anxiety differed significantly (p<0.05) depending on employment. TOC was not significantly associated with employment in either sex. Multiple logistic regression analyses, including possible confounders, indicated that when EOC increased by 10 points, the associated adjusted odds ratio of an unemployed or economically inactive status changed by 1.48 (95% confidence interval, 1.04-2.11; p=0.030) in men and by 1.88 (95% confidence interval, 1.02-3.46; p=0.042) in women. These results suggest that EOC is associated with employment in patients receiving maintenance hemodialysis.

Multimorbidity as an important issue among women: results of a gender difference investigation in a large population-based cross-sectional study in West Asia.

PubMed

Alimohammadian, Masoomeh; Majidi, Azam; Yaseri, Mehdi; Ahmadi, Batoul; Islami, Farhad; Derakhshan, Mohammad; Delavari, Alireza; Amani, Mohammad; Feyz-Sani, Akbar; Poustchi, Hossein; Pourshams, Akram; Sadjadi, Amir Mahdi; Khoshnia, Masoud; Qaravi, Samad; Abnet, Christian C; Dawsey, Sanford; Brennan, Paul; Kamangar, Farin; Boffetta, Paolo; Sadjadi, Alireza; Malekzadeh, Reza

2017-05-09

To investigate the impact of gender on multimorbidity in northern Iran. A cross-sectional analysis of the Golestan cohort data. Golestan Province, Iran. 49 946 residents (age 40-75 years) of Golestan Province, Iran. Researchers collected data related to multimorbidity, defined as co-existence of two or more chronic diseases in an individual, at the beginning of a representative cohort study which recruited its participants from 2004 to 2008. The researchers utilised simple and multiple Poisson regression models with robust variances to examine the simultaneous effects of multiple factors. Women had a 25.0% prevalence of multimorbidity, whereas men had a 13.4% prevalence (p<0.001). Women of all age-groups had a higher prevalence of multimorbidity. Of note, multimorbidity began at a lower age (40-49 years) in women (17.3%) compared with men (8.6%) of the same age (p<0.001). This study identified significant interactions between gender as well as socioeconomic status, ethnicity, physical activity, marital status, education level and smoking (p<0.01). Prevention and control of multimorbidity requires health promotion programmes to increase public awareness about the modifiable risk factors, particularly among women. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Trends and Patterns in a New Time Series of Natural and Anthropogenic Methane Emissions, 1980-2000

NASA Astrophysics Data System (ADS)

Matthews, E.; Bruhwiler, L.; Themelis, N. J.

2007-12-01

We report on a new time series of methane (CH4) emissions from anthropogenic and natural sources developed for a multi-decadal methane modeling study (see following presentation by Bruhwiler et al.). The emission series extends from 1980 through the early 2000s with annual emissions for all countries has several features distinct from the source histories based on IPCC methods typically employed in modeling the global methane cycle. Fossil fuel emissions rely on 7 fuel-process emission combinations and minimize reliance on highly-uncertain emission factors. Emissions from ruminant animals employ regional profiles of bovine populations that account for the influence of variable age- and size-demographics on emissions and are ~15% lower than other estimates. Waste-related emissions are developed using an approach that avoids using of data-poor emission factors and accounts for impacts of recycling and thermal treatment of waste on diverting material from landfills and CH4 capture at landfill facilities. Emissions from irrigated rice use rice-harvest areas under 3 water-management systems and a new historical data set that analyzes multiple sources for trends in water management since 1980. A time series of emissions from natural wetlands was developed by applying a multiple-regression model derived from full process-based model of Walter with analyzed meteorology from the ERA-40 reanalysis.

A county-level cross-sectional analysis of positive deviance to assess multiple population health outcomes in Indiana.

PubMed

Hendryx, Michael; Guerra-Reyes, Lucia; Holland, Benjamin D; McGinnis, Michael Dean; Meanwell, Emily; Middlestadt, Susan E; Yoder, Karen M

2017-10-11

To test a positive deviance method to identify counties that are performing better than statistical expectations on a set of population health indicators. Quantitative, cross-sectional county-level secondary analysis of risk variables and outcomes in Indiana. Data are analysed using multiple linear regression to identify counties performing better or worse than expected given traditional risk indicators, with a focus on 'positive deviants' or counties performing better than expected. Counties in Indiana (n=92) constitute the unit of analysis. Per cent adult obesity, per cent fair/poor health, low birth weight per cent, per cent with diabetes, years of potential life lost, colorectal cancer incidence rate and circulatory disease mortality rate. County performance that outperforms expectations is for the most part outcome specific. But there are a few counties that performed particularly well across most measures. The positive deviance approach provides a means for state and local public health departments to identify places that show better health outcomes despite demographic, social, economic or behavioural disadvantage. These places may serve as case studies or models for subsequent investigations to uncover best practices in the face of adversity and generalise effective approaches to other areas. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

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…

Predicting Patient Advocacy Engagement: A Multiple Regression Analysis Using Data From Health Professionals in Acute-Care Hospitals.

PubMed

Jansson, Bruce S; Nyamathi, Adeline; Heidemann, Gretchen; Duan, Lei; Kaplan, Charles

2015-01-01

Although literature documents the need for hospital social workers, nurses, and medical residents to engage in patient advocacy, little information exists about what predicts the extent they do so. This study aims to identify predictors of health professionals' patient advocacy engagement with respect to a broad range of patients' problems. A cross-sectional research design was employed with a sample of 94 social workers, 97 nurses, and 104 medical residents recruited from eight hospitals in Los Angeles. Bivariate correlations explored whether seven scales (Patient Advocacy Eagerness, Ethical Commitment, Skills, Tangible Support, Organizational Receptivity, Belief Other Professionals Engage, and Belief the Hospital Empowers Patients) were associated with patient advocacy engagement, measured by the validated Patient Advocacy Engagement Scale. Regression analysis examined whether these scales, when controlling for sociodemographic and setting variables, predicted patient advocacy engagement. While all seven predictor scales were significantly associated with patient advocacy engagement in correlational analyses, only Eagerness, Skills, and Belief the Hospital Empowers Patients predicted patient advocacy engagement in regression analyses. Additionally, younger professionals engaged in higher levels of patient advocacy than older professionals, and social workers engaged in greater patient advocacy than nurses. Limitations and the utility of these findings for acute-care hospitals are discussed.

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.

Regional flow duration curves: Geostatistical techniques versus multivariate regression

USGS Publications Warehouse

Pugliese, Alessio; Farmer, William H.; Castellarin, Attilio; Archfield, Stacey A.; Vogel, Richard M.

2016-01-01

A period-of-record flow duration curve (FDC) represents the relationship between the magnitude and frequency of daily streamflows. Prediction of FDCs is of great importance for locations characterized by sparse or missing streamflow observations. We present a detailed comparison of two methods which are capable of predicting an FDC at ungauged basins: (1) an adaptation of the geostatistical method, Top-kriging, employing a linear weighted average of dimensionless empirical FDCs, standardised with a reference streamflow value; and (2) regional multiple linear regression of streamflow quantiles, perhaps the most common method for the prediction of FDCs at ungauged sites. In particular, Top-kriging relies on a metric for expressing the similarity between catchments computed as the negative deviation of the FDC from a reference streamflow value, which we termed total negative deviation (TND). Comparisons of these two methods are made in 182 largely unregulated river catchments in the southeastern U.S. using a three-fold cross-validation algorithm. Our results reveal that the two methods perform similarly throughout flow-regimes, with average Nash-Sutcliffe Efficiencies 0.566 and 0.662, (0.883 and 0.829 on log-transformed quantiles) for the geostatistical and the linear regression models, respectively. The differences between the reproduction of FDC's occurred mostly for low flows with exceedance probability (i.e. duration) above 0.98.

Preoperative Biometric Parameters Predict the Vault after ICL Implantation: A Retrospective Clinical Study.

PubMed

Zheng, Qian-Yin; Xu, Wen; Liang, Guan-Lu; Wu, Jing; Shi, Jun-Ting

2016-01-01

To investigate the correlation between the preoperative biometric parameters of the anterior segment and the vault after implantable Collamer lens (ICL) implantation via this retrospective study. Retrospective clinical study. A total of 78 eyes from 41 patients who underwent ICL implantation surgery were included in this study. Preoperative biometric parameters, including white-to-white (WTW) diameter, central corneal thickness, keratometer, pupil diameter, anterior chamber depth, sulcus-to-sulcus diameter, anterior chamber area (ACA) and central curvature radius of the anterior surface of the lens (Lenscur), were measured. Lenscur and ACA were measured with Rhinoceros 5.0 software on the image scanned with ultrasound biomicroscopy (UBM). The vault was assessed by UBM 3 months after surgery. Multiple stepwise regression analysis was employed to identify the variables that were correlated with the vault. The results showed that the vault was correlated with 3 variables: ACA (22.4 ± 4.25 mm2), WTW (11.36 ± 0.29 mm) and Lenscur (9.15 ± 1.21 mm). The regressive equation was: vault (mm) = 1.785 + 0.017 × ACA + 0.051 × Lenscur - 0.203 × WTW. Biometric parameters of the anterior segment (ACA, WTW and Lenscur) can predict the vault after ICL implantation using a new regression equation. © 2016 The Author(s) Published by S. Karger AG, Basel.

[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.

Family-to-work spillover and appraisals of caregiving by employed women caring for their elderly parents in Japan

PubMed Central

SAKKA, Mariko; SATO, Iori; IKEDA, Mari; HASHIZUME, Hirofumi; UEMORI, Masayo; KAMIBEPPU, Kiyoko

2016-01-01

We examined the differences in family-to-work spillover between employed women who did and did not have caregiving responsibilities for elderly parents and the relationship between family-to-work spillover and negative and positive appraisals of caregiving using moderation analysis. A cross-sectional survey was conducted with middle-aged employed women (age ≥40 years) from four large companies. Negative and positive family-to-work spillover (FWNS and FWPS, respectively) and negative and positive appraisals of caregiving were measured. Data from 386 non-caregivers and 82 caregivers were analyzed using Fisher’s exact tests, Welch’s t-tests, and hierarchical multiple regression. Results showed that FWNS was higher in caregivers than in non-caregivers, while there was no significant difference in FWPS. Caregiver “fulfillment from the caregiving role” (a subscale of positive appraisal) buffered the effects of caregiver “feelings of social restriction” (a subscale of negative appraisal) on FWNS. On the other hand, caregiver “commitment to caregiving tasks” (another positive subscale) intensified the effects of “feelings of social restriction” on FWNS. However, there was no relationship between negative and positive appraisals of caregiving and FWPS. These findings suggest that both negative and positive appraisals of caregiving are important contributors to FWNS among employed women caring for their parents. PMID:26829970

Mental health and substance use among self-employed lawyers and pharmacists.

PubMed

Leignel, S; Schuster, J-P; Hoertel, N; Poulain, X; Limosin, F

2014-04-01

Self-employed workers experience occupational stress and may suffer from various mental health disorders. To assess the mental health, substance use and risk factors for psychological distress in a sample of self-employed lawyers and pharmacists. A cross-sectional study, using self-completion postal questionnaires, of lawyers and pharmacists. The General Health Questionnaire-28 (GHQ-28) was used as a measure of current mental health, and some additional questions evaluated alcohol, tobacco and psychotropic drug use and somatic morbidity. A multiple regression model was used to analyse the respective impact of the different risk factors on psychological suffering. A total of 1282 lawyers and 1153 pharmacists participated representing response rates of 36 and 35%, respectively. According to the GHQ-28 score, the rate of psychological distress was high in the sample overall, especially in lawyers (52 versus 47% in pharmacists, P < 0.05). According to the mean number of drinks per day, 16% of the lawyers and 13% of the pharmacists reported alcohol misuse, and lawyers were twice as likely as pharmacists to smoke (26 versus 13%, P < 0.001). Higher GHQ-28 scores were associated in lawyers with female gender, being widowed or divorced, smoking and using anxiolytic medication and in pharmacists with being younger, smoking, alcohol abuse and anxiolytic and hypnotic use. In our sample of these self-employed groups, both pharmacists and lawyers reported a high rate of psychological distress.

Health and health care of employed women and homemakers: family factors.

PubMed

Muller, C

1986-01-01

Women's increasing participation in the labor force has resulted from availability of fertility control, changed attitudes toward family size, a strong demand for occupations traditionally filled by women, and other factors. Despite many social changes, employed women continue to be concentrated in lower-income pursuits and frequently have major responsibility for the household. This paper is drawn from a study that explored the association of occupation and home responsibilities with the health of employed women and men and compared them with female homemakers. It also examined variations in the use of physician and hospital services. The principal data source was the National Health Interview Survey tapes for 1975-77. Nurturant role responsibilities were derived from records of members of the index adult's household. This paper reports on comparisons of employed women with homemakers using multiple regression analysis, and also on direct comparisons of the three work-sex groups. Study findings suggest that better health is associated with desired, positive roles such as marriage and married parenthood. Worse health is associated with unwelcome role expansions such as single parenthood, child disability, having a sick spouse and marital dissolution. Effects vary by both sex and work status. It is suggested that it is not the number of activities that may be burdensome to women's health but inability to choose one's roles and organize one's resources to meet their demands.

Social Workers' Perceived Role Clarity as Members of an Interdisciplinary Team in Brain Injury Settings.

PubMed

Vungkhanching, Martha; Tonsing, Kareen N

2016-08-11

This study investigated social workers' role clarity as members of an interdisciplinary team in traumatic and acquired brain injury treatment settings. A total of 37 social workers from 7 Western countries completed an anonymous online survey questionnaire. The majority of participants have more than 10 years of experience working in brain injury treatment settings (59.5%), and about 54% have been in their current employment for more than 10 years. Findings revealed that there were significant positive correlations between perceived respect, team collaboration, and perceived value of self for team with role clarity. Multiple regression analysis revealed that perceived value of self for team was a significant predictor of role clarity (p < .05).

Building intelligent communication systems for handicapped aphasiacs.

PubMed

Fu, Yu-Fen; Ho, Cheng-Seen

2010-01-01

This paper presents an intelligent system allowing handicapped aphasiacs to perform basic communication tasks. It has the following three key features: (1) A 6-sensor data glove measures the finger gestures of a patient in terms of the bending degrees of his fingers. (2) A finger language recognition subsystem recognizes language components from the finger gestures. It employs multiple regression analysis to automatically extract proper finger features so that the recognition model can be fast and correctly constructed by a radial basis function neural network. (3) A coordinate-indexed virtual keyboard allows the users to directly access the letters on the keyboard at a practical speed. The system serves as a viable tool for natural and affordable communication for handicapped aphasiacs through continuous finger language input.

On the Misconception of Multicollinearity in Detection of Moderating Effects: Multicollinearity Is Not Always Detrimental.

PubMed

Shieh, Gwowen

2010-05-28

Due to its extensive applicability and computational ease, moderated multiple regression (MMR) has been widely employed to analyze interaction effects between 2 continuous predictor variables. Accordingly, considerable attention has been drawn toward the supposed multicollinearity problem between predictor variables and their cross-product term. This article attempts to clarify the misconception of multicollinearity in MMR studies. The counterintuitive yet beneficial effects of multicollinearity on the ability to detect moderator relationships are explored. Comprehensive treatments and numerical investigations are presented for the simplest interaction model and more complex three-predictor setting. The results provide critical insight that both helps avoid misleading interpretations and yields better understanding for the impact of intercorrelation among predictor variables in MMR analyses.

Problematic mobile phone use and big-five personality domains.

PubMed

Takao, Motoharu

2014-04-01

Although a mobile phone is useful and attractive as a tool for communication and interpersonal interaction, there exists the risk of its problematic or addictive use. This study aims to investigate the correlation between the big-five personality domains and problematic mobile phone use. The Mobile Phone Problem Usage Scale and the NEO Five-Factor Inventory (NEO-FFI) were employed in this study. Survey data were gathered from 504 university students for multiple regression analysis. Problematic mobile phone use is a function of gender, extraversion, neuroticism, openness-to-experience; however, it is not a function of agreeableness or conscientiousness. The measurement of these predictors would enable the screening of and intervening in the potentially problematic behaviors of mobile phone users.

A novel approach to analyzing lung cancer mortality disparities: Using the exposome and a graph-theoretical toolchain

PubMed Central

Juarez, Paul D; Hood, Darryl B; Rogers, Gary L; Baktash, Suzanne H; Saxton, Arnold M; Matthews-Juarez, Patricia; Im, Wansoo; Cifuentes, Myriam Patricia; Phillips, Charles A; Lichtveld, Maureen Y; Langston, Michael A

2017-01-01

Objectives The aim is to identify exposures associated with lung cancer mortality and mortality disparities by race and gender using an exposome database coupled to a graph theoretical toolchain. Methods Graph theoretical algorithms were employed to extract paracliques from correlation graphs using associations between 2162 environmental exposures and lung cancer mortality rates in 2067 counties, with clique doubling applied to compute an absolute threshold of significance. Factor analysis and multiple linear regressions then were used to analyze differences in exposures associated with lung cancer mortality and mortality disparities by race and gender. Results While cigarette consumption was highly correlated with rates of lung cancer mortality for both white men and women, previously unidentified novel exposures were more closely associated with lung cancer mortality and mortality disparities for blacks, particularly black women. Conclusions Exposures beyond smoking moderate lung cancer mortality and mortality disparities by race and gender. Policy Implications An exposome approach and database coupled with scalable combinatorial analytics provides a powerful new approach for analyzing relationships between multiple environmental exposures, pathways and health outcomes. An assessment of multiple exposures is needed to appropriately translate research findings into environmental public health practice and policy. PMID:29152601

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.

Quasi-Likelihood Techniques in a Logistic Regression Equation for Identifying Simulium damnosum s.l. Larval Habitats Intra-cluster Covariates in Togo.

PubMed

Jacob, Benjamin G; Novak, Robert J; Toe, Laurent; Sanfo, Moussa S; Afriyie, Abena N; Ibrahim, Mohammed A; Griffith, Daniel A; Unnasch, Thomas R

2012-01-01

The standard methods for regression analyses of clustered riverine larval habitat data of Simulium damnosum s.l. a major black-fly vector of Onchoceriasis, postulate models relating observational ecological-sampled parameter estimators to prolific habitats without accounting for residual intra-cluster error correlation effects. Generally, this correlation comes from two sources: (1) the design of the random effects and their assumed covariance from the multiple levels within the regression model; and, (2) the correlation structure of the residuals. Unfortunately, inconspicuous errors in residual intra-cluster correlation estimates can overstate precision in forecasted S.damnosum s.l. riverine larval habitat explanatory attributes regardless how they are treated (e.g., independent, autoregressive, Toeplitz, etc). In this research, the geographical locations for multiple riverine-based S. damnosum s.l. larval ecosystem habitats sampled from 2 pre-established epidemiological sites in Togo were identified and recorded from July 2009 to June 2010. Initially the data was aggregated into proc genmod. An agglomerative hierarchical residual cluster-based analysis was then performed. The sampled clustered study site data was then analyzed for statistical correlations using Monthly Biting Rates (MBR). Euclidean distance measurements and terrain-related geomorphological statistics were then generated in ArcGIS. A digital overlay was then performed also in ArcGIS using the georeferenced ground coordinates of high and low density clusters stratified by Annual Biting Rates (ABR). This data was overlain onto multitemporal sub-meter pixel resolution satellite data (i.e., QuickBird 0.61m wavbands ). Orthogonal spatial filter eigenvectors were then generated in SAS/GIS. Univariate and non-linear regression-based models (i.e., Logistic, Poisson and Negative Binomial) were also employed to determine probability distributions and to identify statistically significant parameter estimators from the sampled data. Thereafter, Durbin-Watson test statistics were used to test the null hypothesis that the regression residuals were not autocorrelated against the alternative that the residuals followed an autoregressive process in AUTOREG. Bayesian uncertainty matrices were also constructed employing normal priors for each of the sampled estimators in PROC MCMC. The residuals revealed both spatially structured and unstructured error effects in the high and low ABR-stratified clusters. The analyses also revealed that the estimators, levels of turbidity and presence of rocks were statistically significant for the high-ABR-stratified clusters, while the estimators distance between habitats and floating vegetation were important for the low-ABR-stratified cluster. Varying and constant coefficient regression models, ABR- stratified GIS-generated clusters, sub-meter resolution satellite imagery, a robust residual intra-cluster diagnostic test, MBR-based histograms, eigendecomposition spatial filter algorithms and Bayesian matrices can enable accurate autoregressive estimation of latent uncertainity affects and other residual error probabilities (i.e., heteroskedasticity) for testing correlations between georeferenced S. damnosum s.l. riverine larval habitat estimators. The asymptotic distribution of the resulting residual adjusted intra-cluster predictor error autocovariate coefficients can thereafter be established while estimates of the asymptotic variance can lead to the construction of approximate confidence intervals for accurately targeting productive S. damnosum s.l habitats based on spatiotemporal field-sampled count data.

Employment outcomes among African Americans and Whites with mental illness.

PubMed

Lukyanova, Valentina V; Balcazar, Fabricio E; Oberoi, Ashmeet K; Suarez-Balcazar, Yolanda

2014-01-01

People with mental illness often experience major difficulties in finding and maintaining sustainable employment. African Americans with mental illness have additional challenges to secure a job, as reflected in their significantly lower employment rates compared to Whites. To examine the factors that contribute to racial disparities in employment outcomes for African-American and White Vocational Rehabilitation (VR) consumers with mental illness. This study used VR data from a Midwestern state that included 2,122 African American and 4,284 White participants who reported mental illness in their VR records. Logistic regression analyses were conducted. African Americans had significantly more closures after referral and were closed as non-rehabilitated more often than Whites. Logistic regressions indicated that African Americans are less likely to be employed compared to Whites. The regression also found differences by gender (females more likely to find jobs than males) and age (middle age consumers [36 to 50] were more likely to find jobs than younger consumers [18 to 35]). Case expenditures between $1,000 and $4,999 were significantly lower for African Americans. VR agencies need to remain vigilant of potential discrepancies in service delivery among consumers from various ethnic groups and work hard to assure as much equality as possible.

Pattern variation of fish fingerling abundance in the Na Thap Tidal river of Southern Thailand: 2005-2015

NASA Astrophysics Data System (ADS)

Donroman, T.; Chesoh, S.; Lim, A.

2018-04-01

This study aimed to investigate the variation patterns of fish fingerling abundance based on month, year and sampling site. Monthly collecting data set of the Na Thap tidal river of southern Thailand, were obtained from June 2005 to October 2015. The square root transformation was employed for maintaining the fingerling data normality. Factor analysis was applied for clustering number of fingerling species and multiple linear regression was used to examine the association between fingerling density and year, month and site. Results from factor analysis classified fingerling into 3 factors based on saline preference; saline water, freshwater and ubiquitous species. The results showed a statistically high significant relation between fingerling density, month, year and site. Abundance of saline water and ubiquitous fingerling density showed similar pattern. Downstream site presented highest fingerling density whereas almost of freshwater fingerling occurred in upstream. This finding confirmed that factor analysis and the general linear regression method can be used as an effective tool for predicting and monitoring wild fingerling density in order to sustain fish stock management.

Use of chemical indicators of beer aging for ex-post checking of storage conditions and prediction of the sensory stability of beer.

PubMed

Cejka, Pavel; Culík, Jiří; Horák, Tomáš; Jurková, Marie; Olšovská, Jana

2013-12-26

The rate of beer aging is affected by storage conditions including largely time and temperature. Although bottled beer is commonly stored for up to 1 year, sensorial damage of it is quite frequent. Therefore, a method for retrospective determination of temperature of stored beer was developed. The method is based on the determination of selected carbonyl compounds called as "aging indicators", which are formed during beer aging. The aging indicators were determined using GC-MS after precolumn derivatization with O-(2,3,4,5,6-pentaflourobenzyl)hydroxylamine hydrochloride, and their profile was correlated with the development of old flavor evolving under defined conditions (temperature, time) using both a mathematical and statistical apparatus. Three approaches, including calculation from regression graph, multiple linear regression, and neural networks, were employed. The ultimate uncertainty of the method ranged from 3.0 to 11.0 °C depending on the approach used. Furthermore, the assay was extended to include prediction of beer tendency to sensory aging from freshly bottled beer.

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

EPA Science Inventory

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

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

EPA Science Inventory

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

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

PubMed Central

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

2016-01-01

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

20 CFR 345.102 - Multiple employer limitation.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Multiple employer limitation. 345.102 Section 345.102 Employees' Benefits RAILROAD RETIREMENT BOARD REGULATIONS UNDER THE RAILROAD UNEMPLOYMENT INSURANCE ACT EMPLOYERS' CONTRIBUTIONS AND CONTRIBUTION REPORTS General Provisions and Definitions § 345.102...

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

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.

Paid employment of mothers and fathers of an adult child with multiple disabilities.

PubMed

Einam, M; Cuskelly, M

2002-02-01

Paid employment is increasingly undertaken by mothers as their children age, with the majority of women being in employment by the time their offspring are adult. Opportunities to engage in employment appear to be reduced for mothers of children with disabilities; however, little is known about the employment of mothers or fathers of adults with disabilities. Data were collected regarding the employment decisions of parents of a young adult with multiple disabilities and contrasted with those of parents whose children were all developing normally. Twenty-five mothers and 12 fathers of a young adult with multiple disabilities were interviewed, as were 25 comparison mothers and 19 comparison fathers. Data collected included hours of work, reasons for employment status, attitudes towards work and child care, and psychological well-being. Clear differences were found between the two groups. Mothers and fathers of a child with multiple disabilities showed different engagement patterns with the paid workforce from comparison parents. Hours of work for fathers of a young adult with multiple disabilities showed a bi-modal distribution, with some fathers working fewer hours than usual and others working very long hours. For mothers in both groups, the number of hours in paid employment was negatively associated with reports of psychological problems. Increased attention needs to be given to the employment opportunities of parents of children with disabilities since employment appears to play a protective role for mothers, in particular. Services provided to adults with disabilities will need to change if parents are to have the same life chances as parents without adult offspring with a disability.

Undergraduate Student Motivation in Modularized Developmental Mathematics Courses

ERIC Educational Resources Information Center

Pachlhofer, Keith A.

2017-01-01

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

Categorical Variables in Multiple Regression: Some Cautions.

ERIC Educational Resources Information Center

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

1988-01-01

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

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.

Comparison of Employer Factors in Disability and Other Employment Discrimination Charges

ERIC Educational Resources Information Center

Nazarov, Zafar E.; von Schrader, Sarah

2014-01-01

Purpose: We explore whether certain employer characteristics predict Americans with Disabilities Act (ADA) charges and whether the same characteristics predict receipt of the Age Discrimination in Employment Act and Title VII of the Civil Rights Act charges. Method: We estimate a set of multivariate regressions using the ordinary least squares…

Competitive Employment for People with Autism: Correlates of Successful Closure in Competitive and Supported Employment

ERIC Educational Resources Information Center

Schaller, James; Yang, Nancy K.

2005-01-01

Differences in rates of case closure, case service cost, hours worked per week, and weekly wage between customers with autism closed successfully in competitive employment and supported employment were found using the Rehabilitation Service Administration national database of 2001. Using logistic regression, customer demographic variables related…

The cost of unintended pregnancies for employer-sponsored health insurance plans.

PubMed

Dieguez, Gabriela; Pyenson, Bruce S; Law, Amy W; Lynen, Richard; Trussell, James

2015-04-01

Pregnancy is associated with a significant cost for employers providing health insurance benefits to their employees. The latest study on the topic was published in 2002, estimating the unintended pregnancy rate for women covered by employer-sponsored insurance benefits to be approximately 29%. The primary objective of this study was to update the cost of unintended pregnancy to employer-sponsored health insurance plans with current data. The secondary objective was to develop a regression model to identify the factors and associated magnitude that contribute to unintended pregnancies in the employee benefits population. We developed stepwise multinomial logistic regression models using data from a national survey on maternal attitudes about pregnancy before and shortly after giving birth. The survey was conducted by the Centers for Disease Control and Prevention through mail and via telephone interviews between 2009 and 2011 of women who had had a live birth. The regression models were then applied to a large commercial health claims database from the Truven Health MarketScan to retrospectively assign the probability of pregnancy intention to each delivery. Based on the MarketScan database, we estimate that among employer-sponsored health insurance plans, 28.8% of pregnancies are unintended, which is consistent with national findings of 29% in a survey by the Centers for Disease Control and Prevention. These unintended pregnancies account for 27.4% of the annual delivery costs to employers in the United States, or approximately 1% of the typical employer's health benefits spending for 1 year. Using these findings, we present a regression model that employers could apply to their claims data to identify the risk for unintended pregnancies in their health insurance population. The availability of coverage for contraception without employee cost-sharing, as was required by the Affordable Care Act in 2012, combined with the ability to identify women who are at high risk for an unintended pregnancy, can help employers address the costs of unintended pregnancies in their employee benefits population. This can also help to bring contraception efforts into the mainstream of other preventive and wellness programs, such as smoking cessation, obesity management, and diabetes control programs.

The Cost of Unintended Pregnancies for Employer-Sponsored Health Insurance Plans

PubMed Central

Dieguez, Gabriela; Pyenson, Bruce S.; Law, Amy W.; Lynen, Richard; Trussell, James

2015-01-01

Background Pregnancy is associated with a significant cost for employers providing health insurance benefits to their employees. The latest study on the topic was published in 2002, estimating the unintended pregnancy rate for women covered by employer-sponsored insurance benefits to be approximately 29%. Objectives The primary objective of this study was to update the cost of unintended pregnancy to employer-sponsored health insurance plans with current data. The secondary objective was to develop a regression model to identify the factors and associated magnitude that contribute to unintended pregnancies in the employee benefits population. Methods We developed stepwise multinomial logistic regression models using data from a national survey on maternal attitudes about pregnancy before and shortly after giving birth. The survey was conducted by the Centers for Disease Control and Prevention through mail and via telephone interviews between 2009 and 2011 of women who had had a live birth. The regression models were then applied to a large commercial health claims database from the Truven Health MarketScan to retrospectively assign the probability of pregnancy intention to each delivery. Results Based on the MarketScan database, we estimate that among employer-sponsored health insurance plans, 28.8% of pregnancies are unintended, which is consistent with national findings of 29% in a survey by the Centers for Disease Control and Prevention. These unintended pregnancies account for 27.4% of the annual delivery costs to employers in the United States, or approximately 1% of the typical employer's health benefits spending for 1 year. Using these findings, we present a regression model that employers could apply to their claims data to identify the risk for unintended pregnancies in their health insurance population. Conclusion The availability of coverage for contraception without employee cost-sharing, as was required by the Affordable Care Act in 2012, combined with the ability to identify women who are at high risk for an unintended pregnancy, can help employers address the costs of unintended pregnancies in their employee benefits population. This can also help to bring contraception efforts into the mainstream of other preventive and wellness programs, such as smoking cessation, obesity management, and diabetes control programs. PMID:26005515

Use of Thematic Mapper for water quality assessment

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

Factors associated with experienced discrimination among people using mental health services in England.

PubMed

Hamilton, S; Corker, E; Weeks, C; Williams, P; Henderson, C; Pinfold, V; Rose, D; Thornicroft, G

2016-08-01

Research has found considerable variation in how far individuals with a diagnosis of mental illness experience discrimination. This study tested four hypotheses: (i) a diagnosis of schizophrenia will be associated with more discrimination than depression, anxiety or bipolar disorder; (ii) people with a history of involuntary treatment will report more discrimination than people without; (iii) higher levels of avoidance behaviour due to anticipated discrimination will be associated with higher levels of discrimination and (iv) longer time in contact with services will be associated with higher levels of discrimination. Three thousand five hundred and seventy-nine people using mental health services in England took part in structured telephone interviews about discrimination experiences. A multiple regression model found that study year, age, employment status, length of time in mental health services, disagreeing with the diagnosis, anticipating discrimination in personal relationships and feeling the need to conceal a diagnosis from others were significantly associated with higher levels of experienced discrimination. Findings suggest that discrimination is not related to specific diagnoses but rather is associated with mental health problems generally. An association between unemployment and discrimination may indicate that employment protects against experiences of discrimination, supporting efforts to improve access to employment among people with a diagnosis of mental illness.

Job coach factors associated with community-based employment service programme outcome measures for people with disabilities--a Taiwan case study.

PubMed

Yun-Tung, Wang

2010-01-01

The aim of this study is to explore whether/which job coach factors were significantly associated with the community-based employment service (CBES) programme outcome measures in Taiwan. This study used the 2003-2005 CBES programme for People with Disabilities Database in Taipei City in Taiwan (n = 3924) to do a secondary data analysis using hierarchical multiple linear regression. This study found that 'occurrences of the services provided by the job coaches' variable was definitely the dominant predictor and explained additional 19.6% and 27.8% of the variances of annual salary and annual working month outcome measures, respectively. In addition, among six composition variables of 'occurrences of the services provided by the job coaches', 'occurrences of follow-up guidance', 'occurrences of intensive guidance', and 'occurrences of consultation before interviews with employer/director of human resources' were more powerful than the other three in predicting outcomes. Job coach factors in this study were significantly correlated with CBES programme outcome measures for people with disabilities in Taiwan after controlling for the socio-demographic variables. It indicates that the more inputs in the people with disabilities made by job coaches equates to better outcomes in this Taiwan case study.

Health related quality of life and influencing factors among welders.

PubMed

Qin, Jingxiang; Liu, Wuzhong; Zhu, Jun; Weng, Wei; Xu, Jiaming; Ai, Zisheng

2014-01-01

Occupational exposure to welding fumes is a serious occupational health problem all over the world. Welders are exposed to many occupational hazards; these hazards might cause some occupational diseases. The aim of the study was to assess the health related quality of life (HRQL) of electric welders in Shanghai China and explore influencing factors to HRQL of welders. 301 male welders (without pneumoconiosis) and 305 non-dust male workers in Shanghai were enrolled in this study. Short Form-36 (SF-36) health survey questionnaires were applied in this cross-sectional study. Socio-demographic, working and health factors were also collected. Multiple stepwise regress analysis was used to identify significant factors related to the eight dimension scores. Six dimensions including role-physical (RP), bodily pain (BP), general health (GH), validity (VT), social function (SF), and mental health (MH) were significantly worse in welders compared to non-dust workers. Multiple stepwise regress analysis results show that native place, monthly income, quantity of children, drinking, sleep time, welding type, use of personal protective equipment (PPE), great events in life, and some symptoms including dizziness, discomfort of cervical vertebra, low back pain, cough and insomnia may be influencing factors for HRQL of welders. Among these factors, only sleep time and the use of PPE were salutary. Some dimensions of HRQL of these welders have been affected. Enterprises which employ welders should take measures to protect the health of these people and improve their HRQL.

Efficacy prediction of cevimeline in patients with Sjögren's syndrome.

PubMed

Yamada, Hiroyuki; Nakagawa, Yoichi; Wakamatsu, Ei; Sumida, Takayuki; Yamachika, Shigeo; Nomura, Yoshiaki; Mishima, Kenji; Saito, Ichiro

2007-08-01

The objective of this study was to examine the clinical and immunological factors influencing the efficacy of cevimeline hydrochloride hydrate (cevimeline) for the treatment of xerostomia in patients with Sjögren's syndrome (SS). Thirty primary SS patients who were medicated with cevimeline were enrolled in this study. Whole stimulated sialometry (WSS) was compared between pre- and posttreatment points (4 weeks after oral cevimeline administration) and the increment rate of WSS was calculated. Multiple regression was employed to examine the relative contributions of the clinical and immunological factors, including age, pretreatment WSS, duration of disease, sialography, minor salivary gland biopsy, anti-Ro/SS-A antibodies, anti-La/SS-B antibodies, and antibodies to muscarinic type 3 receptors to the posttreatment WSS. Patients with normal sialography findings, negative minor salivary gland biopsy, and absence of anti-La/SS-B antibodies had significantly higher increment rates of WSS compared with those with positive findings (p=0.042, 0.002, and 0.018, respectively). Results of the multiple regression analysis showed that sialography (coefficient=-0.867, p=0.004) and minor salivary gland biopsy (coefficient=-0.869, p=0.003) had significant associations with the posttreatment WSS. Our preliminary results demonstrated the relationship between the effect of cevimeline on saliva secretion and the degree of salivary gland destruction evaluated by sialography and histopathological findings in the labial minor salivary glands. These diagnostic approaches could provide useful prognostic information on the efficacy of cevimeline in SS patients.

Job satisfaction among dually qualified dental hygienist-therapists in UK primary care: a structural model.

PubMed

Turner, S; Ross, M K; Ibbetson, R J

2011-02-26

To investigate job satisfaction among hygienist-therapists. Increasing numbers of hygienist-therapists work in UK primary dental care teams. Earlier studies suggest a clinical remit/clinical activity mismatch, without investigating any link with job satisfaction. A UK-wide survey of dental hygienist-therapists using a random sample of the General Dental Council Register of Dental Care Professionals. Factors associated with job satisfaction (measured by the Warr-Cook-Wall ten-dimension scale) were entered into a series of multiple regression analyses to build up a path model. Analysis was undertaken on 183 respondents (response rate: 60%). Mean score for overall satisfaction was 5.36 (SD 1.28) out of a range of 1-7. Multiple regression analysis confirmed the following direct predictors of overall job satisfaction: satisfaction with colleagues, remuneration, variety of work; rating of hygiene work as rewarding; and not being self-employed (R(2) = 0.69). Satisfaction with variety of work was the strongest predictor, itself strongly predicted by the extent the clinical remit was undertaken. Dentists' recognition of their remit, quality of clinical work and qualifications had a strong indirect effect on overall job satisfaction. The study suggests both greater use of the therapy skills these individuals possess, and better recognition of their remit, qualifications and quality of work by their dentist colleague, may be linked to higher job satisfaction. The implications for the policy of greater team working in dental primary care are discussed.

Stoichiometry of hydrological C, N, and P losses across climate and geology: An environmental matrix approach across New Zealand primary forests

NASA Astrophysics Data System (ADS)

McGroddy, M. E.; Baisden, W. T.; Hedin, L. O.

2008-03-01

Hydrologic losses can play a key role in regulating ecosystem nutrient balances, particularly in regions where baseline nutrient cycles are not augmented by industrial deposition. We used first-order streams to integrate hydrologic losses at the watershed scale across unpolluted old-growth forests in New Zealand. We employed a matrix approach to resolve how stream water concentrations of dissolved organic carbon (DOC), organic and inorganic nitrogen (DON and DIN), and organic and inorganic phosphorus (DOP and DIP) varied as a function of landscape differences in climate and geology. We found stream water total dissolved nitrogen (TDN) to be dominated by organic forms (medians for DON, 81.3%, nitrate-N, 12.6%, and ammonium-N, 3.9%). The median stream water DOC:TDN:TDP molar ratio of 1050:21:1 favored C slightly over N and P when compared to typical temperate forest foliage ratios. Using the full set of variables in a multiple regression approach explained approximately half of the variability in DON, DOC, and TDP concentrations. Building on this approach we combined a simplified set of variables with a simple water balance model in a regression designed to predict DON export at larger spatial scales. Incorporating the effects of climate and geologic variables on nutrient exports will greatly aid the development of integrated Earth-climate biogeochemical models which are able to take into account multiple element dynamics and complex natural landscapes.

Resting-state functional connectivity in multiple sclerosis: an examination of group differences and individual differences.

PubMed

Janssen, Alisha L; Boster, Aaron; Patterson, Beth A; Abduljalil, Amir; Prakash, Ruchika Shaurya

2013-11-01

Multiple sclerosis (MS) is a neurodegenerative, inflammatory disease of the central nervous system, resulting in physical and cognitive disturbances. The goal of the current study was to examine the association between network integrity and composite measures of cognition and disease severity in individuals with relapsing-remitting MS (RRMS), relative to healthy controls. All participants underwent a neuropsychological and neuroimaging session, where resting-state data was collected. Independent component analysis and dual regression were employed to examine network integrity in individuals with MS, relative to healthy controls. The MS sample exhibited less connectivity in the motor and visual networks, relative to healthy controls, after controlling for group differences in gray matter volume. However, no alterations were observed in the frontoparietal, executive control, or default-mode networks, despite previous evidence of altered neuronal patterns during tasks of exogenous processing. Whole-brain, voxel-wise regression analyses with disease severity and processing speed composites were also performed to elucidate the brain-behavior relationship with neuronal network integrity. Individuals with higher levels of disease severity demonstrated reduced intra-network connectivity of the motor network, and the executive control network, while higher disease burden was associated with greater inter-network connectivity between the medial visual network and areas involved in visuomotor learning. Our findings underscore the importance of examining resting-state oscillations in this population, both as a biomarker of disease progression and a potential target for therapeutic intervention. Copyright © 2013 Elsevier Ltd. All rights reserved.

Maternal risk factors predicting child physical characteristics and dysmorphology in fetal alcohol syndrome and partial fetal alcohol syndrome.

PubMed

May, Philip A; Tabachnick, Barbara G; Gossage, J Phillip; Kalberg, Wendy O; Marais, Anna-Susan; Robinson, Luther K; Manning, Melanie; Buckley, David; Hoyme, H Eugene

2011-12-01

Previous research in South Africa revealed very high rates of fetal alcohol syndrome (FAS), of 46-89 per 1000 among young children. Maternal and child data from studies in this community summarize the multiple predictors of FAS and partial fetal alcohol syndrome (PFAS). Sequential regression was employed to examine influences on child physical characteristics and dysmorphology from four categories of maternal traits: physical, demographic, childbearing, and drinking. Then, a structural equation model (SEM) was constructed to predict influences on child physical characteristics. Individual sequential regressions revealed that maternal drinking measures were the most powerful predictors of a child's physical anomalies (R² = .30, p < .001), followed by maternal demographics (R² = .24, p < .001), maternal physical characteristics (R²=.15, p < .001), and childbearing variables (R² = .06, p < .001). The SEM utilized both individual variables and the four composite categories of maternal traits to predict a set of child physical characteristics, including a total dysmorphology score. As predicted, drinking behavior is a relatively strong predictor of child physical characteristics (β = 0.61, p < .001), even when all other maternal risk variables are included; higher levels of drinking predict child physical anomalies. Overall, the SEM model explains 62% of the variance in child physical anomalies. As expected, drinking variables explain the most variance. But this highly controlled estimation of multiple effects also reveals a significant contribution played by maternal demographics and, to a lesser degree, maternal physical and childbearing variables. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Determinants of Employment Status among People with Multiple Sclerosis.

ERIC Educational Resources Information Center

Roessler, Richard T.; Fitzgerald, Shawn M.; Rumrill, Phillip D.; Koch, Lynn C.

2001-01-01

Identifies factors predicting employment or lack thereof among adults with multiple sclerosis (MS). Results included the following variables as the best predictors of employment: symptom persistence, severity of symptoms, educational attainment, and presence of cognitive limitations. The relevance of the findings for rehabilitation assessment and…

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)

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.

Employee choice of a high-deductible health plan across multiple employers.

PubMed

Lave, Judith R; Men, Aiju; Day, Brian T; Wang, Wei; Zhang, Yuting

2011-02-01

To determine factors associated with selecting a high-deductible health plan (HDHP) rather than a preferred provider plan (PPO) and to examine switching and market segmentation after initial selection. Claims and benefit information for 2005-2007 from nine employers in western Pennsylvania first offering HDHP in 2006. We examined plan growth over time, used logistic regression to determine factors associated with choosing an HDHP, and examined the distribution of healthy and sick members across plan types. We linked employees with their dependents to determine family-level variables. We extracted risk scores, covered charges, employee age, and employee gender from claims data. We determined census-level race, education, and income information. Health status, gender, race, and education influenced the type of individual and family policies chosen. In the second year the HDHP was offered, few employees changed plans. Risk segmentation between HDHPs and PPOs existed, but it did not increase. When given a choice, those who are healthier are more likely to select an HDHP leading to risk segmentation. Risk segmentation did not increase in the second year that HDHPs were offered. © Health Research and Educational Trust.

Assessing digital literacy in web-based physical activity surveillance: the WIN study.

PubMed

Mathew, Merly; Morrow, James R; Frierson, Georita M; Bain, Tyson M

2011-01-01

PURPOSE. Investigate relations between demographic characteristics and submission method, Internet or paper, when physical activity behaviors are reported. DESIGN. Observational. SETTING . Metropolitan. SUBJECTS. Adult women (N  =  918) observed weekly for 2 years (total number of weekly reports, 44,963). MEASURES. Independent variables included age, race, education, income, employment status, and Internet skills. Dependent variables were method of submission (Internet or paper) and adherence. ANALYSIS . Logistic regression to analyze weekly odds of submitting data online and meeting study adherence criteria. Model 1 investigated method of submission, model 2 analyzed meeting study's Internet adherence, and model 3 analyzed meeting total adherence regardless of submission method. RESULTS. Whites, those with good Internet skills, and those reporting higher incomes were more likely to log online. Those who were white, older, and reported good Internet skills were more likely to be at least 75% adherent online. Older women were more likely to be adherent regardless of method. Employed women were less likely to log online or be adherent. CONCLUSION . Providing participants with multiple submission methods may reduce potential bias and provide more generalizable results relevant for future Internet-based research.

Effects of racial and sexual harassment on work and the psychological well-being of African American women.

PubMed

Buchanan, NiCole T; Fitzgerald, Louise F

2008-04-01

Research on workplace harassment has typically examined either racial or sexual harassment, without studying both simultaneously. As a result, it remains unknown whether the co-occurrence of racial and sexual harassment or their interactive effects account for unique variance in work and psychological well-being. In this study, hierarchical linear regression analyses were used to explore the influence of racial and sexual harassment on these outcomes among 91 African American women involved in a sexual harassment employment lawsuit. Results indicated that both sexual and racial harassment contributed significantly to the women's occupational and psychological outcomes. Moreover, their interaction was statistically significant when predicting supervisor satisfaction and perceived organizational tolerance of harassment. Using a sample of African American women employed in an organizational setting where harassment was known to have occurred and examining sexual and racial harassment concomitantly makes this study unique. As such, it provides novel insights and an important contribution to an emerging body of research and underscores the importance of assessing multiple forms of harassment when examining organizational stressors, particularly among women of color.

The relationship between personality, dysfunctional parenting in childhood, and lifetime depression in a sample of employed Japanese adults.

PubMed

Sakado, K; Kuwabara, H; Sato, T; Uehara, T; Sakado, M; Someya, T

2000-10-01

Few studies have explored the relationship between personality, dysfunctional parenting in childhood, and adult depression. Parental rearing styles and personality scores as measured by the Parental Bonding Instrument (PBI) and the Interpersonal Sensitivity Measure (IPSM) were compared in a group of employed Japanese adults with and without a lifetime history of depression. The diagnosis was provided by the Inventory to Diagnose Depression, Lifetime version (IDDL). To estimate the effects of the PBI and the IPSM scores on lifetime depression, a multiple logistic regression analysis was performed. Subjects with lifetime depression were seen to have significantly lower scores on the PBI 'care' and higher scores on the IPSM than the subjects without lifetime depression. Lower levels of maternal care and higher levels of 'interpersonal sensitivity' each independently increased the risk for lifetime depression. The findings of the present study may not be conclusive since the data were retrospectively obtained. Dysfunctional parenting and personality seem to be correlated by lifetime depression, but it is uncertain whether they are independent risk factors

More alike than different: a comparison of male and female RNs in rural and remote Canada.

PubMed

Andrews, Mary E; Stewart, Norma J; Morgan, Debra G; D'Arcy, Carl

2012-05-01

To explore gender differences and similarities on personal, employment and work-life factors and predictors of job satisfaction among registered nurses in rural and remote Canada. Research suggests that men and women are attracted to nursing for different reasons, with job security, range of employment opportunities and wages being important for male nurses. Using data from a large national survey of registered nurses in rural and remote Canada, descriptive and multiple linear regression analyses were used to identify gender differences and similarities. A larger proportion of male nurses reported experiencing aggression in the workplace. Age, annual gross income and colleague support in medicine were not found to be predictors of work satisfaction for the male nurses, although they were for women. There are more similarities than differences between male and female registered nurses in factors that affect job satisfaction. Nursing management needs to increase their awareness of the potential for workplace aggression towards male registered nurses and to explore the perceptions of interpersonal interactions that affect satisfaction in the workplace. © 2011 Blackwell Publishing Ltd.

Similarities and differences regarding changes in attachment preferences and attachment styles in relation to romantic relationship length: longitudinal and concurrent analyses.

PubMed

Umemura, Tomotaka; Lacinová, Lenka; Kotrčová, Kristína; Fraley, R Chris

2018-04-01

This study examines whether attachment preferences and attachment styles with different figures (mother, father, romantic partner, and friends) change over the course of a romantic relationship. Study 1 employed a three-wave longitudinal sample of Czech young adults who were currently in a romantic relationship (N = 870; mean age = 21.57; SD = 1.51; 81% females). Multilevel modeling analyses revealed that, as romantic relationships progressed, attachment preferences for romantic partners increased and preferences for friends decreased. However, preferences for the mother or for the father did not change over time. The parallel pattern was found for attachment avoidance; as romantic relationships progressed, attachment avoidance with romantic partners decreased and avoidance with the best friend increased. Avoidance with mother or with father, however, did not change over time. Study 2 employed a cross-sectional international sample (n = 2,593; mean age = 31.99; SD = 12.13; 79% females). Multiple regression analyses replicated the findings of attachment avoidance in the longitudinal data.

Neuropsychological correlates of sustained attention in schizophrenia.

PubMed

Chen, E Y; Lam, L C; Chen, R Y; Nguyen, D G; Chan, C K; Wilkins, A J

1997-04-11

We employed a simple and relatively undemanding task of monotone counting for the assessment of sustained attention in schizophrenic patients. The monotone counting task has been validated neuropsychologically and is particularly sensitive to right prefrontal lesions. We compared the performance of schizophrenic patients with age- and education-matched controls. We then explored the extent to which a range of commonly employed neuropsychological tasks in schizophrenia research are related to attentional impairment as measured in this way. Monotone counting performance was found to be correlated with digit span (WAIS-R-HK), information (WAIS-R-HK), comprehension (WAIS-R-HK), logical memory (immediate recall) (Weschler Memory Scale, WMS), and visual reproduction (WMS). Multiple regression analysis also identified visual reproduction, digit span and comprehension as significant predictors of attention performance. In contrast, logical memory (delay recall) (WMS), similarity (WAIS-R-HK), semantic fluency, and Wisconsin Card Sorting Test (perseverative errors) were not correlated with attention. In addition, no significant correlation between sustained attention and symptoms was found. These findings are discussed in the context of a weakly modular cognitive system where attentional impairment may contribute selectively to a range of other cognitive deficits.

Post-injury personality in the prediction of outcome following severe acquired brain injury.

PubMed

Cattran, Charlotte Jane; Oddy, Michael; Wood, Rodger Llewellyn; Moir, Jane Frances

2011-01-01

The aim of the study was to examine the utility of five measures of non-cognitive neurobehavioural (NCNB) changes that often occur following acquired brain injury, in predicting outcome (measured in terms of participation and social adaptation) at 1-year follow-up. The study employed a longitudinal, correlational design. Multiple regression was employed to investigate the value of five new NCNB measures of social perception, emotional regulation, motivation, impulsivity and disinhibition in the prediction of outcome as measured by the Mayo-Portland Adaptability Inventory (MPAI). Two NCNB measures (motivation and emotional regulation) were found to significantly predict outcome at 1-year follow-up, accounting for 53% of the variance in MPAI total scores. These measures provide a method of quantifying the extent of NCNB changes following brain injury. The predictive value of the measures indicates that they may represent a useful tool which could aid clinicians in identifying early-on those whose symptoms are likely to persist and who may require ongoing intervention. This could facilitate the planning of rehabilitation programmes.

A Comparison of Methods for Nonparametric Estimation of Item Characteristic Curves for Binary Items

ERIC Educational Resources Information Center

Lee, Young-Sun

2007-01-01

This study compares the performance of three nonparametric item characteristic curve (ICC) estimation procedures: isotonic regression, smoothed isotonic regression, and kernel smoothing. Smoothed isotonic regression, employed along with an appropriate kernel function, provides better estimates and also satisfies the assumption of strict…

Predictors of employment status of treated patients with DSM-III-R diagnosis. Can logistic regression model find a solution?

PubMed

Daradkeh, T K; Karim, L

1994-01-01

To investigate the predictors of employment status of patients with DSM-III-R diagnosis, 55 patients were selected by a simple random technique from the main psychiatric clinic in Al Ain, United Arab Emirates. Structured and formal assessments were carried out to extract the potential predictors of outcome of schizophrenia. Logistic regression model revealed that being married, absence of schizoid personality, free or with minimum symptoms of the illness, later age of onset, and higher educational attainment were the most significant predictors of employment outcome. The implications of the results of this study are discussed in the text.

[Higher salary as an incentive for scientific activity?].

PubMed

Gulsvik, Amund; Aasland, Olaf Gjerløw

2007-08-23

Few publications are available on how salaries are established for physicians with science as their main occupation. The results of a questionnaire survey to medical doctors are reported. A questionnaire was sent to members of The Norwegian Medical Association's branch for doctors in academic medicine in spring 2005. Questions concerned how they thought scientific qualifications and production affected their present salary and what they considered to be a reasonable salary for a researcher with their qualifications and production. 304 of 487 (62%) doctors answered. The study included 128 full-time professors, 101 associate professors or post-doctoral scientists with a PhD, 44 scientists without a PhD and 31 PhD-students. The average age was 52 years, and 28% were women. 71% had a university as their main employer. The median number of peer-reviewed scientific publications was 19 per physician-scientist for the last 5 years. The average annual salary was 498,000 NOK, and the average increase in salary considered to be reasonable was 279,000 NOK. A reasonable salary for evaluating a PhD-thesis was considered to be 18,700 NOK and that for giving a 45-minute lecture was 3,200 NOK. In a multiple linear regression analysis on actual salary, the significant predictors were employer, scientific qualifications, age, and sex. Predictors for the difference between reasonable and actual salary was scientific production and employer. Age, employer or scientific qualifications could not predict who considered a doubling of the present salary (for a 45-minute lecture and evaluating a PhD) to be appropriate. Universities should be aware of the large gap between salaries to physician-scientists employed by universities and to those employed by other institutions. Scientific production should be more emphasized in future negotiations on salaries.

Infant care and wives' depressive symptoms.

PubMed

Lennon, M C; Wasserman, G A; Allen, R

1991-01-01

Although some investigators show that division of child care between spouses is related to the psychological well-being of wives, little attention has been given to the relevance of specific dimensions of child care or to nonemployed as well as employed wives. In this study we differentiate basic child care tasks, i.e., those that are essential for the family's physical well-being from other, more supplemental, or auxiliary tasks. We hypothesize that husbands' failure to perform auxiliary child care will be distressing for wives, regardless of employment status because it contributes to perceptions of marital inequity. On the other hand, husbands' lack of participation in the more time-consuming, basic, tasks will be most distressing for employed wives because it results in an increased overall work load. We also hypothesize that when employed mothers are responsible for arranging child care, and when such care entails financial strains, they are more likely to experience psychological distress. To evaluate these hypotheses we use data drawn from a mail survey of a sample of mothers of infants. Using multiple regression analysis, we find that husbands' involvement in child care and housework, especially in the time-consuming tasks, is relatively low and that the most consistent predictor of husbands' involvement is wives' relative income. In terms of the impact of husbands' involvement on wives' well-being, lower levels of husbands' participation in auxiliary, but not basic, child care are associated with increases in reported symptoms, regardless of wives' employment status. When child care is relatively more costly, employed wives report increased symptoms of depression. We discuss these results in terms of the role played by expectations of husbands and wives about parental responsibility for child care.

Social inequalities in the impact of flexible employment on different domains of psychosocial health.

PubMed

Artazcoz, Lucía; Benach, Joan; Borrell, Carme; Cortès, Imma

2005-09-01

(1) To analyse the impact of flexible employment on mental health and job dissatisfaction; and (2) to examine the constraints imposed by flexible employment on men's and women's partnership formation and people's decision to become parents. For the two objectives the potentially different patterns by sex and social class are explored. Cross sectional health survey. Multiple logistic regression models separated for sex and social class (manual and non-manual workers) and controlling for age were fitted. Four types of contractual arrangements have been considered: permanent, fixed term temporary contract, non-fixed term temporary contract, and no contract. Catalonia (a region in the north east of Spain). Salaried workers interviewed in the 2002 Catalonian health survey with no longstanding limiting illness, aged 16-64 (1474 men and 998 women). Fixed term temporary contracts were not associated with poor mental health status. The impact of other forms of flexible employment on mental health depended on the type of contractual arrangement, sex, and social class and it was restricted to less privileged workers, women, and manual male workers. The impact of flexible employment on living arrangements was higher in men. Among both manual and non-manual male workers, those with fixed term temporary contracts were less likely to have children when married or cohabiting and, additionally, among non-manual male workers they also were more likely to remain single (aOR = 2.35; 95%CI = 1.13 to 4.90). Some forms of temporary contracts are related to adverse health and psychosocial outcomes with different patterns depending on the outcome analysed and on sex and social class. Future research should incorporate variables to capture situations of precariousness associated with flexible employment.

Parents' alcohol use: gender differences in the impact of household and family chores.

PubMed

Kuntsche, Sandra; Knibbe, Ronald A; Gmel, Gerhard

2012-12-01

Social roles influence alcohol use. Nevertheless, little is known about how specific aspects of a given role, here parenthood, may influence alcohol use. The research questions for this study were the following: (i) are family-related indicators (FRI) linked to the alcohol use of mothers and fathers? and (ii) does the level of employment, i.e. full-time, part-time employment or unemployment, moderate the relationship between FRI and parental alcohol use? Survey data of 3217 parents aged 25-50 living in Switzerland. Mean comparisons and multiple regression models of annual frequency of drinking and risky single occasion drinking, quantity per day on FRI (age of the youngest child, number of children in the household, majority of child-care/household duties). Protective relationships between FRI and alcohol use were observed among mothers. In contrast, among fathers, detrimental associations between FRI and alcohol use were observed. Whereas maternal responsibilities in general had a protective effect on alcohol use, the number of children had a detrimental impact on the quantity of alcohol consumed per day when mothers were in paid employment. Among fathers, the correlations between age of the youngest child, number of children and frequency of drinking was moderated by the level of paid employment. The study showed that in Switzerland, a systematic negative relationship was more often found between FRI and women's drinking than men's. Evidence was found that maternal responsibilities per se may protect from alcohol use but can turn into a detrimental triangle if mothers are additionally in paid employment.

Correlated Heterospectral Lipidomics for Biomolecular Profiling of Remyelination in Multiple Sclerosis

PubMed Central

2017-01-01

Analyzing lipid composition and distribution within the brain is important to study white matter pathologies that present focal demyelination lesions, such as multiple sclerosis. Some lesions can endogenously re-form myelin sheaths. Therapies aim to enhance this repair process in order to reduce neurodegeneration and disability progression in patients. In this context, a lipidomic analysis providing both precise molecular classification and well-defined localization is crucial to detect changes in myelin lipid content. Here we develop a correlated heterospectral lipidomic (HSL) approach based on coregistered Raman spectroscopy, desorption electrospray ionization mass spectrometry (DESI-MS), and immunofluorescence imaging. We employ HSL to study the structural and compositional lipid profile of demyelination and remyelination in an induced focal demyelination mouse model and in multiple sclerosis lesions from patients ex vivo. Pixelwise coregistration of Raman spectroscopy and DESI-MS imaging generated a heterospectral map used to interrelate biomolecular structure and composition of myelin. Multivariate regression analysis enabled Raman-based assessment of highly specific lipid subtypes in complex tissue for the first time. This method revealed the temporal dynamics of remyelination and provided the first indication that newly formed myelin has a different lipid composition compared to normal myelin. HSL enables detailed molecular myelin characterization that can substantially improve upon the current understanding of remyelination in multiple sclerosis and provides a strategy to assess remyelination treatments in animal models. PMID:29392175

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.

Wavelet regression model in forecasting crude oil price

NASA Astrophysics Data System (ADS)

Hamid, Mohd Helmie; Shabri, Ani

2017-05-01

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

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

PubMed

Slinker, B K; Glantz, S A

1985-07-01

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

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

ERIC Educational Resources Information Center

Li, Spencer D.

2011-01-01

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

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

ERIC Educational Resources Information Center

Cooper, Paul D.

2010-01-01

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

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

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

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

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

ERIC Educational Resources Information Center

Accordino, Denise B.; Accordino, Michael P.

2011-01-01

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

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

ERIC Educational Resources Information Center

Campbell, S. Duke; Greenberg, Barry

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

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

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

1996-01-01

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

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

ERIC Educational Resources Information Center

Rowell, R. Kevin

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

Determination of total phenolic compounds in compost by infrared spectroscopy.

PubMed

Cascant, M M; Sisouane, M; Tahiri, S; Krati, M El; Cervera, M L; Garrigues, S; de la Guardia, M

2016-06-01

Middle and near infrared (MIR and NIR) were applied to determine the total phenolic compounds (TPC) content in compost samples based on models built by using partial least squares (PLS) regression. The multiplicative scatter correction, standard normal variate and first derivative were employed as spectra pretreatment, and the number of latent variable were optimized by leave-one-out cross-validation. The performance of PLS-ATR-MIR and PLS-DR-NIR models was evaluated according to root mean square error of cross validation and prediction (RMSECV and RMSEP), the coefficient of determination for prediction (Rpred(2)) and residual predictive deviation (RPD) being obtained for this latter values of 5.83 and 8.26 for MIR and NIR, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Can aircraft noise less than or equal 115 to dBA adversely affect reproductive outcome in USAF women?

NASA Astrophysics Data System (ADS)

Brubaker, P. A.

1985-06-01

It has been suggested, mainly through animal studies, that exposure to high noise levels may be associated with lower birth weight, reduced gestational length and other adverse reproductive outcomes. Few studies have been done on humans to show this association. The Air Force employs pregnant women in areas where there is a high potential for exposure to high noise levels. This study proposes a method to determine if there is an association between high frequency noise levels or = 115 dBA and adverse reproductive outcomes through a review of records and self-administered questionnaires in a case-comparison design. Prevelance rates will be calculated and a multiple logistic regression analysis computed for the independent variables that can affect reproduction.

A biocultural perspective on fictive kinship in the Andes: social support and women's immune function in El Alto, Bolivia.

PubMed

Hicks, Kathryn

2014-09-01

This article examines the influence of emotional and instrumental support on women's immune function, a biomarker of stress, in the city of El Alto, Bolivia. It tests the prediction that instrumental support is protective of immune function for women living in this marginal environment. Qualitative and quantitative ethnographic methods were employed to assess perceived emotional and instrumental support and common sources of support; multiple linear regression analysis was used to model the relationship between social support and antibodies to the Epstein-Barr virus. These analyses provided no evidence that instrumental social support is related to women's health, but there is some evidence that emotional support from compadres helps protect immune function. © 2014 by the American Anthropological Association.

Establishing links between health and productivity in the New Zealand workforce.

PubMed

Williden, Micalla; Schofield, Grant; Duncan, Scott

2012-05-01

To provide the first investigation of individual health behaviors and measures of work performance in New Zealand. Health risk assessments were completed by 747 adults aged 18 to 65 years. Associations between measures of productivity and health risk factors were assessed using multiple stepwise regression. Participants with low to moderate psychological distress levels and who were physically active reported a work performance 6.5% (P < 0.001) and 3.5% (P < 0.001) higher, respectively. Furthermore, high psychological distress and smoking accounted for 16.8 (P < 0.001) and 11.6 (P = 0.038) additional absentee hours over the previous 4 weeks. The impact that psychological distress, physical inactivity, and smoking have on productivity suggests that employers may benefit from contributing to health promotion within the workplace.

Improving employee productivity through improved health.

PubMed

Mitchell, Rebecca J; Ozminkowski, Ronald J; Serxner, Seth

2013-10-01

The objective of this study was to estimate productivity-related savings associated with employee participation in health promotion programs. Propensity score weighting and multiple regression techniques were used to estimate savings. These techniques were adjusted for demographic and health status differences between participants who engaged in one or more telephonic health management programs and nonparticipants who were eligible for but did not engage in these programs. Employees who participated in a program and successfully improved their health care or lifestyle showed significant improvements in lost work time. These employees saved an average of $353 per person per year. This reflects about 10.3 hours in additional productive time annually, compared with similar, but nonparticipating employees. Participating in health promotion programs can help improve productivity levels among employees and save money for their employers.

Influence of hydroxypropyl methylcellulose on drug release pattern of a gastroretentive floating drug delivery system using a 3(2) full factorial design.

PubMed

Swain, Kalpana; Pattnaik, Satyanarayan; Mallick, Subrata; Chowdary, Korla Appana

2009-01-01

In the present investigation, controlled release gastroretentive floating drug delivery system of theophylline was developed employing response surface methodology. A 3(2) randomized full factorial design was developed to study the effect of formulation variables like various viscosity grades and contents of hydroxypropyl methylcellulose (HPMC) and their interactions on response variables. The floating lag time for all nine experimental trial batches were less than 2 min and floatation time of more than 12 h. Theophylline release from the polymeric matrix system followed non-Fickian anomalous transport. Multiple regression analysis revealed that both viscosity and content of HPMC had statistically significant influence on all dependent variables but the effect of these variables found to be nonlinear above certain threshold values.

Supporting the patient's role in guideline compliance: a controlled study.

PubMed

Rosenberg, Stephen N; Shnaiden, Tatiana L; Wegh, Arnold A; Juster, Iver A

2008-11-01

Clinical messages alerting physicians to gaps in the care of specific patients have been shown to increase compliance with evidence-based guidelines. This study sought to measure any additional impact on compliance when alerting messages also were sent to patients. For alerts that were generated by computerized clinical rules applied to claims, compliance was determined by subsequent claims evidence (eg, that recommended tests were performed). Compliance was measured in the baseline year and the study year for 4 study group employers (combined membership >100,000) that chose to add patient messaging in the study year, and 28 similar control group employers (combined membership >700,000) that maintained physician messaging but did not add patient messaging. The impact of patient messaging was assessed by comparing changes in compliance from baseline to study year in the 2 groups. Multiple logistic regression was used to control for differences between the groups. Because a given member or physician could receive multiple alerts, generalized estimating equations with clustering by patient and physician were used. Controlling for differences in age, sex, and the severity and types of clinical alerts between the study and control groups, the addition of patient messaging increased compliance by 12.5% (P <.001). This increase was primarily because of improved responses to alerts regarding the need for screening, diagnostic, and monitoring tests. Supplementing clinical alerts to physicians with messages directly to their patients produced a statistically significant increase in compliance with the evidence-based guidelines underlying the alerts.

Multiple Sclerosis and Employment: A Research Review Based on the International Classification of Function

ERIC Educational Resources Information Center

Frain, Michael P.; Bishop, Malachy; Rumrill, Phillip D., Jr.; Chan, Fong; Tansey, Timothy N.; Strauser, David; Chiu, Chung-Yi

2015-01-01

Multiple sclerosis (MS) is an unpredictable, sometimes progressive chronic illness affecting people in the prime of their working lives. This article reviews the effects of MS on employment based on the World Health Organization's International Classification of Functioning, Disability and Health model. Correlations between employment and…

Predictors of health behaviors after the economic downturn: a longitudinal study.

PubMed

Macy, Jonathan T; Chassin, Laurie; Presson, Clark C

2013-07-01

Economic declines and their associated stress, shortage of financial resources, and changes in available time can impair health behaviors. This study tested the association between change in working hours, change in employment status, and financial strain and health behaviors measured after the 2008 recession after controlling for pre-recession levels of the health behaviors. The moderating influences of demographic factors and pre-recession levels of the health behaviors on the association between change in working hours and employment status and financial strain and the health behaviors were also tested. Participants (N = 3984) were from a longitudinal study of a U.S. Midwestern community-based sample. Regression analyses tested the unique relations between change in hours worked per week, change in employment status, and financial strain and five health behaviors over and above demographic factors and pre-recession levels of the same behavior. Models included predictor by covariate interactions. Participants who reported higher levels of financial strain engaged in lower levels of all but one of the five health behaviors, but there were no significant main effects of a change in the number of hours worked per week or change in employment status. Significant interactions revealed moderation of these relations by demographic characteristics, but findings differed across health behaviors. Financial strain negatively affected engagement in multiple healthy behaviors. Promoting the maintenance of healthy behaviors for disease prevention is an important public health goal during times of economic decline. Copyright © 2013 Elsevier Ltd. All rights reserved.

Organizational justice and psychological distress among permanent and non-permanent employees in Japan: a prospective cohort study.

PubMed

Inoue, Akiomi; Kawakami, Norito; Tsuno, Kanami; Tomioka, Kimiko; Nakanishi, Mayuko

2013-06-01

Organizational justice has recently been introduced as a new concept as psychosocial determinants of employee health, and an increase in precarious employment is a challenging issue in occupational health. However, no study investigated the association of organizational justice with mental health among employees while taking into account employment contract. The purpose of the present study was to investigate the prospective association of organizational justice (procedural justice and interactional justice) with psychological distress by employment contract among Japanese employees. A total of 373 males and 644 females from five branches of a manufacturing company in Japan were surveyed. At baseline (August 2009), self-administered questionnaires, including the Organizational Justice Questionnaire (OJQ), the K6 scale (psychological distress scale), the Eysenck Personality Questionnaire-Revised (EPQ-R), and other covariates, were used. After one-year follow-up (August 2010), the K6 scale was used again to assess psychological distress. Multiple logistic regression analyses were conducted by sex and employment contract. After adjusting for demographic characteristics, psychological distress, and neuroticism at baseline, low procedural justice was significantly associated with a higher risk of psychological distress at follow-up among non-permanent female employees, while no significant association of procedural justice or interactional justice with psychological distress at follow-up was observed among permanent male or female employees. The results of non-permanent male employees could not be calculated because of small sample size. Low procedural justice may be an important predictor of psychological distress among non-permanent female employees.

Determinants of community pharmacists' quality of care: a population-based cohort study using pharmacy administrative claims data.

PubMed

Winslade, Nancy; Tamblyn, Robyn

2017-09-21

To determine if a prototype pharmacists' services evaluation programme that uses linked community pharmacy claims and health administrative data to measure pharmacists' performance can be used to identify characteristics of pharmacies providing higher quality of care. Population-based cohort study using community pharmacy claims from 1 November 2009 to 30 June 2010. All community pharmacies in Quebec, Canada. 1742 pharmacies dispensing 8 655 348 antihypertensive prescriptions to 760 700 patients. Patient adherence to antihypertensive medications. Pharmacy level: dispensing workload, volume of pharmacist-provided professional services (eg, refusals to dispense, pharmacotherapy recommendations), pharmacy location, banner/chain, pharmacist overlap and within-pharmacy continuity of care. Patient level: sex, age, income, patient prescription cost, new/chronic therapy, single/multiple antihypertensive medications, single/multiple prescribers and single/multiple dispensing pharmacies. Dispensing level: prescription duration, time of day dispensed and antihypertensive class. Multivariate alternating logistic regression estimated predictors of the primary outcome, accounting for patient and pharmacy clustering. 9.2% of dispensings of antihypertensive medications were provided to non-adherent patients. Male sex, decreasing age, new treatment, multiple prescribers and multiple dispensing pharmacies were risk factors for increased non-adherence. Pharmacies that provided more professional services were less likely to dispense to non-adherent hypertensive patients (OR: 0.60; 95% CI: 0.57 to 0.62) as were those with better scores on the Within-Pharmacy Continuity of Care Index. Neither increased pharmacists' services for improving antihypertensive adherence per se nor increased pharmacist overlap impacted the odds of non-adherence. However, pharmacist overlap was strongly correlated with dispensing workload. There was significant unexplained variability among pharmacies belonging to different banners and chains. Pharmacy administrative claims data can be used to calculate pharmacy-level characteristics associated with improved quality of care. This study supports the importance of pharmacist's professional services and continuity of pharmacist's care. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Production of Selected Key Ductile Iron Castings Used in Large-Scale Windmills

NASA Astrophysics Data System (ADS)

Pan, Yung-Ning; Lin, Hsuan-Te; Lin, Chi-Chia; Chang, Re-Mo

Both the optimal alloy design and microstructures that conform to the mechanical properties requirements of selected key components used in large-scale windmills have been established in this study. The target specifications in this study are EN-GJS-350-22U-LT, EN-GJS-350-22U-LT and EN-GJS-700-2U. In order to meet the impact requirement of spec. EN-GJS-350-22U-LT, the Si content should be kept below 1.97%, and also the maximum pearlite content shouldn't exceed 7.8%. On the other hand, Si content below 2.15% and pearlite content below 12.5% were registered for specification EN-GJS-400-18U-LT. On the other hand, the optimal alloy designs that can comply with specification EN-GJS-700-2U include 0.25%Mn+0.6%Cu+0.05%Sn, 0.25%Mn+0.8%Cu+0.01%Sn and 0.45%Mn+0.6%Cu+0.01%Sn. Furthermore, based upon the experimental results, multiple regression analyses have been performed to correlate the mechanical properties with chemical compositions and microstructures. The derived regression equations can be used to attain the optimal alloy design for castings with target specifications. Furthermore, by employing these regression equations, the mechanical properties can be predicted based upon the chemical compositions and microstructures of cast irons.

Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China

PubMed Central

Xia, Yao; Zhang, Yingtao; Huang, Xiaodong; Huang, Jiawei; Nie, Enqiong; Jing, Qinlong; Wang, Guoling; Yang, Zhicong; Hu, Wenbiao

2018-01-01

Background This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China. Methods Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was used to identify the socio-environmental factors associated with DF infection. A Poisson regression model was employed to examine the spatiotemporal patterns in the spread of DF. Results Spatial clusters of DF were primarily concentrated at the southwest part of Guangzhou city. Age group (65+ years) (Odd Ratio (OR) = 1.49, 95% Confidence Interval (CI) = 1.13 to 2.03), floating population (OR = 1.09, 95% CI = 1.05 to 1.15), low-education (OR = 1.08, 95% CI = 1.01 to 1.16) and non-agriculture (OR = 1.07, 95% CI = 1.03 to 1.11) were associated with DF transmission. Poisson regression results indicated that changes in DF incidence rates were significantly associated with longitude (β = -5.08, P<0.01) and latitude (β = -1.99, P<0.01). Conclusions The study demonstrated that social-environmental factors may play an important role in DF transmission in Guangzhou. As geographic range of notified DF has significantly expanded over recent years, an early warning systems based on spatiotemporal model with socio-environmental is urgently needed to improve the effectiveness and efficiency of dengue control and prevention. PMID:29561835

Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China.

PubMed

Liu, Kangkang; Zhu, Yanshan; Xia, Yao; Zhang, Yingtao; Huang, Xiaodong; Huang, Jiawei; Nie, Enqiong; Jing, Qinlong; Wang, Guoling; Yang, Zhicong; Hu, Wenbiao; Lu, Jiahai

2018-03-01

This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China. Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was used to identify the socio-environmental factors associated with DF infection. A Poisson regression model was employed to examine the spatiotemporal patterns in the spread of DF. Spatial clusters of DF were primarily concentrated at the southwest part of Guangzhou city. Age group (65+ years) (Odd Ratio (OR) = 1.49, 95% Confidence Interval (CI) = 1.13 to 2.03), floating population (OR = 1.09, 95% CI = 1.05 to 1.15), low-education (OR = 1.08, 95% CI = 1.01 to 1.16) and non-agriculture (OR = 1.07, 95% CI = 1.03 to 1.11) were associated with DF transmission. Poisson regression results indicated that changes in DF incidence rates were significantly associated with longitude (β = -5.08, P<0.01) and latitude (β = -1.99, P<0.01). The study demonstrated that social-environmental factors may play an important role in DF transmission in Guangzhou. As geographic range of notified DF has significantly expanded over recent years, an early warning systems based on spatiotemporal model with socio-environmental is urgently needed to improve the effectiveness and efficiency of dengue control and prevention.

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

PubMed

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

2017-03-01

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

Introduction to methodology of dose-response meta-analysis for binary outcome: With application on software.

PubMed

Zhang, Chao; Jia, Pengli; Yu, Liu; Xu, Chang

2018-05-01

Dose-response meta-analysis (DRMA) is widely applied to investigate the dose-specific relationship between independent and dependent variables. Such methods have been in use for over 30 years and are increasingly employed in healthcare and clinical decision-making. In this article, we give an overview of the methodology used in DRMA. We summarize the commonly used regression model and the pooled method in DRMA. We also use an example to illustrate how to employ a DRMA by these methods. Five regression models, linear regression, piecewise regression, natural polynomial regression, fractional polynomial regression, and restricted cubic spline regression, were illustrated in this article to fit the dose-response relationship. And two types of pooling approaches, that is, one-stage approach and two-stage approach are illustrated to pool the dose-response relationship across studies. The example showed similar results among these models. Several dose-response meta-analysis methods can be used for investigating the relationship between exposure level and the risk of an outcome. However the methodology of DRMA still needs to be improved. © 2018 Chinese Cochrane Center, West China Hospital of Sichuan University and John Wiley & Sons Australia, Ltd.

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.

Outcome Expectancy and Sexual Compulsivity among Men who have Sex with Men Living with HIV

PubMed Central

Brown, Monique J.; Serovich, Julianne M.; Kimberly, Judy A.

2016-01-01

Sexual compulsivity is operationalized by engaging in repetitive sexual acts, having multiple sexual partners and/or the excessive use of pornography. Outcome expectancy refers to the beliefs about the consequences of engaging in a given behavior. Research examining the relationship between outcome expectancy and sexual compulsivity is limited. The aim of this study was to assess the association between outcome expectancy and sexual compulsivity among men who have sex with men (MSM) living with HIV. Data were obtained from 338 MSM. Simple and multiple linear regression models were used to assess the association between outcome expectancy and sexual compulsivity. After adjusting for age, race/ethnicity, income, education, and employment status, for every one point increase in outcome expectancies for condom use, HIV disclosure and negotiation of safer sex practices, there was, on average, an approximate one point decrease in sexual compulsivity score. Prevention and intervention programs geared towards reducing sexual compulsivity among MSM should focus on increasing outcome expectancies for condom use, HIV disclosure and negotiation of safer sex practices. PMID:26979416

Robust support vector regression networks for function approximation with outliers.

PubMed

Chuang, Chen-Chia; Su, Shun-Feng; Jeng, Jin-Tsong; Hsiao, Chih-Ching

2002-01-01

Support vector regression (SVR) employs the support vector machine (SVM) to tackle problems of function approximation and regression estimation. SVR has been shown to have good robust properties against noise. When the parameters used in SVR are improperly selected, overfitting phenomena may still occur. However, the selection of various parameters is not straightforward. Besides, in SVR, outliers may also possibly be taken as support vectors. Such an inclusion of outliers in support vectors may lead to seriously overfitting phenomena. In this paper, a novel regression approach, termed as the robust support vector regression (RSVR) network, is proposed to enhance the robust capability of SVR. In the approach, traditional robust learning approaches are employed to improve the learning performance for any selected parameters. From the simulation results, our RSVR can always improve the performance of the learned systems for all cases. Besides, it can be found that even the training lasted for a long period, the testing errors would not go up. In other words, the overfitting phenomenon is indeed suppressed.

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

Structured association analysis leads to insight into Saccharomyces cerevisiae gene regulation by finding multiple contributing eQTL hotspots associated with functional gene modules.

PubMed

Curtis, Ross E; Kim, Seyoung; Woolford, John L; Xu, Wenjie; Xing, Eric P

2013-03-21

Association analysis using genome-wide expression quantitative trait locus (eQTL) data investigates the effect that genetic variation has on cellular pathways and leads to the discovery of candidate regulators. Traditional analysis of eQTL data via pairwise statistical significance tests or linear regression does not leverage the availability of the structural information of the transcriptome, such as presence of gene networks that reveal correlation and potentially regulatory relationships among the study genes. We employ a new eQTL mapping algorithm, GFlasso, which we have previously developed for sparse structured regression, to reanalyze a genome-wide yeast dataset. GFlasso fully takes into account the dependencies among expression traits to suppress false positives and to enhance the signal/noise ratio. Thus, GFlasso leverages the gene-interaction network to discover the pleiotropic effects of genetic loci that perturb the expression level of multiple (rather than individual) genes, which enables us to gain more power in detecting previously neglected signals that are marginally weak but pleiotropically significant. While eQTL hotspots in yeast have been reported previously as genomic regions controlling multiple genes, our analysis reveals additional novel eQTL hotspots and, more interestingly, uncovers groups of multiple contributing eQTL hotspots that affect the expression level of functional gene modules. To our knowledge, our study is the first to report this type of gene regulation stemming from multiple eQTL hotspots. Additionally, we report the results from in-depth bioinformatics analysis for three groups of these eQTL hotspots: ribosome biogenesis, telomere silencing, and retrotransposon biology. We suggest candidate regulators for the functional gene modules that map to each group of hotspots. Not only do we find that many of these candidate regulators contain mutations in the promoter and coding regions of the genes, in the case of the Ribi group, we provide experimental evidence suggesting that the identified candidates do regulate the target genes predicted by GFlasso. Thus, this structured association analysis of a yeast eQTL dataset via GFlasso, coupled with extensive bioinformatics analysis, discovers a novel regulation pattern between multiple eQTL hotspots and functional gene modules. Furthermore, this analysis demonstrates the potential of GFlasso as a powerful computational tool for eQTL studies that exploit the rich structural information among expression traits due to correlation, regulation, or other forms of biological dependencies.

Sexual risk behavior and type of sexual partners in transnational indigenous migrant workers.

PubMed

Caballero-Hoyos, Ramiro; Villaseñor-Sierra, Alberto; Millán-Guerrero, Rebeca; Trujillo-Hernández, Benjamín; Monárrez-Espino, Joel

2013-06-01

Indigenous migrant workers (IMWs) have a high vulnerability to HIV and STDs due to poverty and marginalization. This study examined factors associated with sexual risk behavior (SRB) according to type of partner in transnational young male IMWs at a sugar cane agro-industrial complex in western Mexico. A total of 192 sexually active IMWs were recruited from four laborer shelters to participate in a sexual partner survey. The IMWs were interviewed about their sexual partners and practices over the last 12 months during which it emerged that they had had a total of 360 sexual partners. Multiple linear regression analyses were performed to identify factors related to SRB in 222 main (spouse, mistress and girlfriend) and 138 casual partners (colleague, friend, casual encounter and sex worker). Results showed a significantly higher SRB score with casual partners. For the main partner regression model, prior exposure to HIV- and STD-preventive information and sexual intercourse with higher employment status partners (formal workers vs. self-employed in informal activities and unemployed) were associated with lower SRB scores, but if the sexual relations occurred in Mexico (vs. the U.S.), the SRB scores increased. For the casual partner model, the practice of survival sex (sex in exchange for basic needs), sexual relations in Mexico (vs. the U.S.), and being a circular migrant (person traveling for temporary work to return home when the contract is over) were related to higher SRB scores. Findings support the implementation of preventive interventions using different messages depending on the type of partners, main or casual, within the labor migrant context.

Do nurses wish to continue working for the UK National Health Service? A comparative study of three generations of nurses.

PubMed

Robson, Andrew; Robson, Fiona

2015-01-01

To identify the combination of variables that explain nurses' continuation intention in the UK National Health Service. This alternative arena has permitted the replication of a private sector Australian study. This study provides understanding about the issues that affect nurse retention in a sector where employee attrition is a key challenge, further exacerbated by an ageing workforce. A quantitative study based on a self-completion survey questionnaire completed in 2010. Nurses employed in two UK National Health Service Foundation Trusts were surveyed and assessed using seven work-related constructs and various demographics including age generation. Through correlation, multiple regression and stepwise regression analysis, the potential combined effect of various explanatory variables on continuation intention was assessed, across the entire nursing cohort and in three age-generation groups. Three variables act in combination to explain continuation intention: work-family conflict, work attachment and importance of work to the individual. This combination of significant explanatory variables was consistent across the three generations of nursing employee. Work attachment was identified as the strongest marginal predictor of continuation intention. Work orientation has a greater impact on continuation intention compared with employer-directed interventions such as leader-member exchange, teamwork and autonomy. UK nurses are homogeneous across the three age-generations regarding explanation of continuation intention, with the significant explanatory measures being recognizably narrower in their focus and more greatly concentrated on the individual. This suggests that differentiated approaches to retention should perhaps not be pursued in this sectoral context. © 2014 John Wiley & Sons Ltd.

Predictors of Employment Outcomes for State-Federal Vocational Rehabilitation Consumers with HIV/AIDS

ERIC Educational Resources Information Center

Jung, Youngoh; Schaller, James; Bellini, James

2010-01-01

In this study, the authors investigated the effects of demographic, medical, and vocational rehabilitation service variables on employment outcomes of persons living with HIV/AIDS. Binary logistic regression analyses were conducted to determine predictors of employment outcomes using two groups drawn from Rehabilitation Services Administration…

Employment Hardship among Mexican-Origin Women

ERIC Educational Resources Information Center

De Anda, Roberto M.

2005-01-01

This study compares the prevalence and causes of employment hardship between Mexican-origin and White women. Data come from the March 1992, 1996, and 2000 Current Population Surveys. Using logistic regression, the author assesses whether there is a difference between Mexican-origin and White women in employment hardship, controlling for personal…

Cognitive function and competitive employment in schizophrenia: relative contribution of insight and psychopathology.

PubMed

Giugiario, Michela; Crivelli, Barbara; Mingrone, Cinzia; Montemagni, Cristiana; Scalese, Mara; Sigaudo, Monica; Rocca, Giuseppe; Rocca, Paola

2012-04-01

This study investigated the relationships among insight, psychopathology, cognitive function, and competitive employment in order to determine whether insight and/or psychopathology carried the influence of cognitive function to competitive employment. We recruited 253 outpatients with stable schizophrenia and we further divided our sample into two groups of patients (unemployed and competitive employment subjects). Clinical and neuropsychological assessments were performed. All clinical variables significantly different between the two groups of subjects were subsequently analyzed using a binary logistic regression to assess their independent contribution to competitive employment in the two patients' groups. On the basis of the regression results two mediation analyses were performed. Verbal memory, general psychopathology, and awareness of mental illness were significantly associated with competitive employment in our sample. Both awareness of mental illness and general psychopathology had a role in mediating the verbal memory-competitive employment relationship. Taken together, these findings confirmed the importance of cognitive function in obtaining competitive employment. Our results also highlighted the independent role of general psychopathology and awareness of illness on occupational functioning in schizophrenia. Thus, a greater attention must be given to the systematic investigation of insight and general psychopathology in light of an amelioration of vocational functioning in stable schizophrenia.

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.

Improving virtual screening predictive accuracy of Human kallikrein 5 inhibitors using machine learning models.

PubMed

Fang, Xingang; Bagui, Sikha; Bagui, Subhash

2017-08-01

The readily available high throughput screening (HTS) data from the PubChem database provides an opportunity for mining of small molecules in a variety of biological systems using machine learning techniques. From the thousands of available molecular descriptors developed to encode useful chemical information representing the characteristics of molecules, descriptor selection is an essential step in building an optimal quantitative structural-activity relationship (QSAR) model. For the development of a systematic descriptor selection strategy, we need the understanding of the relationship between: (i) the descriptor selection; (ii) the choice of the machine learning model; and (iii) the characteristics of the target bio-molecule. In this work, we employed the Signature descriptor to generate a dataset on the Human kallikrein 5 (hK 5) inhibition confirmatory assay data and compared multiple classification models including logistic regression, support vector machine, random forest and k-nearest neighbor. Under optimal conditions, the logistic regression model provided extremely high overall accuracy (98%) and precision (90%), with good sensitivity (65%) in the cross validation test. In testing the primary HTS screening data with more than 200K molecular structures, the logistic regression model exhibited the capability of eliminating more than 99.9% of the inactive structures. As part of our exploration of the descriptor-model-target relationship, the excellent predictive performance of the combination of the Signature descriptor and the logistic regression model on the assay data of the Human kallikrein 5 (hK 5) target suggested a feasible descriptor/model selection strategy on similar targets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multiple Testing in the Context of Gene Discovery in Sickle Cell Disease Using Genome-Wide Association Studies.

PubMed

Kuo, Kevin H M

2017-01-01

The issue of multiple testing, also termed multiplicity, is ubiquitous in studies where multiple hypotheses are tested simultaneously. Genome-wide association study (GWAS), a type of genetic association study that has gained popularity in the past decade, is most susceptible to the issue of multiple testing. Different methodologies have been employed to address the issue of multiple testing in GWAS. The purpose of the review is to examine the methodologies employed in dealing with multiple testing in the context of gene discovery using GWAS in sickle cell disease complications.

Fatigue and depression predict physician visits and work disability in women with primary Sjögren's syndrome: results from a cohort study.

PubMed

Westhoff, Gisela; Dörner, Thomas; Zink, Angela

2012-02-01

Patients with primary SS (pSS) are frequently suffering from multiple enduring disorders that raise the risk of work disability and require treatment by various health-care specialists. We aimed at determining predictors of physician visits and work disability in pSS patients. Physician visits within the past 6 months, employment status and sick leave were compared among 176 female pSS patients and 115 age-matched controls. Dryness, pain, fatigue and depression were assessed by rating scales of the EULAR Sjögren's Syndrome Patient Reported Index (ESSPRI), the Profile of Fatigue and Discomfort (PROFAD) and Patient Health Questionnaire depression measurements (PHQ-9). Factors associated with an increased number of physician visits and inability to work were determined by multivariate logistic regression analysis. Patients and controls were comparable in age and education, but differed significantly in the prevalence of depression (38.1 vs 7.9%, P < 0.001), the number of physician visits [17.0 (10.0) vs 6.5 (4.5); P < 0.001] and gainful employment (≤64 years: 52.8 vs 77.1% P < 0.001). Multivariate regression analyses revealed that depression (PHQ-9) and/or fatigue, particularly lack of stamina, but not dryness, were significantly associated with physician visits and working status in pSS patients. Patients with high ratings for the statement 'I have had difficulties to keep going, was easily worn out or lacking in energy' had a highly increased risk of not being gainfully employed (adjusted OR 4.1; 95% CI 1.5, 11.2; P < 0.001). In pSS, lack of stamina and/or depression cause a higher level of individual and societal burden than dry eyes and mouth. Fatigue and depression deserve more recognition as treatment targets in pSS.

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,…

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

ERIC Educational Resources Information Center

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

2006-01-01

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

Regression Models for the Analysis of Longitudinal Gaussian Data from Multiple Sources

PubMed Central

O’Brien, Liam M.; Fitzmaurice, Garrett M.

2006-01-01

We present a regression model for the joint analysis of longitudinal multiple source Gaussian data. Longitudinal multiple source data arise when repeated measurements are taken from two or more sources, and each source provides a measure of the same underlying variable and on the same scale. This type of data generally produces a relatively large number of observations per subject; thus estimation of an unstructured covariance matrix often may not be possible. We consider two methods by which parsimonious models for the covariance can be obtained for longitudinal multiple source data. The methods are illustrated with an example of multiple informant data arising from a longitudinal interventional trial in psychiatry. PMID:15726666

Professional charges not reimbursed to dentists in the U.S.: evidence from Medical Expenditure Panel Survey, 1996.

PubMed

Chattopadhyay, A; Slade, G D; Caplan, D J

2009-12-01

This cross-sectional study examined professional charges not paid to dentists. This analysis used logistic regression in SUDAAN examining the 1996 MEPS data from 12,931 adults. Among people incurring dental care charges, 13.6% had more than $50 of unpaid charge (UC). The percapita UC was $53.30. Total UC was higher for highest income group [45.4% of total] compared to lowest income group [26.0%]. The percapita UC of $76.70 for low income group was significantly greater than for high income group ($47.80, P < 0.01). More Medicaid recipients (52% vs. non-recipients: 12%) incurred at least $50 in UC (P < 0.01). Adjusted odds of incurring UC were greater for those employed (OR = 1.3, 95% CI: 1.0-1.7), and for those with private insurance (OR: 1.5, CI: 1.3-1.9). Number of dental procedure types modified the association between Medicaid recipient and UC (OR = 13.6 for Medicaid recipients undergoing multiple procedure types; OR: 2.3 for Medicaid non-recipients with multiple procedure types; OR: 1.9 for Medicaid recipients receiving single dental procedure. Having private insurance, being unemployed and being Medicaid insured undergoing multiple procedure were strongest predictors of UC.

Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis.

PubMed

Cho, Seoae; Kim, Haseong; Oh, Sohee; Kim, Kyunga; Park, Taesung

2009-12-15

The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.

Multiple dimensions of spirituality in recovery: a lagged mediational analysis of Alcoholics Anonymous' principal theoretical mechanism of behavior change.

PubMed

Krentzman, Amy R; Cranford, James A; Robinson, Elizabeth A R

2013-01-01

Alcoholics Anonymous (AA) states that recovery is possible through spiritual experiences and spiritual awakenings. Research examining spirituality as a mediator of AA's effect on drinking has been mixed. It is unknown whether such findings are due to variations in the operationalization of key constructs, such as AA and spirituality. To answer these questions, the authors used a longitudinal model to test 2 dimensions of AA as focal predictors and 6 dimensions of spirituality as possible mediators of AA's association with drinking. Data from the first 18 months of a 3-year longitudinal study of 364 alcohol-dependent individuals were analyzed. Structural equation modeling was used to replicate the analyses of Kelly et al. (Alcohol Clin Exp Res. 2011;35:454-463) and to compare AA attendance and AA involvement as focal predictors. Multiple regression analyses were used to determine which spirituality dimensions changed as the result of AA participation. A trimmed, data-driven model was employed to test multiple mediation paths simultaneously. The findings of the Kelly et al. study were replicated. AA involvement was a stronger predictor of drinking outcomes than AA attendance. AA involvement predicted increases in private religious practices, daily spiritual experiences, and forgiveness of others. However, only private religious practices mediated the relationship between AA and drinking.

Predictors of Employment Status for People with Multiple Sclerosis

ERIC Educational Resources Information Center

Roessler, Richard T.; Rumrill, Phillip D.; Fitzgerald, Shawn M.

2004-01-01

This study examined the relevance of the disease-and-demographics model for explaining the employment outcomes of adults with multiple sclerosis (MS). Participating in a national survey of their employment concerns, 1,310 adults with MS provided data for the study (274 men, 21%; 1,020 women, 78%; 16 participants did not identify their gender).…

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)

Psychological quality of life and its association with academic employability skills among newly-registered students from three European faculties

PubMed Central

2011-01-01

Background In accord with new European university reforms initiated by the Bologna Process, our objectives were to assess psychological quality of life (QoL) and to analyse its associations with academic employability skills (AES) among students from the Faculty of Language, Literature, Humanities, Arts and Education, Walferdange Luxembourg (F1, mostly vocational/applied courses); the Faculty of Social and Human Sciences, Liege, Belgium (F2, mainly general courses); and the Faculty of Social Work, Iasi, Romania (F3, mainly vocational/professional courses). Method Students who redoubled or who had studied at other universities were excluded. 355 newly-registered first-year students (145 from F1, 125 from F2, and 85 from F3) were invited to complete an online questionnaire (in French, German, English or Romanian) covering socioeconomic data, the AES scale and the QoL-psychological, QoL-social relationships and QoL-environment subscales as measured with the World Health Organisation Quality of Life short-form (WHOQoL-BREF) questionnaire. Analyses included multiple regressions with interactions. Results QoL-psychological, QoL-social relationships and QoL-environment' scores were highest in F1 (Luxembourg), and the QoL-psychological score in F2 (Belgium) was the lower. AES score was higher in F1 than in F3 (Romania). A positive link was found between QoL-psychological and AES for F1 (correlation coefficient 0.29, p < 0.01) and F3 (correlation coefficient 0.30, p < 0.05), but the association was negative for F2 (correlation coefficient -0.25, p < 0.01). QoL-psychological correlated positively with QoL-social relationships (regression coefficient 0.31, p < 0.001) and QoL-environment (regression coefficient 0.35, p < 0.001). Conclusions Psychological quality of life is associated with acquisition of skills that increase employability from the faculties offering vocational/applied/professional courses in Luxembourg and Romania, but not their academically orientated Belgian counterparts. In the context of developing a European Higher Educational Area, these measurements are major indicators that can be used as a guide to promoting programs geared towards counseling, improvement of the social environment, and services to assist with university work and facilitate achievement of future professional projects. PMID:21501507

Psychological quality of life and its association with academic employability skills among newly-registered students from three European faculties.

PubMed

Baumann, Michèle; Ionescu, Ion; Chau, Nearkasen

2011-04-18

In accord with new European university reforms initiated by the Bologna Process, our objectives were to assess psychological quality of life (QoL) and to analyse its associations with academic employability skills (AES) among students from the Faculty of Language, Literature, Humanities, Arts and Education, Walferdange Luxembourg (F1, mostly vocational/applied courses); the Faculty of Social and Human Sciences, Liege, Belgium (F2, mainly general courses); and the Faculty of Social Work, Iasi, Romania (F3, mainly vocational/professional courses). Students who redoubled or who had studied at other universities were excluded. 355 newly-registered first-year students (145 from F1, 125 from F2, and 85 from F3) were invited to complete an online questionnaire (in French, German, English or Romanian) covering socioeconomic data, the AES scale and the QoL-psychological, QoL-social relationships and QoL-environment subscales as measured with the World Health Organisation Quality of Life short-form (WHOQoL-BREF) questionnaire. Analyses included multiple regressions with interactions. QoL-psychological, QoL-social relationships and QoL-environment' scores were highest in F1 (Luxembourg), and the QoL-psychological score in F2 (Belgium) was the lower. AES score was higher in F1 than in F3 (Romania). A positive link was found between QoL-psychological and AES for F1 (correlation coefficient 0.29, p<0.01) and F3 (correlation coefficient 0.30, p<0.05), but the association was negative for F2 (correlation coefficient -0.25, p<0.01). QoL-psychological correlated positively with QoL-social relationships (regression coefficient 0.31, p<0.001) and QoL-environment (regression coefficient 0.35, p<0.001). Psychological quality of life is associated with acquisition of skills that increase employability from the faculties offering vocational/applied/professional courses in Luxembourg and Romania, but not their academically orientated Belgian counterparts. In the context of developing a European Higher Educational Area, these measurements are major indicators that can be used as a guide to promoting programs geared towards counseling, improvement of the social environment, and services to assist with university work and facilitate achievement of future professional projects.

Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods

NASA Astrophysics Data System (ADS)

Seibert, Mathias; Merz, Bruno; Apel, Heiko

2017-03-01

The Limpopo Basin in southern Africa is prone to droughts which affect the livelihood of millions of people in South Africa, Botswana, Zimbabwe and Mozambique. Seasonal drought early warning is thus vital for the whole region. In this study, the predictability of hydrological droughts during the main runoff period from December to May is assessed using statistical approaches. Three methods (multiple linear models, artificial neural networks, random forest regression trees) are compared in terms of their ability to forecast streamflow with up to 12 months of lead time. The following four main findings result from the study. 1. There are stations in the basin at which standardised streamflow is predictable with lead times up to 12 months. The results show high inter-station differences of forecast skill but reach a coefficient of determination as high as 0.73 (cross validated). 2. A large range of potential predictors is considered in this study, comprising well-established climate indices, customised teleconnection indices derived from sea surface temperatures and antecedent streamflow as a proxy of catchment conditions. El Niño and customised indices, representing sea surface temperature in the Atlantic and Indian oceans, prove to be important teleconnection predictors for the region. Antecedent streamflow is a strong predictor in small catchments (with median 42 % explained variance), whereas teleconnections exert a stronger influence in large catchments. 3. Multiple linear models show the best forecast skill in this study and the greatest robustness compared to artificial neural networks and random forest regression trees, despite their capabilities to represent nonlinear relationships. 4. Employed in early warning, the models can be used to forecast a specific drought level. Even if the coefficient of determination is low, the forecast models have a skill better than a climatological forecast, which is shown by analysis of receiver operating characteristics (ROCs). Seasonal statistical forecasts in the Limpopo show promising results, and thus it is recommended to employ them as complementary to existing forecasts in order to strengthen preparedness for droughts.

Comparing least-squares and quantile regression approaches to analyzing median hospital charges.

PubMed

Olsen, Cody S; Clark, Amy E; Thomas, Andrea M; Cook, Lawrence J

2012-07-01

Emergency department (ED) and hospital charges obtained from administrative data sets are useful descriptors of injury severity and the burden to EDs and the health care system. However, charges are typically positively skewed due to costly procedures, long hospital stays, and complicated or prolonged treatment for few patients. The median is not affected by extreme observations and is useful in describing and comparing distributions of hospital charges. A least-squares analysis employing a log transformation is one approach for estimating median hospital charges, corresponding confidence intervals (CIs), and differences between groups; however, this method requires certain distributional properties. An alternate method is quantile regression, which allows estimation and inference related to the median without making distributional assumptions. The objective was to compare the log-transformation least-squares method to the quantile regression approach for estimating median hospital charges, differences in median charges between groups, and associated CIs. The authors performed simulations using repeated sampling of observed statewide ED and hospital charges and charges randomly generated from a hypothetical lognormal distribution. The median and 95% CI and the multiplicative difference between the median charges of two groups were estimated using both least-squares and quantile regression methods. Performance of the two methods was evaluated. In contrast to least squares, quantile regression produced estimates that were unbiased and had smaller mean square errors in simulations of observed ED and hospital charges. Both methods performed well in simulations of hypothetical charges that met least-squares method assumptions. When the data did not follow the assumed distribution, least-squares estimates were often biased, and the associated CIs had lower than expected coverage as sample size increased. Quantile regression analyses of hospital charges provide unbiased estimates even when lognormal and equal variance assumptions are violated. These methods may be particularly useful in describing and analyzing hospital charges from administrative data sets. © 2012 by the Society for Academic Emergency Medicine.

Economic Expansion Is a Major Determinant of Physician Supply and Utilization

PubMed Central

Cooper, Richard A; Getzen, Thomas E; Laud, Prakash

2003-01-01

Objective To assess the relationship between levels of economic development and the supply and utilization of physicians. Data Sources Data were obtained from the American Medical Association, American Osteopathic Association, Organization for Economic Cooperation and Development (OECD), Bureau of Health Professions, Bureau of Labor Statistics, Bureau of Economic Analysis, Census Bureau, Health Care Financing Administration, and historical sources. Study Design Economic development, expressed as real per capita gross domestic product (GDP) or personal income, was correlated with per capita health care labor and physician supply within countries and states over periods of time spanning 25–70 years and across countries, states, and metropolitan statistical areas (MSAs) at multiple points in time over periods of up to 30 years. Longitudinal data were analyzed in four complementary ways: (1) simple univariate regressions; (2) regressions in which temporal trends were partialled out; (3) time series comparing percentage differences across segments of time; and (4) a bivariate Granger causality test. Cross-sectional data were assessed at multiple time points by means of univariate regression analyses. Principal Findings Under each analytic scenario, physician supply correlated with differences in GDP or personal income. Longitudinal correlations were associated with temporal lags of approximately 5 years for health employment and 10 years for changes in physician supply. The magnitude of changes in per capita physician supply in the United States was equivalent to differences of approximately 0.75 percent for each 1.0 percent difference in GDP. The greatest effects of economic expansion were on the medical specialties, whereas the surgical and hospital-based specialties were affected to a lesser degree, and levels of economic expansion had little influence on family/general practice. Conclusions Economic expansion has a strong, lagged relationship with changes in physician supply. This suggests that economic projections could serve as a gauge for projecting the future utilization of physician services. PMID:12785567

Socio-economic factors associated with infant mortality in Italy: an ecological study

PubMed Central

2012-01-01

Introduction One issue that continues to attract the attention of public health researchers is the possible relationship in high-income countries between income, income inequality and infant mortality (IM). The aim of this study was to assess the associations between IM and major socio-economic determinants in Italy. Methods Associations between infant mortality rates in the 20 Italian regions (2006–2008) and the Gini index of income inequality, mean household income, percentage of women with at least 8 years of education, and percentage of unemployed aged 15–64 years were assessed using Pearson correlation coefficients. Univariate linear regression and multiple stepwise linear regression analyses were performed to determine the magnitude and direction of the effect of the four socio-economic variables on IM. Results The Gini index and the total unemployment rate showed a positive strong correlation with IM (r = 0.70; p < 0.001 and r = 0.84; p < 0.001 respectively), mean household income showed a strong negative correlation (r = −0.78; p < 0.001), while female educational attainment presented a weak negative correlation (r = −0.45; p < 0.05). Using a multiple stepwise linear regression model, only unemployment rate was independently associated with IM (b = 0.15, p < 0.001). Conclusions In Italy, a high-income country where health care is universally available, variations in IM were strongly associated with relative and absolute income and unemployment rate. These results suggest that in Italy IM is not only related to income distribution, as demonstrated for other developed countries, but also to economic factors such as absolute income and unemployment. In order to reduce IM and the existing inequalities, the challenge for Italian decision makers is to promote economic growth and enhance employment levels. PMID:22898293

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.

77 FR 3121 - Program Integrity: Gainful Employment-Debt Measures; Correction

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-23

...On June 13, 2011, the Secretary of Education (Secretary) published a notice of final regulations in the Federal Register for Program Integrity: Gainful Employment--Debt Measures (Gainful Employment--Debt Measures) (76 FR 34386). In the preamble of the final regulations, we used the wrong data to calculate the percent of total variance in institutions' repayment rates that may be explained by race/ethnicity. Our intent was to use the data that included all minority students per institution. However, we mistakenly used the data for a subset of minority students per institution. We have now recalculated the total variance using the data that includes all minority students. Through this document, we correct, in the preamble of the Gainful Employment--Debt Measures final regulations, the errors resulting from this misapplication. We do not change the regression analysis model itself; we are using the same model with the appropriate data. Through this notice we also correct, in the preamble of the Gainful Employment--Debt Measures final regulations, our description of one component of the regression analysis. The preamble referred to use of an institutional variable measuring acceptance rates. This description was incorrect; in fact we used an institutional variable measuring retention rates. Correcting this language does not change the regression analysis model itself or the variance explained by the model. The text of the final regulations remains unchanged.

Impact of low vision on employment.

PubMed

Mojon-Azzi, Stefania M; Sousa-Poza, Alfonso; Mojon, Daniel S

2010-01-01

We investigated the influence of self-reported corrected eyesight on several variables describing the perception by employees and self-employed persons of their employment. Our study was based on data from the Survey of Health, Ageing and Retirement in Europe (SHARE). SHARE is a multidisciplinary, cross-national database of microdata on health, socioeconomic status, social and family networks, collected on 31,115 individuals in 11 European countries and in Israel. With the help of ordered logistic regressions and binary logistic regressions, we analyzed the influence of perceived visual impairment--corrected by 19 covariates capturing socioeconomic and health-related factors--on 10 variables describing the respondents' employment situation. Based on data covering 10,340 working individuals, the results of the logistic and ordered regressions indicate that respondents with lower levels of self-reported general eyesight were significantly less satisfied with their jobs, felt they had less freedom to decide, less opportunity to develop new skills, less support in difficult situations, less recognition for their work, and an inadequate salary. Respondents with a lower eyesight level more frequently reported that they feared their health might limit their ability to work before regular retirement age and more often indicated that they were seeking early retirement. Analysis of this dataset from 12 countries demonstrates the strong impact of self-reported visual impairment on individual employment, and therefore on job satisfaction, productivity, and well-being. Copyright © 2010 S. Karger AG, Basel.

29 CFR 2520.101-2 - Annual reporting by multiple employer welfare arrangements and certain other entities offering or...

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 9 2010-07-01 2010-07-01 false Annual reporting by multiple employer welfare arrangements and certain other entities offering or providing coverage for medical care to the employees of two or more employers. 2520.101-2 Section 2520.101-2 Labor Regulations Relating to Labor (Continued) EMPLOYEE...

Gender and Perceived Illness Severity: Differential Indicators of Employment Concerns for Adults with Multiple Sclerosis?

ERIC Educational Resources Information Center

Roessler, Richard T.; Turner, Ronna C.; Robertson, Judith L.; Rumrill,Phillip D.

2005-01-01

Although research has indicated a link between gender and perceived illness severity and the employment status of people with multiple sclerosis (MS), it has not addressed questions regarding the relationship between those variables and specific types of employment concerns. In this study, a sample of 1,310 adults with MS replied to a mail survey…

Employment among Working-Age Adults with Multiple Sclerosis: A Data-Mining Approach to Identifying Employment Interventions

ERIC Educational Resources Information Center

Bishop, Malachy; Chan, Fong; Rumrill, Phillip D., Jr.; Frain, Michael P.; Tansey, Timothy N.; Chiu, Chung-Yi; Strauser, David; Umeasiegbu, Veronica I.

2015-01-01

Purpose: To examine demographic, functional, and clinical multiple sclerosis (MS) variables affecting employment status in a national sample of adults with MS in the United States. Method: The sample included 4,142 working-age (20-65 years) Americans with MS (79.1% female) who participated in a national survey. The mean age of participants was…

Predictors of Employment for Youths with Visual Impairments: Findings from the Second National Longitudinal Transition Study

ERIC Educational Resources Information Center

McDonnall, Michele Capella

2011-01-01

The study reported here identified factors that predict employment for transition-age youths with visual impairments. Logistic regression was used to predict employment at two levels. Significant variables were early and recent work experiences, completion of a postsecondary program, difficulty with transportation, independent travel skills, and…

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.

Does substance misuse moderate the relationship between criminal thinking and recidivism?

PubMed Central

Caudy, Michael S.; Folk, Johanna B.; Stuewig, Jeffrey B.; Wooditch, Alese; Martinez, Andres; Maass, Stephanie; Tangney, June P.; Taxman, Faye S.

2014-01-01

Purpose Some differential intervention frameworks contend that substance use is less robustly related to recidivism outcomes than other criminogenic needs such as criminal thinking. The current study tested the hypothesis that substance use disorder severity moderates the relationship between criminal thinking and recidivism. Methods The study utilized two independent criminal justice samples. Study 1 included 226 drug-involved probationers. Study 2 included 337 jail inmates with varying levels of substance use disorder severity. Logistic regression was employed to test the main and interactive effects of criminal thinking and substance use on multiple dichotomous indicators of recidivism. Results Bivariate analyses revealed a significant correlation between criminal thinking and recidivism in the jail sample (r = .18, p < .05) but no significant relationship in the probation sample. Logistic regressions revealed that SUD symptoms moderated the relationship between criminal thinking and recidivism in the jail-based sample (B = −.58, p < .05). A significant moderation effect was not observed in the probation sample. Conclusions Study findings indicate that substance use disorder symptoms moderate the strength of the association between criminal thinking and recidivism. These findings demonstrate the need for further research into the interaction between various dynamic risk factors. PMID:25598559

[Gaussian process regression and its application in near-infrared spectroscopy analysis].

PubMed

Feng, Ai-Ming; Fang, Li-Min; Lin, Min

2011-06-01

Gaussian process (GP) is applied in the present paper as a chemometric method to explore the complicated relationship between the near infrared (NIR) spectra and ingredients. After the outliers were detected by Monte Carlo cross validation (MCCV) method and removed from dataset, different preprocessing methods, such as multiplicative scatter correction (MSC), smoothing and derivate, were tried for the best performance of the models. Furthermore, uninformative variable elimination (UVE) was introduced as a variable selection technique and the characteristic wavelengths obtained were further employed as input for modeling. A public dataset with 80 NIR spectra of corn was introduced as an example for evaluating the new algorithm. The optimal models for oil, starch and protein were obtained by the GP regression method. The performance of the final models were evaluated according to the root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP) and correlation coefficient (r). The models give good calibration ability with r values above 0.99 and the prediction ability is also satisfactory with r values higher than 0.96. The overall results demonstrate that GP algorithm is an effective chemometric method and is promising for the NIR analysis.

[A study on facilitators and inhibitors to the introduction of outsourcing in the hospital information systems in Korea].

PubMed

Choy, Soon; Shin, Hyeong-Sik; Choi, Inyoung; Kim, Sukil

2007-01-01

This study was conducted to investigate the current status of outsourcing in Korean hospital information systems and the factors influencing its introduction. The authors surveyed 136 hospitals located in Seoul and its surrounding vicinities from June 7 to June 23, 2006. The facilitators and inhibitors to outsourcing in hospital information systems were derived from literature and expert reviews. Multiple logistic regression analysis was applied to identify the major influencing factors on outsourcing in hospital information systems. Eighty-six (63.2%) of the 136 hospitals surveyed, which were mainly tertiary hospitals, responded to using outsourcing for their hospital information systems. "Hardware and software maintenance and support," "application development," and "management of service and staff" were the major areas of outsourcing. Outsourcing had been employed for 4-7 years by 45.5% of the hospitals and the proportion of the budget used for outsourcing was less than 20%. A need for an extension in outsourcing was agreed on by 76.5% of the hospitals. The multiple logistic regression analysis showed that both consumer satisfaction and security risk have an influence on hospital information system outsourcing. Outsourcing in hospital information systems is expected to increase just as in other industries. One primary facilitator to outsourcing in other industries is consumer satisfaction. We found that this was also a facilitator to outsourcing in hospital information systems. Security risk, which is usually considered an inhibitor to information technology outsourcing, was proven to be an inhibitor here as well. The results of this study may help hospital information systems establish a strategy and management plan for outsourcing.

Spirituality and spiritual care perspectives among baccalaureate nursing students in Saudi Arabia: A cross-sectional study.

PubMed

Cruz, Jonas Preposi; Alshammari, Farhan; Alotaibi, Khalaf Aied; Colet, Paolo C

2017-02-01

No study has been undertaken to understand how spirituality and spiritual care is perceived and implemented by Saudi nursing students undergoing training for their future professional roles as nurses. This study was conducted to investigate the perception of Baccalaureate nursing students toward spirituality and spiritual care. A descriptive, cross-sectional design was employed. A convenience sample of 338 baccalaureate nursing students in two government-run universities in Saudi Arabia was included in this study. A self-administered questionnaire, consisting of a demographic and spiritual care background information sheet and the Spiritual Care-Giving Scale Arabic version (SCGS-A), was used for data collection. A multivariate multiple regression analysis and multiple linear regression analyses were performed accordingly. The mean value on the SCGS-A was 3.84±1.26. Spiritual perspective received the highest mean (4.14±1.45), followed by attribute for spiritual care (3.96±1.48), spiritual care attitude (3.81±1.47), defining spiritual care (3.71±1.51) and spiritual care values (3.57±1.47). Gender, academic level and learning spiritual care from classroom or clinical discussions showed a statistically significant multivariate effect on the five factors of SCGS-A. Efforts should be done to formally integrate holistic concept including all the facets of spirituality and spiritual care in the nursing curriculum. The current findings can be used to inform the development and testing of holistic nursing conceptual framework in nursing education in Saudi Arabia and other Arab Muslim countries. Copyright © 2016 Elsevier Ltd. All rights reserved.

Validity of bioelectrical impedance measurement in predicting fat-free mass of Chinese children and adolescents.

PubMed

Wang, Lin; Hui, Stanley Sai-chuen; Wong, Stephen Heung-sang

2014-11-15

The current study aimed to examine the validity of various published bioelectrical impedance analysis (BIA) equations in estimating FFM among Chinese children and adolescents and to develop BIA equations for the estimation of fat-free mass (FFM) appropriate for Chinese children and adolescents. A total of 255 healthy Chinese children and adolescents aged 9 to 19 years old (127 males and 128 females) from Tianjin, China, participated in the BIA measurement at 50 kHz between the hand and the foot. The criterion measure of FFM was also employed using dual-energy X-ray absorptiometry (DEXA). FFM estimated from 24 published BIA equations was cross-validated against the criterion measure from DEXA. Multiple linear regression was conducted to examine alternative BIA equation for the studied population. FFM estimated from the 24 published BIA equations yielded high correlations with the directly measured FFM from DEXA. However, none of the 24 equations was statistically equivalent with the DEXA-measured FFM. Using multiple linear regression and cross-validation against DEXA measurement, an alternative prediction equation was determined as follows: FFM (kg)=1.613+0.742×height (cm)2/impedance (Ω)+0.151×body weight (kg); R2=0.95; SEE=2.45 kg; CV=6.5, 93.7% of the residuals of all the participants fell within the 95% limits of agreement. BIA was highly correlated with FFM in Chinese children and adolescents. When the new developed BIA equations are applied, BIA can provide a practical and valid measurement of body composition in Chinese children and adolescents.

Validity of Bioelectrical Impedance Measurement in Predicting Fat-Free Mass of Chinese Children and Adolescents

PubMed Central

Wang, Lin; Hui, Stanley Sai-chuen; Wong, Stephen Heung-sang

2014-01-01

Background The current study aimed to examine the validity of various published bioelectrical impedance analysis (BIA) equations in estimating FFM among Chinese children and adolescents and to develop BIA equations for the estimation of fat-free mass (FFM) appropriate for Chinese children and adolescents. Material/Methods A total of 255 healthy Chinese children and adolescents aged 9 to 19 years old (127 males and 128 females) from Tianjin, China, participated in the BIA measurement at 50 kHz between the hand and the foot. The criterion measure of FFM was also employed using dual-energy X-ray absorptiometry (DEXA). FFM estimated from 24 published BIA equations was cross-validated against the criterion measure from DEXA. Multiple linear regression was conducted to examine alternative BIA equation for the studied population. Results FFM estimated from the 24 published BIA equations yielded high correlations with the directly measured FFM from DEXA. However, none of the 24 equations was statistically equivalent with the DEXA-measured FFM. Using multiple linear regression and cross-validation against DEXA measurement, an alternative prediction equation was determined as follows: FFM (kg)=1.613+0.742×height (cm)2/impedance (Ω)+0.151×body weight (kg); R2=0.95; SEE=2.45kg; CV=6.5, 93.7% of the residuals of all the participants fell within the 95% limits of agreement. Conclusions BIA was highly correlated with FFM in Chinese children and adolescents. When the new developed BIA equations are applied, BIA can provide a practical and valid measurement of body composition in Chinese children and adolescents. PMID:25398209

Numerical Investigation of the Residual Stress Distribution of Flat-Faced and Convexly Curved Tablets Using the Finite Element Method.

PubMed

Otoguro, Saori; Hayashi, Yoshihiro; Miura, Takahiro; Uehara, Naoto; Utsumi, Shunichi; Onuki, Yoshinori; Obata, Yasuko; Takayama, Kozo

2015-01-01

The stress distribution of tablets after compression was simulated using a finite element method, where the powder was defined by the Drucker-Prager cap model. The effect of tablet shape, identified by the surface curvature, on the residual stress distribution was investigated. In flat-faced tablets, weak positive shear stress remained from the top and bottom die walls toward the center of the tablet. In the case of the convexly curved tablet, strong positive shear stress remained on the upper side and in the intermediate part between the die wall and the center of the tablet. In the case of x-axial stress, negative values were observed for all tablets, suggesting that the x-axial force always acts from the die wall toward the center of the tablet. In the flat tablet, negative x-axial stress remained from the upper edge to the center bottom. The x-axial stress distribution differed between the flat and convexly curved tablets. Weak stress remained in the y-axial direction of the flat tablet, whereas an upward force remained at the center of the convexly curved tablet. By employing multiple linear regression analysis, the mechanical properties of the tablets were predicted accurately as functions of their residual stress distribution. However, the multiple linear regression prediction of the dissolution parameters of acetaminophen, used here as a model drug, was limited, suggesting that the dissolution of active ingredients is not a simple process; further investigation is needed to enable accurate predictions of dissolution parameters.

A fuzzy-logic-based model to predict biogas and methane production rates in a pilot-scale mesophilic UASB reactor treating molasses wastewater.

PubMed

Turkdogan-Aydinol, F Ilter; Yetilmezsoy, Kaan

2010-10-15

A MIMO (multiple inputs and multiple outputs) fuzzy-logic-based model was developed to predict biogas and methane production rates in a pilot-scale 90-L mesophilic up-flow anaerobic sludge blanket (UASB) reactor treating molasses wastewater. Five input variables such as volumetric organic loading rate (OLR), volumetric total chemical oxygen demand (TCOD) removal rate (R(V)), influent alkalinity, influent pH and effluent pH were fuzzified by the use of an artificial intelligence-based approach. Trapezoidal membership functions with eight levels were conducted for the fuzzy subsets, and a Mamdani-type fuzzy inference system was used to implement a total of 134 rules in the IF-THEN format. The product (prod) and the centre of gravity (COG, centroid) methods were employed as the inference operator and defuzzification methods, respectively. Fuzzy-logic predicted results were compared with the outputs of two exponential non-linear regression models derived in this study. The UASB reactor showed a remarkable performance on the treatment of molasses wastewater, with an average TCOD removal efficiency of 93 (+/-3)% and an average volumetric TCOD removal rate of 6.87 (+/-3.93) kg TCOD(removed)/m(3)-day, respectively. Findings of this study clearly indicated that, compared to non-linear regression models, the proposed MIMO fuzzy-logic-based model produced smaller deviations and exhibited a superior predictive performance on forecasting of both biogas and methane production rates with satisfactory determination coefficients over 0.98. 2010 Elsevier B.V. All rights reserved.

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

PubMed

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

2018-05-10

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

Investigation of relationship between social capital and quality of life in female headed families

PubMed Central

Rimaz, Shahnaz; Dastoorpoor, Maryam; Vesali, Samira; Saiepour, Narges; Nedjat, Saharnaz; Sadeghi, Masoumeh; Merghati Khoei, Effat

2015-01-01

Background: Although most studies on female-headed families focus on women's access to social support, the associations between social capital and quality of life in these families are unclear in many societies (such as Iran). This study aimed to determine the associations between social capital and quality of life in Iranian female headed families. Methods: This cross-sectional study was performed on 152 female-headed households supported by Tehran Municipality, district 9 from April 2011 to July 2012. Convenience sampling was employed. Data were collected using demographic questionnaire, the Iranian version of World Health Organization Quality of Life, and the Word Bank Social Capital. Descriptive and multiple regression methods were used to analyze the data. Results: The mean±SD age of participants was 50.8±13.8 years. Findings revealed that in quality of life, the domains of environment health and social relation received the lowest (9.87 ± 2.41) and the highest (12.61 ±3.43) scores respectively; and with respect to social capital, membership in groups and social trust had the least (19.61 ± 17.11) and the most (51.04 ± 17.37) scores, respectively. The multiple regression model revealed a significant positive association between total score of the quality of life and the total score for the social capital (p< 0.001). Conclusion: Findings suggest that quality of life of female-headed families and social capital domains are strongly related. This means that by improving the social capital, women’s life can also be improved. PMID:26793661

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%).

Attitude and practice of physical activity and social problem-solving ability among university students.

PubMed

Sone, Toshimasa; Kawachi, Yousuke; Abe, Chihiro; Otomo, Yuki; Sung, Yul-Wan; Ogawa, Seiji

2017-04-04

Effective social problem-solving abilities can contribute to decreased risk of poor mental health. In addition, physical activity has a favorable effect on mental health. These previous studies suggest that physical activity and social problem-solving ability can interact by helping to sustain mental health. The present study aimed to determine the association between attitude and practice of physical activity and social problem-solving ability among university students. Information on physical activity and social problem-solving was collected using a self-administered questionnaire. We analyzed data from 185 students who participated in the questionnaire surveys and psychological tests. Social problem-solving as measured by the Social Problem-Solving Inventory-Revised (SPSI-R) (median score 10.85) was the dependent variable. Multiple logistic regression analysis was employed to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for higher SPSI-R according to physical activity categories. The multiple logistic regression analysis indicated that the ORs (95% CI) in reference to participants who said they never considered exercising were 2.08 (0.69-6.93), 1.62 (0.55-5.26), 2.78 (0.86-9.77), and 6.23 (1.81-23.97) for participants who did not exercise but intended to start, tried to exercise but did not, exercised but not regularly, and exercised regularly, respectively. This finding suggested that positive linear association between physical activity and social problem-solving ability (p value for linear trend < 0.01). The present findings suggest that regular physical activity or intention to start physical activity may be an effective strategy to improve social problem-solving ability.

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.

Rehabilitation technology services and employment outcomes among consumers using division of rehabilitation services.

PubMed

Sprong, Matthew Evan; Dallas, Bryan; Paul, Erina; Xia, Michelle

2018-05-03

The primary goal of the study was to evaluate how the use of rehabilitation technology impacted closure status for consumers receiving services in fiscal year (FY) 2014. Rehabilitation Service Administration (RSA-911) Case Service Report FY 2014 archival dataset was obtained from the U.S. Department of Education (2014) and secondary analyses was performed for this study. RSA-911 archival data is updated on an annual basis and consists of all state-federal rehabilitation consumers who were served in the specific fiscal year. The dataset contains information related to each consumer's demographic information (e.g. age, gender, race) and other supplemental information (e.g. weekly earnings at closure, cause of disability, services provided). A multiple logistic regression analysis was utilized and revealed that white consumers receiving rehabilitation technology (RT) services have significantly higher closure rate than consumers of other races, RT services differ by the employment status at application, RT services differ by the type of disability, educational level at application for people receiving RT services did predict closure status (i.e. exiting with an employment outcome), IEP status did not predict closure status, weekly earnings at application did predict closure status and the interaction effect between IEP and RT services is statistically significant. The odds ratio (ORs) were presented at the 95% confidence interval (CI). Vocational rehabilitation counselors needs training to correctly identify appropriate RT services for consumers, so that the likelihood of exiting with an employment outcome is obtained. Implications for Rehabilitation RT services significantly improved their chances of successful employment compared to those who did not receive RT services. Education at closure would also have some significant impact on employment outcomes. Training in Assistive Technology (AT) for Vocational Rehabilitation counselors will assist in the proper identification of AT requirements, which may lead to a higher likelihood of consumers exiting with an employment outcome.

Is suicidal ideation linked to working hours and shift work in Korea?

PubMed

Yoon, Chang-Gyo; Bae, Kyu-Jung; Kang, Mo-Yeol; Yoon, Jin-Ha

2015-01-01

This study attempted to use the community health survey (CHS) to identify the effect of long working hours (long WHs) and night/shift work on suicidal ideation among the employed population of Korea. This study used data from 67,471 subjects who were administered the 2008 CHS which obtained information regarding sociodemographic characteristics, health behaviors and working environment, using structured questionnaires and personal interviews. We adopted multiple logistic regression models for gender and employment stratification. Among male employees, suicidal ideation was significantly associated with only moderately long WHs (51-60 hours), after controlling covariates (adjusted odds ratio [aOR], 1.30; 95% confidence interval [95%CI], 1.07 to 1.57). Self-employed/male employer populations had higher suicidal ideation when they had moderately long WHs (aOR, 1.23; 95%CI, 1.01 to 1.50) and very long WHs (over 60 hours) (aOR, 1.31; 95%CI, 1.08 to 1.59). Among the female population, suicidal ideation was significantly association with moderately long WHs in the employee group (aOR, 1.31; 95%CI, 1.08 to 1.58) and moderately (aOR, 1.35; 95%CI, 1.08 to 1.69) and very (aOR, 1.33; 95%CI, 1.07 to 1.65) long WHs in the self-employed/employer group. Shift work was a significant predictor only in the female population in the employee groups (aOR, 1.45; 95%CI, 1.23 to 1.70). Long WHs and shift work were associated with suicidal ideation when taking into account gender and employment differences. The harmful effects of exceptionally long WHs in Korea, among other Organization for Economic Co-operation and Development (OECD) countries, raise concerns about public and occupational health. To address the issue of long WHs, labor policies that reduce maximum working hours and facilitate job stability are needed.

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

Predictors of employer satisfaction: technical and non-technical skills.

PubMed

Danielson, Jared A; Wu, Tsui-Feng; Fales-Williams, Amanda J; Kirk, Ryan A; Preast, Vanessa A

2012-01-01

Employers of 2007-2009 graduates from Iowa State University College of Veterinary Medicine were asked to respond to a survey regarding their overall satisfaction with their new employees as well as their new employees' preparation in several technical and non-technical skill areas. Seventy-five responses contained complete data and were used in the analysis. Four technical skill areas (data collection, data interpretation, planning, and taking action) and five non-technical skill areas (interpersonal skills, ability to deal with legal issues, business skills, making referrals, and problem solving) were identified. All of the skill area subscales listed above had appropriate reliability (Cronbach's alpha>0.70) and were positively and significantly correlated with overall employer satisfaction. Results of two simultaneous regression analyses indicated that of the four technical skill areas, taking action is the most salient predictor of employer satisfaction. Of the five non-technical skill areas, interpersonal skills, business skills, making referrals, and problem solving were the most important skills in predicting employer satisfaction. Hierarchical regression analysis revealed that all technical skills explained 25% of the variation in employer satisfaction; non-technical skills explained an additional 42% of the variation in employer satisfaction.

Does personality influence job acquisition and tenure in people with severe mental illness enrolled in supported employment programs?

PubMed

Fortin, Guillaume; Lecomte, Tania; Corbière, Marc

2017-06-01

When employment difficulties in people with severe mental illness (SMI) occur, it could be partly linked to issues not specific to SMI, such as personality traits or problems. Despite the fact that personality has a marked influence on almost every aspect of work behavior, it has scarcely been investigated in the context of employment for people with SMI. We aimed to evaluate if personality was more predictive than clinical variables of different competitive work outcomes, namely acquisition of competitive employment, delay to acquisition and job tenure. A sample of 82 people with a SMI enrolled in supported employment programs (SEP) was recruited and asked to complete various questionnaires and interviews. Statistical analyses included logistic regressions and survival analyses (Cox regressions). Prior employment, personality problems and negative symptoms are significantly related to acquisition of a competitive employment and to delay to acquisition whereas the conscientiousness personality trait was predictive of job tenure. Our results point out the relevance of personality traits and problems as predictors of work outcomes in people with SMI registered in SEP. Future studies should recruit larger samples and also investigate these links with other factors related to work outcomes.

Demographic predictors of emotional intelligence among radiation therapists.

PubMed

Stami, Trakis; Ritin, Fernandez; Dominique, Parrish

2018-04-23

Contemporary health care services are more productive and successful when their health professionals have emotional intelligence (EI). The objective of this study was to explore the demographic predictors of EI among radiation therapists working in cancer care centres in NSW, Australia. Data were collected using a cross-sectional self-administered survey. Emotional intelligence was measured using the Trait Emotional Intelligence Questionnaire- Short version (TEIQue - SF). Multiple regression analysis was used to identify if age, years of experience, gender, highest level of education obtained or level of current employment were predictors of EI. A total of 205 radiation therapists participated in this study. The mean scores for Global EI, emotionality, self-control, wellbeing and sociability dimensions were 5.16 (SD = 0.6), 5.3 (SD = 0.7), 4.9 (SD = 0.9), 5.7 (SD = 0.8) and 4.7 (SD = 0.8) respectively. Age and level of current employment were identified as predictors of global EI. Gender and level of education were significant predictors of the EI emotionality dimension. Levels of employment along with level of education were both significant predictors of the sociability dimension of EI. Being a young radiation therapist, female, and having higher levels of employment and higher levels of education were predictors of EI. Given that level of education and level of employment are both amendable demographic factors, strategies to address these factors to reduce the effects of emotional struggle experienced by radiation therapists in their work need to be implemented. © 2018 The Authors. Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology.

Effect of unemployment on cardiovascular risk factors and mental health.

PubMed

Zagożdżon, P; Parszuto, J; Wrotkowska, M; Dydjow-Bendek, D

2014-09-01

Following the economic changes in Poland, increasing health discrepancies were observed during a period of 20 years, which may be partly attributable to the consequences of unemployment. To assess the association between unemployment, major cardiovascular risk factors and mental health. A cross-sectional study in which data were collected between 2009 and 2010 during preventive health examinations by an occupational medicine service in Gdansk, Poland. Data on blood pressure, resting heart rate, information about smoking habits, body mass index and history of use of mental health services were collected during these assessments. Multiple logistic regression was used during data analysis to adjust for age, gender, education and length of employment. Study participants comprised 3052 unemployed and 2059 employed individuals. After adjustment for age, gender, education and number of previous employments, the odds ratio (OR) for hypertension in relation to unemployment was 1.02 [95% confidence interval (95% CI) 0.84-1.23]. There was a statistically significant negative association between being overweight and unemployment (OR = 0.81, 95% CI: 0.66-0.99). Smoking was positively associated with unemployment after adjustment for age and sex (OR = 1.45, 95% CI: 1.25-1.67). There was a positive relationship between mental ill-health and unemployment among study participants (OR = 2.05, 95% CI: 0.91-4.65), but this was not statistically significant. The patterns of major cardiovascular risk factors differed between unemployed and employed individuals in Poland. Our observations suggest employment status is a predictor of specific disease risk profiles; consequently, specific preventive measures are needed in unemployed individuals. © The Author 2014. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Increased risk of death with congenital anomalies in the offspring of male semiconductor workers.

PubMed

Lin, Ching-Chun; Wang, Jung-Der; Hsieh, Gong-Yih; Chang, Yu-Yin; Chen, Pau-Chung

2008-01-01

Female workers in the semiconductor industry have higher risks of subfertility and spontaneous abortion, but no studies exploring male-mediated developmental toxicity have been published. This study aimed to investigate whether the offspring of male workers employed in the semiconductor manufacturing industry had an increased risk of death with congenital anomalies. The 6,834 male workers had been employed in the eight semiconductor companies in Taiwan between 1980 and 1994. We identified the live born children with or without congenital anomalies of the workers using the National Birth and Death Registries from the Department of Health, Taiwan. Multiple logistic regression models were used to estimate the odds ratios (OR) of birth outcomes and deaths, controlling for infant sex, maternal age, and paternal education. A total of 5,702 children were born to male workers during the period 1980-1994. There were increased risks of deaths with congenital anomalies (adjusted OR, 3.26; and 95% confidence interval [CI], 1.12-9.44) and heart anomalies (OR, 4.15; 95% CI, 1.08-15.95) in the offspring of male workers who were employed during the two months before conception. We found evidence of a possible link between paternal preconception exposure of semiconductor manufacturing and an increased risk of congenital anomalies, especially of the heart. The possible etiological basis needs to be corroborated in further research.

Logistic regression for risk factor modelling in stuttering research.

PubMed

Reed, Phil; Wu, Yaqionq

2013-06-01

To outline the uses of logistic regression and other statistical methods for risk factor analysis in the context of research on stuttering. The principles underlying the application of a logistic regression are illustrated, and the types of questions to which such a technique has been applied in the stuttering field are outlined. The assumptions and limitations of the technique are discussed with respect to existing stuttering research, and with respect to formulating appropriate research strategies to accommodate these considerations. Finally, some alternatives to the approach are briefly discussed. The way the statistical procedures are employed are demonstrated with some hypothetical data. Research into several practical issues concerning stuttering could benefit if risk factor modelling were used. Important examples are early diagnosis, prognosis (whether a child will recover or persist) and assessment of treatment outcome. After reading this article you will: (a) Summarize the situations in which logistic regression can be applied to a range of issues about stuttering; (b) Follow the steps in performing a logistic regression analysis; (c) Describe the assumptions of the logistic regression technique and the precautions that need to be checked when it is employed; (d) Be able to summarize its advantages over other techniques like estimation of group differences and simple regression. Copyright © 2012 Elsevier Inc. All rights reserved.

The effects of cultural values on mental health among the Taiwanese people: mediating of attitudes toward emotional expression.

PubMed

Chu, Li-Chuan

2015-03-01

Empirical evidence has demonstrated that an individual's cultural values can influence his or her mental health. This study extends previous research by proposing and testing a model that examines mediating processes underlying the relationship between individuals' cultural values and their mental health. This 2-stage study used data collected from 208 (at time 1) and 159 (at time 2) full-time staff employed by private enterprises in Taiwan. The author tested hypotheses through the use of hierarchical multiple regression. The results showed that under horizontal individualism and vertical collectivism, the predictors of negative mental health (ie, somatic symptoms, anxiety and insomnia, social dysfunction and/or severe depression) were partially and almost completely achieved through the mediating effect of the negative attitudes toward emotional expression. © 2012 APJPH.

Remote sensing of biomass and annual net aerial primary productivity of a salt marsh

NASA Technical Reports Server (NTRS)

Hardisky, M. A.; Klemas, V.; Daiber, F. C.; Roman, C. T.

1984-01-01

Net aerial primary productivity is the rate of storage of organic matter in above-ground plant issues exceeding the respiratory use by the plants during the period of measurement. It is pointed out that this plant tissue represents the fixed carbon available for transfer to and consumption by the heterotrophic organisms in a salt marsh or the estuary. One method of estimating annual net aerial primary productivity (NAPP) required multiple harvesting of the marsh vegetation. A rapid nondestructive remote sensing technique for estimating biomass and NAPP would, therefore, be a significant asset. The present investigation was designed to employ simple regression models, equating spectral radiance indices with Spartina alterniflora biomass to nondestructively estimate salt marsh biomass. The results of the study showed that the considered approach can be successfully used to estimate salt marsh biomass.

Prevalence of hepatitis B virus markers among hospital personnel in Israel: correlation with some risk factors.

PubMed

Weiss, Y; Rabinovitch, M; Cahaner, Y; Noy, D; Siegman-Igra, Y

1994-03-01

During 1986-1987, 480 employees of the Tel-Aviv Medical Center were screened for hepatitis B virus (HBV) markers as a preliminary step in a vaccination campaign. One hundred and seventeen (24.4%) had evidence of previous infection, including nine (1.9%) carriers. The effect of potential risk factors on seropositivity was evaluated by multiple logistic regression analysis, which enabled assessment of the individual contribution of each risk factor under the specific environmental conditions. The following risk factors were found to influence seropositivity: origin from Third World countries as opposed to the Western World, employment as sanitary workers, age over 40 years, and history of accidental needle punctures. In the heterogeneous Israeli population, hospital workers had a relatively high prevalence of HBV markers, probably resulting from occupational exposure.

Determinants of residential mobility decisions: the role of government services in relation to other factors

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

Varady, D.P.

This article is one of the first to test for the relative importance of concerns about public services in affecting residential mobility decisions over and beyond normal mobility factors. A secondary aim is to test for the validity of a residential mobility model formulated by Speare and associates. Multiple regression analysis was employed using 1974 to 1977 data from the longitudinal version of the Annual Housing Survey. Concerns about public services did not play a meaningful role in the analysis. This implies that efforts to hold middle-income residents in declining neighborhoods, through improved services, will not succeed. The results supportedmore » the Speare mobility model; housing satisfaction acted as an intermediary variable between background characteristics and mobility behavior. 30 references, 4 figures, 5 tables.« less

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.

Prevalence of "HIV/AIDS related" parental death and its association with sexual behavior of secondary school youth in Addis Ababa, Ethiopia: a cross sectional study.

PubMed

Menna, Takele; Ali, Ahmed; Worku, Alemayehu

2014-10-30

Human immunodeficiency virus infection is a global crisis that represents a serious health threat, particularly among younger people. Various studies show that both orphan and non-orphan adolescents and youths experience vulnerability to HIV. Nevertheless, the findings hitherto are mixed and inconclusive. The aim of this study, therefore, was to assess the prevalence of parental death and its association with multiple sexual partners among secondary school students for evidence based interventions. A cross-sectional study was conducted among secondary school youth in Addis Ababa, Ethiopia. A multistage sampling technique was used to select a representative sample of 2,169 school youths. Sexual health behavior related data were collected using self-administered questionnaire. Binary logistic regression was employed to examine the relation between parental death and multiple sexual partners. Among the 2,169 eligible study participants 1948 (90%) completed the self-administered questionnaires. Of those 1,182(60.7%) were females. The overall prevalence of parental death was 347(17.8%.) with 95% CI (16.2%, 19.6%). The HIV/AIDS proportionate mortality ratio was 28% (97/347).A multivariate logistic regression analysis showed that high HIV/AIDS related knowledge (AOR = 0.39; 95% CI, 0.18-0.84), positive attitude towards HIV prevention methods (AOR = 0.48; 95% CI, 0.23-0.97), being tested for HIV (AOR = 0.52; 95% CI, 0.31-0.87) and chewing Khat (AOR = 2.59; 95% CI,1.28-5.26)] were significantly associated with having multiple sexual partners among secondary school youths. Significant proportion of secondary school youths had lost at least one parent due to various causes. High knowledge of HIV/AIDS, positive attitude towards 'ABC' rules for HIV prevention, being tested for HIV and chewing khat are more likely to be factors associated with multiple sexual partnership among secondary school students in Addis Ababa.Therefore, the school based interventions against the HIV/AIDS epidemic should be strengthened with particular emphasis on the effects of HIV/AIDS related knowledge, attitude towards preventive measures, mechanisms for improving HIV Counseling and Testing coverage and the associated prevailing risk factors.

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...

Rural-urban analyses of health-related quality of life among people with multiple sclerosis.

PubMed

Buchanan, Robert J; Zhu, Li; Schiffer, Randolph; Radin, Dagmar; James, Wesley

2008-01-01

Health-related quality of life (HRQOL) is a multi-dimensional construct including aspects of life quality or function that are affected by physical health and symptoms, psychosocial factors, and psychiatric conditions. HRQOL gives a broader measure of the burden of disease than physical impairment or disability levels. To identify factors associated with HRQOL among people with multiple sclerosis (MS) utilizing the SF-8 Health Survey. Data presented in this study were collected in a survey of 1,518 people with MS living in all 50 states. The survey sample was randomly selected from the database of the National Multiple Sclerosis Society, using ZIP codes to recruit the survey sample. A multiple linear regression model was employed to analyze the survey data, with the Physical Component Summary and the Mental Component Summary of the SF-8 the dependent variables. Independent variables were demographic characteristics, MS-disease characteristics, and health services utilized. People with MS in rural areas tended to report lower physically related HRQOL. Worsening MS symptoms were associated with reduced physical and mental dimensions of HRQOL. In addition, people with MS who received a diagnosis of depression tended to have reduced physical and mental dimensions of HRQOL. Receiving MS care at an MS clinic was associated with better physically related HRQOL, while having a neurologist as principal care physician was associated with better mental-related HRQOL. The challenge is to increase the access that people living with MS in rural areas have to MS-focused specialty care.

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

PubMed

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

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

FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors.

PubMed

Lorenzo-Seva, Urbano; Ferrando, Pere J

2011-03-01

We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.

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

ERIC Educational Resources Information Center

Kim, Rae Seon

2011-01-01

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

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.

Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms.

PubMed

Barzegar, Rahim; Moghaddam, Asghar Asghari; Deo, Ravinesh; Fijani, Elham; Tziritis, Evangelos

2018-04-15

Constructing accurate and reliable groundwater risk maps provide scientifically prudent and strategic measures for the protection and management of groundwater. The objectives of this paper are to design and validate machine learning based-risk maps using ensemble-based modelling with an integrative approach. We employ the extreme learning machines (ELM), multivariate regression splines (MARS), M5 Tree and support vector regression (SVR) applied in multiple aquifer systems (e.g. unconfined, semi-confined and confined) in the Marand plain, North West Iran, to encapsulate the merits of individual learning algorithms in a final committee-based ANN model. The DRASTIC Vulnerability Index (VI) ranged from 56.7 to 128.1, categorized with no risk, low and moderate vulnerability thresholds. The correlation coefficient (r) and Willmott's Index (d) between NO 3 concentrations and VI were 0.64 and 0.314, respectively. To introduce improvements in the original DRASTIC method, the vulnerability indices were adjusted by NO 3 concentrations, termed as the groundwater contamination risk (GCR). Seven DRASTIC parameters utilized as the model inputs and GCR values utilized as the outputs of individual machine learning models were served in the fully optimized committee-based ANN-predictive model. The correlation indicators demonstrated that the ELM and SVR models outperformed the MARS and M5 Tree models, by virtue of a larger d and r value. Subsequently, the r and d metrics for the ANN-committee based multi-model in the testing phase were 0.8889 and 0.7913, respectively; revealing the superiority of the integrated (or ensemble) machine learning models when compared with the original DRASTIC approach. The newly designed multi-model ensemble-based approach can be considered as a pragmatic step for mapping groundwater contamination risks of multiple aquifer systems with multi-model techniques, yielding the high accuracy of the ANN committee-based model. Copyright © 2017 Elsevier B.V. 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.

A Method for Assessing the Quality of Model-Based Estimates of Ground Temperature and Atmospheric Moisture Using Satellite Data

NASA Technical Reports Server (NTRS)

Wu, Man Li C.; Schubert, Siegfried; Lin, Ching I.; Stajner, Ivanka; Einaudi, Franco (Technical Monitor)

2000-01-01

A method is developed for validating model-based estimates of atmospheric moisture and ground temperature using satellite data. The approach relates errors in estimates of clear-sky longwave fluxes at the top of the Earth-atmosphere system to errors in geophysical parameters. The fluxes include clear-sky outgoing longwave radiation (CLR) and radiative flux in the window region between 8 and 12 microns (RadWn). The approach capitalizes on the availability of satellite estimates of CLR and RadWn and other auxiliary satellite data, and multiple global four-dimensional data assimilation (4-DDA) products. The basic methodology employs off-line forward radiative transfer calculations to generate synthetic clear-sky longwave fluxes from two different 4-DDA data sets. Simple linear regression is used to relate the clear-sky longwave flux discrepancies to discrepancies in ground temperature ((delta)T(sub g)) and broad-layer integrated atmospheric precipitable water ((delta)pw). The slopes of the regression lines define sensitivity parameters which can be exploited to help interpret mismatches between satellite observations and model-based estimates of clear-sky longwave fluxes. For illustration we analyze the discrepancies in the clear-sky longwave fluxes between an early implementation of the Goddard Earth Observing System Data Assimilation System (GEOS2) and a recent operational version of the European Centre for Medium-Range Weather Forecasts data assimilation system. The analysis of the synthetic clear-sky flux data shows that simple linear regression employing (delta)T(sub g)) and broad layer (delta)pw provides a good approximation to the full radiative transfer calculations, typically explaining more thin 90% of the 6 hourly variance in the flux differences. These simple regression relations can be inverted to "retrieve" the errors in the geophysical parameters, Uncertainties (normalized by standard deviation) in the monthly mean retrieved parameters range from 7% for (delta)T(sub g) to approx. 20% for the lower tropospheric moisture between 500 hPa and surface. The regression relationships developed from the synthetic flux data, together with CLR and RadWn observed with the Clouds and Earth Radiant Energy System instrument, ire used to assess the quality of the GEOS2 T(sub g) and pw. Results showed that the GEOS2 T(sub g) is too cold over land, and pw in upper layers is too high over the tropical oceans and too low in the lower atmosphere.

"I WILL SURVIVE" A Construct Validation Study on the Measurement of Sustainable Employability Using Different Age Conceptualizations.

PubMed

Le Blanc, Pascale M; Van der Heijden, Beatrice I J M; Van Vuuren, Tinka

2017-01-01

Though the importance of sustainable employability throughout people's working life is undisputed, up till now only one attempt for a conceptual definition has been made (van der Klink et al., 2016). Following the suggestions to further refine and improve this definition recently put forward by Fleuren et al. (2016), we propose an approach to sustainable employability that is based on the Ability-Motivation-Opportunity (AMO) framework, and incorporates three indicators: the ability, the motivation, and the opportunity to continue working, respectively. As sustainable employability is considered to be an important aspect of successful aging at work, this study used four different conceptualizations of aging at work to set up convergent and divergent validity of our operationalization of sustainable employability: calendar age, organizational age (job and organizational tenure), functional age (work ability), and life-span age (partner and children). We formulated several hypotheses that were tested by analyzing data from an online survey among 180 employees from Dutch public service organizations who filled out a questionnaire on different age concepts, and their ability, motivation, and opportunity to continue working. Multiple regression analyses were performed, and results showed that the four conceptualizations of aging were differently related to the three indicators of sustainable employability. Life-span age, in terms of having children, had the strongest negative relationship with the ability to continue working, organizational age (i.e., organizational tenure) had the strongest negative relationship with the motivation to continue working, and functional age had the strongest negative relationship with the opportunity to continue working. Moreover, functional age was significantly negatively related to the other two indicators of sustainable employability too, while life-span age appeared to enhance the ability and motivation to continue working (in terms of having children) and the perceived opportunity to continue working (in terms of having a partner). Calendar age was only important for the opportunity to continue working and appeared to have a negative association with this outcome variable. These results lend support to our proposed operationalization of sustainable employability by showing that the three indicators are differently related to different age conceptualizations thus expanding previous research on the conceptualization of sustainable employability.

Quality by design: optimization of a liquid filled pH-responsive macroparticles using Draper-Lin composite design.

PubMed

Rafati, Hasan; Talebpour, Zahra; Adlnasab, Laleh; Ebrahimi, Samad Nejad

2009-07-01

In this study, pH responsive macroparticles incorporating peppermint oil (PO) were prepared using a simple emulsification/polymer precipitation technique. The formulations were examined for their properties and the desired quality was then achieved using a quality by design (QBD) approach. For this purpose, a Draper-Lin small composite design study was employed in order to investigate the effect of four independent variables, including the PO to water ratio, the concentration of pH sensitive polymer (hydroxypropyl methylcellulose phthalate), acid and plasticizer concentrations, on the encapsulation efficiency and PO loading. The analysis of variance showed that the polymer concentration was the most important variable on encapsulation efficiency (p < 0.05). The multiple regression analysis of the results led to equations that adequately described the influence of the independent variables on the selected responses. Furthermore, the desirability function was employed as an effective tool for transforming each response separately and encompassing all of these responses in an overall desirability function for global optimization of the encapsulation process. The optimized macroparticles were predicted to yield 93.4% encapsulation efficiency and 72.8% PO loading, which were remarkably close to the experimental values of 89.2% and 69.5%, consequently.