Vocational Rehabilitation Service Patterns and Outcomes for Individuals with Autism of Different Ages

ERIC Educational Resources Information Center

Chen, June L.; Sung, Connie; Pi, Sukyeong

2015-01-01

Young adults with autism spectrum disorders (ASD) often experience employment difficulties. Using Rehabilitation Service Administration data (RSA-911), this study investigated the service patterns and factors related to the employment outcomes of individuals with ASD in different age groups. Hierarchical logistic regression analyses were conducted…

Nonstandard Employment in the Nonmetropolitan United States

ERIC Educational Resources Information Center

McLaughlin, Diane K.; Coleman-Jensen, Alisha J.

2008-01-01

We examine the prevalence of nonstandard employment in the nonmetropolitan United States using the Current Population Survey Supplement on Contingent Work (1999 and 2001). We find that nonstandard work is more prevalent in nonmetropolitan than in central city or suburban areas. Logistic regression models controlling for sociodemographic and work…

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.

Accounting for Slipping and Other False Negatives in Logistic Models of Student Learning

ERIC Educational Resources Information Center

MacLellan, Christopher J.; Liu, Ran; Koedinger, Kenneth R.

2015-01-01

Additive Factors Model (AFM) and Performance Factors Analysis (PFA) are two popular models of student learning that employ logistic regression to estimate parameters and predict performance. This is in contrast to Bayesian Knowledge Tracing (BKT) which uses a Hidden Markov Model formalism. While all three models tend to make similar predictions,…

Factors Associated with Participation in Employment for High School Leavers with Autism

ERIC Educational Resources Information Center

Chiang, Hsu-Min; Cheung, Ying Kuen; Li, Huacheng; Tsai, Luke Y.

2013-01-01

This study aimed to identify the factors associated with participation in employment for high school leavers with autism. A secondary data analysis of the National Longitudinal Transition Study 2 (NLTS2) data was performed. Potential factors were assessed using a weighted multivariate logistic regression. This study found that annual household…

Effect of folic acid on appetite in children: ordinal logistic and fuzzy logistic regressions.

PubMed

Namdari, Mahshid; Abadi, Alireza; Taheri, S Mahmoud; Rezaei, Mansour; Kalantari, Naser; Omidvar, Nasrin

2014-03-01

Reduced appetite and low food intake are often a concern in preschool children, since it can lead to malnutrition, a leading cause of impaired growth and mortality in childhood. It is occasionally considered that folic acid has a positive effect on appetite enhancement and consequently growth in children. The aim of this study was to assess the effect of folic acid on the appetite of preschool children 3 to 6 y old. The study sample included 127 children ages 3 to 6 who were randomly selected from 20 preschools in the city of Tehran in 2011. Since appetite was measured by linguistic terms, a fuzzy logistic regression was applied for modeling. The obtained results were compared with a statistical ordinal logistic model. After controlling for the potential confounders, in a statistical ordinal logistic model, serum folate showed a significantly positive effect on appetite. A small but positive effect of folate was detected by fuzzy logistic regression. Based on fuzzy regression, the risk for poor appetite in preschool children was related to the employment status of their mothers. In this study, a positive association was detected between the levels of serum folate and improved appetite. For further investigation, a randomized controlled, double-blind clinical trial could be helpful to address causality. Copyright © 2014 Elsevier Inc. All rights reserved.

Differences in Household Saving between Non-Hispanic White and Hispanic Households

ERIC Educational Resources Information Center

Fisher, Patti J.; Hsu, Chungwen

2012-01-01

This study uses the 2007 Survey of Consumer Finances to empirically explore differences in saving behavior between Hispanic (N = 533) and non-Hispanic White (N = 2,473) households. The results of the logistic regression model show that self-employed Hispanics were more likely to save, while self-employment was not significant for Whites. Being…

Differential item functioning analysis with ordinal logistic regression techniques. DIFdetect and difwithpar.

PubMed

Crane, Paul K; Gibbons, Laura E; Jolley, Lance; van Belle, Gerald

2006-11-01

We present an ordinal logistic regression model for identification of items with differential item functioning (DIF) and apply this model to a Mini-Mental State Examination (MMSE) dataset. We employ item response theory ability estimation in our models. Three nested ordinal logistic regression models are applied to each item. Model testing begins with examination of the statistical significance of the interaction term between ability and the group indicator, consistent with nonuniform DIF. Then we turn our attention to the coefficient of the ability term in models with and without the group term. If including the group term has a marked effect on that coefficient, we declare that it has uniform DIF. We examined DIF related to language of test administration in addition to self-reported race, Hispanic ethnicity, age, years of education, and sex. We used PARSCALE for IRT analyses and STATA for ordinal logistic regression approaches. We used an iterative technique for adjusting IRT ability estimates on the basis of DIF findings. Five items were found to have DIF related to language. These same items also had DIF related to other covariates. The ordinal logistic regression approach to DIF detection, when combined with IRT ability estimates, provides a reasonable alternative for DIF detection. There appear to be several items with significant DIF related to language of test administration in the MMSE. More attention needs to be paid to the specific criteria used to determine whether an item has DIF, not just the technique used to identify DIF.

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.

Factors Contributing to Successful Employment Outcomes for Hispanic Women Who Are Deaf: Utilization of Chi-Squared Automatic Interaction Detector and Logistic Regression Analysis

ERIC Educational Resources Information Center

Feist, Amber M.

2013-01-01

Hispanic women who are deaf constitute a heterogeneous group of individuals with varying vocational needs. To understand the unique needs of this population, it is important to analyze how consumer characteristics, presence of public supports, and type of services provided influence employment outcomes for Hispanic women who are deaf. The purpose…

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.

Logistic regression analysis of factors associated with avascular necrosis of the femoral head following femoral neck fractures in middle-aged and elderly patients.

PubMed

Ai, Zi-Sheng; Gao, You-Shui; Sun, Yuan; Liu, Yue; Zhang, Chang-Qing; Jiang, Cheng-Hua

2013-03-01

Risk factors for femoral neck fracture-induced avascular necrosis of the femoral head have not been elucidated clearly in middle-aged and elderly patients. Moreover, the high incidence of screw removal in China and its effect on the fate of the involved femoral head require statistical methods to reflect their intrinsic relationship. Ninety-nine patients older than 45 years with femoral neck fracture were treated by internal fixation between May 1999 and April 2004. Descriptive analysis, interaction analysis between associated factors, single factor logistic regression, multivariate logistic regression, and detailed interaction analysis were employed to explore potential relationships among associated factors. Avascular necrosis of the femoral head was found in 15 cases (15.2 %). Age × the status of implants (removal vs. maintenance) and gender × the timing of reduction were interactive according to two-factor interactive analysis. Age, the displacement of fractures, the quality of reduction, and the status of implants were found to be significant factors in single factor logistic regression analysis. Age, age × the status of implants, and the quality of reduction were found to be significant factors in multivariate logistic regression analysis. In fine interaction analysis after multivariate logistic regression analysis, implant removal was the most important risk factor for avascular necrosis in 56-to-85-year-old patients, with a risk ratio of 26.00 (95 % CI = 3.076-219.747). The middle-aged and elderly have less incidence of avascular necrosis of the femoral head following femoral neck fractures treated by cannulated screws. The removal of cannulated screws can induce a significantly high incidence of avascular necrosis of the femoral head in elderly patients, while a high-quality reduction is helpful to reduce avascular necrosis.

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

PubMed

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

2016-01-01

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

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.

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.

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

Influence of professional preparation and class structure on sexuality topics taught in middle and high schools.

PubMed

Rhodes, Darson L; Kirchofer, Gregg; Hammig, Bart J; Ogletree, Roberta J

2013-05-01

This study examined the impact of professional preparation and class structure on sexuality topics taught and use of practice-based instructional strategies in US middle and high school health classes. Data from the classroom-level file of the 2006 School Health Policies and Programs were used. A series of multivariable logistic regression models were employed to determine if sexuality content taught was dependent on professional preparation and /or class structure (HE only versus HE/another subject combined). Additional multivariable logistic regression models were employed to determine if use of practice-based instructional strategies was dependent upon professional preparation and/or class structure. Years of teaching health topics and size of the school district were included as covariates in the multivariable logistic regression models. Findings indicated professionally prepared health educators were significantly more likely to teach 7 of the 13 sexuality topics as compared to nonprofessionally prepared health educators. There was no statistically significant difference in the instructional strategies used by professionally prepared and nonprofessionally prepared health educators. Exclusively health education classes versus combined classes were significantly more likely to have included 6 of the 13 topics and to have incorporated practice-based instructional strategies in the curricula. This study indicated professional preparation and class structure impacted sexuality content taught. Class structure also impacted whether opportunities for students to practice skills were made available. Results support the need for continued advocacy for professionally prepared health educators and health only courses. © 2013, American School Health Association.

Understanding Civic Identity in College

ERIC Educational Resources Information Center

Weerts, David J.; Cabrera, Alberto F.

2015-01-01

Past literature has examined ways in which college students adopt civic identities. However, little is known about characteristics of students that vary in their expression of these identities. Drawing on data from American College Testing (ACT), this study employs multinomial logistic regression to understand attributes of students who vary in…

Stigmatizing Attributions and Vocational Rehabilitation Outcomes of People with Disabilities

ERIC Educational Resources Information Center

Chan, Jacob Yui-Chung; Keegan, John P.; Ditchman, Nicole; Gonzalez, Rene; Zheng, Lisa Xi; Chan, Fong

2011-01-01

Objective: To determine whether employment outcomes of people with disabilities can be predicted by the social-cognitive/attribution theory of stigmatization. Design: Ex post facto design using data mining technique and logistic regression analysis. Participants: Data from 40,585 vocational rehabilitation (VR) consumers were extracted from the…

Race and Unemployment: Labor Market Experiences of Black and White Men, 1968-1988.

ERIC Educational Resources Information Center

Wilson, Franklin D.; And Others

1995-01-01

Estimation of multinomial logistic regression models on a sample of unemployed workers suggested that persistently higher black unemployment is due to differential access to employment opportunities by region, occupational placement, labor market segmentation, and discrimination. The racial gap in unemployment is greatest for college-educated…

Epidemiological determinants of successful vaccine development.

PubMed

Nishiura, Hiroshi; Mizumoto, Kenji

2013-01-01

Epidemiological determinants of successful vaccine development were explored using measurable biological variables including antigenic stability and requirement of T-cell immunity. Employing a logistic regression model, we demonstrate that a high affinity with blood and immune cells and pathogen interactions (e.g. interference) would be the risk factors of failure for vaccine development.

Self-Efficacy for Resolving Environmental Uncertainties: Implications for Entrepreneurial Educational and Support Programs

ERIC Educational Resources Information Center

Pushkarskaya, Helen; Usher, Ellen L.

2010-01-01

Using a unique sample of rural Kentucky residents, we demonstrated that, in the domain of operational and competitive environmental uncertainties, self-efficacy beliefs are significantly higher among nascent entrepreneurs than among non-entrepreneurs. We employed the hierarchical logistic regression analysis to demonstrate that this result is…

Drunkorexia: Understanding the Co-Occurrence of Alcohol Consumption and Eating/Exercise Weight Management Behaviors

ERIC Educational Resources Information Center

Barry, Adam E.; Piazza-Gardner, Anna K.

2012-01-01

Objective: Examine the co-occurrence of alcohol consumption, physical activity, and disordered eating behaviors via a drunkorexia perspective. Participants: Nationally representative sample (n = 22,488) of college students completing the Fall 2008 National College Health Assessment. Methods: Hierarchical logistic regression was employed to…

Graduate Unemployment in South Africa: Social Inequality Reproduced

ERIC Educational Resources Information Center

Baldry, Kim

2016-01-01

In this study, I examine the influence of demographic and educational characteristics of South African graduates on their employment/unemployment status. A sample of 1175 respondents who graduated between 2006 and 2012 completed an online survey. Using binary logistic regression, the strongest determinants of unemployment were the graduates' race,…

Commitment of Licensed Social Workers to Aging Practice

ERIC Educational Resources Information Center

Simons, Kelsey; Bonifas, Robin; Gammonley, Denise

2011-01-01

This study sought to identify client, professional, and employment characteristics that enhance licensed social workers' commitment to aging practice. A series of binary logistic regressions were performed using data from 181 licensed, full-time social workers who reported aging as their primary specialty area as part of the 2004 NASW's national…

Prediction of siRNA potency using sparse logistic regression.

PubMed

Hu, Wei; Hu, John

2014-06-01

RNA interference (RNAi) can modulate gene expression at post-transcriptional as well as transcriptional levels. Short interfering RNA (siRNA) serves as a trigger for the RNAi gene inhibition mechanism, and therefore is a crucial intermediate step in RNAi. There have been extensive studies to identify the sequence characteristics of potent siRNAs. One such study built a linear model using LASSO (Least Absolute Shrinkage and Selection Operator) to measure the contribution of each siRNA sequence feature. This model is simple and interpretable, but it requires a large number of nonzero weights. We have introduced a novel technique, sparse logistic regression, to build a linear model using single-position specific nucleotide compositions which has the same prediction accuracy of the linear model based on LASSO. The weights in our new model share the same general trend as those in the previous model, but have only 25 nonzero weights out of a total 84 weights, a 54% reduction compared to the previous model. Contrary to the linear model based on LASSO, our model suggests that only a few positions are influential on the efficacy of the siRNA, which are the 5' and 3' ends and the seed region of siRNA sequences. We also employed sparse logistic regression to build a linear model using dual-position specific nucleotide compositions, a task LASSO is not able to accomplish well due to its high dimensional nature. Our results demonstrate the superiority of sparse logistic regression as a technique for both feature selection and regression over LASSO in the context of siRNA design.

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.

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.

Impact of maternal education, employment and family size on nutritional status of children.

PubMed

Iftikhar, Aisha; Bari, Attia; Bano, Iqbal; Masood, Qaisar

2017-01-01

To determine the impact of maternal education, employment, and family size on nutritional status of children. It was case control study conducted at OPD of children Hospital Lahore, from September 2015 to April 2017. Total 340 children (170 cases and 170 controls) with age range of six months to five years along with their mothers were included. Anthropometric measurements were plotted against WHO growth Charts. 170 wasted (<-2 SD) were matched with 170 controls (≥ -2 SD). Maternal education, employment and family size were compared between the cases and control. Confounding variables noted and dichotomized. Univariate analysis was carried out for factors under consideration i.e.; Maternal Education, employment and family size to study the association of each factor. Logistic regression analysis was applied to study the independent association. Maternal education had significant association with growth parameters; OR of 1.32 with confidence interval of (CI= 1.1 to 1.623). Employment status of mothers had OR of 1.132 with insignificant confidence interval of (CI=0.725 to 1.768). Family size had OR of one with insignificant confidence interval (CI=0.8 -1.21). Association remained same after applying bivariate logistic regression analysis. Maternal education has definite and significant effect on nutritional status of children. This is the key factor to be addressed for prevention or improvement of childhood malnutrition. For this it is imperative to launch sustainable programs at national and regional level to uplift women educational status to combat this ever increasing burden of malnutrition.

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

Foreign Diploma versus Immigrant Background: Determinants of Labour Market Success or Failure?

ERIC Educational Resources Information Center

Storen, Liv Anne; Wiers-Jenssen, Jannecke

2010-01-01

This article compares the labour market situation of graduates with different types of international background. The authors look at four groups of graduates: immigrants and ethnic Norwegians graduated in Norway and immigrants and ethnic Norwegians graduated abroad. By employing multinomial logistic regression analyses the authors find that ethnic…

Does the EDI Measure School Readiness in the Same Way across Different Groups of Children?

ERIC Educational Resources Information Center

Guhn, Martin; Gadermann, Anne; Zumbo, Bruno D.

2007-01-01

The present study investigates whether the Early Development Instrument (Offord & Janus, 1999) measures school readiness similarly across different groups of children. We employ ordinal logistic regression to investigate differential item functioning, a method of examining measurement bias. For 40,000 children, our analysis compares groups…

Music and Suicidality: A Quantitative Review and Extension

ERIC Educational Resources Information Center

Stack, Steven; Lester, David; Rosenberg, Jonathan S.

2012-01-01

This article provides the first quantitative review of the literature on music and suicidality. Multivariate logistic regression techniques are applied to 90 findings from 21 studies. Investigations employing ecological data on suicide completions are 19.2 times more apt than other studies to report a link between music and suicide. More recent…

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…

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…

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.

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

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

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.

A Multilevel Study of Students' Motivations of Studying Accounting: Implications for Employers

ERIC Educational Resources Information Center

Law, Philip; Yuen, Desmond

2012-01-01

Purpose: The purpose of this study is to examine the influence of factors affecting students' choice of accounting as a study major in Hong Kong. Design/methodology/approach: Multinomial logistic regression and Hierarchical Generalized Linear Modeling (HGLM) are used to analyze the survey data for the level one and level two data, which is the…

A Statewide Study of Gang Membership in California Secondary Schools

ERIC Educational Resources Information Center

Estrada, Joey Nuñez, Jr.; Gilreath, Tamika D.; Astor, Ron Avi; Benbenishty, Rami

2016-01-01

To date, there is a paucity of empirical evidence that examines gang membership in schools. Using statewide data of 7th-, 9th-, and 11th-grade students from California, this study focuses on the prevalence of gang membership by county, region, ethnicity, and grade level. Bivariate and multivariate logistic regression analyses were employed with…

The Effect of Postsecondary Coenrollment on College Success: Initial Evidence and Implications for Policy and Future Research

ERIC Educational Resources Information Center

Wang, Xueli; McCready, Bo

2013-01-01

Drawing upon the latest data from the Beginning Postsecondary Students Longitudinal Study (BPS:04/09) and the Postsecondary Education Transcript Data (PETS:09), this study employed propensity score matching and postmatching logistic regression to estimate the extent to which postsecondary coenrollment affects persistence and attainment of students…

So Close, yet So Far Away: Early vs. Late Dropouts

ERIC Educational Resources Information Center

Ma, Yanli; Cragg, Kristina M.

2013-01-01

While some students drop out early in their academic career, others drop out close to completion. What similarities and differences exist between these early and late dropouts? Using a sample 3,520 first-time, full-time (FTFT) students seeking a bachelor's degree at a state university, this study employs multinomial logistic regression to model…

The Relationship of Selected Supply- and Demand-Side Factors to Forms of Perceived Discrimination among Adults with Multiple Sclerosis

ERIC Educational Resources Information Center

Roessler, Richard T.; Neath, Jeanne; McMahon, Brian T.; Rumrill, Phillip D.

2007-01-01

Single-predictor and stepwise multinomial logistic regression analyses and an external validation were completed on 3,082 allegations of employment discrimination by adults with multiple sclerosis. Women filed two thirds of the allegations, and individuals between 31 and 50 made the vast majority of discrimination charges (73%). Allegations…

Resilience, Syndemic Factors, and Serosorting Behaviors among HIV-Positive and HIV-Negative Substance-Using MSM

ERIC Educational Resources Information Center

Kurtz, Steven P.; Buttram, Mance E.; Surratt, Hilary L.; Stall, Ronald D.

2012-01-01

Serosorting is commonly employed by MSM to reduce HIV risk. We hypothesize that MSM perceive serosorting to be effective, and that serosorting is predicted by resilience and inversely related to syndemic characteristics. Surveys included 504 substance-using MSM. Logistic regression models examined syndemic and resilience predictors of serosorting,…

High School Predictors of College Persistence: The Significance of Engagement and Teacher Interaction

ERIC Educational Resources Information Center

Sciarra, Daniel T.; Seirup, Holly J.; Sposato, Elizabeth

2016-01-01

This study investigated factors from high school that might predict college persistence. The sample consisted of 7,271 participants in three waves of data collection (2002, 2004 and 2006) who participated in the Educational Longitudinal Study (ELS; U.S. Department of Education, 2008). A multinomial logistic regression mode was employed to…

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.

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 effect of high leverage points on the logistic ridge regression estimator having multicollinearity

NASA Astrophysics Data System (ADS)

Ariffin, Syaiba Balqish; Midi, Habshah

2014-06-01

This article is concerned with the performance of logistic ridge regression estimation technique in the presence of multicollinearity and high leverage points. In logistic regression, multicollinearity exists among predictors and in the information matrix. The maximum likelihood estimator suffers a huge setback in the presence of multicollinearity which cause regression estimates to have unduly large standard errors. To remedy this problem, a logistic ridge regression estimator is put forward. It is evident that the logistic ridge regression estimator outperforms the maximum likelihood approach for handling multicollinearity. The effect of high leverage points are then investigated on the performance of the logistic ridge regression estimator through real data set and simulation study. The findings signify that logistic ridge regression estimator fails to provide better parameter estimates in the presence of both high leverage points and multicollinearity.

Education, Employment, Income, and Marital Status Among Adults Diagnosed With Inflammatory Bowel Diseases During Childhood or Adolescence.

PubMed

El-Matary, Wael; Dufault, Brenden; Moroz, Stan P; Schellenberg, Jeannine; Bernstein, Charles N

2017-04-01

We aimed to assess levels of education attained, employment, and marital status of adults diagnosed with inflammatory bowel diseases (IBD) during childhood or adolescence, compared with healthy individuals in Canada. We performed a cross-sectional study of adults diagnosed with IBD in childhood or adolescence at Children's Hospital in Winnipeg, Manitoba from January 1978 through December 2007. Participants (n = 112) answered a semi-structured questionnaire on educational achievements, employment, and marital status. Patients were matched for age and sex with random healthy individuals from the 2012 Canadian Community Health Survey (controls, 5 per patient). Conditional binary logistic regression and random-effects ordinal logistic regression models were used for analysis. Patients were followed for a mean duration of 14.3 years (range, 3.1-34.5 years). Persons with IBD were more likely to earn more money per annum and attain a post-secondary school degree or receive a diploma than controls (odds ratio, 1.72; 95% confidence interval, 1.13-2.60; P < .01 and odds ratio, 2.73; 95% confidence interval, 1.48-5.04; P < .01, respectively). There was no significant difference between patients and controls in employment or marital status. Adults diagnosed with IBD during childhood seem to achieve higher education levels than individuals without IBD. This observation should provide reassurance to children with IBD and their parents. ClinicalTrials.gov number: NCT02152241. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.

Employment and financial burden of families with preschool children diagnosed with autism spectrum disorders in urban China: results from a descriptive study.

PubMed

Ou, Jian-Jun; Shi, Li-Juan; Xun, Guang-Lei; Chen, Chen; Wu, Ren-Rong; Luo, Xue-Rong; Zhang, Feng-Yu; Zhao, Jing-Ping

2015-01-22

Autism spectrum disorder (ASD) affects many aspects of family life, such as social and economic burden. Little investigation of this phenomenon has been carried out in China. We designed this study to evaluate the employment and financial burdens of families with ASD-diagnosed preschoolers. Four hundred and fifty-nine nuclear families of children with ASD, 418 with some other disability (OD) and 424 with typically developing (TD) children were recruited for this study. Employment and financial burdens of families were evaluated using a structured questionnaire; logistic regression was used to examine differences in job change measures by group, and ordinal logistic regression was used to investigate the association between household income and group. Fifty-eight percent of families with ASD children and 19% of families with OD children reported that childcare problems had greatly affected their employment decisions, compared with 9% of families with TD children (p < 0.001). Age of child, parental education and parental age notwithstanding, having a child with ASD and having a child with OD were both associated with increased odds of reporting that childcare greatly interfered with employment (ASD, OR: 15.936; OD, OR: 2.502; all p < 0.001) and decreased the odds of living in a higher-income household (ASD, estimate = -1.271; OD, estimate = -0.569; all p < 0.001). The average loss of annual income associated with having a child with ASD was Chinese RenMinBi (RMB) 44,077 ($7,226), compared with RMB 20,788 ($3,408) for families of OD children. ASD is associated with severe employment and financial burdens, much more than for OD, in families with preschool children.

Association between family structure, maternal education level, and maternal employment with sedentary lifestyle in primary school-age children.

PubMed

Vázquez-Nava, Francisco; Treviño-Garcia-Manzo, Norberto; Vázquez-Rodríguez, Carlos F; Vázquez-Rodríguez, Eliza M

2013-01-01

To determine the association between family structure, maternal education level, and maternal employment with sedentary lifestyle in primary school-age children. Data were obtained from 897 children aged 6 to 12 years. A questionnaire was used to collect information. Body mass index (BMI) was determined using the age- and gender-specific Centers for Disease Control and Prevention definition. Children were categorized as: normal weight (5(th) percentile≤BMI<85(th) percentile), at risk for overweight (85(th)≤BMI<95(th) percentile), overweight (≥ 95(th) percentile). For the analysis, overweight was defined as BMI at or above the 85(th) percentile for each gender. Adjusted odds ratios (adjusted ORs) for physical inactivity were determined using a logistic regression model. The prevalence of overweight was 40.7%, and of sedentary lifestyle, 57.2%. The percentage of non-intact families was 23.5%. Approximately 48.7% of the mothers had a non-acceptable educational level, and 38.8% of the mothers worked outside of the home. The logistic regression model showed that living in a non-intact family household (adjusted OR=1.67; 95% CI=1.04-2.66) is associated with sedentary lifestyle in overweight children. In the group of normal weight children, logistic regression analysis show that living in a non-intact family, having a mother with a non-acceptable education level, and having a mother who works outside of the home were not associated with sedentary lifestyle. Living in a non-intact family, more than low maternal educational level and having a working mother, appears to be associated with sedentary lifestyle in overweight primary school-age children. Copyright © 2013 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

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

PubMed

Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance

2017-06-01

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

A comparison of Cox and logistic regression for use in genome-wide association studies of cohort and case-cohort design.

PubMed

Staley, James R; Jones, Edmund; Kaptoge, Stephen; Butterworth, Adam S; Sweeting, Michael J; Wood, Angela M; Howson, Joanna M M

2017-06-01

Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort designs, as it is less computationally expensive. Although Cox and logistic regression models have been compared previously in cohort studies, this work does not completely cover the GWAS setting nor extend to the case-cohort study design. Here, we evaluated Cox and logistic regression applied to cohort and case-cohort genetic association studies using simulated data and genetic data from the EPIC-CVD study. In the cohort setting, there was a modest improvement in power to detect SNP-disease associations using Cox regression compared with logistic regression, which increased as the disease incidence increased. In contrast, logistic regression had more power than (Prentice weighted) Cox regression in the case-cohort setting. Logistic regression yielded inflated effect estimates (assuming the hazard ratio is the underlying measure of association) for both study designs, especially for SNPs with greater effect on disease. Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies. First to analyse all SNPs with logistic regression to identify associated variants below a pre-defined P-value threshold, and second to fit Cox regression (appropriately weighted in case-cohort studies) to those identified SNPs to ensure accurate estimation of association with disease.

Exploring Individual and Structural Factors Associated with Employment Among Young Transgender Women of Color Using a No-Cost Transgender Legal Resource Center.

PubMed

Hill, Brandon J; Rosentel, Kris; Bak, Trevor; Silverman, Michael; Crosby, Richard; Salazar, Laura; Kipke, Michele

2017-01-01

The purpose of this study was to explore individual and structural factors associated with employment among young transgender women (TW) of color. Sixty-five trans women of color were recruited from the Transgender Legal Defense and Education Fund to complete a 30-min interviewer-assisted survey assessing sociodemographics, housing, workplace discrimination, job-seeking self-efficacy, self-esteem, perceived public passability, and transactional sex work. Logistic regression models revealed that stable housing (structural factor) and job-seeking self-efficacy (individual factor) were significantly associated with currently being employed. Our findings underscore the need for multilevel approaches to assist TW of color gain employment.

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.

The crux of the method: assumptions in ordinary least squares and logistic regression.

PubMed

Long, Rebecca G

2008-10-01

Logistic regression has increasingly become the tool of choice when analyzing data with a binary dependent variable. While resources relating to the technique are widely available, clear discussions of why logistic regression should be used in place of ordinary least squares regression are difficult to find. The current paper compares and contrasts the assumptions of ordinary least squares with those of logistic regression and explains why logistic regression's looser assumptions make it adept at handling violations of the more important assumptions in ordinary least squares.

Overloading among crash-involved vehicles in China: identification of factors associated with overloading and crash severity.

PubMed

Zhang, Guangnan; Li, Yanyan; King, Mark J; Zhong, Qiaoting

2018-03-21

Motor vehicle overloading is correlated with the possibility of road crash occurrence and severity. Although overloading of motor vehicles is pervasive in developing nations, few empirical analyses have been performed on factors that might influence the occurrence of overloading. This study aims to address this shortcoming by seeking evidence from several years of crash data from Guangdong province, China. Data on overloading and other factors are extracted for crash-involved vehicles from traffic crash records for 2006-2010 provided by the Traffic Management Bureau in Guangdong province. Logistic regression is applied to identify risk factors for overloading in crash-involved vehicles and within these crashes to identify factors contributing to greater crash severity. Driver, vehicle, road and environmental characteristics and violation types are considered in the regression models. In addition to the basic logistic models, association analysis is employed to identify the potential interactions among different risk factors during fitting the logistic models of overloading and severity. Crash-involved vehicles driven by males from rural households and in an unsafe condition are more likely to be overloaded and to be involved in higher severity overloaded vehicle crashes. If overloaded vehicles speed, the risk of severe traffic crash casualties increases. Young drivers (aged under 25 years) in mountainous areas are more likely to be involved in higher severity overloaded vehicle crashes. This study identifies several factors associated with overloading in crash-involved vehicles and with higher severity overloading crashes and provides an important reference for future research on those specific risk factors. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Using Dominance Analysis to Determine Predictor Importance in Logistic Regression

ERIC Educational Resources Information Center

Azen, Razia; Traxel, Nicole

2009-01-01

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

An Attempt at Quantifying Factors that Affect Efficiency in the Management of Solid Waste Produced by Commercial Businesses in the City of Tshwane, South Africa

PubMed Central

Worku, Yohannes; Muchie, Mammo

2012-01-01

Objective. The objective was to investigate factors that affect the efficient management of solid waste produced by commercial businesses operating in the city of Pretoria, South Africa. Methods. Data was gathered from 1,034 businesses. Efficiency in solid waste management was assessed by using a structural time-based model designed for evaluating efficiency as a function of the length of time required to manage waste. Data analysis was performed using statistical procedures such as frequency tables, Pearson's chi-square tests of association, and binary logistic regression analysis. Odds ratios estimated from logistic regression analysis were used for identifying key factors that affect efficiency in the proper disposal of waste. Results. The study showed that 857 of the 1,034 businesses selected for the study (83%) were found to be efficient enough with regards to the proper collection and disposal of solid waste. Based on odds ratios estimated from binary logistic regression analysis, efficiency in the proper management of solid waste was significantly influenced by 4 predictor variables. These 4 influential predictor variables are lack of adherence to waste management regulations, wrong perception, failure to provide customers with enough trash cans, and operation of businesses by employed managers, in a decreasing order of importance. PMID:23209483

The Effect of Participating in Indiana's Twenty-First Century Scholars Program on College Enrollments

ERIC Educational Resources Information Center

Toutkoushian, Robert K.; Hossler, Don; DesJardins, Stephen L.; McCall, Brian; Gonzalez Canche, Manuel S.

2015-01-01

Our study adds to prior work on Indiana's Twenty-first Century Scholars(TFCS) program by focusing on whether participating in--rather than completing--the program affects the likelihood of students going to college and where they initially enrolled. We first employ binary and multinomial logistic regression to obtain estimates of the impact of the…

Applying Kaplan-Meier to Item Response Data

ERIC Educational Resources Information Center

McNeish, Daniel

2018-01-01

Some IRT models can be equivalently modeled in alternative frameworks such as logistic regression. Logistic regression can also model time-to-event data, which concerns the probability of an event occurring over time. Using the relation between time-to-event models and logistic regression and the relation between logistic regression and IRT, this…

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.

An Alternative Flight Software Trigger Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions Using Inaccurate or Scarce Information

NASA Technical Reports Server (NTRS)

Smith, Kelly M.; Gay, Robert S.; Stachowiak, Susan J.

2013-01-01

In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles.

An Alternative Flight Software Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions using Inaccurate or Scarce Information

NASA Technical Reports Server (NTRS)

Smith, Kelly; Gay, Robert; Stachowiak, Susan

2013-01-01

In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles

An Alternative Flight Software Trigger Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions using Inaccurate or Scarce Information

NASA Technical Reports Server (NTRS)

Smith, Kelly M.; Gay, Robert S.; Stachowiak, Susan J.

2013-01-01

In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter. In order to increase overall robustness, the vehicle also has an alternate method of triggering the drogue parachute deployment based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this velocity-based trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers excellent performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles.

Discriminating between adaptive and carcinogenic liver hypertrophy in rat studies using logistic ridge regression analysis of toxicogenomic data: The mode of action and predictive models.

PubMed

Liu, Shujie; Kawamoto, Taisuke; Morita, Osamu; Yoshinari, Kouichi; Honda, Hiroshi

2017-03-01

Chemical exposure often results in liver hypertrophy in animal tests, characterized by increased liver weight, hepatocellular hypertrophy, and/or cell proliferation. While most of these changes are considered adaptive responses, there is concern that they may be associated with carcinogenesis. In this study, we have employed a toxicogenomic approach using a logistic ridge regression model to identify genes responsible for liver hypertrophy and hypertrophic hepatocarcinogenesis and to develop a predictive model for assessing hypertrophy-inducing compounds. Logistic regression models have previously been used in the quantification of epidemiological risk factors. DNA microarray data from the Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System were used to identify hypertrophy-related genes that are expressed differently in hypertrophy induced by carcinogens and non-carcinogens. Data were collected for 134 chemicals (72 non-hypertrophy-inducing chemicals, 27 hypertrophy-inducing non-carcinogenic chemicals, and 15 hypertrophy-inducing carcinogenic compounds). After applying logistic ridge regression analysis, 35 genes for liver hypertrophy (e.g., Acot1 and Abcc3) and 13 genes for hypertrophic hepatocarcinogenesis (e.g., Asns and Gpx2) were selected. The predictive models built using these genes were 94.8% and 82.7% accurate, respectively. Pathway analysis of the genes indicates that, aside from a xenobiotic metabolism-related pathway as an adaptive response for liver hypertrophy, amino acid biosynthesis and oxidative responses appear to be involved in hypertrophic hepatocarcinogenesis. Early detection and toxicogenomic characterization of liver hypertrophy using our models may be useful for predicting carcinogenesis. In addition, the identified genes provide novel insight into discrimination between adverse hypertrophy associated with carcinogenesis and adaptive hypertrophy in risk assessment. Copyright © 2017 Elsevier Inc. All rights reserved.

Working women making it work: intimate partner violence, employment, and workplace support.

PubMed

Swanberg, Jennifer; Macke, Caroline; Logan, T K

2007-03-01

Partner violence may have significant consequences on women's employment, yet limited information is available about how women cope on the job with perpetrators' tactics and the consequences of her coping methods on employment status. This article investigates whether there is an association between workplace disclosure of victimization and current employment status; and whether there is an association between receiving workplace support and current employment status among women who disclosed victimization circumstances to someone at work. Using a sample of partner victimized women who were employed within the past year (N = 485), cross-tabulation and ANOVA procedures were conducted to examine the differences between currently employed and unemployed women. Binary logistic regressions were conducted to examine whether disclosure and receiving workplace support were significantly associated with current employment. Results indicate that disclosure and workplace support are associated with employment. Implications for clinical practice, workplace policies, and future research are discussed.

Binary logistic regression modelling: Measuring the probability of relapse cases among drug addict

NASA Astrophysics Data System (ADS)

Ismail, Mohd Tahir; Alias, Siti Nor Shadila

2014-07-01

For many years Malaysia faced the drug addiction issues. The most serious case is relapse phenomenon among treated drug addict (drug addict who have under gone the rehabilitation programme at Narcotic Addiction Rehabilitation Centre, PUSPEN). Thus, the main objective of this study is to find the most significant factor that contributes to relapse to happen. The binary logistic regression analysis was employed to model the relationship between independent variables (predictors) and dependent variable. The dependent variable is the status of the drug addict either relapse, (Yes coded as 1) or not, (No coded as 0). Meanwhile the predictors involved are age, age at first taking drug, family history, education level, family crisis, community support and self motivation. The total of the sample is 200 which the data are provided by AADK (National Antidrug Agency). The finding of the study revealed that age and self motivation are statistically significant towards the relapse cases..

Cancer prevalence and education by cancer site: logistic regression analysis.

PubMed

Johnson, Stephanie; Corsten, Martin J; McDonald, James T; Gupta, Michael

2010-10-01

Previously, using the American National Health Interview Survey (NHIS) and a logistic regression analysis, we found that upper aerodigestive tract (UADT) cancer is correlated with low socioeconomic status (SES). The objective of this study was to determine if this correlation between low SES and cancer prevalence exists for other cancers. We again used the NHIS and employed education level as our main measure of SES. We controlled for potentially confounding factors, including smoking status and alcohol consumption. We found that only two cancer subsites shared the pattern of increased prevalence with low education level and decreased prevalence with high education level: UADT cancer and cervical cancer. UADT cancer and cervical cancer were the only two cancers identified that had a link between prevalence and lower education level. This raises the possibility that an associated risk factor for the two cancers is causing the relationship between lower education level and prevalence.

Exploring Individual and Structural Factors Associated with Employment Among Young Transgender Women of Color Using a No-Cost Transgender Legal Resource Center

PubMed Central

Hill, Brandon J.; Rosentel, Kris; Bak, Trevor; Silverman, Michael; Crosby, Richard; Salazar, Laura; Kipke, Michele

2017-01-01

Abstract Purpose: The purpose of this study was to explore individual and structural factors associated with employment among young transgender women (TW) of color. Methods: Sixty-five trans women of color were recruited from the Transgender Legal Defense and Education Fund to complete a 30-min interviewer-assisted survey assessing sociodemographics, housing, workplace discrimination, job-seeking self-efficacy, self-esteem, perceived public passability, and transactional sex work. Results: Logistic regression models revealed that stable housing (structural factor) and job-seeking self-efficacy (individual factor) were significantly associated with currently being employed. Conclusion: Our findings underscore the need for multilevel approaches to assist TW of color gain employment. PMID:28795154

Discriminating between adaptive and carcinogenic liver hypertrophy in rat studies using logistic ridge regression analysis of toxicogenomic data: The mode of action and predictive models

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

Liu, Shujie; Kawamoto, Taisuke; Morita, Osamu

Chemical exposure often results in liver hypertrophy in animal tests, characterized by increased liver weight, hepatocellular hypertrophy, and/or cell proliferation. While most of these changes are considered adaptive responses, there is concern that they may be associated with carcinogenesis. In this study, we have employed a toxicogenomic approach using a logistic ridge regression model to identify genes responsible for liver hypertrophy and hypertrophic hepatocarcinogenesis and to develop a predictive model for assessing hypertrophy-inducing compounds. Logistic regression models have previously been used in the quantification of epidemiological risk factors. DNA microarray data from the Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System weremore » used to identify hypertrophy-related genes that are expressed differently in hypertrophy induced by carcinogens and non-carcinogens. Data were collected for 134 chemicals (72 non-hypertrophy-inducing chemicals, 27 hypertrophy-inducing non-carcinogenic chemicals, and 15 hypertrophy-inducing carcinogenic compounds). After applying logistic ridge regression analysis, 35 genes for liver hypertrophy (e.g., Acot1 and Abcc3) and 13 genes for hypertrophic hepatocarcinogenesis (e.g., Asns and Gpx2) were selected. The predictive models built using these genes were 94.8% and 82.7% accurate, respectively. Pathway analysis of the genes indicates that, aside from a xenobiotic metabolism-related pathway as an adaptive response for liver hypertrophy, amino acid biosynthesis and oxidative responses appear to be involved in hypertrophic hepatocarcinogenesis. Early detection and toxicogenomic characterization of liver hypertrophy using our models may be useful for predicting carcinogenesis. In addition, the identified genes provide novel insight into discrimination between adverse hypertrophy associated with carcinogenesis and adaptive hypertrophy in risk assessment. - Highlights: • Hypertrophy (H) and hypertrophic carcinogenesis (C) were studied by toxicogenomics. • Important genes for H and C were selected by logistic ridge regression analysis. • Amino acid biosynthesis and oxidative responses may be involved in C. • Predictive models for H and C provided 94.8% and 82.7% accuracy, respectively. • The identified genes could be useful for assessment of liver hypertrophy.« less

Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

NASA Astrophysics Data System (ADS)

Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun

2014-12-01

Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.

Do Basic Skills Predict Youth Unemployment (16- to 24-Year-Olds) Also when Controlled for Accomplished Upper-Secondary School? A Cross-Country Comparison

ERIC Educational Resources Information Center

Lundetrae, Kjersti; Gabrielsen, Egil; Mykletun, Reidar

2010-01-01

Basic skills and educational level are closely related, and both might affect employment. Data from the Adult Literacy and Life Skills Survey were used to examine whether basic skills in terms of literacy and numeracy predicted youth unemployment (16-24 years) while controlling for educational level. Stepwise logistic regression showed that in…

Gender, Alcohol Consumption Patterns, and Engagement in Sexually Intimate Behaviors among Adolescents and Young Adults in Nha Trang, Viet Nam

ERIC Educational Resources Information Center

Kaljee, Linda M.; Green, Mackenzie S.; Zhan, Min; Riel, Rosemary; Lerdboon, Porntip; Lostutter, Ty W.; Tho, Le Huu; Luong, Vo Van; Minh, Truong Tan

2011-01-01

A randomly selected cross-sectional survey was conducted with 880 youth (16 to 24 years) in Nha Trang City to assess relationships between alcohol consumption and sexual behaviors. A timeline followback method was employed. Chi-square, generalized logit modeling and logistic regression analyses were performed. Of the sample, 78.2% male and 56.1%…

Determinants of Increasing Duration of First Unemployment among First Degree Holders in Rwanda: A Logistic Regression Analysis

ERIC Educational Resources Information Center

Niragire, François; Nshimyiryo, Alphonse

2017-01-01

Unexpectedly, the duration of first unemployment among first degree holders has quickly increased in Rwanda after considerable loss of the skilled labour during the war and Genocide perpetrated against Tutsi in 1994. The time it takes a higher education graduate to land a first employment is a key indicator for the evaluation of and optimal…

Factors Affecting Employment Among Informal Caregivers Assisting People with Multiple Sclerosis

PubMed Central

Huang, Chunfeng; Zheng, Zhida

2013-01-01

The objective of this study was to identify characteristics of informal caregivers, caregiving, and the people with multiple sclerosis (MS) receiving assistance that are associated with reduced caregiver employment. Data were collected during telephone interviews with 530 MS caregivers, including 215 employed caregivers, with these survey data analyzed using logistic regression. Poorer cognitive ability by the care recipient to make decisions about daily tasks and more caregiving hours per week predicted reduced caregiver employment. Better physical health domains of caregiver quality of life were associated with significantly lower odds of reduced employment. Health professionals treating informal caregivers, as well as those treating people with MS, need to be aware of respite, support, and intervention programs available to MS caregivers and refer them to these programs, which could reduce the negative impact of caregiving on employment. PMID:24453784

Climate change, weather and road deaths.

PubMed

Robertson, Leon

2018-06-01

In 2015, a 7% increase in road deaths per population in the USA reversed the 35-year downward trend. Here I test the hypothesis that weather influenced the change in trend. I used linear regression to estimate the effect of temperature and precipitation on miles driven per capita in urbanizedurbanised areas of the USA during 2010. I matched date and county of death with temperature on that date and number of people exposed to that temperature to calculate the risk per persons exposed to specific temperatures. I employed logistic regression analysis of temperature, precipitation and other risk factors prevalent in 2014 to project expected deaths in 2015 among the 100 most populous counties in the USA. Comparison of actual and projected deaths provided an estimate of deaths expected without the temperature increase. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Risk factors for amendment in type, duration and setting of prescribed outpatient parenteral antimicrobial therapy (OPAT) for adult patients with cellulitis: a retrospective cohort study and CART analysis.

PubMed

Quirke, Michael; Curran, Emma May; O'Kelly, Patrick; Moran, Ruth; Daly, Eimear; Aylward, Seamus; McElvaney, Gerry; Wakai, Abel

2018-01-01

To measure the percentage rate and risk factors for amendment in the type, duration and setting of outpatient parenteral antimicrobial therapy ( OPAT) for the treatment of cellulitis. A retrospective cohort study of adult patients receiving OPAT for cellulitis was performed. Treatment amendment (TA) was defined as hospital admission or change in antibiotic therapy in order to achieve clinical response. Multivariable logistic regression (MVLR) and classification and regression tree (CART) analysis were performed. There were 307 patients enrolled. TA occurred in 36 patients (11.7%). Significant risk factors for TA on MVLR were increased age, increased Numerical Pain Scale Score (NPSS) and immunocompromise. The median OPAT duration was 7 days. Increased age, heart rate and C reactive protein were associated with treatment prolongation. CART analysis selected age <64.5 years, female gender and NPSS <2.5 in the final model, generating a low-sensitivity (27.8%), high-specificity (97.1%) decision tree. Increased age, NPSS and immunocompromise were associated with OPAT amendment. These identified risk factors can be used to support an evidence-based approach to patient selection for OPAT in cellulitis. The CART algorithm has good specificity but lacks sensitivity and is shown to be inferior in this study to logistic regression modelling. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

BINGE DRINKING, SMOKING AND MARIJUANA USE: THE ROLE OF WOMEN's LABOR FORCE PARTICIPATION.

PubMed

Cunradi, Carol B; Ames, Genevieve M; Xiao, Hong

2014-01-01

This study analyzed the role of women's labor force participation in relation to binge drinking, smoking and marijuana use among employment age married/cohabiting women. The sample consisted of 956 women who were employed as construction workers (n=104), or were unemployed (n=101), homemakers (n=227) or employed in non-physically demanding occupations (n=524). Results of multivariate logistic regression analyses showed that women construction workers were at elevated risk for smoking and monthly binge drinking; unemployed women were more likely to use marijuana. Women in both categories were at risk for polysubstance use. Additional research is needed to explicate how labor force participation influences women's substance use.

Who Gets Promoted? Gender Differences in Science and Engineering Academia

NASA Astrophysics Data System (ADS)

Olson, Kristen

Using a nationally representative sample of doctoral academic scientists and engineers, this study examines gender differences in the likelihood of having tenure and senior faculty ranks after controlling for academic age, field, doctoral origins, employing educational institution, productivity, postdoctoral positions, work activities, and family characteristics. Logistic regressions show that many of these controls are significant; that biology and employment at comprehensive universities have a gender-specific advantage for women; and that postdoctoral positions, teaching instead of doing administrative work, and having children have a gender-specific disadvantage. Although the statistical methods employed here do not reveal the exact nature of how gender inequities in science and engineering careers arise, the author suggests that they exist.

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

PubMed

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

2015-06-01

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

Standards for Standardized Logistic Regression Coefficients

ERIC Educational Resources Information Center

Menard, Scott

2011-01-01

Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

A Bayesian goodness of fit test and semiparametric generalization of logistic regression with measurement data.

PubMed

Schörgendorfer, Angela; Branscum, Adam J; Hanson, Timothy E

2013-06-01

Logistic regression is a popular tool for risk analysis in medical and population health science. With continuous response data, it is common to create a dichotomous outcome for logistic regression analysis by specifying a threshold for positivity. Fitting a linear regression to the nondichotomized response variable assuming a logistic sampling model for the data has been empirically shown to yield more efficient estimates of odds ratios than ordinary logistic regression of the dichotomized endpoint. We illustrate that risk inference is not robust to departures from the parametric logistic distribution. Moreover, the model assumption of proportional odds is generally not satisfied when the condition of a logistic distribution for the data is violated, leading to biased inference from a parametric logistic analysis. We develop novel Bayesian semiparametric methodology for testing goodness of fit of parametric logistic regression with continuous measurement data. The testing procedures hold for any cutoff threshold and our approach simultaneously provides the ability to perform semiparametric risk estimation. Bayes factors are calculated using the Savage-Dickey ratio for testing the null hypothesis of logistic regression versus a semiparametric generalization. We propose a fully Bayesian and a computationally efficient empirical Bayesian approach to testing, and we present methods for semiparametric estimation of risks, relative risks, and odds ratios when parametric logistic regression fails. Theoretical results establish the consistency of the empirical Bayes test. Results from simulated data show that the proposed approach provides accurate inference irrespective of whether parametric assumptions hold or not. Evaluation of risk factors for obesity shows that different inferences are derived from an analysis of a real data set when deviations from a logistic distribution are permissible in a flexible semiparametric framework. © 2013, The International Biometric Society.

Propensity score estimation: machine learning and classification methods as alternatives to logistic regression

PubMed Central

Westreich, Daniel; Lessler, Justin; Funk, Michele Jonsson

2010-01-01

Summary Objective Propensity scores for the analysis of observational data are typically estimated using logistic regression. Our objective in this Review was to assess machine learning alternatives to logistic regression which may accomplish the same goals but with fewer assumptions or greater accuracy. Study Design and Setting We identified alternative methods for propensity score estimation and/or classification from the public health, biostatistics, discrete mathematics, and computer science literature, and evaluated these algorithms for applicability to the problem of propensity score estimation, potential advantages over logistic regression, and ease of use. Results We identified four techniques as alternatives to logistic regression: neural networks, support vector machines, decision trees (CART), and meta-classifiers (in particular, boosting). Conclusion While the assumptions of logistic regression are well understood, those assumptions are frequently ignored. All four alternatives have advantages and disadvantages compared with logistic regression. Boosting (meta-classifiers) and to a lesser extent decision trees (particularly CART) appear to be most promising for use in the context of propensity score analysis, but extensive simulation studies are needed to establish their utility in practice. PMID:20630332

Robust mislabel logistic regression without modeling mislabel probabilities.

PubMed

Hung, Hung; Jou, Zhi-Yu; Huang, Su-Yun

2018-03-01

Logistic regression is among the most widely used statistical methods for linear discriminant analysis. In many applications, we only observe possibly mislabeled responses. Fitting a conventional logistic regression can then lead to biased estimation. One common resolution is to fit a mislabel logistic regression model, which takes into consideration of mislabeled responses. Another common method is to adopt a robust M-estimation by down-weighting suspected instances. In this work, we propose a new robust mislabel logistic regression based on γ-divergence. Our proposal possesses two advantageous features: (1) It does not need to model the mislabel probabilities. (2) The minimum γ-divergence estimation leads to a weighted estimating equation without the need to include any bias correction term, that is, it is automatically bias-corrected. These features make the proposed γ-logistic regression more robust in model fitting and more intuitive for model interpretation through a simple weighting scheme. Our method is also easy to implement, and two types of algorithms are included. Simulation studies and the Pima data application are presented to demonstrate the performance of γ-logistic regression. © 2017, The International Biometric Society.

Fungible weights in logistic regression.

PubMed

Jones, Jeff A; Waller, Niels G

2016-06-01

In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression.

PubMed

Westreich, Daniel; Lessler, Justin; Funk, Michele Jonsson

2010-08-01

Propensity scores for the analysis of observational data are typically estimated using logistic regression. Our objective in this review was to assess machine learning alternatives to logistic regression, which may accomplish the same goals but with fewer assumptions or greater accuracy. We identified alternative methods for propensity score estimation and/or classification from the public health, biostatistics, discrete mathematics, and computer science literature, and evaluated these algorithms for applicability to the problem of propensity score estimation, potential advantages over logistic regression, and ease of use. We identified four techniques as alternatives to logistic regression: neural networks, support vector machines, decision trees (classification and regression trees [CART]), and meta-classifiers (in particular, boosting). Although the assumptions of logistic regression are well understood, those assumptions are frequently ignored. All four alternatives have advantages and disadvantages compared with logistic regression. Boosting (meta-classifiers) and, to a lesser extent, decision trees (particularly CART), appear to be most promising for use in the context of propensity score analysis, but extensive simulation studies are needed to establish their utility in practice. Copyright (c) 2010 Elsevier Inc. All rights reserved.

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.

Employment Barriers Among Welfare Recipients and Applicants With Chronically Ill Children

PubMed Central

Smith, Lauren A.; Romero, Diana; Wood, Pamela R.; Wampler, Nina S.; Chavkin, Wendy; Wise, Paul H.

2002-01-01

Objectives. This study evaluated the association of chronic child illness with parental employment among individuals who have had contact with the welfare system. Methods. Parents of children with chronic illnesses were interviewed. Results. Current and former welfare recipients and welfare applicants were more likely than those with no contact with the welfare system to report that their children’s illnesses adversely affected their employment. Logistic regression analyses showed that current and former receipt of welfare, pending welfare application, and high rates of child health care use were predictors of unemployment. Conclusions. Welfare recipients and applicants with chronically ill children face substantial barriers to employment, including high child health care use rates and missed work. The welfare reform reauthorization scheduled to occur later in 2002 should address the implications of chronic child illness for parental employment. PMID:12197972

Difficulties of care-work reconciliation: employed and nonemployed mothers of children with intellectual disability.

PubMed

Chou, Yueh-Ching; Fu, Li-Yeh; Pu, Cheng-Yun; Chang, Heng-Hao

2012-09-01

Whether employed and nonemployed mothers of children with intellectual disability (ID) have different experiences with reconciliation between care and work has rarely been explored. A survey was conducted in a county in Taiwan and 487 mothers aged younger than 65 and having a child with ID were interviewed face to face at their homes to explore whether there are different factors related to the reconciliation between care and work among employed and nonemployed mothers. Except for the common ground of mothers' health and care demands, logistic regression revealed work flexibility and care support were important for employed mothers. In contrast, the success of reconciliation for nonemployed mothers was determined by their individual characteristics (i.e., age, marital status, family income). Reconciliation policies for mothers with different employment statuses need to use different strategies.

'Many people know the law, but also many people violate it': discrimination experienced by people living with HIV/AIDS in Vietnam--results of a national study.

PubMed

Messersmith, Lisa J; Semrau, Katherine; Hammett, Theodore M; Phong, Nguyen Tuan; Tung, Nguyen Duy; Nguyen, Ha; Glandon, Douglas; Huong, Nguyen Mai; Anh, Hoang Tu

2013-01-01

In Vietnam, discrimination against people living with HIV/AIDS (PLHIV) is defined within and prohibited by the 2007 national HIV/AIDS law. Despite the law, PLHIV face discrimination in health care, employment, education and other spheres. This study presents the first national estimates of the levels and types of discrimination that are defined in Vietnamese law and experienced by PLHIV in Vietnam. A nationally representative sample of 1200 PLHIV was surveyed, and 129 PLHIV participated in focus group discussions (FGDs). In the last 12 months, nearly half of the survey population experienced at least one form of discrimination and many experienced up to six different types of discrimination. The most common forms of discrimination included disclosure of HIV status without consent; denial of access to education for children; loss of employment; advice, primarily from health care providers, to abstain from sex; and physical and emotional harm. In logistic regression analysis, the experience of discrimination differed by gender, region of residence and membership status in a PLHIV support group. The logistic regression and FGD results indicate that disclosure of HIV status without consent was associated with experiencing other forms of discrimination. Key programme and policy recommendations are discussed.

Should metacognition be measured by logistic regression?

PubMed

Rausch, Manuel; Zehetleitner, Michael

2017-03-01

Are logistic regression slopes suitable to quantify metacognitive sensitivity, i.e. the efficiency with which subjective reports differentiate between correct and incorrect task responses? We analytically show that logistic regression slopes are independent from rating criteria in one specific model of metacognition, which assumes (i) that rating decisions are based on sensory evidence generated independently of the sensory evidence used for primary task responses and (ii) that the distributions of evidence are logistic. Given a hierarchical model of metacognition, logistic regression slopes depend on rating criteria. According to all considered models, regression slopes depend on the primary task criterion. A reanalysis of previous data revealed that massive numbers of trials are required to distinguish between hierarchical and independent models with tolerable accuracy. It is argued that researchers who wish to use logistic regression as measure of metacognitive sensitivity need to control the primary task criterion and rating criteria. Copyright © 2017 Elsevier Inc. All rights reserved.

Presenteeism among self-employed workers: Korean working conditions survey.

PubMed

Kim, Min-Su; Park, Jae Bum; Min, Kyoung-Bok; Lee, Kyung-Jong; Kwon, Kimin

2014-01-01

Presenteeism has become a public concern recently. Thus, we aimed to understand the relationship between self-employed workers and presenteeism using a nationally representative sample of Korean workers. Using data from the Korean Working Conditions Survey conducted in 2011, a total of 43,392 workers including paid employees and self-employed workers were analyzed. The effect of employment status on presenteeism was analyzed using logistic regression analysis. The independent variables were socioeconomic characteristics, working conditions, and working environments. Among the 43,392 workers, 34,783 were paid and 8,609 were self-employed. Self-employed workers were more likely to exhibit presenteeism than were paid workers. An elevated odds ratio of 1.27 (95% CI 1.19-1.36) was found for presenteeism among self-employed workers. Being self-employed was significantly related with exhibiting presenteeism. Additional research should investigate whether other factors mediate the relationship between employment status and presenteeism as well as ways to reduce presenteeism among self-employed workers.

A Longitudinal Study of Work After Retirement: Examining Predictors of Bridge Employment, Continued Career Employment, and Retirement.

PubMed

Bennett, Misty M; Beehr, Terry A; Lepisto, Lawrence R

2016-09-01

Older employees are increasingly accepting bridge employment, which occurs when older workers take employment for pay after they retire from their main career. This study examined predictors of workers' decisions to engage in bridge employment versus full retirement and career employment. A national sample of 482 older people in the United States was surveyed regarding various work-related and nonwork related predictors of retirement decisions, and their retirement status was measured 5 years later. In bivariate analyses, both work-related variables (career goal achievement and experienced pressure to retire) and nonwork-related variables (psychological distress and traditional gender role orientation) predicted taking bridge employment, but in multinomial logistic regression, only nonwork variables had unique effects. Few predictors differentiated the bridge employed and fully retired groups. Nonwork variables were salient in making the decision to retire, and bridge employment may be conceptually more similar to full retirement than to career employment. © The Author(s) 2016.

Cognitive and Social Functioning Correlates of Employment Among People with Severe Mental Illness.

PubMed

Saavedra, Javier; López, Marcelino; González, Sergio; Arias, Samuel; Crawford, Paul

2016-10-01

We assess how social and cognitive functioning is associated to gaining employment for 213 people diagnosed with severe mental illness taking part in employment programs in Andalusia (Spain). We used the Repeatable Battery for the Assessment of Neuropsychological Status and the Social Functioning Scale and conducted two binary logistical regression analyses. Response variables were: having a job or not, in ordinary companies (OCs) and social enterprises, and working in an OC or not. There were two variables with significant adjusted odds ratios for having a job: "attention" and "Educational level". There were five variables with significant odds ratios for having a job in an OC: "Sex", "Educational level", "Attention", "Communication", and "Independence-competence". The study looks at the possible benefits of combining employment with support and social enterprises in employment programs for these people and underlines how both social and cognitive functioning are central to developing employment models.

London Measure of Unplanned Pregnancy: guidance for its use as an outcome measure

PubMed Central

Hall, Jennifer A; Barrett, Geraldine; Copas, Andrew; Stephenson, Judith

2017-01-01

Background The London Measure of Unplanned Pregnancy (LMUP) is a psychometrically validated measure of the degree of intention of a current or recent pregnancy. The LMUP is increasingly being used worldwide, and can be used to evaluate family planning or preconception care programs. However, beyond recommending the use of the full LMUP scale, there is no published guidance on how to use the LMUP as an outcome measure. Ordinal logistic regression has been recommended informally, but studies published to date have all used binary logistic regression and dichotomized the scale at different cut points. There is thus a need for evidence-based guidance to provide a standardized methodology for multivariate analysis and to enable comparison of results. This paper makes recommendations for the regression method for analysis of the LMUP as an outcome measure. Materials and methods Data collected from 4,244 pregnant women in Malawi were used to compare five regression methods: linear, logistic with two cut points, and ordinal logistic with either the full or grouped LMUP score. The recommendations were then tested on the original UK LMUP data. Results There were small but no important differences in the findings across the regression models. Logistic regression resulted in the largest loss of information, and assumptions were violated for the linear and ordinal logistic regression. Consequently, robust standard errors were used for linear regression and a partial proportional odds ordinal logistic regression model attempted. The latter could only be fitted for grouped LMUP score. Conclusion We recommend the linear regression model with robust standard errors to make full use of the LMUP score when analyzed as an outcome measure. Ordinal logistic regression could be considered, but a partial proportional odds model with grouped LMUP score may be required. Logistic regression is the least-favored option, due to the loss of information. For logistic regression, the cut point for un/planned pregnancy should be between nine and ten. These recommendations will standardize the analysis of LMUP data and enhance comparability of results across studies. PMID:28435343

Logistic models--an odd(s) kind of regression.

PubMed

Jupiter, Daniel C

2013-01-01

The logistic regression model bears some similarity to the multivariable linear regression with which we are familiar. However, the differences are great enough to warrant a discussion of the need for and interpretation of logistic regression. Copyright © 2013 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

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.

A modified approach to estimating sample size for simple logistic regression with one continuous covariate.

PubMed

Novikov, I; Fund, N; Freedman, L S

2010-01-15

Different methods for the calculation of sample size for simple logistic regression (LR) with one normally distributed continuous covariate give different results. Sometimes the difference can be large. Furthermore, some methods require the user to specify the prevalence of cases when the covariate equals its population mean, rather than the more natural population prevalence. We focus on two commonly used methods and show through simulations that the power for a given sample size may differ substantially from the nominal value for one method, especially when the covariate effect is large, while the other method performs poorly if the user provides the population prevalence instead of the required parameter. We propose a modification of the method of Hsieh et al. that requires specification of the population prevalence and that employs Schouten's sample size formula for a t-test with unequal variances and group sizes. This approach appears to increase the accuracy of the sample size estimates for LR with one continuous covariate.

Predictors of adherence with self-care guidelines among persons with type 2 diabetes: results from a logistic regression tree analysis.

PubMed

Yamashita, Takashi; Kart, Cary S; Noe, Douglas A

2012-12-01

Type 2 diabetes is known to contribute to health disparities in the U.S. and failure to adhere to recommended self-care behaviors is a contributing factor. Intervention programs face difficulties as a result of patient diversity and limited resources. With data from the 2005 Behavioral Risk Factor Surveillance System, this study employs a logistic regression tree algorithm to identify characteristics of sub-populations with type 2 diabetes according to their reported frequency of adherence to four recommended diabetes self-care behaviors including blood glucose monitoring, foot examination, eye examination and HbA1c testing. Using Andersen's health behavior model, need factors appear to dominate the definition of which sub-groups were at greatest risk for low as well as high adherence. Findings demonstrate the utility of easily interpreted tree diagrams to design specific culturally appropriate intervention programs targeting sub-populations of diabetes patients who need to improve their self-care behaviors. Limitations and contributions of the study are discussed.

Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

NASA Astrophysics Data System (ADS)

Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami

2017-06-01

A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.

PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

EPA Science Inventory

The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

Predicting U.S. Army Reserve Unit Manning Using Market Demographics

DTIC Science & Technology

2015-06-01

develops linear regression , classification tree, and logistic regression models to determine the ability of the location to support manning requirements... logistic regression model delivers predictive results that allow decision-makers to identify locations with a high probability of meeting unit...manning requirements. The recommendation of this thesis is that the USAR implement the logistic regression model. 14. SUBJECT TERMS U.S

Analyzing Student Learning Outcomes: Usefulness of Logistic and Cox Regression Models. IR Applications, Volume 5

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2005-01-01

Logistic and Cox regression methods are practical tools used to model the relationships between certain student learning outcomes and their relevant explanatory variables. The logistic regression model fits an S-shaped curve into a binary outcome with data points of zero and one. The Cox regression model allows investigators to study the duration…

Detection of high GS risk group prostate tumors by diffusion tensor imaging and logistic regression modelling.

PubMed

Ertas, Gokhan

2018-07-01

To assess the value of joint evaluation of diffusion tensor imaging (DTI) measures by using logistic regression modelling to detect high GS risk group prostate tumors. Fifty tumors imaged using DTI on a 3 T MRI device were analyzed. Regions of interests focusing on the center of tumor foci and noncancerous tissue on the maps of mean diffusivity (MD) and fractional anisotropy (FA) were used to extract the minimum, the maximum and the mean measures. Measure ratio was computed by dividing tumor measure by noncancerous tissue measure. Logistic regression models were fitted for all possible pair combinations of the measures using 5-fold cross validation. Systematic differences are present for all MD measures and also for all FA measures in distinguishing the high risk tumors [GS ≥ 7(4 + 3)] from the low risk tumors [GS ≤ 7(3 + 4)] (P < 0.05). Smaller value for MD measures and larger value for FA measures indicate the high risk. The models enrolling the measures achieve good fits and good classification performances (R 2 adj  = 0.55-0.60, AUC = 0.88-0.91), however the models using the measure ratios perform better (R 2 adj  = 0.59-0.75, AUC = 0.88-0.95). The model that employs the ratios of minimum MD and maximum FA accomplishes the highest sensitivity, specificity and accuracy (Se = 77.8%, Sp = 96.9% and Acc = 90.0%). Joint evaluation of MD and FA diffusion tensor imaging measures is valuable to detect high GS risk group peripheral zone prostate tumors. However, use of the ratios of the measures improves the accuracy of the detections substantially. Logistic regression modelling provides a favorable solution for the joint evaluations easily adoptable in clinical practice. Copyright © 2018 Elsevier Inc. All rights reserved.

Logistic Regression: Concept and Application

ERIC Educational Resources Information Center

Cokluk, Omay

2010-01-01

The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…

Characteristics of Illinois School Districts That Employ School Nurses.

PubMed

Searing, Lisabeth M; Guenette, Molly

2016-08-01

Research indicates that school nursing services are cost-effective, but the National Association of School Nurses estimates that 25% of schools do not have a school nurse (SN). The purpose of this study was to identify the characteristics of Illinois school districts that employed SNs. This was a secondary data analysis of Illinois School Report Card system data as well as data obtained from district websites regarding SNs. Employment of an SN was determined for 95% of the 862 existing districts. Binary logistic regression analysis found that district size was the largest significant predictor of employment of an SN. Other factors included the type of district and diversity of the teaching staff as well as the percentage of students receiving special education services or with limited English proficiency. These findings indicate where to focus advocacy and policy efforts to encourage employment of SNs. © The Author(s) 2015.

Worklife After Traumatic Spinal Cord Injury

PubMed Central

Pflaum, Christopher; McCollister, George; Strauss, David J; Shavelle, Robert M; DeVivo, Michael J

2006-01-01

Objective: To develop predictive models to estimate worklife expectancy after spinal cord injury (SCI). Design: Inception cohort study. Setting: Model SCI Care Systems throughout the United States. Participants: 20,143 persons enrolled in the National Spinal Cord Injury Statistical Center database since 1973. Intervention: Not applicable. Main Outcome Measure: Postinjury employment rates and worklife expectancy. Results: Using logistic regression, we found a greater likelihood of being employed in any given year to be significantly associated with younger age, white race, higher education level, being married, having a nonviolent cause of injury, paraplegia, ASIA D injury, longer time postinjury, being employed at injury and during the previous postinjury year, higher general population employment rate, lower level of Social Security Disability Insurance benefits, and calendar years after the passage of the Americans with Disabilities Act. Conclusions: The likelihood of postinjury employment varies substantially among persons with SCI. Given favorable patient characteristics, worklife should be considerably higher than previous estimates. PMID:17044388

Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet

2010-05-01

This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross application model yields reasonable results which can be used for preliminary landslide hazard mapping.

Feminism, status inconsistency, and women's intimate partner victimization in heterosexual relationships.

PubMed

Franklin, Cortney A; Menaker, Tasha A

2014-07-01

This study used a random community sample of 303 women in romantic relationships to investigate the role of educational and employment status inconsistency and patriarchal family ideology as risk factors for intimate partner violence (IPV) victimization, while considering demographic factors and relationship context variables. Sequential multivariate logistic regression models demonstrated a decrease in the odds of IPV victimization for Hispanic women and women who were older as compared with their counterparts. In addition, increased relationship distress, family-of-origin violence, and employment status inconsistency significantly increased the odds of IPV. Clinical intervention strategies and future research directions are discussed. © The Author(s) 2014.

An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression

PubMed Central

Weiss, Brandi A.; Dardick, William

2015-01-01

This article introduces an entropy-based measure of data–model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify the quality of classification and separation of group membership. Entropy complements preexisting measures of data–model fit and provides unique information not contained in other measures. Hypothetical data scenarios, an applied example, and Monte Carlo simulation results are used to demonstrate the application of entropy in logistic regression. Entropy should be used in conjunction with other measures of data–model fit to assess how well logistic regression models classify cases into observed categories. PMID:29795897

Logistic regression applied to natural hazards: rare event logistic regression with replications

NASA Astrophysics Data System (ADS)

Guns, M.; Vanacker, V.

2012-06-01

Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

Large unbalanced credit scoring using Lasso-logistic regression ensemble.

PubMed

Wang, Hong; Xu, Qingsong; Zhou, Lifeng

2015-01-01

Recently, various ensemble learning methods with different base classifiers have been proposed for credit scoring problems. However, for various reasons, there has been little research using logistic regression as the base classifier. In this paper, given large unbalanced data, we consider the plausibility of ensemble learning using regularized logistic regression as the base classifier to deal with credit scoring problems. In this research, the data is first balanced and diversified by clustering and bagging algorithms. Then we apply a Lasso-logistic regression learning ensemble to evaluate the credit risks. We show that the proposed algorithm outperforms popular credit scoring models such as decision tree, Lasso-logistic regression and random forests in terms of AUC and F-measure. We also provide two importance measures for the proposed model to identify important variables in the data.

An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression.

PubMed

Weiss, Brandi A; Dardick, William

2016-12-01

This article introduces an entropy-based measure of data-model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify the quality of classification and separation of group membership. Entropy complements preexisting measures of data-model fit and provides unique information not contained in other measures. Hypothetical data scenarios, an applied example, and Monte Carlo simulation results are used to demonstrate the application of entropy in logistic regression. Entropy should be used in conjunction with other measures of data-model fit to assess how well logistic regression models classify cases into observed categories.

Perceived Race-Based Discrimination, Employment Status, and Job Stress in a National Sample of Black Women: Implications for Health Outcomes

PubMed Central

Mays, Vickie M.; Coleman, Lerita M.; Jackson, James S.

2013-01-01

Previous research has not systematically examined the relationship of perceived race-based discriminations to labor force participation or job related stresses–problems experienced by Black women. The present study investigated the relative contributions of perceived race-based discriminations and sociodemographic characteristics to employment status and job stress in a national probability sample (the National Survey of Black Americans; J. S. Jackson, 1991) of Black women in the United States. Logit and polychotomous logistic regression analyses revealed that Black women’s current employment status was best explained by sociodemographic measures. In contrast, the combination of perceived discrimination and sociodemographics differentially affects patterns of employment status and perceived job stress in the work environment of Black women. Implications of these findings for the health of African American women are discussed. PMID:9547054

Exploring unobserved heterogeneity in bicyclists' red-light running behaviors at different crossing facilities.

PubMed

Guo, Yanyong; Li, Zhibin; Wu, Yao; Xu, Chengcheng

2018-06-01

Bicyclists running the red light at crossing facilities increase the potential of colliding with motor vehicles. Exploring the contributing factors could improve the prediction of running red-light probability and develop countermeasures to reduce such behaviors. However, individuals could have unobserved heterogeneities in running a red light, which make the accurate prediction more challenging. Traditional models assume that factor parameters are fixed and cannot capture the varying impacts on red-light running behaviors. In this study, we employed the full Bayesian random parameters logistic regression approach to account for the unobserved heterogeneous effects. Two types of crossing facilities were considered which were the signalized intersection crosswalks and the road segment crosswalks. Electric and conventional bikes were distinguished in the modeling. Data were collected from 16 crosswalks in urban area of Nanjing, China. Factors such as individual characteristics, road geometric design, environmental features, and traffic variables were examined. Model comparison indicates that the full Bayesian random parameters logistic regression approach is statistically superior to the standard logistic regression model. More red-light runners are predicted at signalized intersection crosswalks than at road segment crosswalks. Factors affecting red-light running behaviors are gender, age, bike type, road width, presence of raised median, separation width, signal type, green ratio, bike and vehicle volume, and average vehicle speed. Factors associated with the unobserved heterogeneity are gender, bike type, signal type, separation width, and bike volume. Copyright © 2018 Elsevier Ltd. All rights reserved.

Measurements of the talus in the assessment of population affinity.

PubMed

Bidmos, Mubarak A; Dayal, Manisha R; Adegboye, Oyelola A

2018-06-01

As part of their routine work, forensic anthropologists are expected to report population affinity as part of the biological profile of an individual. The skull is the most widely used bone for the estimation of population affinity but it is not always present in a forensic case. Thus, other bones that preserve well have been shown to give a good indication of either the sex or population affinity of an individual. In this study, the potential of measurements of the talus was investigated for the purpose of estimating population affinity in South Africans. Nine measurements from two hundred and twenty tali of South African Africans (SAA) and South African Whites (SAW) from the Raymond A. Dart Collection of Human Skeletons were used. Direct and step-wise discriminant function and logistic regression analyses were carried out using SPSS and SAS. Talar length was the best single variable for discriminating between these two groups for males while in females the head height was the best single predictor. Average accuracies for correct population affinity classification using logistic regression analysis were higher than those obtained from discriminant function analysis. This study was the first of its type to employ discriminant function analyses and logistic regression analyses to estimate the population affinity of an individual from the talus. Thus these equations can now be used by South African anthropologists when estimating the population affinity of dismembered or damaged or incomplete skeletal remains of SAA and SAW. Copyright © 2018 Elsevier B.V. All rights reserved.

Cosmic Radiation and Cataracts in Airline Pilots

NASA Astrophysics Data System (ADS)

Rafnsson, V.; Olafsdottir, E.; Hrafnkelsson, J.; de Angelis, G.; Sasaki, H.; Arnarson, A.; Jonasson, F.

Nuclear cataracts have been associated with ionising radiation exposure in previous studies. A population based case-control study on airline pilots has been performed to investigate whether employment as a commercial pilot and consequent exposure to cosmic radiation were associated to lens opacification, when adjusted for known risk factors for cataracts. Cases of opacification of the ocular lens were found in surveys among pilots and a random sample of the Icelandic population. Altogether 445 male subjects underwent a detailed eye examination and answered a questionnaire. Information from the airline company on the 79 pilots employment time, annual hours flown per aircraft type, the timetables and the flight profiles made calculation of individual cumulated radiation dose (mSv) possible. Lens opacification were classified and graded according to WHO simplified cataracts grading system using slit lamp. The odds ratio from logistic regression of nuclear cataracts risk among cases and controls was 3.02 (95% CI 1.44 to 6.35) for pilots compared with non-pilots, adjusted for age, smoking and sunbathing habits, whereas that of cortical cataracts risk among cases and controls was lower than unity (non significant) for pilots compared with non-pilots in a logistic regression analysis adjusted for same factors. Length of employment as a pilot and cumulated radiation dose (mSv) were significantly related to the risk of nuclear cataracts. So the association between radiation exposure of pilots and the risk of nuclear cataracts, adjusted for age, smoking and sunbathing habits, indicates that cosmic radiation may be cause of nuclear cataract among commercial pilots.

The relationship between quality of work life and location of cross-training among obstetric nurses in urban northeastern Ontario, Canada: A population-based cross sectional study.

PubMed

Nowrouzi, Behdin; Lightfoot, Nancy; Carter, Lorraine; Larivière, Michel; Rukholm, Ellen; Schinke, Robert; Belanger-Gardner, Diane

2015-01-01

The purpose of this mixed methods study was to examine the quality of work life of registered nurses working in obstetrics at 4 hospitals in northeastern Ontario and explore demographic and occupational factors related to nurses' quality of work life (QWL). A stratified random sample of registered nurses (N = 111) selected from the 138 eligible registered nurses (80.4%) of staff in the labor, delivery, recovery, and postpartum areas at the 4 hospitals participated. Logistic regression analyses were used to consider QWL in relation to the following: 1) demographic factors, and 2) stress, employment status and educational attainment. In the logistic regression model, the odds of a higher quality of work life for nurses who were cross trained (nurses who can work across all areas of obstetrical care) were estimated to be 3.82 (odds ratio = 3.82, 95% confidence interval: 1.01-14.5) times the odds of a higher quality of work life for nurses who were not cross trained. This study highlights a relationship between quality of work life and associated factors including location of cross-training among obstetrical nurses in northeastern Ontario. These findings are supported by the qualitative interviews that examine in depth their relationship to QWL. Given the limited number of employment opportunities in the rural and remote regions, it is paramount that employers and employees work closely together in creating positive environments that promote nurses' QWL. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

Classification of individual well-being scores for the determination of adverse health and productivity outcomes in employee populations.

PubMed

Shi, Yuyan; Sears, Lindsay E; Coberley, Carter R; Pope, James E

2013-04-01

Adverse health and productivity outcomes have imposed a considerable economic burden on employers. To facilitate optimal worksite intervention designs tailored to differing employee risk levels, the authors established cutoff points for an Individual Well-Being Score (IWBS) based on a global measure of well-being. Cross-sectional associations between IWBS and adverse health and productivity outcomes, including high health care cost, emergency room visits, short-term disability days, absenteeism, presenteeism, low job performance ratings, and low intentions to stay with the employer, were studied in a sample of 11,702 employees from a large employer. Receiver operating characteristics curves were evaluated to detect a single optimal cutoff value of IWBS for predicting 2 or more adverse outcomes. More granular segmentation was achieved by computing relative risks of each adverse outcome from logistic regressions accounting for sociodemographic characteristics. Results showed strong and significant nonlinear associations between IWBS and health and productivity outcomes. An IWBS of 75 was found to be the optimal single cutoff point to discriminate 2 or more adverse outcomes. Logistic regression models found abrupt reductions of relative risk also clustered at IWBS cutoffs of 53, 66, and 88, in addition to 75, which segmented employees into high, high-medium, medium, low-medium, and low risk groups. To determine validity and generalizability, cutoff values were applied in a smaller employee population (N=1853) and confirmed significant differences between risk groups across health and productivity outcomes. The reported segmentation of IWBS into discrete cohorts based on risk of adverse health and productivity outcomes should facilitate well-being comparisons and worksite interventions.

Mental health, employment and gender. Cross-sectional evidence in a sample of refugees from Bosnia-Herzegovina living in two Swedish regions.

PubMed

Blight, Karin Johansson; Ekblad, Solvig; Persson, Jan-Olov; Ekberg, Jan

2006-04-01

Large regional differences regarding access to employment have been observed amongst persons from Bosnia-Herzegovina coming to Sweden in 1993-1994. This has led to questions about the role of mental health. To explore this further, postal survey questionnaires were distributed to a community sample (N = 650) that was stratified and, within strata, randomly selected from a sampling frame of persons coming to Sweden from Bosnia-Herzegovina in 1993-1994. Four hundred and thirteen persons returned the questionnaire providing a response rate of 63.5%. The aim was to increase knowledge about the relationship between mental health and employment in the chosen population. The main mental health outcome measure was the Göteborg Quality of Life instrument from which 360 respondents were grouped according to low or high symptom levels. Data were cross tabulated (chi2-tested) against background variables such as age, gender and occupational status, and then tested using binary logistic regression. Binary logistic regression revealed unemployed men but not women, and women who had been working for longer periods during 1993-1999, to be associated with high levels of symptoms of poor mental health. Women living in the urban region were also overrepresented in the high symptom group. These findings indicate that, job occupancy is important to the health of men in the study. However, for the women, further understanding is needed, as job occupancy at some level as well as living in the urban region appear to be associated with poor mental health.

Fatigue design of a cellular phone folder using regression model-based multi-objective optimization

NASA Astrophysics Data System (ADS)

Kim, Young Gyun; Lee, Jongsoo

2016-08-01

In a folding cellular phone, the folding device is repeatedly opened and closed by the user, which eventually results in fatigue damage, particularly to the front of the folder. Hence, it is important to improve the safety and endurance of the folder while also reducing its weight. This article presents an optimal design for the folder front that maximizes its fatigue endurance while minimizing its thickness. Design data for analysis and optimization were obtained experimentally using a test jig. Multi-objective optimization was carried out using a nonlinear regression model. Three regression methods were employed: back-propagation neural networks, logistic regression and support vector machines. The AdaBoost ensemble technique was also used to improve the approximation. Two-objective Pareto-optimal solutions were identified using the non-dominated sorting genetic algorithm (NSGA-II). Finally, a numerically optimized solution was validated against experimental product data, in terms of both fatigue endurance and thickness index.

Examining the Relationship Between Symptomatic Burden and Self-reported Productivity Losses Among Patients With Uterine Fibroids in the United States.

PubMed

Soliman, Ahmed M; Anand, Savita Bakhshi; Coyne, Karin S; Castelli-Haley, Jane; Snabes, Michael; Owens, Charlotte D

2017-10-01

To evaluate the impact of uterine fibroid symptoms on employment and household productivity. An online survey of US women between 18 and 54 was conducted. Productivity was assessed using the health related productivity questionnaire (HRPQ). Descriptive statistics and logistic multivariable regressions examined the relationship between uterine fibroids (UF) symptom experience and employment and household productivity. Of 1365 eligible women, 873 (64.0%) were employed. Women lost an average of 0.8 hours to employment-related absenteeism and 4.4 hours due to employment-related presenteeism for 5.1 hours of employment productivity lost/week. Women lost an average of 1.4 hours due to household-related absenteeism and 1.6 hours due to household-related presenteeism for a total of 3.0 hours of household lost productivity. Productivity losses increased with increases in symptom burden. UF has a substantial impact on employment-related and household-related productivity.

Determinants of perceived sexism and their role on the association of sexism with mental health.

PubMed

Borrell, Carme; Artazcoz, Lucia; Gil-González, Diana; Pérez, Katherine; Pérez, Glòria; Vives-Cases, Carmen; Rohlfs, Izabella

2011-08-31

The authors of this study sought to compare the socioeconomic factors related to perceived sexism in employed and non-employed Spanish women and to examine whether the relationship of perceived sexism with mental health outcomes is reduced when such factors are taken into account. Data were taken from the 2006 Spanish Health Survey, including women aged 20-64 years (n=10,927). Multivariate logistic regression models were used to analyze the independent relationships between socioeconomic variables and perceived sexism and also between perceived sexism and poor mental health. In this latter case, socioeconomic variables were included by blocks in the logistic models. Perceived sexism was higher among employed women (3.9% vs. 2.8% among non-employed) and mainly among those in a managerial position (11.35%; adjusted OR: 2.71, 95% CI: 1.30-5.67) and having irregular working hours (5.5%; adjusted OR: 1.60, 95% CI: 1.10-2.34). Socioeconomic and family characteristics were associated with perceived sexism among women. Perceived sexism was associated with poor mental health, and this remained the case when different independent variables were taken into account. These results highlight the importance of taking into account gender discrimination in different aspects of our society, such as work and family organization, and in planning mental health interventions.

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

Power and Sample Size Calculations for Logistic Regression Tests for Differential Item Functioning

ERIC Educational Resources Information Center

Li, Zhushan

2014-01-01

Logistic regression is a popular method for detecting uniform and nonuniform differential item functioning (DIF) effects. Theoretical formulas for the power and sample size calculations are derived for likelihood ratio tests and Wald tests based on the asymptotic distribution of the maximum likelihood estimators for the logistic regression model.…

A Methodology for Generating Placement Rules that Utilizes Logistic Regression

ERIC Educational Resources Information Center

Wurtz, Keith

2008-01-01

The purpose of this article is to provide the necessary tools for institutional researchers to conduct a logistic regression analysis and interpret the results. Aspects of the logistic regression procedure that are necessary to evaluate models are presented and discussed with an emphasis on cutoff values and choosing the appropriate number of…

Comparison of standard maximum likelihood classification and polytomous logistic regression used in remote sensing

Treesearch

John Hogland; Nedret Billor; Nathaniel Anderson

2013-01-01

Discriminant analysis, referred to as maximum likelihood classification within popular remote sensing software packages, is a common supervised technique used by analysts. Polytomous logistic regression (PLR), also referred to as multinomial logistic regression, is an alternative classification approach that is less restrictive, more flexible, and easy to interpret. To...

Occupational factors contributing to low self-esteem in registered nurses and licensed practical nurses: a multivariate analysis.

PubMed

Imai, K

2001-03-01

The present study examines job-related factors leading to low self-esteem in nurses. The lowering of self-esteem suggests that such nurses had difficulty in fully accepting themselves and their circumstances. Subjects were registered nurses (RN) and licensed practical nurses (LPN) at hospitals, and unemployed registered nurses (UEN) seeking employment. Questionnaires were provided at 53 hospitals and a Nurse Bank in Kanagawa Prefecture. The responses of 552 RN, 146 LPN and 433 UEN were analyzed. Questions were asked about personal life, past or present nursing experience, working conditions, nursing skills, satisfaction with work performance and self-esteem. Factors giving rise to low self-esteem were determined using logistic regression analysis and logistic discriminant analysis. Employment status and qualifications were determined to be the most important factors determining the self-esteem of nurses. The next most important factors were 'a limited number of years of experience (less than five years)' and 'dissatisfaction with discretion and responsibility as a nurse' (P < 0.01). Adjusted odds ratio for a reduction in self-esteem for LPN was 4.07 times higher than for UEN, and 2.2 times higher than for RN by logistic regression analysis. LPN are treated as unskilled workers, and thus significant differences were apparent in their performance of certain job tasks. These differences were analyzed using discriminant analysis, and were referred to as follows, 1: Advanced assessment skills, 2: Advanced technical skills, 3: Advanced communication skills, and 4: Nursing plan and documentation (positive discrimination rate was 70.8%). Job dissatisfaction is closely associated with the level of professional training. Continuous education and a feedback system for various levels of nurses are needed.

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

PubMed

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

2018-05-20

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

Large Unbalanced Credit Scoring Using Lasso-Logistic Regression Ensemble

PubMed Central

Wang, Hong; Xu, Qingsong; Zhou, Lifeng

2015-01-01

Recently, various ensemble learning methods with different base classifiers have been proposed for credit scoring problems. However, for various reasons, there has been little research using logistic regression as the base classifier. In this paper, given large unbalanced data, we consider the plausibility of ensemble learning using regularized logistic regression as the base classifier to deal with credit scoring problems. In this research, the data is first balanced and diversified by clustering and bagging algorithms. Then we apply a Lasso-logistic regression learning ensemble to evaluate the credit risks. We show that the proposed algorithm outperforms popular credit scoring models such as decision tree, Lasso-logistic regression and random forests in terms of AUC and F-measure. We also provide two importance measures for the proposed model to identify important variables in the data. PMID:25706988

Birth preparedness and complication readiness among prenatal attendees in a teaching hospital in South West Nigeria.

PubMed

Aduloju, Olusola P; Akintayo, Akinyemi A; Aduloju, Tolulope; Akin-Akintayo, Oladunni O

2017-11-01

To assess birth preparedness and complication readiness (BPCR) as well as knowledge of danger signs during pregnancy, labor/delivery, and the postpartum period. A cross-sectional study was undertaken of pregnant women attending the prenatal clinic at a tertiary hospital in Nigeria between October and December 2016. A pretested and structured questionnaire was used to collect data on BPCR, and logistic regression was performed to determine factors affecting BPCR. Of 325 participants, 274 (84.3%) had knowledge of BPCR components, and 265 (81.5%) were well prepared for birth and its complications. However, only 89 (27.4%) knew key danger signs during labor/delivery and 81 (24.9%) knew those in the first 2 days after delivery. Older age, higher parity, tertiary education of women, paid employment of women and their spouses, higher social class, frequent prenatal visits, and knowledge of danger signs were significantly associated with BPCR (P<0.05). Higher parity, maternal government employment, and knowledge of danger signs during pregnancy remained determinants of BPCR on logistic regression (P<0.05). Although there was a high level of knowledge and practice of BPCR, knowledge of key danger signs was low. Therefore, prenatal education needs to be improved with an emphasis on teaching pregnant women to recognize key danger signs. © 2017 International Federation of Gynecology and Obstetrics.

[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.

An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression

ERIC Educational Resources Information Center

Weiss, Brandi A.; Dardick, William

2016-01-01

This article introduces an entropy-based measure of data-model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify…

What Are the Odds of that? A Primer on Understanding Logistic Regression

ERIC Educational Resources Information Center

Huang, Francis L.; Moon, Tonya R.

2013-01-01

The purpose of this Methodological Brief is to present a brief primer on logistic regression, a commonly used technique when modeling dichotomous outcomes. Using data from the National Education Longitudinal Study of 1988 (NELS:88), logistic regression techniques were used to investigate student-level variables in eighth grade (i.e., enrolled in a…

On the Usefulness of a Multilevel Logistic Regression Approach to Person-Fit Analysis

ERIC Educational Resources Information Center

Conijn, Judith M.; Emons, Wilco H. M.; van Assen, Marcel A. L. M.; Sijtsma, Klaas

2011-01-01

The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this…

Employment status of veterans receiving substance abuse treatment from the U.S. Department of Veterans Affairs.

PubMed

Humensky, Jennifer L; Jordan, Neil; Stroupe, Kevin T; Hynes, Denise

2013-02-01

This study examined employment outcomes of veterans with substance use disorders and comorbid general medical and psychiatric disorders following substance abuse treatment. The authors obtained employment and other information reported by 5,729 veterans at intake and at follow-up three to nine months after receiving substance abuse treatment from the U.S. Department of Veterans Affairs during 2001-2010. Random-effects logistic regression models examined the probability of having employment earnings and days of paid work during the past 30 days among veterans with comorbid conditions. The percentage of veterans with any days of paid work rose from 28% at intake to 35% at follow-up. Veterans with comorbid anxiety and general medical conditions had lower odds of having earnings from employment or days of paid work at follow-up. Veterans with substance use disorders, particularly those with comorbid general medical and anxiety disorders, may be at risk of employment problems.

Neighbourhood non-employment and daily smoking: a population-based study of women and men in Sweden.

PubMed

Ohlander, Emma; Vikström, Max; Lindström, Martin; Sundquist, Kristina

2006-02-01

To examine whether neighbourhood non-employment is associated with daily smoking after adjustment for individual characteristics, such as employment status. Cross-sectional study of a simple, random sample of 31,164 women and men aged 25-64, representative of the entire population in Sweden. Data were collected from the years 1993-2000. The individual variables included age, sex, employment status, occupation and housing tenure. Logistic regression was used in the analysis with neighbourhood non-employment rates measured at small area market statistics level. There was a significant association between neighbourhood non-employment rates and daily smoking for both women and men. After adjustment for employment status and housing tenure the odds ratios of daily smoking were 1.39 (95% CI = 1.22-1.58) for women and 1.41 (95% CI = 1.23-1.61) for men living in neighbourhoods with the highest non-employment rates. The individual variables of unemployment, low occupational level and renting were associated with daily smoking. Neighbourhood non-employment is associated with daily smoking. Smoking prevention in primary health care should address both individuals and neighbourhoods.

Employment of Low-Income African American and Latino Teens: Does Neighborhood Social Mix Matter?

PubMed Central

Santiago, Anna; Lucero, Jessica

2014-01-01

We quantify how teen employment outcomes for low-income African Americans and Latinos relate to their neighborhood conditions during ages 14–17. Data come from surveys of Denver Housing Authority (DHA) households who have lived in public housing scattered throughout Denver County. Because DHA household allocation mimics random assignment to neighborhood, this program represents a natural experiment for overcoming geographic selection bias. Our logistic and Tobit regression analyses found overall greater odds of teen employment and more hours worked for those who lived in neighborhoods with higher percentages of pre-1940 vintage housing, property crime rates and child abuse rates, though the strength of relationships was highly contingent on gender and ethnicity. Teen employment prospects of African Americans were especially diminished by residence in more socially vulnerable, violent neighborhoods, implying selective potential gains from social mixing alternatives. PMID:26273120

Does cancer in a child affect parents' employment and earnings? A population-based study.

PubMed

Syse, Astri; Larsen, Inger Kristin; Tretli, Steinar

2011-06-01

Cancer in a child may adversely affect parents' work opportunities due to enlarged care burdens and/or altered priorities. Few studies exist, and possible effects on parental employment and earnings were therefore explored. Data on the entire Norwegian population aged 27-65 with children under the age of 20 in 1990-2002 (N=1.2 million) was retrieved from national registries. Employment rates for parents of 3263 children with cancer were compared to those of parents with children without cancer by means of logistic regression models. Log-linear regression models were used to explore childhood cancer's effect on parental earnings for the large majority of parents who remained employed. Cancer in a child was in general not associated with a reduced risk of employment, although some exceptions exist among both mothers and fathers. For employed mothers, CNS cancers, germinal cell cancers, and unspecified leukemia were associated with significant reductions in earnings (10%, 21%, and 60%, respectively). Reductions were particularly pronounced for mothers with a young and alive child, and became more pronounced with time elapsed from diagnosis. Fathers' earnings were not affected significantly. Parents' employment is not adversely affected by a child's cancer in Norway. Earnings are reduced in certain instances, but the overall effects are minor. Generous welfare options and flexible labor markets typical for Nordic welfare states may account for this. In line with traditional caregiving responsibilities, reductions in earnings were most pronounced for mothers. Copyright © 2010 Elsevier Ltd. All rights reserved.

Dynamic Dimensionality Selection for Bayesian Classifier Ensembles

DTIC Science & Technology

2015-03-19

learning of weights in an otherwise generatively learned naive Bayes classifier. WANBIA-C is very cometitive to Logistic Regression but much more...classifier, Generative learning, Discriminative learning, Naïve Bayes, Feature selection, Logistic regression , higher order attribute independence 16...discriminative learning of weights in an otherwise generatively learned naive Bayes classifier. WANBIA-C is very cometitive to Logistic Regression but

A review of logistic regression models used to predict post-fire tree mortality of western North American conifers

Treesearch

Travis Woolley; David C. Shaw; Lisa M. Ganio; Stephen Fitzgerald

2012-01-01

Logistic regression models used to predict tree mortality are critical to post-fire management, planning prescribed bums and understanding disturbance ecology. We review literature concerning post-fire mortality prediction using logistic regression models for coniferous tree species in the western USA. We include synthesis and review of: methods to develop, evaluate...

Preserving Institutional Privacy in Distributed binary Logistic Regression.

PubMed

Wu, Yuan; Jiang, Xiaoqian; Ohno-Machado, Lucila

2012-01-01

Privacy is becoming a major concern when sharing biomedical data across institutions. Although methods for protecting privacy of individual patients have been proposed, it is not clear how to protect the institutional privacy, which is many times a critical concern of data custodians. Built upon our previous work, Grid Binary LOgistic REgression (GLORE)1, we developed an Institutional Privacy-preserving Distributed binary Logistic Regression model (IPDLR) that considers both individual and institutional privacy for building a logistic regression model in a distributed manner. We tested our method using both simulated and clinical data, showing how it is possible to protect the privacy of individuals and of institutions using a distributed strategy.

Covariate Imbalance and Adjustment for Logistic Regression Analysis of Clinical Trial Data

PubMed Central

Ciolino, Jody D.; Martin, Reneé H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.

2014-01-01

In logistic regression analysis for binary clinical trial data, adjusted treatment effect estimates are often not equivalent to unadjusted estimates in the presence of influential covariates. This paper uses simulation to quantify the benefit of covariate adjustment in logistic regression. However, International Conference on Harmonization guidelines suggest that covariate adjustment be pre-specified. Unplanned adjusted analyses should be considered secondary. Results suggest that that if adjustment is not possible or unplanned in a logistic setting, balance in continuous covariates can alleviate some (but never all) of the shortcomings of unadjusted analyses. The case of log binomial regression is also explored. PMID:24138438

Differentially private distributed logistic regression using private and public data.

PubMed

Ji, Zhanglong; Jiang, Xiaoqian; Wang, Shuang; Xiong, Li; Ohno-Machado, Lucila

2014-01-01

Privacy protecting is an important issue in medical informatics and differential privacy is a state-of-the-art framework for data privacy research. Differential privacy offers provable privacy against attackers who have auxiliary information, and can be applied to data mining models (for example, logistic regression). However, differentially private methods sometimes introduce too much noise and make outputs less useful. Given available public data in medical research (e.g. from patients who sign open-consent agreements), we can design algorithms that use both public and private data sets to decrease the amount of noise that is introduced. In this paper, we modify the update step in Newton-Raphson method to propose a differentially private distributed logistic regression model based on both public and private data. We try our algorithm on three different data sets, and show its advantage over: (1) a logistic regression model based solely on public data, and (2) a differentially private distributed logistic regression model based on private data under various scenarios. Logistic regression models built with our new algorithm based on both private and public datasets demonstrate better utility than models that trained on private or public datasets alone without sacrificing the rigorous privacy guarantee.

Logistic regression analysis of conventional ultrasonography, strain elastosonography, and contrast-enhanced ultrasound characteristics for the differentiation of benign and malignant thyroid nodules

PubMed Central

Deng, Yingyuan; Wang, Tianfu; Chen, Siping; Liu, Weixiang

2017-01-01

The aim of the study is to screen the significant sonographic features by logistic regression analysis and fit a model to diagnose thyroid nodules. A total of 525 pathological thyroid nodules were retrospectively analyzed. All the nodules underwent conventional ultrasonography (US), strain elastosonography (SE), and contrast -enhanced ultrasound (CEUS). Those nodules’ 12 suspicious sonographic features were used to assess thyroid nodules. The significant features of diagnosing thyroid nodules were picked out by logistic regression analysis. All variables that were statistically related to diagnosis of thyroid nodules, at a level of p < 0.05 were embodied in a logistic regression analysis model. The significant features in the logistic regression model of diagnosing thyroid nodules were calcification, suspected cervical lymph node metastasis, hypoenhancement pattern, margin, shape, vascularity, posterior acoustic, echogenicity, and elastography score. According to the results of logistic regression analysis, the formula that could predict whether or not thyroid nodules are malignant was established. The area under the receiver operating curve (ROC) was 0.930 and the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 83.77%, 89.56%, 87.05%, 86.04%, and 87.79% respectively. PMID:29228030

Logistic regression analysis of conventional ultrasonography, strain elastosonography, and contrast-enhanced ultrasound characteristics for the differentiation of benign and malignant thyroid nodules.

PubMed

Pang, Tiantian; Huang, Leidan; Deng, Yingyuan; Wang, Tianfu; Chen, Siping; Gong, Xuehao; Liu, Weixiang

2017-01-01

The aim of the study is to screen the significant sonographic features by logistic regression analysis and fit a model to diagnose thyroid nodules. A total of 525 pathological thyroid nodules were retrospectively analyzed. All the nodules underwent conventional ultrasonography (US), strain elastosonography (SE), and contrast -enhanced ultrasound (CEUS). Those nodules' 12 suspicious sonographic features were used to assess thyroid nodules. The significant features of diagnosing thyroid nodules were picked out by logistic regression analysis. All variables that were statistically related to diagnosis of thyroid nodules, at a level of p < 0.05 were embodied in a logistic regression analysis model. The significant features in the logistic regression model of diagnosing thyroid nodules were calcification, suspected cervical lymph node metastasis, hypoenhancement pattern, margin, shape, vascularity, posterior acoustic, echogenicity, and elastography score. According to the results of logistic regression analysis, the formula that could predict whether or not thyroid nodules are malignant was established. The area under the receiver operating curve (ROC) was 0.930 and the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 83.77%, 89.56%, 87.05%, 86.04%, and 87.79% respectively.

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

PubMed

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

2017-06-01

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

Utilisation of cancer screening services by disabled women in Chile

PubMed Central

Rotarou, Elena S.

2017-01-01

Background Research has shown that women with disabilities face additional challenges in accessing and using healthcare services compared to non-disabled women. However, relatively little is known about the utilisation of cancer screening services for women with disabilities. This study addresses this gap by examining the utilisation of the Papanicolaou test and mammography for disabled women in Chile. Methods We used cross-sectional data, taken from a 2015 nationally-representative survey. Initially, we employed logistic regressions to test for differences in utilisation rates for the Papanicolaou test (66,281 observations) and the mammogram (35,294 observations) between disabled and non-disabled women. Next, logistic regressions were used to investigate the demographic, socioeconomic, and health-related factors affecting utilisation rates for cancer screening services for disabled women (sample sizes: 5,823 observations for the Papanicolaou test and 5,731 observations for the mammogram). Results Disabled women were less likely to undergo screening tests than non-disabled women. For the Papanicolaou test and mammography, the multivariable regression models showed that living in rural areas, having higher education, being affiliated with a private health insurance company, giving a good health self-assessment score, and being under medical treatment for other illnesses were associated with higher utilisation rates. On the other hand, being single, inactive with regard to employment, and having a better income were linked with lower utilisation. While utilisation rates for both disabled and non-disabled women have increased since 2006, the utilisation disparity has slightly increased. Conclusions This study shows the influence of various factors in the utilisation rates of preventive cancer screening services for disabled women. To develop effective initiatives targeting inequalities in the utilisation of cancer screening tests, it is important to move beyond an exclusively single-disease approach and acknowledge the complexity of the patient population. PMID:28459874

Utilisation of cancer screening services by disabled women in Chile.

PubMed

Sakellariou, Dikaios; Rotarou, Elena S

2017-01-01

Research has shown that women with disabilities face additional challenges in accessing and using healthcare services compared to non-disabled women. However, relatively little is known about the utilisation of cancer screening services for women with disabilities. This study addresses this gap by examining the utilisation of the Papanicolaou test and mammography for disabled women in Chile. We used cross-sectional data, taken from a 2015 nationally-representative survey. Initially, we employed logistic regressions to test for differences in utilisation rates for the Papanicolaou test (66,281 observations) and the mammogram (35,294 observations) between disabled and non-disabled women. Next, logistic regressions were used to investigate the demographic, socioeconomic, and health-related factors affecting utilisation rates for cancer screening services for disabled women (sample sizes: 5,823 observations for the Papanicolaou test and 5,731 observations for the mammogram). Disabled women were less likely to undergo screening tests than non-disabled women. For the Papanicolaou test and mammography, the multivariable regression models showed that living in rural areas, having higher education, being affiliated with a private health insurance company, giving a good health self-assessment score, and being under medical treatment for other illnesses were associated with higher utilisation rates. On the other hand, being single, inactive with regard to employment, and having a better income were linked with lower utilisation. While utilisation rates for both disabled and non-disabled women have increased since 2006, the utilisation disparity has slightly increased. This study shows the influence of various factors in the utilisation rates of preventive cancer screening services for disabled women. To develop effective initiatives targeting inequalities in the utilisation of cancer screening tests, it is important to move beyond an exclusively single-disease approach and acknowledge the complexity of the patient population.

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.

The influence of intrinsic and extrinsic job values on turnover intention among continuing care assistants in Nova Scotia.

PubMed

Dill, Donna M; Keefe, Janice M; McGrath, Daniel S

2012-01-01

This article examines the influence that intrinsic and extrinsic job values have on the turnover intention of continuing care assistants (CCAs) who work either in home care or facility-based care in Nova Scotia (n = 188). Factor analysis of job values identified three latent job values structures: "compensation and commitment," "flexibility and opportunity," and "positive work relationships." Using binary logistic regression, we examined the predictive utility of these factors on two indices of turnover intention. Regression results indicate that, in general, job values constructs did not significantly predict turnover intention when controlling for demographics and job characteristics. However, a trend was found for the "positive work relationships" factor in predicting consideration of changing employers. In addition, CCAs who work in facility-based care were significantly more likely to have considered leaving their current employer. With projected increases in the demand for these workers in both home and continuing care, more attention is needed to identify and address factors to reduce turnover intention.

Modeling the probability of giving birth at health institutions among pregnant women attending antenatal care in West Shewa Zone, Oromia, Ethiopia: a cross sectional study.

PubMed

Dida, Nagasa; Birhanu, Zewdie; Gerbaba, Mulusew; Tilahun, Dejen; Morankar, Sudhakar

2014-06-01

Although ante natal care and institutional delivery is effective means for reducing maternal morbidity and mortality, the probability of giving birth at health institutions among ante natal care attendants has not been modeled in Ethiopia. Therefore, the objective of this study was to model predictors of giving birth at health institutions among expectant mothers following antenatal care. Facility based cross sectional study design was conducted among 322 consecutively selected mothers who were following ante natal care in two districts of West Shewa Zone, Oromia Regional State, Ethiopia. Participants were proportionally recruited from six health institutions. The data were analyzed using SPSS version 17.0. Multivariable logistic regression was employed to develop the prediction model. The final regression model had good discrimination power (89.2%), optimum sensitivity (89.0%) and specificity (80.0%) to predict the probability of giving birth at health institutions. Accordingly, self efficacy (beta=0.41), perceived barrier (beta=-0.31) and perceived susceptibility (beta=0.29) were significantly predicted the probability of giving birth at health institutions. The present study showed that logistic regression model has predicted the probability of giving birth at health institutions and identified significant predictors which health care providers should take into account in promotion of institutional delivery.

Predictors of employment status among adults with Autism Spectrum Disorder.

PubMed

Ohl, Alisha; Grice Sheff, Mira; Small, Sarah; Nguyen, Jamie; Paskor, Kelly; Zanjirian, Aliza

2017-01-01

In the United States, adults with Autism Spectrum Disorder (ASD) experience high rates of unemployment and underemployment in relation to adults with other disabilities and the general population. Yet there is little research examining their employment experiences and the predictors of employment status. The purpose of this study was to examine the employment characteristics and histories of both employed and unemployed adults with ASD, and the factors that contributed to their employment status. This cross-sectional study used an online survey and the Short Effort Reward Imbalance (ERI) Scale to gather data. Multivariate logistic regression analyses were used to examine predictors of employment status and self-reported health. Of the 254 adults with ASD who participated in this study, 61.42% were employed and 38.58% were unemployed. Over half of the participants reported job imbalance on the Short ERI Scale and the vast majority did not receive any job assistance. Participants who disclosed their ASD diagnosis to their employer were more than three times as likely to be employed than those who did not disclose. Education level was also a significant predictor of employment status. This study suggests disability disclosure and education level are factors that contribute to employment status.

Fisher Scoring Method for Parameter Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

NASA Astrophysics Data System (ADS)

Widyaningsih, Purnami; Retno Sari Saputro, Dewi; Nugrahani Putri, Aulia

2017-06-01

GWOLR model combines geographically weighted regression (GWR) and (ordinal logistic reression) OLR models. Its parameter estimation employs maximum likelihood estimation. Such parameter estimation, however, yields difficult-to-solve system of nonlinear equations, and therefore numerical approximation approach is required. The iterative approximation approach, in general, uses Newton-Raphson (NR) method. The NR method has a disadvantage—its Hessian matrix is always the second derivatives of each iteration so it does not always produce converging results. With regard to this matter, NR model is modified by substituting its Hessian matrix into Fisher information matrix, which is termed Fisher scoring (FS). The present research seeks to determine GWOLR model parameter estimation using Fisher scoring method and apply the estimation on data of the level of vulnerability to Dengue Hemorrhagic Fever (DHF) in Semarang. The research concludes that health facilities give the greatest contribution to the probability of the number of DHF sufferers in both villages. Based on the number of the sufferers, IR category of DHF in both villages can be determined.

Occupational exposures and non-Hodgkin's lymphoma: Canadian case-control study.

PubMed

Karunanayake, Chandima P; McDuffie, Helen H; Dosman, James A; Spinelli, John J; Pahwa, Punam

2008-08-07

The objective was to study the association between Non-Hodgkin's Lymphoma (NHL) and occupational exposures related to long held occupations among males in six provinces of Canada. A population based case-control study was conducted from 1991 to 1994. Males with newly diagnosed NHL (ICD-10) were stratified by province of residence and age group. A total of 513 incident cases and 1506 population based controls were included in the analysis. Conditional logistic regression was conducted to fit statistical models. Based on conditional logistic regression modeling, the following factors independently increased the risk of NHL: farmer and machinist as long held occupations; constant exposure to diesel exhaust fumes; constant exposure to ionizing radiation (radium); and personal history of another cancer. Men who had worked for 20 years or more as farmer and machinist were the most likely to develop NHL. An increased risk of developing NHL is associated with the following: long held occupations of faer and machinist; exposure to diesel fumes; and exposure to ionizing radiation (radium). The risk of NHL increased with the duration of employment as a farmer or machinist.

Classification of Individual Well-Being Scores for the Determination of Adverse Health and Productivity Outcomes in Employee Populations

PubMed Central

Sears, Lindsay E.; Coberley, Carter R.; Pope, James E.

2013-01-01

Abstract Adverse health and productivity outcomes have imposed a considerable economic burden on employers. To facilitate optimal worksite intervention designs tailored to differing employee risk levels, the authors established cutoff points for an Individual Well-Being Score (IWBS) based on a global measure of well-being. Cross-sectional associations between IWBS and adverse health and productivity outcomes, including high health care cost, emergency room visits, short-term disability days, absenteeism, presenteeism, low job performance ratings, and low intentions to stay with the employer, were studied in a sample of 11,702 employees from a large employer. Receiver operating characteristics curves were evaluated to detect a single optimal cutoff value of IWBS for predicting 2 or more adverse outcomes. More granular segmentation was achieved by computing relative risks of each adverse outcome from logistic regressions accounting for sociodemographic characteristics. Results showed strong and significant nonlinear associations between IWBS and health and productivity outcomes. An IWBS of 75 was found to be the optimal single cutoff point to discriminate 2 or more adverse outcomes. Logistic regression models found abrupt reductions of relative risk also clustered at IWBS cutoffs of 53, 66, and 88, in addition to 75, which segmented employees into high, high-medium, medium, low-medium, and low risk groups. To determine validity and generalizability, cutoff values were applied in a smaller employee population (N=1853) and confirmed significant differences between risk groups across health and productivity outcomes. The reported segmentation of IWBS into discrete cohorts based on risk of adverse health and productivity outcomes should facilitate well-being comparisons and worksite interventions. (Population Health Management 2013;16:90–98) PMID:23013034

Effects of sense of coherence on depressive symptoms after employment in the Japan Self-Defense Force among male young adults.

PubMed

Kobayashi, Tohru

2017-01-01

Objective　The present study aimed to explore the effects of sense of coherence (SOC) on depressive symptoms after employment in the Japan Self-Defense Force among male young adults.Methods　In April 2013, 953 new male members of the Japan Ground Self-Defense Force (JGSDF; age range: 18-24 years) participated in this study. Depressive symptoms were assessed using the 20-item version of the Center for Epidemiologic Studies Depression scale (CES-D), which defines a score of 16 or greater as indicating the presence of depressive symptoms. The SOC score was assessed using a 13-item version (SOC-13), in which a score of 59 or greater is as assigned to the high score group. A second survey was conducted two months later, in June of 2013. For the analysis, we selected participants without depressive symptoms at the baseline survey. The association between SOC scores at baseline and the onset of depressive symptoms was examined using a logistic regression analysis.Results　The final analysis was conducted on data on 389 new male members of the JGSDF. The logistic regression analysis showed a significant reduction in the onset of depressive symptoms among the group with high SOC scores (odds ratios: 0.59, 95% confidence interval=0.35-0.98) as compared with that observed in the group with low SOC scores.Conclusions　The present study clarified that SOC among male young adults has a buffering effect on the risk of developing depressive symptoms after employment in the Japan Self-Defense Force. Our results may be useful for improving the mental health of new employees.

Workplace support for employees with cancer

PubMed Central

Nowrouzi, B.; Lightfoot, N.; Cote, K.; Watson, R.

2009-01-01

Objective The aim of the present study was to survey human resources personnel about how their northeastern Ontario workplaces assist employees with cancer. Study Design and Setting This cross-sectional study was conducted from December 2007 to April 2008. Surveys were sent to 255 workplaces in northeastern Ontario with 25 or more employees, and 101 workplaces responded (39.6% response rate). Logistic regression modelling was used to identify factors associated with more or less workplace support. More or less workplace support was defined by provision of paid time to employees with medical appointments and an offer of a return-to-work meeting and reduced hours for employees with cancer. Factors considered in the model included organization size, geographic location (urban, rural), and workplace type (private sector, public sector). Results Most of the human resources staff who completed the surveys were women (67.4%), and respondents ranged in age from 25 to 70 years (mean: 45.30 ± 8.10 years). Respondents reported working for organizations that ranged in size from 25 to more than 9000 employees. In the logistic regression model, large organization size [odds ratio (or): 6.97; 95% confidence interval (ci): 1.34 to 36.2] and public sector (or: 4.98; 95% ci: 1.16 to 21.3) were associated with employer assistance. Public sector employers provided assistance at a rate 5 times that of private sector employers, and large organizations (>50 employees) provided assistance at a rate 7 times that of smaller organizations. Conclusions In the population studied, employees with cancer benefit from working in larger and public sector organizations. The data suggest a need for further support for employees with cancer in some other organizations. PMID:19862358

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.

GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models.

PubMed

Chen, Wei; Li, Hui; Hou, Enke; Wang, Shengquan; Wang, Guirong; Panahi, Mahdi; Li, Tao; Peng, Tao; Guo, Chen; Niu, Chao; Xiao, Lele; Wang, Jiale; Xie, Xiaoshen; Ahmad, Baharin Bin

2018-09-01

The aim of the current study was to produce groundwater spring potential maps using novel ensemble weights-of-evidence (WoE) with logistic regression (LR) and functional tree (FT) models. First, a total of 66 springs were identified by field surveys, out of which 70% of the spring locations were used for training the models and 30% of the spring locations were employed for the validation process. Second, a total of 14 affecting factors including aspect, altitude, slope, plan curvature, profile curvature, stream power index (SPI), topographic wetness index (TWI), sediment transport index (STI), lithology, normalized difference vegetation index (NDVI), land use, soil, distance to roads, and distance to streams was used to analyze the spatial relationship between these affecting factors and spring occurrences. Multicollinearity analysis and feature selection of the correlation attribute evaluation (CAE) method were employed to optimize the affecting factors. Subsequently, the novel ensembles of the WoE, LR, and FT models were constructed using the training dataset. Finally, the receiver operating characteristic (ROC) curves, standard error, confidence interval (CI) at 95%, and significance level P were employed to validate and compare the performance of three models. Overall, all three models performed well for groundwater spring potential evaluation. The prediction capability of the FT model, with the highest AUC values, the smallest standard errors, the narrowest CIs, and the smallest P values for the training and validation datasets, is better compared to those of other models. The groundwater spring potential maps can be adopted for the management of water resources and land use by planners and engineers. Copyright © 2018 Elsevier B.V. All rights reserved.

Measuring moral hazard and adverse selection by propensity scoring in the mixed health care economy of Hong Kong.

PubMed

Wong, Irene O L; Lindner, Michael J; Cowling, Benjamin J; Lau, Eric H Y; Lo, Su-Vui; Leung, Gabriel M

2010-04-01

To evaluate the presence of moral hazard, adjusted for the propensity to have self-purchased insurance policies, employer-based medical benefits, and welfare-associated medical benefits in Hong Kong. Based on 2005 population survey, we used logistic regression and zero-truncated negative binomial/Poisson regressions to assess the presence of moral hazard by comparing inpatient and outpatient utilization between insured and uninsured individuals. We fitted each enabling factor specific to the type of service covered, and adjusted for predisposing socioeconomic and demographic factors. We used a propensity score approach to account for potential adverse selection. Employment-based benefits coverage was associated with increased access and intensity of use for both inpatient and outpatient care, except for public hospital use. Similarly, welfare-based coverage had comparable effect sizes as employment-based schemes, except for the total number of public ambulatory episodes. Self-purchased insurance facilitated access but did not apparently induce greater demand of services among ever users. Nevertheless, there was no evidence of moral hazard in public hospital use. Our findings suggest that employment-based benefits coverage lead to the greatest degree of moral hazard in Hong Kong. Future studies should focus on confirming these observational findings using a randomized design. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

Logistic regression for dichotomized counts.

PubMed

Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

2016-12-01

Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

Predicting 30-day Hospital Readmission with Publicly Available Administrative Database. A Conditional Logistic Regression Modeling Approach.

PubMed

Zhu, K; Lou, Z; Zhou, J; Ballester, N; Kong, N; Parikh, P

2015-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". Hospital readmissions raise healthcare costs and cause significant distress to providers and patients. It is, therefore, of great interest to healthcare organizations to predict what patients are at risk to be readmitted to their hospitals. However, current logistic regression based risk prediction models have limited prediction power when applied to hospital administrative data. Meanwhile, although decision trees and random forests have been applied, they tend to be too complex to understand among the hospital practitioners. Explore the use of conditional logistic regression to increase the prediction accuracy. We analyzed an HCUP statewide inpatient discharge record dataset, which includes patient demographics, clinical and care utilization data from California. We extracted records of heart failure Medicare beneficiaries who had inpatient experience during an 11-month period. We corrected the data imbalance issue with under-sampling. In our study, we first applied standard logistic regression and decision tree to obtain influential variables and derive practically meaning decision rules. We then stratified the original data set accordingly and applied logistic regression on each data stratum. We further explored the effect of interacting variables in the logistic regression modeling. We conducted cross validation to assess the overall prediction performance of conditional logistic regression (CLR) and compared it with standard classification models. The developed CLR models outperformed several standard classification models (e.g., straightforward logistic regression, stepwise logistic regression, random forest, support vector machine). For example, the best CLR model improved the classification accuracy by nearly 20% over the straightforward logistic regression model. Furthermore, the developed CLR models tend to achieve better sensitivity of more than 10% over the standard classification models, which can be translated to correct labeling of additional 400 - 500 readmissions for heart failure patients in the state of California over a year. Lastly, several key predictor identified from the HCUP data include the disposition location from discharge, the number of chronic conditions, and the number of acute procedures. It would be beneficial to apply simple decision rules obtained from the decision tree in an ad-hoc manner to guide the cohort stratification. It could be potentially beneficial to explore the effect of pairwise interactions between influential predictors when building the logistic regression models for different data strata. Judicious use of the ad-hoc CLR models developed offers insights into future development of prediction models for hospital readmissions, which can lead to better intuition in identifying high-risk patients and developing effective post-discharge care strategies. Lastly, this paper is expected to raise the awareness of collecting data on additional markers and developing necessary database infrastructure for larger-scale exploratory studies on readmission risk prediction.

Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran

NASA Astrophysics Data System (ADS)

Zeraatpisheh, Mojtaba; Ayoubi, Shamsollah; Jafari, Azam; Finke, Peter

2017-05-01

The efficiency of different digital and conventional soil mapping approaches to produce categorical maps of soil types is determined by cost, sample size, accuracy and the selected taxonomic level. The efficiency of digital and conventional soil mapping approaches was examined in the semi-arid region of Borujen, central Iran. This research aimed to (i) compare two digital soil mapping approaches including Multinomial logistic regression and random forest, with the conventional soil mapping approach at four soil taxonomic levels (order, suborder, great group and subgroup levels), (ii) validate the predicted soil maps by the same validation data set to determine the best method for producing the soil maps, and (iii) select the best soil taxonomic level by different approaches at three sample sizes (100, 80, and 60 point observations), in two scenarios with and without a geomorphology map as a spatial covariate. In most predicted maps, using both digital soil mapping approaches, the best results were obtained using the combination of terrain attributes and the geomorphology map, although differences between the scenarios with and without the geomorphology map were not significant. Employing the geomorphology map increased map purity and the Kappa index, and led to a decrease in the 'noisiness' of soil maps. Multinomial logistic regression had better performance at higher taxonomic levels (order and suborder levels); however, random forest showed better performance at lower taxonomic levels (great group and subgroup levels). Multinomial logistic regression was less sensitive than random forest to a decrease in the number of training observations. The conventional soil mapping method produced a map with larger minimum polygon size because of traditional cartographic criteria used to make the geological map 1:100,000 (on which the conventional soil mapping map was largely based). Likewise, conventional soil mapping map had also a larger average polygon size that resulted in a lower level of detail. Multinomial logistic regression at the order level (map purity of 0.80), random forest at the suborder (map purity of 0.72) and great group level (map purity of 0.60), and conventional soil mapping at the subgroup level (map purity of 0.48) produced the most accurate maps in the study area. The multinomial logistic regression method was identified as the most effective approach based on a combined index of map purity, map information content, and map production cost. The combined index also showed that smaller sample size led to a preference for the order level, while a larger sample size led to a preference for the great group level.

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.

Predictors of re-employment: a question of attitude, behavior, or gender?

PubMed

Andersson, Kin

2015-08-01

This longitudinal study examined the predictive value of attitudes, personal-related variables, job search behaviour, and demographic variables on re-employment among 142 assembly workers who had been made redundant. Participants completed a questionnaire within a week after leaving their jobs, and another 15 months later. Results of hierarchical logistic regression revealed that gender (being male), was the strongest predictor of re-employment. Willingness to relocate and desire to change occupation also increased the odds of re-employment 15 months after dismissal. On the other hand - having children at home and anonymous-passive job-search behaviour, which is more prevalent among women, decreased the odds for re-employment. The study is contributing to research by revealing gender differences in job search behaviour and the importance of focusing qualitative differences instead of merely quantitative measures in job-search behaviour. And even more important, despite attitude and job-search behaviour, there is still differences that seems to be related to gender and family responsibility. © 2015 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

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.

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.

Gender differences in vocational rehabilitation service predictors of successful competitive employment for transition-aged individuals with autism.

PubMed

Sung, Connie; Sánchez, Jennifer; Kuo, Hung-Jen; Wang, Chia-Chiang; Leahy, Michael J

2015-10-01

As males and females with autism spectrum disorder (ASD) experience different symptomology, their needs for vocational rehabilitation (VR) are unique as they transition into adulthood. This study examined the effects of gender differences in VR service predictors on employment outcomes for transition-aged individuals with ASD. A total of 1696 individuals (857 males and 839 females) were analyzed from a sample of RSA-911 data of FY 2011. Hierarchical logistic regression analyses were conducted. Results revealed both gender-independent VR service predictors (with job placement and on-the-job supports more beneficial for both genders) and gender-specific predictors of employment (with counseling and guidance, job search assistance, and other services more beneficial for the male group). This study provides support for individualized gender-specific VR services for people with ASD.

Evaluation of logistic regression models and effect of covariates for case-control study in RNA-Seq analysis.

PubMed

Choi, Seung Hoan; Labadorf, Adam T; Myers, Richard H; Lunetta, Kathryn L; Dupuis, Josée; DeStefano, Anita L

2017-02-06

Next generation sequencing provides a count of RNA molecules in the form of short reads, yielding discrete, often highly non-normally distributed gene expression measurements. Although Negative Binomial (NB) regression has been generally accepted in the analysis of RNA sequencing (RNA-Seq) data, its appropriateness has not been exhaustively evaluated. We explore logistic regression as an alternative method for RNA-Seq studies designed to compare cases and controls, where disease status is modeled as a function of RNA-Seq reads using simulated and Huntington disease data. We evaluate the effect of adjusting for covariates that have an unknown relationship with gene expression. Finally, we incorporate the data adaptive method in order to compare false positive rates. When the sample size is small or the expression levels of a gene are highly dispersed, the NB regression shows inflated Type-I error rates but the Classical logistic and Bayes logistic (BL) regressions are conservative. Firth's logistic (FL) regression performs well or is slightly conservative. Large sample size and low dispersion generally make Type-I error rates of all methods close to nominal alpha levels of 0.05 and 0.01. However, Type-I error rates are controlled after applying the data adaptive method. The NB, BL, and FL regressions gain increased power with large sample size, large log2 fold-change, and low dispersion. The FL regression has comparable power to NB regression. We conclude that implementing the data adaptive method appropriately controls Type-I error rates in RNA-Seq analysis. Firth's logistic regression provides a concise statistical inference process and reduces spurious associations from inaccurately estimated dispersion parameters in the negative binomial framework.

Differentially private distributed logistic regression using private and public data

PubMed Central

2014-01-01

Background Privacy protecting is an important issue in medical informatics and differential privacy is a state-of-the-art framework for data privacy research. Differential privacy offers provable privacy against attackers who have auxiliary information, and can be applied to data mining models (for example, logistic regression). However, differentially private methods sometimes introduce too much noise and make outputs less useful. Given available public data in medical research (e.g. from patients who sign open-consent agreements), we can design algorithms that use both public and private data sets to decrease the amount of noise that is introduced. Methodology In this paper, we modify the update step in Newton-Raphson method to propose a differentially private distributed logistic regression model based on both public and private data. Experiments and results We try our algorithm on three different data sets, and show its advantage over: (1) a logistic regression model based solely on public data, and (2) a differentially private distributed logistic regression model based on private data under various scenarios. Conclusion Logistic regression models built with our new algorithm based on both private and public datasets demonstrate better utility than models that trained on private or public datasets alone without sacrificing the rigorous privacy guarantee. PMID:25079786

A retrospective analysis to identify the factors affecting infection in patients undergoing chemotherapy.

PubMed

Park, Ji Hyun; Kim, Hyeon-Young; Lee, Hanna; Yun, Eun Kyoung

2015-12-01

This study compares the performance of the logistic regression and decision tree analysis methods for assessing the risk factors for infection in cancer patients undergoing chemotherapy. The subjects were 732 cancer patients who were receiving chemotherapy at K university hospital in Seoul, Korea. The data were collected between March 2011 and February 2013 and were processed for descriptive analysis, logistic regression and decision tree analysis using the IBM SPSS Statistics 19 and Modeler 15.1 programs. The most common risk factors for infection in cancer patients receiving chemotherapy were identified as alkylating agents, vinca alkaloid and underlying diabetes mellitus. The logistic regression explained 66.7% of the variation in the data in terms of sensitivity and 88.9% in terms of specificity. The decision tree analysis accounted for 55.0% of the variation in the data in terms of sensitivity and 89.0% in terms of specificity. As for the overall classification accuracy, the logistic regression explained 88.0% and the decision tree analysis explained 87.2%. The logistic regression analysis showed a higher degree of sensitivity and classification accuracy. Therefore, logistic regression analysis is concluded to be the more effective and useful method for establishing an infection prediction model for patients undergoing chemotherapy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Simulating land-use changes by incorporating spatial autocorrelation and self-organization in CLUE-S modeling: a case study in Zengcheng District, Guangzhou, China

NASA Astrophysics Data System (ADS)

Mei, Zhixiong; Wu, Hao; Li, Shiyun

2018-06-01

The Conversion of Land Use and its Effects at Small regional extent (CLUE-S), which is a widely used model for land-use simulation, utilizes logistic regression to estimate the relationships between land use and its drivers, and thus, predict land-use change probabilities. However, logistic regression disregards possible spatial autocorrelation and self-organization in land-use data. Autologistic regression can depict spatial autocorrelation but cannot address self-organization, while logistic regression by considering only self-organization (NElogistic regression) fails to capture spatial autocorrelation. Therefore, this study developed a regression (NE-autologistic regression) method, which incorporated both spatial autocorrelation and self-organization, to improve CLUE-S. The Zengcheng District of Guangzhou, China was selected as the study area. The land-use data of 2001, 2005, and 2009, as well as 10 typical driving factors, were used to validate the proposed regression method and the improved CLUE-S model. Then, three future land-use scenarios in 2020: the natural growth scenario, ecological protection scenario, and economic development scenario, were simulated using the improved model. Validation results showed that NE-autologistic regression performed better than logistic regression, autologistic regression, and NE-logistic regression in predicting land-use change probabilities. The spatial allocation accuracy and kappa values of NE-autologistic-CLUE-S were higher than those of logistic-CLUE-S, autologistic-CLUE-S, and NE-logistic-CLUE-S for the simulations of two periods, 2001-2009 and 2005-2009, which proved that the improved CLUE-S model achieved the best simulation and was thereby effective to a certain extent. The scenario simulation results indicated that under all three scenarios, traffic land and residential/industrial land would increase, whereas arable land and unused land would decrease during 2009-2020. Apparent differences also existed in the simulated change sizes and locations of each land-use type under different scenarios. The results not only demonstrate the validity of the improved model but also provide a valuable reference for relevant policy-makers.

Support for smoke-free policies in the Cyprus hospitality industry.

PubMed

Lazuras, Lambros; Savva, Christos S; Talias, Michael A; Soteriades, Elpidoforos S

2015-12-01

The present study used attitudinal and behavioural indicators to measure support for smoke-free policies among employers and employees in the hospitality industry in Cyprus. A representative sample of 600 participants (95 % response rate) completed anonymous structured questionnaires on demographic variables, smoking status, exposure to second-hand smoke at work and related health beliefs, social norms, and smoke-free policy support. Participants were predominantly males (68.3 %), with a mean age of 40 years (SD = 12.69), and 39.7 % were employers/owners of the hospitality venue. Analysis of variance showed that employers and smokers were less supportive of smoke-free policies, as compared to employees and non-smokers. Linear regression models showed that attitudes towards smoke-free policy were predicted by smoking status, SHS exposure and related health beliefs, and social norm variables. Logistic regression analysis showed that willingness to confront a policy violator was predicted by SHS exposure, perceived prevalence of smoker clients, and smoke-free policy attitudes. SHS exposure and related health beliefs, and normative factors should be targeted by interventions aiming to promote policy support in the hospitality industry in Cyprus.

Unitary Response Regression Models

ERIC Educational Resources Information Center

Lipovetsky, S.

2007-01-01

The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…

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

PubMed

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

2017-04-01

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

Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

PubMed

Nikbakht, Roya; Bahrampour, Abbas

2017-01-01

Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.

Illness consequences after myocardial infarction: problems with physical functioning and return to work.

PubMed

Brink, Eva; Brändström, Yvonne; Cliffordsson, Christina; Herlitz, Johan; Karlson, Björn W

2008-12-01

This paper is a report of a study to explore health problems, physical and mental functioning, and physical activity in working-age patients after myocardial infarction, in order to assess the possible effects of these factors on return to work. A diagnosis of myocardial infarction may discourage patients from continuing an active working life. Enabling myocardial infarction patients to return to work has benefits for both individuals and society. A convenience sample was recruited of 88 patients,

Patterns of drug treatment entry by Latino male injection drug users from different national/geographical backgrounds.

PubMed

Reynoso-Vallejo, Humberto; Chassler, Deborah; Witas, Julie; Lundgren, Lena M

2008-02-01

This study examined patterns of treatment entry by Puerto Rican, Central American, Dominican, and other Latino male injection drug users (IDUs) in the state of Massachusetts over the time period 1996-2002. Specifically, it explored whether these populations had different patterns relative to three paths: entry into detoxification only, entry into residential treatment, or entry into methadone maintenance. Using a state-level MIS dataset on all substance abuse treatment entries to all licensed treatment programs, bi-variate and logistic regression methods were employed to examine patterns of drug treatment utilization among Latino men residing in Massachusetts. Three logistic regression models, which controlled for age, education, homelessness, employment, history of mental health treatment, health insurance, criminal justice involvement, having injected drugs in the past month, and number of treatment entries, indicated that Puerto Rican men were significantly less likely to only use detoxification services and residential treatment services, and significantly more likely to enter methadone maintenance compared to Latino men from Central American, Dominican, or other Latino backgrounds. For example, Central American men were 2.4 times more likely to enter only detoxification programs and 54% less likely to enter methadone maintenance programs than Puerto Rican male IDUs. For program planning, include the need to (a) develop varied drug treatment services to meet the needs of non-homogenous Latino groups within the population, (b) tailor outreach efforts to effectively reach all Latino groups, and (c) increase awareness among practitioners of differential patterns of treatment utilization.

Identifying patterns of item missing survey data using latent groups: an observational study.

PubMed

Barnett, Adrian G; McElwee, Paul; Nathan, Andrea; Burton, Nicola W; Turrell, Gavin

2017-10-30

To examine whether respondents to a survey of health and physical activity and potential determinants could be grouped according to the questions they missed, known as 'item missing'. Observational study of longitudinal data. Residents of Brisbane, Australia. 6901 people aged 40-65 years in 2007. We used a latent class model with a mixture of multinomial distributions and chose the number of classes using the Bayesian information criterion. We used logistic regression to examine if participants' characteristics were associated with their modal latent class. We used logistic regression to examine whether the amount of item missing in a survey predicted wave missing in the following survey. Four per cent of participants missed almost one-fifth of the questions, and this group missed more questions in the middle of the survey. Eighty-three per cent of participants completed almost every question, but had a relatively high missing probability for a question on sleep time, a question which had an inconsistent presentation compared with the rest of the survey. Participants who completed almost every question were generally younger and more educated. Participants who completed more questions were less likely to miss the next longitudinal wave. Examining patterns in item missing data has improved our understanding of how missing data were generated and has informed future survey design to help reduce missing data. © 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.

Working hours and depressive symptomatology among full-time employees: Results from the fourth Korean National Health and Nutrition Examination Survey (2007-2009).

PubMed

Kim, Inah; Kim, Hyunjoo; Lim, Sinye; Lee, Mira; Bahk, Jinwook; June, Kyung Ja; Kim, Soyeon; Chang, Won Joon

2013-09-01

This study aimed to examine the distribution of working hours and the association between working hours and depressive symptomatology using representative data from a national, population-based survey. Data came from the fourth Korean National Health and Nutrition Examination Survey (2007-2009), which employed a systematic, stratified cluster-sampling method. We used logistic regression procedures to estimate the importance of weekly working hours as a predictor of depressive symptomatology. The prevalence of depressive symptomatology was 10.2%. The work week, which averaged 48.3 hours for the sample as a whole, was longer for men (49.8 hours) than women (45.3 hours), and 12.1% of respondents were engaged in shift work. In logistic regression analyses, compared to those working < 52 hours per week, the odds ratios (OR) of working hours as a predictor of depressive symptomatology were 1.19 [95% confidence interval (95% CI) 0.77-1.85] for those working 52-59 hours per week and 1.62 (95% CI 1.20-2.18) for those working ≥ 60 hours per week, after adjustment for demographic characteristics, health behaviors, socioeconomic status, employment status, and work schedules. It showed a positive dose-response relationship between working hours and depressive symptomatology (P = 0.0059). Working hours in Korea are long. There is an association between working hours and depressive symptomatology, and there seems be a trend in working hours and depressive symptomatology.

Precarious employment and health: analysis of the Comprehensive National Survey in Japan.

PubMed

Tsurugano, Shinobu; Inoue, Mariko; Yano, Eiji

2012-01-01

Recent studies suggest that unstable employment contracts may affect the health of workers. Many Japanese workers working full time in ostensibly permanent positions actually operate within unstable and precarious employment conditions. We compared the health status of Japanese workers with precarious employment contracts with that of permanent workers using the 2007 Comprehensive Survey of Living Conditions of the People on Health and Welfare (n=205,994). We classified their employment status as 'permanent' vs. 'precarious' (part-time, dispatch, or contract/non-regular) and compared their health conditions. Among both sexes, precarious workers were more likely than permanent workers to have poor self-rated health or more subjective symptoms, with more workers in full-time employment suffering from serious psychological distress (SPD) and more female workers who smoke. Using logistic regression, we identified a positive association between precarious employment and SPD and current smoking among workers engaged in full-time employment after adjusting for age, marital status, and work-related conditions. This study demonstrates that precarious employment contracts are associated with poor self-rated health, psychological distress, and tobacco use, especially among people working full-time jobs. These results suggest that engagement in full-time work under unstable employment status impairs workers' health.

Association Between Smartphone Use and Musculoskeletal Discomfort in Adolescent Students.

PubMed

Yang, Shang-Yu; Chen, Ming-De; Huang, Yueh-Chu; Lin, Chung-Ying; Chang, Jer-Hao

2017-06-01

Despite the substantial increase in the number of adolescent smartphone users, few studies have investigated the behavioural effects of smartphone use on adolescent students as it relates to musculoskeletal discomfort. The purpose of this study was to explore the association between smartphone use and musculoskeletal discomfort in students at a Taiwanese junior college. We hypothesised that the duration of smartphone use would be associated with increased instances of musculoskeletal discomfort in these students. This cross-sectional study employed a convenience sampling method to recruit students from a junior college in southern Taiwan. All the students (n = 315) were asked to answer questionnaires on smartphone use. A descriptive analysis, stepwise regression, and logistic regression were used to examine specific components of smartphone use and their relationship to musculoskeletal discomfort. Nearly half of the participants experienced neck and shoulder discomfort. The stepwise regression results indicated that the number of body parts with discomfort (F = 6.009, p < 0.05) increased with hours spent using ancillary smartphone functions. The logistic regression analysis showed that the students who talked on the phone >3 h/day had a higher risk of upper back discomfort than did those who talked on the phone <1 h/day [odds ratio (OR) = 4.23, p < 0.05]. This study revealed that the relationship between smartphone use and musculoskeletal discomfort is related to the duration of smartphone ancillary function use. Moreover, hours spent talking on the phone was a predictor of upper back discomfort.

Mixed conditional logistic regression for habitat selection studies.

PubMed

Duchesne, Thierry; Fortin, Daniel; Courbin, Nicolas

2010-05-01

1. Resource selection functions (RSFs) are becoming a dominant tool in habitat selection studies. RSF coefficients can be estimated with unconditional (standard) and conditional logistic regressions. While the advantage of mixed-effects models is recognized for standard logistic regression, mixed conditional logistic regression remains largely overlooked in ecological studies. 2. We demonstrate the significance of mixed conditional logistic regression for habitat selection studies. First, we use spatially explicit models to illustrate how mixed-effects RSFs can be useful in the presence of inter-individual heterogeneity in selection and when the assumption of independence from irrelevant alternatives (IIA) is violated. The IIA hypothesis states that the strength of preference for habitat type A over habitat type B does not depend on the other habitat types also available. Secondly, we demonstrate the significance of mixed-effects models to evaluate habitat selection of free-ranging bison Bison bison. 3. When movement rules were homogeneous among individuals and the IIA assumption was respected, fixed-effects RSFs adequately described habitat selection by simulated animals. In situations violating the inter-individual homogeneity and IIA assumptions, however, RSFs were best estimated with mixed-effects regressions, and fixed-effects models could even provide faulty conclusions. 4. Mixed-effects models indicate that bison did not select farmlands, but exhibited strong inter-individual variations in their response to farmlands. Less than half of the bison preferred farmlands over forests. Conversely, the fixed-effect model simply suggested an overall selection for farmlands. 5. Conditional logistic regression is recognized as a powerful approach to evaluate habitat selection when resource availability changes. This regression is increasingly used in ecological studies, but almost exclusively in the context of fixed-effects models. Fitness maximization can imply differences in trade-offs among individuals, which can yield inter-individual differences in selection and lead to departure from IIA. These situations are best modelled with mixed-effects models. Mixed-effects conditional logistic regression should become a valuable tool for ecological research.

Advanced colorectal neoplasia risk stratification by penalized logistic regression.

PubMed

Lin, Yunzhi; Yu, Menggang; Wang, Sijian; Chappell, Richard; Imperiale, Thomas F

2016-08-01

Colorectal cancer is the second leading cause of death from cancer in the United States. To facilitate the efficiency of colorectal cancer screening, there is a need to stratify risk for colorectal cancer among the 90% of US residents who are considered "average risk." In this article, we investigate such risk stratification rules for advanced colorectal neoplasia (colorectal cancer and advanced, precancerous polyps). We use a recently completed large cohort study of subjects who underwent a first screening colonoscopy. Logistic regression models have been used in the literature to estimate the risk of advanced colorectal neoplasia based on quantifiable risk factors. However, logistic regression may be prone to overfitting and instability in variable selection. Since most of the risk factors in our study have several categories, it was tempting to collapse these categories into fewer risk groups. We propose a penalized logistic regression method that automatically and simultaneously selects variables, groups categories, and estimates their coefficients by penalizing the [Formula: see text]-norm of both the coefficients and their differences. Hence, it encourages sparsity in the categories, i.e. grouping of the categories, and sparsity in the variables, i.e. variable selection. We apply the penalized logistic regression method to our data. The important variables are selected, with close categories simultaneously grouped, by penalized regression models with and without the interactions terms. The models are validated with 10-fold cross-validation. The receiver operating characteristic curves of the penalized regression models dominate the receiver operating characteristic curve of naive logistic regressions, indicating a superior discriminative performance. © The Author(s) 2013.

Using Logistic Regression To Predict the Probability of Debris Flows Occurring in Areas Recently Burned By Wildland Fires

USGS Publications Warehouse

Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.

2003-01-01

Logistic regression was used to predict the probability of debris flows occurring in areas recently burned by wildland fires. Multiple logistic regression is conceptually similar to multiple linear regression because statistical relations between one dependent variable and several independent variables are evaluated. In logistic regression, however, the dependent variable is transformed to a binary variable (debris flow did or did not occur), and the actual probability of the debris flow occurring is statistically modeled. Data from 399 basins located within 15 wildland fires that burned during 2000-2002 in Colorado, Idaho, Montana, and New Mexico were evaluated. More than 35 independent variables describing the burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows were delineated from National Elevation Data using a Geographic Information System (GIS). (2) Data describing the burn severity, geology, land surface gradient, rainfall, and soil properties were determined for each basin. These data were then downloaded to a statistics software package for analysis using logistic regression. (3) Relations between the occurrence/non-occurrence of debris flows and burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated and several preliminary multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combination produced the most effective model. The multivariate model that best predicted the occurrence of debris flows was selected. (4) The multivariate logistic regression model was entered into a GIS, and a map showing the probability of debris flows was constructed. The most effective model incorporates the percentage of each basin with slope greater than 30 percent, percentage of land burned at medium and high burn severity in each basin, particle size sorting, average storm intensity (millimeters per hour), soil organic matter content, soil permeability, and soil drainage. The results of this study demonstrate that logistic regression is a valuable tool for predicting the probability of debris flows occurring in recently-burned landscapes.

The association between alcohol use and depressive symptoms across socioeconomic status among 40- and 45-year-old Norwegian adults.

PubMed

Martinez, Priscilla; Neupane, Sudan Prasad; Perlestenbakken, Berit; Toutoungi, Christina; Bramness, Jørgen G

2015-11-19

Little population-based data among middle-aged adults exists examining the relationships between depressive symptoms, alcohol use, and socio-economic status (SES). This study aimed to describe the relationships between depressive symptoms and alcohol use at different levels of SES and to determine differences across SES levels among a population-based sample of 40 and 45 year old adults in Norway. This analysis was based on data from two Norwegian health studies conducted in 2000 and 2001, and included community-dwelling Norwegian men and women aged 40 and 45 years. Self-reported frequency and quantity of alcoholic drinks was used to calculate past-year typical quantity of drinks consumed and frequency of 5+ drinks per occasion, or heavy episodic drinking (HED). Depressive symptoms were assessed with the 10-item Hopkins Symptom Checklist, and SES was measured as education level and employment status. To observe the association between depressive symptoms and alcohol use at each level of SES we fitted multinomial logistic regression models using each alcohol outcome as a dependent variable stratified by level of education and employment. To observe differences across levels of SES, we examined the interaction between depressive symptoms and SES level in multinomial logistic regression models for each alcohol measures. Having depressive symptoms was significantly associated with an increased risk of 5+ typical drinks among people in the lowest (RRR = 1.60, p ≤ 0.05) education level, and not among people in the highest. Conversely, significant associations were observed among all levels of employment. For frequency of HED, depressive symptoms was not significantly associated with frequency of HED at any education level. Depressive symptoms was associated with 13+ past year HED episodes among people with no employment (RRR = 1.97, p ≤ 0.05), and part-time employment (RRR = 2.33, p ≤ 0.01), and no association was observed among people with full-time employment. A significant interaction was observed for depressive symptoms and employment for risk of 13+ past-year HED episodes. The results show a variety of associations between depressive symptoms and alcohol use among people with lower SES, and suggest type of alcohol use and SES measure may influence the observation of an association between depressive symptoms and alcohol use at different SES levels.

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis

PubMed Central

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Background: Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. Methods: In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. Results: The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Conclusion: Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended. PMID:26793655

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

PubMed

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

Seeking and securing work: Individual-level predictors of employment of psychiatric survivors.

PubMed

Hall, Peter V; Montgomery, Phyllis; Davie, Samantha; Dickins, Kevin; Forchuk, Cheryl; Jeng, Momodou S; Kersey, Melissa; Meier, Amanda; Lahey, Pam; Rudnick, Abraham; Solomon, Michelle; Warner, Laura

2015-01-01

For people with mental illness (psychiatric survivors), seeking and securing employment involves personal, social, and environmental factors. In Canada, psychiatric survivors are under-represented in the workforce, and services can help by tailoring their supports to help make the most gains in employment. Determine whether individual socio-demographic and health factors predict seeking and securing employment among psychiatric survivors. A community sample of psychiatric survivors from a Southwestern Ontario region participated in this study. Stepwise logistic regression was used to analyze data from 363 participants who had completed a variety of questionnaires to ascertain individual characteristics and employment outcomes. Health service utilization, living circumstances, homelessness, substance use issues, general health, social integration, ethnicity, having children under 18, and being a student emerged as significant predictors of seeking and securing work. Other commonly accepted human capital indicators, such as education and age, were not predictive of employment search behavior and outcomes. Individual characteristics that predict employment search and success outcomes for psychiatric survivors include aspects related to treatment and living circumstances, which stands in contrast to predictors of employment for the general population, suggesting that employment support services may need to be tailored to psychiatric survivors specifically.

Employment and insurance outcomes and factors associated with employment among long-term thyroid cancer survivors: a population-based study from the PROFILES registry.

PubMed

Tamminga, S J; Bültmann, U; Husson, O; Kuijpens, J L P; Frings-Dresen, M H W; de Boer, A G E M

2016-04-01

To obtain insight into employment and insurance outcomes of thyroid cancer survivors and to examine the association between not having employment and other factors including quality of life. In this cross-sectional population-based study, long-term thyroid cancer survivors from the Netherlands participated. Clinical data were collected from the cancer registry. Information on employment, insurance, socio-demographic characteristics, long-term side effects, and quality of life was collected with questionnaires. Of the 223 cancer survivors (response rate 87 %), 71 % were employed. Of the cancer survivors who tried to obtain insurance, 6 % reported problems with obtaining health care insurance, 62 % with life insurance, and 16 % with a mortgage. In a multivariate logistic regression analysis, higher age (OR 1.07, CI 1.02-1.11), higher level of fatigue (OR 1.07, CI 1.01-1.14), and lower educational level (OR 3.22, CI 1.46-7.09) were associated with not having employment. Employment was associated with higher quality of life. Many thyroid cancer survivors face problems when obtaining a life insurance, and older, fatigued, and lower educated thyroid cancer survivors may be at risk for not having employment.

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.

Predictors of course in obsessive-compulsive disorder: logistic regression versus Cox regression for recurrent events.

PubMed

Kempe, P T; van Oppen, P; de Haan, E; Twisk, J W R; Sluis, A; Smit, J H; van Dyck, R; van Balkom, A J L M

2007-09-01

Two methods for predicting remissions in obsessive-compulsive disorder (OCD) treatment are evaluated. Y-BOCS measurements of 88 patients with a primary OCD (DSM-III-R) diagnosis were performed over a 16-week treatment period, and during three follow-ups. Remission at any measurement was defined as a Y-BOCS score lower than thirteen combined with a reduction of seven points when compared with baseline. Logistic regression models were compared with a Cox regression for recurrent events model. Logistic regression yielded different models at different evaluation times. The recurrent events model remained stable when fewer measurements were used. Higher baseline levels of neuroticism and more severe OCD symptoms were associated with a lower chance of remission, early age of onset and more depressive symptoms with a higher chance. Choice of outcome time affects logistic regression prediction models. Recurrent events analysis uses all information on remissions and relapses. Short- and long-term predictors for OCD remission show overlap.

Estimating the exceedance probability of rain rate by logistic regression

NASA Technical Reports Server (NTRS)

Chiu, Long S.; Kedem, Benjamin

1990-01-01

Recent studies have shown that the fraction of an area with rain intensity above a fixed threshold is highly correlated with the area-averaged rain rate. To estimate the fractional rainy area, a logistic regression model, which estimates the conditional probability that rain rate over an area exceeds a fixed threshold given the values of related covariates, is developed. The problem of dependency in the data in the estimation procedure is bypassed by the method of partial likelihood. Analyses of simulated scanning multichannel microwave radiometer and observed electrically scanning microwave radiometer data during the Global Atlantic Tropical Experiment period show that the use of logistic regression in pixel classification is superior to multiple regression in predicting whether rain rate at each pixel exceeds a given threshold, even in the presence of noisy data. The potential of the logistic regression technique in satellite rain rate estimation is discussed.

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.

Comparison of naïve Bayes and logistic regression for computer-aided diagnosis of breast masses using ultrasound imaging

NASA Astrophysics Data System (ADS)

Cary, Theodore W.; Cwanger, Alyssa; Venkatesh, Santosh S.; Conant, Emily F.; Sehgal, Chandra M.

2012-03-01

This study compares the performance of two proven but very different machine learners, Naïve Bayes and logistic regression, for differentiating malignant and benign breast masses using ultrasound imaging. Ultrasound images of 266 masses were analyzed quantitatively for shape, echogenicity, margin characteristics, and texture features. These features along with patient age, race, and mammographic BI-RADS category were used to train Naïve Bayes and logistic regression classifiers to diagnose lesions as malignant or benign. ROC analysis was performed using all of the features and using only a subset that maximized information gain. Performance was determined by the area under the ROC curve, Az, obtained from leave-one-out cross validation. Naïve Bayes showed significant variation (Az 0.733 +/- 0.035 to 0.840 +/- 0.029, P < 0.002) with the choice of features, but the performance of logistic regression was relatively unchanged under feature selection (Az 0.839 +/- 0.029 to 0.859 +/- 0.028, P = 0.605). Out of 34 features, a subset of 6 gave the highest information gain: brightness difference, margin sharpness, depth-to-width, mammographic BI-RADs, age, and race. The probabilities of malignancy determined by Naïve Bayes and logistic regression after feature selection showed significant correlation (R2= 0.87, P < 0.0001). The diagnostic performance of Naïve Bayes and logistic regression can be comparable, but logistic regression is more robust. Since probability of malignancy cannot be measured directly, high correlation between the probabilities derived from two basic but dissimilar models increases confidence in the predictive power of machine learning models for characterizing solid breast masses on ultrasound.

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

PubMed

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

2015-05-12

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

Variable Selection in Logistic Regression.

DTIC Science & Technology

1987-06-01

23 %. AUTIOR(.) S. CONTRACT OR GRANT NUMBE Rf.i %Z. D. Bai, P. R. Krishnaiah and . C. Zhao F49620-85- C-0008 " PERFORMING ORGANIZATION NAME AND AOORESS...d I7 IOK-TK- d 7 -I0 7’ VARIABLE SELECTION IN LOGISTIC REGRESSION Z. D. Bai, P. R. Krishnaiah and L. C. Zhao Center for Multivariate Analysis...University of Pittsburgh Center for Multivariate Analysis University of Pittsburgh Y !I VARIABLE SELECTION IN LOGISTIC REGRESSION Z- 0. Bai, P. R. Krishnaiah

Predicting the effect of disability on employment status and income.

PubMed

Randolph, Diane Smith

2004-01-01

Research shows that participation in employment contributes to life satisfaction for persons with disabilities [18]. Title I of the Americans with Disabilities Act (ADA) sought to prohibit discrimination against persons with disabilities in the workplace, however, the ADA's effectiveness remains controversial. This research utilizes data from the disability supplement of the 2000 Behavioral Risk Factor Surveillance System to examine the impact of disability status on predicting employment status and income. Confounding variables such as gender, age, educational level, race and marital/parental status are examined regarding their influence on results. Results from analysis utilizing zero-order correlation, linear and logistic regression analysis techniques revealed that disability status has a significant predictive effect on inability to work. Furthermore, results continue to show that despite legislation, the higher the level of disability, the lower the employment status (those employed for wages) and income. Finally, disability status, coupled with being female or decreased educational level, consistently shows significance in predicting lower employment status and income than men or non-minorities with disabilities. Future research opportunities and policy implications are discussed with regard to the results presented.

In-school service predictors of employment for individuals with intellectual disability.

PubMed

Park, Jiyoon; Bouck, Emily

2018-06-01

Although there are many secondary data analyses of the National Longitudinal Transition Study-2 (NLTS-2) to investigate post-school outcome for students with disabilities, there has been a lack of research with in-school service predictors and post-school outcome for students with specific disability categories. This study was a secondary data analysis of NLTS-2 to investigate the relationship between current employment status and in-school services for individuals with intellectual disability. Statistical methods such as descriptive statistics and logistic regression were used to analyze NLTS-2 data set. The main findings included that in-school services were correlated with current employment status, and that primary disability (i.e., mild intellectual disability and moderate/severe intellectual disability) was associated with current employment status. In-school services are critical in predicting current employment for individuals with intellectual disability. Also, data suggest additional research is needed to investigate various in-school services and variables that could predict employment differences between individuals with mild and moderate/severe intellectual disability. Copyright © 2018 Elsevier Ltd. All rights reserved.

Family and Market: Nonagricultural Employment in Rural China.

PubMed

Song, Jing; Logan, John

2010-01-01

This study relies on the 2005 wave of Chinese General Social Survey (CGSS) to investigate nonagricultural employment in rural China. Given China's move away from collective agriculture, households began to act as the basic unit of production, which allows some peasants to leave the family farm, enter the wage sector or run private business. The first model runs logistic regressions to estimate the type of employment for individual men and women in a married couple, and the second model is conducted at the couple level to estimate the likelihood of four outcomes: both spouses, neither spouse, or one spouse (husband or wife) in nonagricultural jobs. Both models reveal that better educated persons are more likely to be engaged in nonagricultural work. Women's employment is more responsive to the presence of grandparents and young children in the household, yet "young" grandparents and "old" grandparents make a difference. At the market level, local geographic, economic and labor force conditions of the village also play an important role in shaping family employment patterns, and the eastern and central regions illustrate a higher likelihood of nonagricultural employment than the western region.

Multinomial Logistic Regression Predicted Probability Map To Visualize The Influence Of Socio-Economic Factors On Breast Cancer Occurrence in Southern Karnataka

NASA Astrophysics Data System (ADS)

Madhu, B.; Ashok, N. C.; Balasubramanian, S.

2014-11-01

Multinomial logistic regression analysis was used to develop statistical model that can predict the probability of breast cancer in Southern Karnataka using the breast cancer occurrence data during 2007-2011. Independent socio-economic variables describing the breast cancer occurrence like age, education, occupation, parity, type of family, health insurance coverage, residential locality and socioeconomic status of each case was obtained. The models were developed as follows: i) Spatial visualization of the Urban- rural distribution of breast cancer cases that were obtained from the Bharat Hospital and Institute of Oncology. ii) Socio-economic risk factors describing the breast cancer occurrences were complied for each case. These data were then analysed using multinomial logistic regression analysis in a SPSS statistical software and relations between the occurrence of breast cancer across the socio-economic status and the influence of other socio-economic variables were evaluated and multinomial logistic regression models were constructed. iii) the model that best predicted the occurrence of breast cancer were identified. This multivariate logistic regression model has been entered into a geographic information system and maps showing the predicted probability of breast cancer occurrence in Southern Karnataka was created. This study demonstrates that Multinomial logistic regression is a valuable tool for developing models that predict the probability of breast cancer Occurrence in Southern Karnataka.

Modelling of binary logistic regression for obesity among secondary students in a rural area of Kedah

NASA Astrophysics Data System (ADS)

Kamaruddin, Ainur Amira; Ali, Zalila; Noor, Norlida Mohd.; Baharum, Adam; Ahmad, Wan Muhamad Amir W.

2014-07-01

Logistic regression analysis examines the influence of various factors on a dichotomous outcome by estimating the probability of the event's occurrence. Logistic regression, also called a logit model, is a statistical procedure used to model dichotomous outcomes. In the logit model the log odds of the dichotomous outcome is modeled as a linear combination of the predictor variables. The log odds ratio in logistic regression provides a description of the probabilistic relationship of the variables and the outcome. In conducting logistic regression, selection procedures are used in selecting important predictor variables, diagnostics are used to check that assumptions are valid which include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers and a test statistic is calculated to determine the aptness of the model. This study used the binary logistic regression model to investigate overweight and obesity among rural secondary school students on the basis of their demographics profile, medical history, diet and lifestyle. The results indicate that overweight and obesity of students are influenced by obesity in family and the interaction between a student's ethnicity and routine meals intake. The odds of a student being overweight and obese are higher for a student having a family history of obesity and for a non-Malay student who frequently takes routine meals as compared to a Malay student.

Understanding logistic regression analysis.

PubMed

Sperandei, Sandro

2014-01-01

Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.

Factors affecting employment outcomes for people with disabilities who received Disability Employment Services in Taiwan.

PubMed

Jang, Yuh; Wang, Yun-Tung; Lin, Meng-Hsiu

2014-03-01

One of the most important rehabilitation goals is to return people with disabilities to paid employment. The purposes of this study were (1) to explore employment status and (2) to identify factors that may affect the employment outcomes of people with disabilities who received Disability Employment Services (DES). A retrospective study was conducted on clients who commenced and closed DES between January 2008 and December 2010 in a metropolitan city in Taiwan, using the files from the National Vocational Rehabilitation Services Documentary System. Sixty-nine percent (1,684 out of 2,452) of the clients in this study were engaged in paid employment after receiving DES. Logistic regression analyses indicated that clients with no psychiatric disability or mild impairment and with useful vocational qualifications, typical work experience, more post-employment services, and less pre-employment services were associated with a higher rate of successful employment outcomes. This study provides empirical evidence of the association between person- and DES-related factors and the employment outcomes of people with disabilities. Future improvements in health, school-to-work transition services, and vocational rehabilitation for people with disabilities should place more emphasis on providing work-based work experience, professional vocational training, access to college/professional education, career exploration, effective supported employment services, and other post-employment services.

Predicting Employment in the Mental Health Treatment Study: Do Client Factors Matter?

PubMed

Metcalfe, Justin D; Drake, Robert E; Bond, Gary R

2017-05-01

For people with psychiatric disabilities, demographic characteristics and measures of clinical status are often used to allocate scarce employment services. This study examined a battery of potential client predictors of competitive employment, testing the hypothesis that evidence-based supported employment would mitigate the negative effects of poor work history, uncontrolled symptoms, substance abuse, and other client factors. In a secondary analysis of 2055 unemployed Social Security Disability Insurance beneficiaries with schizophrenia or affective disorders, we examined 20 baseline client factors as predictors of competitive employment. The analysis used logistic regression to identify significant client predictors and then examined interactions between significant predictors and receipt of evidence-based supported employment. Work history was a strong predictor of employment, and other client measures (fewer years on disability rolls, Hispanic ethnicity, and fewer physical health problems) were modestly predictive. Evidence-based supported employment mitigated negative client factors, including poor work history. Participants with a poor work history benefitted from supported employment even more than those with a recent work experience. Evidence-based supported employment helps people with serious mental illness, especially those with poor job histories, to obtain competitive employment. Factors commonly considered barriers to employment, such as diagnosis, substance use, hospitalization history, and misconceptions about disability benefits, often have little or no impact on competitive employment outcomes.

Comparing Methodologies for Developing an Early Warning System: Classification and Regression Tree Model versus Logistic Regression. REL 2015-077

ERIC Educational Resources Information Center

Koon, Sharon; Petscher, Yaacov

2015-01-01

The purpose of this report was to explicate the use of logistic regression and classification and regression tree (CART) analysis in the development of early warning systems. It was motivated by state education leaders' interest in maintaining high classification accuracy while simultaneously improving practitioner understanding of the rules by…

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.

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.

Correlates of consistent condom use among men who have sex with men recruited through the Internet in Huzhou city: a cross-sectional survey.

PubMed

Jin, Meihua; Yang, Zhongrong; Dong, Zhengquan; Han, Jiankang

2013-12-01

There is growing evidence that men who have sex with men (MSM) are currently a group at high risk of HIV infection in China. Our study aims to know the factors affecting consistent condom use among MSM recruited through the internet in Huzhou city. An anonymous cross-sectional study was conducted by recruiting 410 MSM living in Huzhou city via the Internet. The socio-demographic profiles (age, education level, employment status, etc.) and sexual risk behaviors of the respondents were investigated. Bivariate logistic regression analyses were performed to compare the differences between consistent condom users and inconsistent condom users. Variables with significant bivariate between groups' differences were used as candidate variables in a stepwise multivariate logistic regression model. All statistical analyses were performed using SPSS for Windows 17.0, and a p value < 0.05 was considered to be statistically significant. According to their condom use, sixty-eight respondents were classified into two groups. One is consistent condom users, and the other is inconsistent condom users. Multivariate logistic regression showed that respondents who had a comprehensive knowledge of HIV (OR = 4.08, 95% CI: 1.85-8.99), who had sex with male sex workers (OR = 15.30, 95% CI: 5.89-39.75) and who had not drunk alcohol before sex (OR = 3.10, 95% CI: 1.38-6.95) were more likely to be consistent condom users. Consistent condom use among MSM was associated with comprehensive knowledge of HIV and a lack of alcohol use before sexual contact. As a result, reducing alcohol consumption and enhancing education regarding the risks of HIV among sexually active MSM would be effective in preventing of HIV transmission.

Race-ethnicity and poverty after spinal cord injury.

PubMed

Krause, J S; Dismuke, C E; Acuna, J; Sligh-Conway, C; Walker, E; Washington, K; Reed, K S

2014-02-01

Secondary analysis of existing data. Our objective was to examine the relationship between race-ethnicity and poverty status after spinal cord injury (SCI). A large specialty hospital in the southeastern United States. Participants were 2043 adults with traumatic SCI in the US. Poverty status was measured using criteria from the US Census Bureau. Whereas only 14% of non-Hispanic White participants were below the poverty level, 41.3% of non-Hispanic Blacks were in poverty. Logistic regression with three different models identified several significant predictors of poverty, including marital status, years of education, level of education, age and employment status. Non-Hispanic Blacks had 2.75 greater odds of living in poverty after controlling for other factors, including education and employment. We may need to consider quality of education and employment to better understand the elevated risk of poverty among non-Hispanic Blacks in the US.

The Impact of Physical Work Demands on Need for Recovery, Employment Status, Retirement Intentions, and Ability to Extend Working Careers: A Longitudinal Study Among Older Workers.

PubMed

Gommans, Fleur G; Jansen, Nicole W H; Mackey, Martin G; Stynen, Dave; de Grip, Andries; Kant, I Jmert

2016-04-01

Prospectively investigating whether different approaches of physical work demands are associated with need for recovery (NFR), employment status, retirement intentions, and ability to prolong working life among older employees from the industry and health care sector. A subsample from the Maastricht Cohort Study was studied (n = 1126). Poisson, Cox, and logistic regression analyses were performed to investigate outcomes. Perceiving physical work demands as strenuous was associated with higher NFR. Continuous physical strain was associated with being out of employment 4 years later. Employees with the highest amount of physical work demands perceived they were less able to prolong working life, although no significant associations between physical work demands and retirement intentions were found. Overall, physical work demands were associated with adverse outcomes, with divergent insights for the different approaches of physical work demands.

Characteristics associated with non-disclosure of Type 2 diabetes at work.

PubMed

Olesen, K; Cleal, B; Skinner, T; Willaing, I

2017-08-01

To explore factors associated with non-disclosure of Type 2 diabetes to employers among Danish workers with Type 2 diabetes. A total of 705 workers with Type 2 diabetes completed a Danish cross-sectional survey. Logistic regression models were used to estimate the associations between background characteristics and probability of non-disclosure of diabetes to the employer. The models were mutually adjusted for background characteristics, socioeconomic-, diabetes- and work-related factors. Among the participants, 23% had not disclosed their Type 2 diabetes to their current employer. Non-disclosure was associated with more sickness absence, more years with diabetes, greater use of diabetic medication, higher educational level and a perception of not being respected by superior. Personal traits such as gender, age and well-being were not associated with disclosure. Among the feasible targets for interventions, good psychosocial work environment was associated with disclosure. © 2017 Diabetes UK.

Brief Report: Vocational Outcomes for Young Adults with Autism Spectrum Disorders at Six Months After Virtual Reality Job Interview Training

PubMed Central

Fleming, Michael F.; Wright, Michael A.; Losh, Molly; Boteler Humm, Laura; Olsen, Dale; Bell, Morris D.

2016-01-01

Young adults with high-functioning autism spectrum disorder (ASD) have low employment rates and job interviewing presents a critical barrier to employment for them. Results from a prior randomized controlled efficacy trial suggested virtual reality job interview training (VR-JIT) improved interviewing skills among trainees with ASD, but not controls with ASD. We conducted a brief survey with 23 of 26 participants from this study to evaluate their vocational outcomes at 6-month follow-up with a focus on whether or not they attained a competitive position (employment or competitive volunteering). Logistic regression indicated VR-JIT trainees had greater odds of attaining a competitive position than controls (OR 7.82, p < 0.05). Initial evidence suggests VR-JIT is a promising intervention that enhances vocational outcomes among young adults with high-functioning ASD. PMID:25986176

Brief report: vocational outcomes for young adults with autism spectrum disorders at six months after virtual reality job interview training.

PubMed

Smith, Matthew J; Fleming, Michael F; Wright, Michael A; Losh, Molly; Humm, Laura Boteler; Olsen, Dale; Bell, Morris D

2015-10-01

Young adults with high-functioning autism spectrum disorder (ASD) have low employment rates and job interviewing presents a critical barrier to employment for them. Results from a prior randomized controlled efficacy trial suggested virtual reality job interview training (VR-JIT) improved interviewing skills among trainees with ASD, but not controls with ASD. We conducted a brief survey with 23 of 26 participants from this study to evaluate their vocational outcomes at 6-month follow-up with a focus on whether or not they attained a competitive position (employment or competitive volunteering). Logistic regression indicated VR-JIT trainees had greater odds of attaining a competitive position than controls (OR 7.82, p < 0.05). Initial evidence suggests VR-JIT is a promising intervention that enhances vocational outcomes among young adults with high-functioning ASD.

Health assessment of self-employed in the food service industry.

PubMed

Grégoris, Marina; Deschamps, Frédéric; Salles, Julie; Sanchez, Stéphane

2017-07-01

Objectives This study's objective was to assess the morbidity of self-employed workers in the food service industry, an industry with a large amount of occupational health risks. Methods A cross-sectional study, consisting of 437 participants, was conducted between 2011 and 2013 in Champagne-Ardenne, France. The health questionnaire included an interview, a clinical examination, and medical investigations. Results The study population consisted of 146 self-employed workers (not working for an employer) and 291 employees (working with employment contracts for an employer). Logistic regression analysis revealed that self-employed workers had a higher morbidity than employees, after adjusting for age (OR: 3.45; 95% CI: 1.28 to 9.25). Main adverse health conditions were joint pain (71.2% self-employed vs. 38.1% employees, p < 0.001), ear disorders (54.1% self-employed vs. 33.7%, employees, p < 0.001), and cardiovascular diseases (47.3% self-employed vs. 21% employees, p < 0.001). Conclusions The study highlights the need for occupational health services for self-employed workers in France so that they may benefit from prevention of occupational risks and health surveillance. Results were presented to the self-employed healthcare insurance fund in order to establish an occupational health risks prevention system.

Employment status transitions in employees with and without chronic disease in the Netherlands.

PubMed

de Boer, Angela G E M; Geuskens, Goedele A; Bültmann, Ute; Boot, Cécile R L; Wind, Haije; Koppes, Lando L J; Frings-Dresen, Monique H W

2018-07-01

Objectives were to: (1) longitudinally assess transitions in employment status of employees with and without chronic disease; and (2) assess predictors of exit from paid employment. Transitions in employment status at 1- and 2-year follow-up were assessed in a longitudinal cohort study of employees aged 15-63 years. Generalised estimating equations (GEE) and logistic regression analyses were performed to analyse differences in transitions and identify sociodemographic, health- and work-related predictors. At 1- and 2-year follow-up, 10,038 employees (37% with chronic disease) and 7636 employees responded. Employees with chronic disease had higher probability of leaving paid employment [OR 1.4 (1.1-1.6)] and unemployment, disability pension and early retirement. Employees without chronic disease had higher chance of moving into self-employment or study. At 2-year follow-up, employees with cardiovascular disease (15%), chronic mental disease (11%), diabetes (10%) and musculoskeletal disease (10%), had left paid employment most often. Higher age, poor health, burnout, low co-worker support and chronic disease limitations were predictors for leaving paid employment. Employees with chronic disease leave paid work more often for unfavourable work outcomes.

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

Expression of Proteins Involved in Epithelial-Mesenchymal Transition as Predictors of Metastasis and Survival in Breast Cancer Patients

DTIC Science & Technology

2013-11-01

Ptrend 0.78 0.62 0.75 Unconditional logistic regression was used to estimate odds ratios (OR) and 95 % confidence intervals (CI) for risk of node...Ptrend 0.71 0.67 Unconditional logistic regression was used to estimate odds ratios (OR) and 95 % confidence intervals (CI) for risk of high-grade tumors... logistic regression was used to estimate odds ratios (OR) and 95 % confidence intervals (CI) for the associations between each of the seven SNPs and

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

PubMed

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

2018-01-01

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

Quantifying discrimination of Framingham risk functions with different survival C statistics.

PubMed

Pencina, Michael J; D'Agostino, Ralph B; Song, Linye

2012-07-10

Cardiovascular risk prediction functions offer an important diagnostic tool for clinicians and patients themselves. They are usually constructed with the use of parametric or semi-parametric survival regression models. It is essential to be able to evaluate the performance of these models, preferably with summaries that offer natural and intuitive interpretations. The concept of discrimination, popular in the logistic regression context, has been extended to survival analysis. However, the extension is not unique. In this paper, we define discrimination in survival analysis as the model's ability to separate those with longer event-free survival from those with shorter event-free survival within some time horizon of interest. This definition remains consistent with that used in logistic regression, in the sense that it assesses how well the model-based predictions match the observed data. Practical and conceptual examples and numerical simulations are employed to examine four C statistics proposed in the literature to evaluate the performance of survival models. We observe that they differ in the numerical values and aspects of discrimination that they capture. We conclude that the index proposed by Harrell is the most appropriate to capture discrimination described by the above definition. We suggest researchers report which C statistic they are using, provide a rationale for their selection, and be aware that comparing different indices across studies may not be meaningful. Copyright © 2012 John Wiley & Sons, Ltd.

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.

Demand for Self-Employed Health Insurance.

PubMed

Emamgholipour, Sara; Arab, Mohammad; Ebrahimzadeh, Javad

2016-10-01

Health insurance provides financial support for health care expenditures. There are two types of health insurance: compulsory and voluntary. Voluntary health insurance can be divided into two categories: self-employed and supplementary. In this study, the main factors that affect the demand for self-employed health insurance in Iran were determined. In this cross-sectional study, data were derived from the 2013 Household Income and Expenditure Survey from the Statistical Center of Iran. Then, a logistic regression model was designed to determine the factors influencing health insurance demand. The age, income, and education level of the head of the household directly correlated with the demand for self-employed health insurance. There was no significant relationship between the demand for health insurance and the gender or marital status of the head of the household. In addition, there were no significant relationships between occupation or house ownership and the demand for health insurance in rural households. To promote voluntary health insurance, it is helpful to identify effective factors that stimulate the health insurance demand.

The alarming problems of confounding equivalence using logistic regression models in the perspective of causal diagrams.

PubMed

Yu, Yuanyuan; Li, Hongkai; Sun, Xiaoru; Su, Ping; Wang, Tingting; Liu, Yi; Yuan, Zhongshang; Liu, Yanxun; Xue, Fuzhong

2017-12-28

Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is, therefore, important to highlight the problems of logistic regression and search the alternative method. Four causal diagram models were defined to summarize confounding equivalence. Both theoretical proofs and simulation studies were performed to verify whether conditioning on different confounding equivalence sets had the same bias-reducing potential and then to select the optimum adjusting strategy, in which logistic regression model and inverse probability weighting based marginal structural model (IPW-based-MSM) were compared. The "do-calculus" was used to calculate the true causal effect of exposure on outcome, then the bias and standard error were used to evaluate the performances of different strategies. Adjusting for different sets of confounding equivalence, as judged by identical Markov boundaries, produced different bias-reducing potential in the logistic regression model. For the sets satisfied G-admissibility, adjusting for the set including all the confounders reduced the equivalent bias to the one containing the parent nodes of the outcome, while the bias after adjusting for the parent nodes of exposure was not equivalent to them. In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under IPW-based-MSM. Compared with logistic regression, the IPW-based-MSM could obtain unbiased causal effect estimation when the adjusted confounders satisfied G-admissibility and the optimal strategy was to adjust for the parent nodes of outcome, which obtained the highest precision. All adjustment strategies through logistic regression were biased for causal effect estimation, while IPW-based-MSM could always obtain unbiased estimation when the adjusted set satisfied G-admissibility. Thus, IPW-based-MSM was recommended to adjust for confounders set.

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.

Modeling Governance KB with CATPCA to Overcome Multicollinearity in the Logistic Regression

NASA Astrophysics Data System (ADS)

Khikmah, L.; Wijayanto, H.; Syafitri, U. D.

2017-04-01

The problem often encounters in logistic regression modeling are multicollinearity problems. Data that have multicollinearity between explanatory variables with the result in the estimation of parameters to be bias. Besides, the multicollinearity will result in error in the classification. In general, to overcome multicollinearity in regression used stepwise regression. They are also another method to overcome multicollinearity which involves all variable for prediction. That is Principal Component Analysis (PCA). However, classical PCA in only for numeric data. Its data are categorical, one method to solve the problems is Categorical Principal Component Analysis (CATPCA). Data were used in this research were a part of data Demographic and Population Survey Indonesia (IDHS) 2012. This research focuses on the characteristic of women of using the contraceptive methods. Classification results evaluated using Area Under Curve (AUC) values. The higher the AUC value, the better. Based on AUC values, the classification of the contraceptive method using stepwise method (58.66%) is better than the logistic regression model (57.39%) and CATPCA (57.39%). Evaluation of the results of logistic regression using sensitivity, shows the opposite where CATPCA method (99.79%) is better than logistic regression method (92.43%) and stepwise (92.05%). Therefore in this study focuses on major class classification (using a contraceptive method), then the selected model is CATPCA because it can raise the level of the major class model accuracy.

Effects of employment and education on preterm and full-term infant mortality in Korea.

PubMed

Ko, Y-J; Shin, S-H; Park, S M; Kim, H-S; Lee, J-Y; Kim, K H; Cho, B

2014-03-01

The infant mortality rate is a sensitive and commonly used indicator of the socio-economic status of a population. Generally, studies investigating the relationship between infant mortality and socio-economic status have focused on full-term infants in Western populations. This study examined the effects of education level and employment status on full-term and preterm infant mortality in Korea. Data were collected from the National Birth Registration Database and merged with data from the National Death Certification Database. Prospective cohort study. In total, 1,316,184 singleton births registered in Korea's National Birth Registration Database between January 2004 and December 2006 were included in the study. Multivariate logistic regression analysis was performed. Paternal and maternal education levels were inversely related to infant mortality in preterm and full-term infants following multivariate adjusted logistic models. Parental employment status was not associated with infant mortality in full-term infants, but was associated with infant mortality in preterm infants, after adjusting for place of birth, gender, marital status, paternal age, maternal age and parity. Low paternal and maternal education levels were found to be associated with infant mortality in both full-term and preterm infants. Low parental employment status was found to be associated with infant mortality in preterm infants but not in full-term infants. In order to reduce inequalities in infant mortality, public health interventions should focus on providing equal access to education. Copyright © 2013 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Factors contributing to employment patterns after liver transplantation.

PubMed

Beal, Eliza W; Tumin, Dmitry; Mumtaz, Khalid; Nau, Michael; Tobias, Joseph D; Hayes, Don; Washburn, Kenneth; Black, Sylvester M

2017-06-01

Many liver transplant recipients return to work, but their patterns of employment are unclear. We examine patterns of employment 5 years after liver transplantation. First-time liver transplant recipients ages 18-60 years transplanted from 2002 to 2009 and surviving at least 5 years were identified in the United Network for Organ Sharing registry. Recipients' post-transplant employment status was classified as follows: (i) never employed; (ii) returned to work within 2 years and remained employed (continuous employment); (iii) returned to work within 2 years, but was subsequently unemployed (intermittent employment); or (iv) returned to work ≥3 years post-transplant (delayed employment). Of 28 306 liver recipients identified during the study period, 12 998 survived at least 5 years and contributed at least 1 follow-up of employment status. A minority of patients (4654; 36%) were never employed, while 3780 (29%) were continuously employed, 3027 (23%) were intermittently employed, and 1537 (12%) had delayed employment. In multivariable logistic regression analysis, predictors of intermittent and delayed employment included lower socioeconomic status, higher local unemployment rates, and post-transplant comorbidities or complications. Never, intermittent, and delayed employment are common after liver transplantation. Socioeconomic and labor market characteristics may add to clinical factors that limit liver transplant recipients' continuous employment. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Logistic regression models of factors influencing the location of bioenergy and biofuels plants

Treesearch

T.M. Young; R.L. Zaretzki; J.H. Perdue; F.M. Guess; X. Liu

2011-01-01

Logistic regression models were developed to identify significant factors that influence the location of existing wood-using bioenergy/biofuels plants and traditional wood-using facilities. Logistic models provided quantitative insight for variables influencing the location of woody biomass-using facilities. Availability of "thinnings to a basal area of 31.7m2/ha...

Sample size adjustments for varying cluster sizes in cluster randomized trials with binary outcomes analyzed with second-order PQL mixed logistic regression.

PubMed

Candel, Math J J M; Van Breukelen, Gerard J P

2010-06-30

Adjustments of sample size formulas are given for varying cluster sizes in cluster randomized trials with a binary outcome when testing the treatment effect with mixed effects logistic regression using second-order penalized quasi-likelihood estimation (PQL). Starting from first-order marginal quasi-likelihood (MQL) estimation of the treatment effect, the asymptotic relative efficiency of unequal versus equal cluster sizes is derived. A Monte Carlo simulation study shows this asymptotic relative efficiency to be rather accurate for realistic sample sizes, when employing second-order PQL. An approximate, simpler formula is presented to estimate the efficiency loss due to varying cluster sizes when planning a trial. In many cases sampling 14 per cent more clusters is sufficient to repair the efficiency loss due to varying cluster sizes. Since current closed-form formulas for sample size calculation are based on first-order MQL, planning a trial also requires a conversion factor to obtain the variance of the second-order PQL estimator. In a second Monte Carlo study, this conversion factor turned out to be 1.25 at most. (c) 2010 John Wiley & Sons, Ltd.

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

Analysis of Feature Intervisibility and Cumulative Visibility Using GIS, Bayesian and Spatial Statistics: A Study from the Mandara Mountains, Northern Cameroon

PubMed Central

Wright, David K.; MacEachern, Scott; Lee, Jaeyong

2014-01-01

The locations of diy-geδ-bay (DGB) sites in the Mandara Mountains, northern Cameroon are hypothesized to occur as a function of their ability to see and be seen from points on the surrounding landscape. A series of geostatistical, two-way and Bayesian logistic regression analyses were performed to test two hypotheses related to the intervisibility of the sites to one another and their visual prominence on the landscape. We determine that the intervisibility of the sites to one another is highly statistically significant when compared to 10 stratified-random permutations of DGB sites. Bayesian logistic regression additionally demonstrates that the visibility of the sites to points on the surrounding landscape is statistically significant. The location of sites appears to have also been selected on the basis of lower slope than random permutations of sites. Using statistical measures, many of which are not commonly employed in archaeological research, to evaluate aspects of visibility on the landscape, we conclude that the placement of DGB sites improved their conspicuousness for enhanced ritual, social cooperation and/or competition purposes. PMID:25383883

Utilization of maternal health care services among indigenous women in Bangladesh: A study on the Mru tribe.

PubMed

Islam, Rakibul M

2017-01-01

Despite startling developments in maternal health care services, use of these services has been disproportionately distributed among different minority groups in Bangladesh. This study aimed to explore the factors associated with the use of these services among the Mru indigenous women in Bangladesh. A total of 374 currently married Mru women were interviewed using convenience sampling from three administrative sub-districts of the Bandarban district from June to August of 2009. Associations were assessed using Chi-square tests, and a binary logistic regression model was employed to explore factors associated with the use of maternal health care services. Among the women surveyed, 30% had ever visited maternal health care services in the Mru community, a very low proportion compared with mainstream society. Multivariable logistic regression analyses revealed that place of residence, religion, school attendance, place of service provided, distance to the service center, and exposure to mass media were factors significantly associated with the use of maternal health care services among Mru women. Considering indigenous socio-cultural beliefs and practices, comprehensive community-based outreach health programs are recommended in the community with a special emphasis on awareness through maternal health education and training packages for the Mru adolescents.

Refining the notion of maturing out: results from the national epidemiologic survey on alcohol and related conditions.

PubMed

Vergés, Alvaro; Haeny, Angela M; Jackson, Kristina M; Bucholz, Kathleen K; Grant, Julia D; Trull, Timothy J; Wood, Phillip K; Sher, Kenneth J

2013-12-01

Our aim was to determine if the decrease in drug use disorders with age is attributable to changes in persistence, as implied by the notion of maturing out. Also, we examined the association between role transitions and persistence, recurrence, and new onset of drug use disorders. We performed secondary analysis of the 2 waves of the National Epidemiologic Survey on Alcohol and Related Conditions data (baseline assessment 2001-2002, follow-up conducted 2004-2005). We conducted logistic regressions and multinomial logistic regression to determine the effect of age on wave 2 diagnosis status, as well as the interaction between age and role transitions. Rates of persistence were stable over the life span, whereas rates of new onset and recurrence decreased with age. Changes in parenthood, marital, and employment status were associated with persistence, new onset, and recurrence. We found an interaction between marital status and age. Our findings challenge commonly held notions that the age-related decrease in drug use disorders is attributable to an increase in persistence, and that the effects of role transitions are stronger during young, compared with middle and older, adulthood.

Discrete post-processing of total cloud cover ensemble forecasts

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Haiden, Thomas; Pappenberger, Florian

2017-04-01

This contribution presents an approach to post-process ensemble forecasts for the discrete and bounded weather variable of total cloud cover. Two methods for discrete statistical post-processing of ensemble predictions are tested. The first approach is based on multinomial logistic regression, the second involves a proportional odds logistic regression model. Applying them to total cloud cover raw ensemble forecasts from the European Centre for Medium-Range Weather Forecasts improves forecast skill significantly. Based on station-wise post-processing of raw ensemble total cloud cover forecasts for a global set of 3330 stations over the period from 2007 to early 2014, the more parsimonious proportional odds logistic regression model proved to slightly outperform the multinomial logistic regression model. Reference Hemri, S., Haiden, T., & Pappenberger, F. (2016). Discrete post-processing of total cloud cover ensemble forecasts. Monthly Weather Review 144, 2565-2577.

Fuzzy multinomial logistic regression analysis: A multi-objective programming approach

NASA Astrophysics Data System (ADS)

Abdalla, Hesham A.; El-Sayed, Amany A.; Hamed, Ramadan

2017-05-01

Parameter estimation for multinomial logistic regression is usually based on maximizing the likelihood function. For large well-balanced datasets, Maximum Likelihood (ML) estimation is a satisfactory approach. Unfortunately, ML can fail completely or at least produce poor results in terms of estimated probabilities and confidence intervals of parameters, specially for small datasets. In this study, a new approach based on fuzzy concepts is proposed to estimate parameters of the multinomial logistic regression. The study assumes that the parameters of multinomial logistic regression are fuzzy. Based on the extension principle stated by Zadeh and Bárdossy's proposition, a multi-objective programming approach is suggested to estimate these fuzzy parameters. A simulation study is used to evaluate the performance of the new approach versus Maximum likelihood (ML) approach. Results show that the new proposed model outperforms ML in cases of small datasets.

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.

A Primer on Logistic Regression.

ERIC Educational Resources Information Center

Woldbeck, Tanya

This paper introduces logistic regression as a viable alternative when the researcher is faced with variables that are not continuous. If one is to use simple regression, the dependent variable must be measured on a continuous scale. In the behavioral sciences, it may not always be appropriate or possible to have a measured dependent variable on a…

A Solution to Separation and Multicollinearity in Multiple Logistic Regression

PubMed Central

Shen, Jianzhao; Gao, Sujuan

2010-01-01

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

A Solution to Separation and Multicollinearity in Multiple Logistic Regression.

PubMed

Shen, Jianzhao; Gao, Sujuan

2008-10-01

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

[Influences of environmental factors and interaction of several chemokines gene-environmental on systemic lupus erythematosus].

PubMed

Ye, Dong-qing; Hu, Yi-song; Li, Xiang-pei; Huang, Fen; Yang, Shi-gui; Hao, Jia-hu; Yin, Jing; Zhang, Guo-qing; Liu, Hui-hui

2004-11-01

To explore the impact of environmental factors, daily lifestyle, psycho-social factors and the interactions between environmental factors and chemokines genes on systemic lupus erythematosus (SLE). Case-control study was carried out and environmental factors for SLE were analyzed by univariate and multivariate unconditional logistic regression. Interactions between environmental factors and chemokines polymorphism contributing to systemic lupus erythematosus were also analyzed by logistic regression model. There were nineteen factors associated with SLE when univariate unconditional logistic regression was used. However, when multivariate unconditional logistic regression was used, only five factors showed having impacts on the disease, in which drinking well water (OR=0.099) was protective factor for SLE, and multiple drug allergy (OR=8.174), over-exposure to sunshine (OR=18.339), taking antibiotics (OR=9.630) and oral contraceptives were risk factors for SLE. When unconditional logistic regression model was used, results showed that there was interaction between eating irritable food and -2518MCP-1G/G genotype (OR=4.387). No interaction between environmental factors was found that contributing to SLE in this study. Many environmental factors were related to SLE, and there was an interaction between -2518MCP-1G/G genotype and eating irritable food.

A deeper look at two concepts of measuring gene-gene interactions: logistic regression and interaction information revisited.

PubMed

Mielniczuk, Jan; Teisseyre, Paweł

2018-03-01

Detection of gene-gene interactions is one of the most important challenges in genome-wide case-control studies. Besides traditional logistic regression analysis, recently the entropy-based methods attracted a significant attention. Among entropy-based methods, interaction information is one of the most promising measures having many desirable properties. Although both logistic regression and interaction information have been used in several genome-wide association studies, the relationship between them has not been thoroughly investigated theoretically. The present paper attempts to fill this gap. We show that although certain connections between the two methods exist, in general they refer two different concepts of dependence and looking for interactions in those two senses leads to different approaches to interaction detection. We introduce ordering between interaction measures and specify conditions for independent and dependent genes under which interaction information is more discriminative measure than logistic regression. Moreover, we show that for so-called perfect distributions those measures are equivalent. The numerical experiments illustrate the theoretical findings indicating that interaction information and its modified version are more universal tools for detecting various types of interaction than logistic regression and linkage disequilibrium measures. © 2017 WILEY PERIODICALS, INC.

An examination of retention factors among registered nurses in Northeastern Ontario, Canada: Nurses intent to stay in their current position.

PubMed

Nowrouzi, Behdin; Rukholm, Ellen; Lariviere, Michel; Carter, Lorraine; Koren, Irene; Mian, Oxana; Giddens, Emilia

2016-03-10

The purpose of the study was to examine factors related to the retention of registered nurses in northeastern Ontario, Canada. A cross-sectional survey of registered nurses working in northeastern Ontario, Canada was conducted. Logistic regression analyses were used to consider intent to stay in current employment in relation to the following: 1) demographic factors, and 2) occupation and career satisfaction factors. A total of 459 (29.8% response rate) questionnaires were completed. The adjusted odds logistic regression analysis of RNs who intended to remain in their current position for the next five years, demonstrated that respondents in the 46 to 56 age group (OR: 2.65; 95% CI: 1.50 to 4.69), the importance of staff development in the organization (OR: 3.04; 95% CI: 1.13 to 8.13) northeastern Ontario lifestyle (OR: 2.61; 95% CI: 1.55 to 4.40), working in nursing for 14 to 22.5 years (OR: 2.55; 95% CI: 1.10 to 5.93), and working between 0 to 1 hour of overtime per week (OR: 1.20; 95% CI: 1.20 to 4.64) were significant factors in staying in their current position for the next five years. This study shows that a further understanding of the work environment could assist with developing retention for rural nurses. Furthermore, employers may use such information to ameliorate the working conditions of nurses, while researchers may use such evidence to develop interventions that are applicable to improving the working conditions of nurses.

Self-reported HIV antibody testing among Latino urban day laborers.

PubMed

Solorio, Maria Rosa; Galvan, Frank H

2009-12-01

To identify the characteristics of male Latino urban day laborers who self-report having tested for human immunodeficiency virus (HIV). A cross-sectional survey was conducted with 356 Latino day laborers, aged 18 to 40 years, who had been sexually active in the previous 12 months, from 6 day labor sites in the City of Los Angeles. Most of the men were single, mainly from Mexico and Guatemala, and had been employed as a day laborer for fewer than 3 years; 38% had an annual income of $4000 or less. Ninety-two percent of the men reported having sex with women only, and 8% reported a history of having sex with men and women. Forty-six percent had received an HIV test in the previous 12 months and 1 person tested positive. In univariate logistic regression analyses, day laborers who were aged 26 years or older, had more than 3 years in the United States, had more than 1 year but fewer than 5 years employed as a day laborer, and had annual incomes greater than $4000 were significantly more likely to self-report HIV testing in the previous 12 months. In a multivariate logistic regression analysis, only higher annual income was found to be significantly associated with self-reported HIV testing. Interventions that target lower-income Latino day laborers are needed to promote early HIV detection. HIV detection offers individual benefits through treatment, with decreased morbidity and mortality, as well as public health benefits through decreased rates of HIV transmission in the community.

The characteristics of non-respondents and respondents of a mental health survey among evacuees in a disaster: The Fukushima Health Management Survey

PubMed Central

Horikoshi, Naoko; Iwasa, Hajime; Yasumura, Seiji; Maeda, Masaharu

2017-01-01

Abstract The Fukushima Medical University conducted a mental health care program for evacuees after the Fukushima Daiichi nuclear power plant accident. However, the mental health status of non-respondents has not been considered for surveys using questionnaires. Therefore, the aim of this study was to clarify the characteristics of non-respondents and respondents. The target population of the survey (FY2011-2013) is people living in the nationally designated evacuation zone of Fukushima prefecture. Among these, the participants were 967 people (20 years or older). We examined factors that affected the difference between the groups of participants (i.e., non-respondents and respondents) using multivariate logistic regression analysis. Employment was higher in non-respondents (p=0.022) and they were also more socially isolated (p=0.047) when compared to respondents; non-respondents had a higher proportional risk of psychological distress compared to respondents (p<0.033). The results of the multivariate logistic regression analysis showed that, within the participants there was a significant association between employment status (OR=1.99, 95% confidence interval [CI]:1.12-3.51) and psychological distress (OR=2.17, 95% CI: 1.01-4.66). We found that non-respondents had a significantly higher proportion of psychological distress compared to the respondents. Although the non-respondents were the high-risk group, it is not possible to grasp the complexity of the situation by simply using questionnaire surveys. Therefore, in the future it is necessary to direct our efforts towards the mental health of non-respondents and respondents alike. PMID:29237989

The characteristics of non-respondents and respondents of a mental health survey among evacuees in a disaster: The Fukushima Health Management Survey.

PubMed

Horikoshi, Naoko; Iwasa, Hajime; Yasumura, Seiji; Maeda, Masaharu

2017-12-19

The Fukushima Medical University conducted a mental health care program for evacuees after the Fukushima Daiichi nuclear power plant accident. However, the mental health status of non-respondents has not been considered for surveys using questionnaires. Therefore, the aim of this study was to clarify the characteristics of non-respondents and respondents. The target population of the survey (FY2011-2013) is people living in the nationally designated evacuation zone of Fukushima prefecture. Among these, the participants were 967 people (20 years or older). We examined factors that affected the difference between the groups of participants (i.e., non-respondents and respondents) using multivariate logistic regression analysis. Employment was higher in non-respondents (p=0.022) and they were also more socially isolated (p=0.047) when compared to respondents; non-respondents had a higher proportional risk of psychological distress compared to respondents (p<0.033). The results of the multivariate logistic regression analysis showed that, within the participants there was a significant association between employment status (OR=1.99, 95% confidence interval [CI]:1.12-3.51) and psychological distress (OR=2.17, 95% CI:1.01-4.66). We found that non-respondents had a significantly higher proportion of psychological distress compared to the respondents. Although the non-respondents were the high-risk group, it is not possible to grasp the complexity of the situation by simply using questionnaire surveys. Therefore, in the future it is necessary to direct our efforts towards the mental health of non-respondents and respondents alike.

Controlling Type I Error Rates in Assessing DIF for Logistic Regression Method Combined with SIBTEST Regression Correction Procedure and DIF-Free-Then-DIF Strategy

ERIC Educational Resources Information Center

Shih, Ching-Lin; Liu, Tien-Hsiang; Wang, Wen-Chung

2014-01-01

The simultaneous item bias test (SIBTEST) method regression procedure and the differential item functioning (DIF)-free-then-DIF strategy are applied to the logistic regression (LR) method simultaneously in this study. These procedures are used to adjust the effects of matching true score on observed score and to better control the Type I error…

Work stress, asthma control and asthma-specific quality of life: Initial evidence from a cross-sectional study.

PubMed

Hartmann, Bettina; Leucht, Verena; Loerbroks, Adrian

2017-03-01

Research has suggested that psychological stress is positively associated with asthma morbidity. One major source of stress in adulthood is one's occupation. However, to date, potential links of work stress with asthma control or asthma-specific quality of life have not been examined. We aimed to address this knowledge gap. In 2014/2015, we conducted a cross-sectional study among adults with asthma in Germany (n = 362). For the current analyses that sample was restricted to participants in employment and reporting to have never been diagnosed with chronic obstructive pulmonary disease (n = 94). Work stress was operationalized by the 16-item effort-reward-imbalance (ERI) questionnaire, which measures the subcomponents "effort", "reward" and "overcommitment." Participants further completed the Asthma Control Test and the Asthma Quality of Life Questionnaire-Sydney. Multivariable associations were quantified by linear regression and logistic regression. Effort, reward and their ratio (i.e. ERI ratio) did not show meaningful associations with asthma morbidity. By contrast, increasing levels of overcommitment were associated with poorer asthma control and worse quality of life in both linear regression (ß = -0.26, p = 0.01 and ß = 0.44, p < 0.01, respectively) and logistic regression (odds ratio [OR] = 1.87, 95% confidence interval [CI] = 1.14-3.07 and OR = 2.34, 95% CI = 1.32-4.15, respectively). The present study provides initial evidence of a positive relationship of work-related overcommitment with asthma control and asthma-specific quality of life. Longitudinal studies with larger samples are needed to confirm our findings and to disentangle the potential causality of associations.

Are low wages risk factors for hypertension?

PubMed Central

Du, Juan

2012-01-01

Objective: Socio-economic status (SES) is strongly correlated with hypertension. But SES has several components, including income and correlations in cross-sectional data need not imply SES is a risk factor. This study investigates whether wages—the largest category within income—are risk factors. Methods: We analysed longitudinal, nationally representative US data from four waves (1999, 2001, 2003 and 2005) of the Panel Study of Income Dynamics. The overall sample was restricted to employed persons age 25–65 years, n = 17 295. Separate subsamples were constructed of persons within two age groups (25–44 and 45–65 years) and genders. Hypertension incidence was self-reported based on physician diagnosis. Our study was prospective since data from three base years (1999, 2001, 2003) were used to predict newly diagnosed hypertension for three subsequent years (2001, 2003, 2005). In separate analyses, data from the first base year were used to predict time-to-reporting hypertension. Logistic regressions with random effects and Cox proportional hazards regressions were run. Results: Negative and strongly statistically significant correlations between wages and hypertension were found both in logistic and Cox regressions, especially for subsamples containing the younger age group (25–44 years) and women. Correlations were stronger when three health variables—obesity, subjective measures of health and number of co-morbidities—were excluded from regressions. Doubling the wage was associated with 25–30% lower chances of hypertension for persons aged 25–44 years. Conclusions: The strongest evidence for low wages being risk factors for hypertension among working people were for women and persons aged 25–44 years. PMID:22262559

Are low wages risk factors for hypertension?

PubMed

Leigh, J Paul; Du, Juan

2012-12-01

Socio-economic status (SES) is strongly correlated with hypertension. But SES has several components, including income and correlations in cross-sectional data need not imply SES is a risk factor. This study investigates whether wages-the largest category within income-are risk factors. We analysed longitudinal, nationally representative US data from four waves (1999, 2001, 2003 and 2005) of the Panel Study of Income Dynamics. The overall sample was restricted to employed persons age 25-65 years, n = 17 295. Separate subsamples were constructed of persons within two age groups (25-44 and 45-65 years) and genders. Hypertension incidence was self-reported based on physician diagnosis. Our study was prospective since data from three base years (1999, 2001, 2003) were used to predict newly diagnosed hypertension for three subsequent years (2001, 2003, 2005). In separate analyses, data from the first base year were used to predict time-to-reporting hypertension. Logistic regressions with random effects and Cox proportional hazards regressions were run. Negative and strongly statistically significant correlations between wages and hypertension were found both in logistic and Cox regressions, especially for subsamples containing the younger age group (25-44 years) and women. Correlations were stronger when three health variables-obesity, subjective measures of health and number of co-morbidities-were excluded from regressions. Doubling the wage was associated with 25-30% lower chances of hypertension for persons aged 25-44 years. The strongest evidence for low wages being risk factors for hypertension among working people were for women and persons aged 25-44 years.

The intersectionality of postsecondary pathways: the case of high school students with special education needs.

PubMed

Robson, Karen L; Anisef, Paul; Brown, Robert S; Parekh, Gillian

2014-08-01

Using data from the Toronto District School Board, we examine the postsecondary pathways of students with special education needs (SEN). We consider both university and college pathways, employing multilevel multinomial logistic regressions, conceptualizing our findings within a life course and intersectionality framework. Our findings reveal that having SEN reduces the likelihood of confirming university, but increases the likelihood of college confirmation. We examine a set of known determinants of postsecondary education (PSE) pathways that were derived from the literature and employ exploratory statistical interactions to examine if the intersection of various traits differentially impacts upon the PSE trajectories of students with SEN. Our findings reveal that parental education, neighborhood wealth, race, and streaming impact on the postsecondary pathways of students with SEN in Toronto.

Exploring factors influencing smoking behaviour in Malaysia.

PubMed

Cheah, Yong Kang; Naidu, Balkish Mahadir

2012-01-01

The objective of present study is to investigate the determinants of smoking behaviour among adults in Malaysia. Findings of the Third National Health and Morbidity Survey (NHMS-3) by the Ministry of Health, Malaysia, were used. The sample consisted of 34,539 observations. A logistic regression model was thus applied to estimate the probability to participate in smoking. Age, income, gender, marital status, ethnicity, employment status, residential area, education, lifestyle and health status were statistically significant in affecting the likelihood of smoking. Specifically, youngsters, low income earners, males, unmarried individuals, Malays, employed individuals, rural residents and primary educated individuals were more likely to smoke. In conclusion, socio-demographic, lifestyle and health factors have significant impacts on smoking participation in Malaysia. Based on these empirical findings, several policy implications are suggested.

Predictors of sustained organizational commitment among nurses with temporary job contracts.

PubMed

Jalonen, Paivi; Virtanen, Marianna; Vahtera, Jussi; Elovainio, Marko; Kivimaki, Mika

2006-05-01

To examine sociodemographic, work-related factors and psychological health as predictors of sustained organizational commitment among temporary hospital employees. The participants were 412 nurses who had a temporary job contract and reported being committed to their organization at baseline. Organizational commitment was measured again 2 years later. The results of logistic regression analysis showed that age over 35 years, high job control, high participative safety, high perceived justice in decision making, and low psychological distress predicted sustained organizational commitment at follow-up. The change from temporary employment to a permanent job and high job control predicted sustained organizational commitment even after the effect of all the other predictors was taken into account. Organizations that employ temporary workers should pay attention to the job control and career prospects of temporary staff.

Contributions of Therapist Characteristics and Stability to Intensive In-home Therapy Youth Outcomes

PubMed Central

Greeson, Johanna K. P.; Guo, Shenyang; Barth, Richard P.; Hurley, Sarah; Sisson, Jocelyn

2014-01-01

Objective This study examines the influence of therapist and youth characteristics on post-discharge outcomes from intensive in-home therapy. Method Data for 1,416 youth and 412 therapists were obtained from a behavioral health services provider. The Huber–White method was used to account for nested data; ordered logistic regression was employed to assess outcomes. Results Therapist gender and employment stability were significantly associated with youth outcomes. The likelihood of an undesirable outcome was significantly less for cases with female therapists. Conclusion Findings underscore the need for additional study concerning the impact of therapist characteristics and stability on youth outcomes, and to improve the understanding of the relationship between the two. Future studies in these areas would advance social work practice in family-based treatment programs. PMID:24944505

Access disparities to Magnet hospitals for patients undergoing neurosurgical operations

PubMed Central

Missios, Symeon; Bekelis, Kimon

2017-01-01

Background Centers of excellence focusing on quality improvement have demonstrated superior outcomes for a variety of surgical interventions. We investigated the presence of access disparities to hospitals recognized by the Magnet Recognition Program of the American Nurses Credentialing Center (ANCC) for patients undergoing neurosurgical operations. Methods We performed a cohort study of all neurosurgery patients who were registered in the New York Statewide Planning and Research Cooperative System (SPARCS) database from 2009–2013. We examined the association of African-American race and lack of insurance with Magnet status hospitalization for neurosurgical procedures. A mixed effects propensity adjusted multivariable regression analysis was used to control for confounding. Results During the study period, 190,535 neurosurgical patients met the inclusion criteria. Using a multivariable logistic regression, we demonstrate that African-Americans had lower admission rates to Magnet institutions (OR 0.62; 95% CI, 0.58–0.67). This persisted in a mixed effects logistic regression model (OR 0.77; 95% CI, 0.70–0.83) to adjust for clustering at the patient county level, and a propensity score adjusted logistic regression model (OR 0.75; 95% CI, 0.69–0.82). Additionally, lack of insurance was associated with lower admission rates to Magnet institutions (OR 0.71; 95% CI, 0.68–0.73), in a multivariable logistic regression model. This persisted in a mixed effects logistic regression model (OR 0.72; 95% CI, 0.69–0.74), and a propensity score adjusted logistic regression model (OR 0.72; 95% CI, 0.69–0.75). Conclusions Using a comprehensive all-payer cohort of neurosurgery patients in New York State we identified an association of African-American race and lack of insurance with lower rates of admission to Magnet hospitals. PMID:28684152

Adjusting for Confounding in Early Postlaunch Settings: Going Beyond Logistic Regression Models.

PubMed

Schmidt, Amand F; Klungel, Olaf H; Groenwold, Rolf H H

2016-01-01

Postlaunch data on medical treatments can be analyzed to explore adverse events or relative effectiveness in real-life settings. These analyses are often complicated by the number of potential confounders and the possibility of model misspecification. We conducted a simulation study to compare the performance of logistic regression, propensity score, disease risk score, and stabilized inverse probability weighting methods to adjust for confounding. Model misspecification was induced in the independent derivation dataset. We evaluated performance using relative bias confidence interval coverage of the true effect, among other metrics. At low events per coefficient (1.0 and 0.5), the logistic regression estimates had a large relative bias (greater than -100%). Bias of the disease risk score estimates was at most 13.48% and 18.83%. For the propensity score model, this was 8.74% and >100%, respectively. At events per coefficient of 1.0 and 0.5, inverse probability weighting frequently failed or reduced to a crude regression, resulting in biases of -8.49% and 24.55%. Coverage of logistic regression estimates became less than the nominal level at events per coefficient ≤5. For the disease risk score, inverse probability weighting, and propensity score, coverage became less than nominal at events per coefficient ≤2.5, ≤1.0, and ≤1.0, respectively. Bias of misspecified disease risk score models was 16.55%. In settings with low events/exposed subjects per coefficient, disease risk score methods can be useful alternatives to logistic regression models, especially when propensity score models cannot be used. Despite better performance of disease risk score methods than logistic regression and propensity score models in small events per coefficient settings, bias, and coverage still deviated from nominal.

The weight of work: the association between maternal employment and overweight in low- and middle-income countries.

PubMed

Oddo, Vanessa M; Bleich, Sara N; Pollack, Keshia M; Surkan, Pamela J; Mueller, Noel T; Jones-Smith, Jessica C

2017-10-18

Maternal employment has increased in low-and middle-income countries (LMIC) and is a hypothesized risk factor for maternal overweight due to increased income and behavioral changes related to time allocation. However, few studies have investigated this relationship in LMIC. Using cross-sectional samples from Demographic and Health Surveys, we investigated the association between maternal employment and overweight (body mass index [BMI] ≥ 25 kg/m 2 ) among women in 38 LMIC (N = 162,768). We categorized mothers as formally employed, informally employed, or non-employed based on 4 indicators: employment status in the last 12 months; aggregate occupation category (skilled, unskilled); type of earnings (cash only, cash and in-kind, in-kind only, unpaid); and seasonality of employment (all year, seasonal/occasional employment). Formally employed women were largely employed year-round in skilled occupations and earned a wage (e.g. professional), whereas informally employed women were often irregularly employed in unskilled occupations and in some cases, were paid in-kind (e.g. domestic work). For within-country analyses, we used adjusted logistic regression models and included an interaction term to assess heterogeneity in the association by maternal education level. We then used meta-analysis and meta-regression to explore differences in the associations pooled across countries. Compared to non-employed mothers, formally employed mothers had higher odds of overweight (pooled odds ratio [POR] = 1.3; 95% Confidence Interval [CI] 1.2, 1.4) whereas informally employed mothers, compared to non-employed mothers, had lower odds of overweight (POR = 0.72; 95% CI: 0.64, 0.81). In 14 LMIC, the association varied by education. In these countries, the magnitude of the formal employment-overweight association was larger for women with low education (POR = 1.5; 95% CI: 1.1, 1.9) compared to those with high education (POR = 1.2; 95% CI: 1.0, 1.3). Formally employed mothers in LMIC have higher odds of overweight and the association varies by educational attainment in 14 countries. This knowledge highlights the importance of workplace initiatives to reduce the risk of overweight among working women in LMIC.

On the use and misuse of scalar scores of confounders in design and analysis of observational studies.

PubMed

Pfeiffer, R M; Riedl, R

2015-08-15

We assess the asymptotic bias of estimates of exposure effects conditional on covariates when summary scores of confounders, instead of the confounders themselves, are used to analyze observational data. First, we study regression models for cohort data that are adjusted for summary scores. Second, we derive the asymptotic bias for case-control studies when cases and controls are matched on a summary score, and then analyzed either using conditional logistic regression or by unconditional logistic regression adjusted for the summary score. Two scores, the propensity score (PS) and the disease risk score (DRS) are studied in detail. For cohort analysis, when regression models are adjusted for the PS, the estimated conditional treatment effect is unbiased only for linear models, or at the null for non-linear models. Adjustment of cohort data for DRS yields unbiased estimates only for linear regression; all other estimates of exposure effects are biased. Matching cases and controls on DRS and analyzing them using conditional logistic regression yields unbiased estimates of exposure effect, whereas adjusting for the DRS in unconditional logistic regression yields biased estimates, even under the null hypothesis of no association. Matching cases and controls on the PS yield unbiased estimates only under the null for both conditional and unconditional logistic regression, adjusted for the PS. We study the bias for various confounding scenarios and compare our asymptotic results with those from simulations with limited sample sizes. To create realistic correlations among multiple confounders, we also based simulations on a real dataset. Copyright © 2015 John Wiley & Sons, Ltd.

[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.

Association between coagulation function and patients with primary angle closure glaucoma: a 5-year retrospective case-control study.

PubMed

Li, Shengjie; Gao, Yanting; Shao, Mingxi; Tang, Binghua; Cao, Wenjun; Sun, Xinghuai

2017-11-04

To evaluate the association between coagulation function and patients with primary angle closure glaucoma (PACG). A retrospective, hospital-based, case-control study. Shanghai, China. A total of 1778 subjects were recruited from the Eye & ENT Hospital of Fudan University from January 2010 to December 2015, including patients with PACG (male=296; female=569) and control subjects (male=290; female=623). Sociodemographic data and clinical data were collected. The one-way analysis of variance test was used to compare the levels of laboratory parameters among the mild, moderate and severe PACG groups. Multivariate logistic regression analyses were performed to identify the independent risk factors for PACG. The nomogram was constructed based on the logistic regression model using the R project for statistical computing (R V.3.3.2). The activated partial thromboplastin time (APTT) of the PACG group was approximately 4% shorter (p<0.001) than that of the control group. The prothrombin time (PT) was approximately 2.40% shorter (p<0.001) in patients with PACG compared with the control group. The thrombin time was also approximately 2.14% shorter (p<0.001) in patients with PACG compared with the control group. The level of D-dimer was significantly higher (p=0.042) in patients with PACG. Moreover, the mean platelet volume (MPV) of the PACG group was significantly higher (p=0.013) than that of the control group. A similar trend was observed when coagulation parameters were compared between the PACG and control groups with respect to gender and/or age. Multiple logistic regression analyses revealed that APTT (OR=1.032, 95% CI 1.000 to 1.026), PT (OR=1.249, 95% CI 1.071 to 1.457) and MPV (OR=1.185, 95% CI 1.081 to 1.299) were independently associated with PACG. Patients with PACG had a shorter coagulation time. Our results suggest that coagulation function is significantly associated with patients with PACG and may play an important role in the onset and development of PACG. © 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.

Biomechanics laboratory-based prediction algorithm to identify female athletes with high knee loads that increase risk of ACL injury

PubMed Central

Myer, Gregory D; Ford, Kevin R; Khoury, Jane; Succop, Paul; Hewett, Timothy E

2014-01-01

Objective Knee abduction moment (KAM) during landing predicts non-contact anterior cruciate ligament (ACL) injury risk with high sensitivity and specificity in female athletes. The purpose of this study was to employ sensitive laboratory (lab-based) tools to determine predictive mechanisms that underlie increased KAM during landing. Methods Female basketball and soccer players (N=744) from a single county public school district were recruited to participate in testing of anthropometrics, maturation, laxity/flexibility, strength and landing biomechanics. Linear regression was used to model KAM, and logistic regression was used to examine high (>25.25 Nm of KAM) versus low KAM as surrogate for ACL injury risk. Results The most parsimonious model included independent predictors (β±1 SE) (1) peak knee abduction angle (1.78±0.05; p<0.001), (2) peak knee extensor moment (0.17±0.01; p<0.001), (3) knee flexion range of motion (0.15±0.03; p<0.01), (4) body mass index (BMI) Z-score (−1.67±0.36; p<0.001) and (5) tibia length (−0.50±0.14; p<0.001) and accounted for 78% of the variance in KAM during landing. The logistic regression model that employed these same variables predicted high KAM status with 85% sensitivity and 93% specificity and a C-statistic of 0.96. Conclusions Increased knee abduction angle, quadriceps recruitment, tibia length and BMI with decreased knee flexion account for 80% of the measured variance in KAM during a drop vertical jump. Clinical relevance Females who demonstrate increased KAM are more responsive and more likely to benefit from neuromuscular training. These findings should significantly enhance the identification of those at increased risk and facilitate neuromuscular training targeted to this important risk factor (high KAM) for ACL injury. PMID:20558526

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.

Employment, social capital, and community participation among Israelis with disabilities.

PubMed

Araten-Bergman, Tal; Stein, Michael Ashley

2014-01-01

Employment, social capital, and community participation have emerged in recent years as significant concepts for realizing the human rights of individuals with disabilities. Yet the theoretical interrelationship of these concepts remains largely overlooked, as does the empirical basis for understanding the underlying connections. This study explores the relationship between employment status, social capital, community participation, and well-being among Israelis with disabilities. It also explores the unique contribution of social capital to the well-being and integration of individuals with disabilities. 274 participants with self-reported disabilities completed a questionnaire containing measures of individual social capital, community participation, well-being, and background data. Correlation and Univariate analysis were used to compare scores between employed (n=131) and non-employed (n=143) participants, and logistic regression analysis was conducted to test the unique contribution of employment to social inclusion and well-being. Employed participants reported significantly higher levels of social capital and were more integrated in leisure and civic activities than their non-employed counterparts. Moreover, employment status was found to have a significant contribution to the variance in the subjective well-being of participants. By more fully understanding the importance of social capital for community inclusion, practitioners can better address the importance of network-building during the rehabilitation process as a means of promoting social and vocational integration.

No rationale for 1 variable per 10 events criterion for binary logistic regression analysis.

PubMed

van Smeden, Maarten; de Groot, Joris A H; Moons, Karel G M; Collins, Gary S; Altman, Douglas G; Eijkemans, Marinus J C; Reitsma, Johannes B

2016-11-24

Ten events per variable (EPV) is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth's correction, are compared. The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect ('separation'). We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth's correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

4D-Fingerprint Categorical QSAR Models for Skin Sensitization Based on Classification Local Lymph Node Assay Measures

PubMed Central

Li, Yi; Tseng, Yufeng J.; Pan, Dahua; Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Hopfinger, Anton J.

2008-01-01

Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the Local Lymph Node Assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, eg. Quantitative Structure-Activity Relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data have been constructed. The descriptors used to generate these models are derived from the 4D-molecular similarity paradigm and are referred to as universal 4D-fingerprints. A training set of 132 structurally diverse compounds and a test set of 15 structurally diverse compounds were used in this study. The statistical methodologies used to build the models are logistic regression (LR), and partial least square coupled logistic regression (PLS-LR), which prove to be effective tools for studying skin sensitization measures expressed in the two categorical terms of sensitizer and non-sensitizer. QSAR models with low values of the Hosmer-Lemeshow goodness-of-fit statistic, χHL2, are significant and predictive. For the training set, the cross-validated prediction accuracy of the logistic regression models ranges from 77.3% to 78.0%, while that of PLS-logistic regression models ranges from 87.1% to 89.4%. For the test set, the prediction accuracy of logistic regression models ranges from 80.0%-86.7%, while that of PLS-logistic regression models ranges from 73.3%-80.0%. The QSAR models are made up of 4D-fingerprints related to aromatic atoms, hydrogen bond acceptors and negatively partially charged atoms. PMID:17226934

Tobacco advertising, environmental smoking bans, and smoking in Chinese urban areas.

PubMed

Yang, Tingzhong; Rockett, Ian R H; Li, Mu; Xu, Xiaochao; Gu, Yaming

2012-07-01

To evaluate whether cigarette smoking in Chinese urban areas was respectively associated with exposure to tobacco advertising and smoking bans in households, workplaces, and public places. Participants were 4735 urban residents aged 15 years and older, who were identified through multi-stage quota-sampling conducted in six Chinese cities. Data were collected on individual sociodemographics and smoking status, and regional tobacco control measures. The sample was characterized in terms of smoking prevalence, and multilevel logistic models were employed to analyze the association between smoking and tobacco advertising and environmental smoking restrictions, respectively. Smoking prevalence was 30%. Multilevel logistic regression analysis showed that smoking was positively associated with exposure to tobacco advertising, and negatively associated with workplace and household smoking bans. The association of smoking with both tobacco advertising and environmental smoking bans further justifies implementation of comprehensive smoking interventions and tobacco control programs in China. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

MODELING SNAKE MICROHABITAT FROM RADIOTELEMETRY STUDIES USING POLYTOMOUS LOGISTIC REGRESSION

EPA Science Inventory

Multivariate analysis of snake microhabitat has historically used techniques that were derived under assumptions of normality and common covariance structure (e.g., discriminant function analysis, MANOVA). In this study, polytomous logistic regression (PLR which does not require ...

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.

Calculating the individual probability of successful ocriplasmin treatment in eyes with VMT syndrome: a multivariable prediction model from the EXPORT study.

PubMed

Paul, Christoph; Heun, Christine; Müller, Hans-Helge; Hoerauf, Hans; Feltgen, Nicolas; Wachtlin, Joachim; Kaymak, Hakan; Mennel, Stefan; Koss, Michael Janusz; Fauser, Sascha; Maier, Mathias M; Schumann, Ricarda G; Mueller, Simone; Chang, Petrus; Schmitz-Valckenberg, Steffen; Kazerounian, Sara; Szurman, Peter; Lommatzsch, Albrecht; Bertelmann, Thomas

2017-10-31

To evaluate predictive factors for the treatment success of ocriplasmin and to use these factors to generate a multivariate model to calculate the individual probability of successful treatment. Data were collected in a retrospective, multicentre cohort study. Patients with vitreomacular traction (VMT) syndrome without a full-thickness macular hole were included if they received an intravitreal injection (IVI) of ocriplasmin. Five factors (age, gender, lens status, presence of epiretinal membrane (ERM) formation and horizontal diameter of VMT) were assessed on their association with VMT resolution. A multivariable logistic regression model was employed to further analyse these factors and calculate the individual probability of successful treatment. 167 eyes of 167 patients were included. Univariate analysis revealed a significant correlation to VMT resolution for all analysed factors: age (years) (OR 0.9208; 95% CI 0.8845 to 0.9586; p<0.0001), gender (male) (OR 0.480; 95% CI 0.241 to 0.957; p=0.0371), lens status (phakic) (OR 2.042; 95% CI 1.054 to 3.958; p=0.0344), ERM formation (present) (OR 0.384; 95% CI 0.179 to 0.821; p=0.0136) and horizontal VMT diameter (µm) (OR 0.99812; 95% CI 0.99684 to 0.99941, p=0.0042). A significant multivariable logistic regression model was established with age and VMT diameter. Known predictive factors for VMT resolution after ocriplasmin IVI were confirmed in our study. We were able to combine them into a formula, ultimately allowing the calculation of an individual probability of treatment success with ocriplasmin in patients with VMT syndrome without FTHM. © 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.

Selecting risk factors: a comparison of discriminant analysis, logistic regression and Cox's regression model using data from the Tromsø Heart Study.

PubMed

Brenn, T; Arnesen, E

1985-01-01

For comparative evaluation, discriminant analysis, logistic regression and Cox's model were used to select risk factors for total and coronary deaths among 6595 men aged 20-49 followed for 9 years. Groups with mortality between 5 and 93 per 1000 were considered. Discriminant analysis selected variable sets only marginally different from the logistic and Cox methods which always selected the same sets. A time-saving option, offered for both the logistic and Cox selection, showed no advantage compared with discriminant analysis. Analysing more than 3800 subjects, the logistic and Cox methods consumed, respectively, 80 and 10 times more computer time than discriminant analysis. When including the same set of variables in non-stepwise analyses, all methods estimated coefficients that in most cases were almost identical. In conclusion, discriminant analysis is advocated for preliminary or stepwise analysis, otherwise Cox's method should be used.

Modification of the Mantel-Haenszel and Logistic Regression DIF Procedures to Incorporate the SIBTEST Regression Correction

ERIC Educational Resources Information Center

DeMars, Christine E.

2009-01-01

The Mantel-Haenszel (MH) and logistic regression (LR) differential item functioning (DIF) procedures have inflated Type I error rates when there are large mean group differences, short tests, and large sample sizes.When there are large group differences in mean score, groups matched on the observed number-correct score differ on true score,…

Satellite rainfall retrieval by logistic regression

NASA Technical Reports Server (NTRS)

Chiu, Long S.

1986-01-01

The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.

Practical Session: Logistic Regression

NASA Astrophysics Data System (ADS)

Clausel, M.; Grégoire, G.

2014-12-01

An exercise is proposed to illustrate the logistic regression. One investigates the different risk factors in the apparition of coronary heart disease. It has been proposed in Chapter 5 of the book of D.G. Kleinbaum and M. Klein, "Logistic Regression", Statistics for Biology and Health, Springer Science Business Media, LLC (2010) and also by D. Chessel and A.B. Dufour in Lyon 1 (see Sect. 6 of http://pbil.univ-lyon1.fr/R/pdf/tdr341.pdf). This example is based on data given in the file evans.txt coming from http://www.sph.emory.edu/dkleinb/logreg3.htm#data.

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

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

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test ofmore » the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.« less

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

NASA Astrophysics Data System (ADS)

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam

2015-10-01

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.

The cross-validated AUC for MCP-logistic regression with high-dimensional data.

PubMed

Jiang, Dingfeng; Huang, Jian; Zhang, Ying

2013-10-01

We propose a cross-validated area under the receiving operator characteristic (ROC) curve (CV-AUC) criterion for tuning parameter selection for penalized methods in sparse, high-dimensional logistic regression models. We use this criterion in combination with the minimax concave penalty (MCP) method for variable selection. The CV-AUC criterion is specifically designed for optimizing the classification performance for binary outcome data. To implement the proposed approach, we derive an efficient coordinate descent algorithm to compute the MCP-logistic regression solution surface. Simulation studies are conducted to evaluate the finite sample performance of the proposed method and its comparison with the existing methods including the Akaike information criterion (AIC), Bayesian information criterion (BIC) or Extended BIC (EBIC). The model selected based on the CV-AUC criterion tends to have a larger predictive AUC and smaller classification error than those with tuning parameters selected using the AIC, BIC or EBIC. We illustrate the application of the MCP-logistic regression with the CV-AUC criterion on three microarray datasets from the studies that attempt to identify genes related to cancers. Our simulation studies and data examples demonstrate that the CV-AUC is an attractive method for tuning parameter selection for penalized methods in high-dimensional logistic regression models.

Associations of employment frustration with self-rated physical and mental health among Asian American immigrants in the U.S. Labor force.

PubMed

de Castro, A B; Rue, Tessa; Takeuchi, David T

2010-01-01

This study examined the associations between employment frustration and both self-rated physical health (SRPH) and self-rated mental health (SRMH) among Asian American immigrants. A cross-sectional quantitative analysis was conducted utilizing data from 1,181 Asian immigrants participating in the National Latino and Asian American Study. Employment frustration was measured by self-report of having difficulty finding the work one wants because of being of Asian descent. SRPH and SRMH were each assessed using a global one-item measure, with responses ranging from poor to excellent. Control variables included gender, age, ethnicity, education, occupation, income, whether immigrated for employment, years in the United States, English proficiency, and a general measure for everyday discrimination. Ordered logistic regression showed that employment frustration was negatively associated with SRPH. This relationship, however, was no longer significant in multivariate models including English proficiency. The negative association between employment frustration and SRMH persisted even when including all control variables. The findings suggest that Asian immigrants in the United States who experience employment frustration report lower levels of both physical and mental health. However, English proficiency may attenuate the relationship of employment frustration with physical health. © 2010 Wiley Periodicals, Inc.

Parkinson's disease: a population-based investigation of life satisfaction and employment.

PubMed

Gustafsson, Helena; Nordström, Peter; Stråhle, Stefan; Nordström, Anna

2015-01-01

To investigate relationships between individuals' socioeconomic situations and quality of life in working-aged subjects with Parkinson's disease. A population-based cohort comprising 1,432 people with Parkinson's disease and 1,135 matched controls, who responded to a questionnaire. Logistic regression analysis was performed to identify factors associated with life satisfaction and likelihood of employment. In multivariate analyses, Parkinson's disease was associated with an increased risk of dissatisfaction with life (odds ratio (OR) = 5.4, 95% confidence interval (95% CI) = 4.2-7.1) and reduced likelihood of employment (OR = 0.30, 95% CI = 0.25-0.37). Employers' support was associated with greater likelihood of employment (p < 0.001). Twenty-four percent of people with Parkinson's disease for ≥ 10 years remained employed and 6% worked full-time. People with Parkinson's disease also more frequently experienced work demands that exceeded their capacity; this factor and unemployment independently correlated with greater risk of dissatisfaction with life (both p < 0.05). People with Parkinson's disease have an increased risk of dissatisfaction with life. Employment situation is important for general life satisfaction among working-aged individuals. People with Parkinson's disease appear to find it difficult to meet the challenge of achieving a balanced employment situation.

Substance use, symptom, and employment outcomes of persons with a workplace mandate for chemical dependency treatment.

PubMed

Weisner, Constance; Lu, Yun; Hinman, Agatha; Monahan, John; Bonnie, Richard J; Moore, Charles D; Chi, Felicia W; Appelbaum, Paul S

2009-05-01

This study examined the role of workplace mandates to chemical dependency treatment in treatment adherence, alcohol and drug abstinence, severity of employment problems, and severity of psychiatric problems. The sample included 448 employed members of a private, nonprofit U.S. managed care health plan who entered chemical dependency treatment with a workplace mandate (N=75) or without one (N=373); 405 of these individuals were followed up at one year (N=70 and N=335, respectively), and 362 participated in a five-year follow up (N=60 and N=302, respectively). Propensity scores predicting receipt of a workplace mandate were calculated. Logistic regression and ordinary least-squares regression were used to predict length of stay in chemical dependency treatment, alcohol and drug abstinence, and psychiatric and employment problem severity at one and five years. Overall, participants with a workplace mandate had one- and five-year outcomes similar to those without such a mandate. Having a workplace mandate also predicted longer treatment stays and improvement in employment problems. When other factors related to outcomes were controlled for, having a workplace mandate predicted abstinence at one year, with length of stay as a mediating variable. Workplace mandates can be an effective mechanism for improving work performance and other outcomes. Study participants who had a workplace mandate were more likely than those who did not have a workplace mandate to be abstinent at follow-up, and they did as well in treatment, both short and long term. Pressure from the workplace likely gets people to treatment earlier and provides incentives for treatment adherence.

Recession, employment and self-rated health: a study on the gender gap.

PubMed

Aguilar-Palacio, I; Carrera-Lasfuentes, P; Sánchez-Recio, R; Alonso, J P; Rabanaque, M J

2018-01-01

Employment status and economic recession have been associated with negative effects on self-rated health, and this effect differs by gender. We analysed the effects of the Spanish economic recession in terms of self-rated health, its differential effect among genders and its influence on gender gap. Repeated cross-sectional study using Spanish health surveys (2001-2014). Logistic regression models were conducted to explore the association between self-rated health and employment status and its evolution over time and gender. To test the impact of the economic recession, pooled data regression models were conducted. In this study, we considered 104,577 subjects. During the last 15 years, women have entered the labour market, leading to wide changes in the Spanish traditional family roles. Instead of an increasing proportion of women workers, gender employment differences persist. Therefore, in 2014, the prevalence of workers was 55.77% in men, whereas in women, it was 44.01%. Self-rated health trends during the economic recession differ by gender, with women improving slightly their self-rated health from a low self-rated health prevalence of 38.76% in 2001 to 33.78% in 2014. On the contrary, men seem more vulnerable to employment circumstances, which have led to substantial reduction in the gender gap. Although a gender gap persists, the change in socio-economic roles seems to increase women's self-rated health, reducing this gap. It is important to promote women's labour market inclusion, even in economic recession periods. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Burnout does not help predict depression among French school teachers.

PubMed

Bianchi, Renzo; Schonfeld, Irvin Sam; Laurent, Eric

2015-11-01

Burnout has been viewed as a phase in the development of depression. However, supportive research is scarce. We examined whether burnout predicted depression among French school teachers. We conducted a 2-wave, 21-month study involving 627 teachers (73% female) working in French primary and secondary schools. Burnout was assessed with the Maslach Burnout Inventory and depression with the 9-item depression module of the Patient Health Questionnaire (PHQ-9). The PHQ-9 grades depressive symptom severity and provides a provisional diagnosis of major depression. Depression was treated both as a continuous and categorical variable using linear and logistic regression analyses. We controlled for gender, age, and length of employment. Controlling for baseline depressive symptoms, linear regression analysis showed that burnout symptoms at time 1 (T1) did not predict depressive symptoms at time 2 (T2). Baseline depressive symptoms accounted for about 88% of the association between T1 burnout and T2 depressive symptoms. Only baseline depressive symptoms predicted depressive symptoms at follow-up. Similarly, logistic regression analysis revealed that burnout symptoms at T1 did not predict incident cases of major depression at T2 when depressive symptoms at T1 were included in the predictive model. Only baseline depressive symptoms predicted cases of major depression at follow-up. This study does not support the view that burnout is a phase in the development of depression. Assessing burnout symptoms in addition to "classical" depressive symptoms may not always improve our ability to predict future depression.

Prediction of sickness absence: development of a screening instrument

PubMed Central

Duijts, S F A; Kant, IJ; Landeweerd, J A; Swaen, G M H

2006-01-01

Objectives To develop a concise screening instrument for early identification of employees at risk for sickness absence due to psychosocial health complaints. Methods Data from the Maastricht Cohort Study on “Fatigue at Work” were used to identify items to be associated with an increased risk of sickness absence. The analytical procedures univariate logistic regression, backward stepwise linear regression, and multiple logistic regression were successively applied. For both men and women, sum scores were calculated, and sensitivity and specificity rates of different cut‐off points on the screening instrument were defined. Results In women, results suggested that feeling depressed, having a burnout, being tired, being less interested in work, experiencing obligatory change in working days, and living alone, were strong predictors of sickness absence due to psychosocial health complaints. In men, statistically significant predictors were having a history of sickness absence, compulsive thinking, being mentally fatigued, finding it hard to relax, lack of supervisor support, and having no hobbies. A potential cut‐off point of 10 on the screening instrument resulted in a sensitivity score of 41.7% for women and 38.9% for men, and a specificity score of 91.3% for women and 90.6% for men. Conclusions This study shows that it is possible to identify predictive factors for sickness absence and to develop an instrument for early identification of employees at risk for sickness absence. The results of this study increase the possibility for both employers and policymakers to implement interventions directed at the prevention of sickness absence. PMID:16698807

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.

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.

The influence of endometriosis-related symptoms on work life and work ability: a study of Danish endometriosis patients in employment.

PubMed

Hansen, Karina E; Kesmodel, Ulrik S; Baldursson, Einar B; Schultz, Rikke; Forman, Axel

2013-07-01

Little is known about the implications of endometriosis on women's work life. This study aimed at examining the relation between endometriosis-related symptoms and work ability in employed women with endometriosis. In a cohort study, 610 patients with diagnosed endometriosis and 751 reference women completed an electronic survey based on the Endometriosis Health Profile 30-questionnaire and the Work Ability Index (short form). Percentages were reported for all data. Binary and multivariate logistic regression analyses were used to assess risk factors for low work ability. The level of statistical significance was set at p<0.025 in all analyses. In binary analyses a diagnosis of endometriosis was associated with more sick days, work disturbances due to symptoms, lower work ability and a wide number of other implications on work life in employed women. Moreover, a higher pain level and degree of symptoms were associated with low work ability. Full regression analysis indicated that tiredness, frequent pain, a higher daily pain level, a higher number of sick days and feeling depressed at work were associated with low work ability. A long delay from symptom onset to diagnosis was associated with low work ability. These data indicate a severe impact of endometriosis on the work ability of employed women with endometriosis and add to the evidence that this disease represents a significant socio-economic burden. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A simple approach to power and sample size calculations in logistic regression and Cox regression models.

PubMed

Vaeth, Michael; Skovlund, Eva

2004-06-15

For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

Comparing exposure assessment methods for traffic-related air pollution in an adverse pregnancy outcome study

PubMed Central

Wu, Jun; Wilhelm, Michelle; Chung, Judith; Ritz, Beate

2011-01-01

Background Previous studies reported adverse impacts of traffic-related air pollution exposure on pregnancy outcomes. Yet, little information exists on how effect estimates are impacted by the different exposure assessment methods employed in these studies. Objectives To compare effect estimates for traffic-related air pollution exposure and preeclampsia, preterm birth (gestational age less than 37 weeks), and very preterm birth (gestational age less than 30 weeks) based on four commonly-used exposure assessment methods. Methods We identified 81,186 singleton births during 1997–2006 at four hospitals in Los Angeles and Orange Counties, California. Exposures were assigned to individual subjects based on residential address at delivery using the nearest ambient monitoring station data [carbon monoxide (CO), nitrogen dioxide (NO2), nitric oxide (NO), nitrogen oxides (NOx), ozone (O3), and particulate matter less than 2.5 (PM2.5) or less than 10 (PM10) μm in aerodynamic diameter], both unadjusted and temporally-adjusted land-use regression (LUR) model estimates (NO, NO2, and NOx), CALINE4 line-source air dispersion model estimates (NOx and PM2.5), and a simple traffic-density measure. We employed unconditional logistic regression to analyze preeclampsia in our birth cohort, while for gestational age-matched risk sets with preterm and very preterm birth we employed conditional logistic regression. Results We observed elevated risks for preeclampsia, preterm birth, and very preterm birth from maternal exposures to traffic air pollutants measured at ambient stations (CO, NO, NO2, and NOx) and modeled through CALINE4 (NOx and PM2.5) and LUR (NO2 and NOx). Increased risk of preterm birth and very preterm birth were also positively associated with PM10 and PM2.5 air pollution measured at ambient stations. For LUR-modeled NO2 and NOx exposures, elevated risks for all the outcomes were observed in Los Angeles only – the region for which the LUR models were initially developed. Unadjusted LUR models often produced odds ratios somewhat larger in size than temporally-adjusted models. The size of effect estimates was smaller for exposures based on simpler traffic density measures than the other exposure assessment methods. Conclusion We generally confirmed that traffic-related air pollution was associated with adverse reproductive outcomes regardless of the exposure assessment method employed, yet the size of the estimated effect depended on how both temporal and spatial variations were incorporated into exposure assessment. The LUR model was not transferable even between two contiguous areas within the same large metropolitan area in Southern California. PMID:21453913

Robust logistic regression to narrow down the winner's curse for rare and recessive susceptibility variants.

PubMed

Kesselmeier, Miriam; Lorenzo Bermejo, Justo

2017-11-01

Logistic regression is the most common technique used for genetic case-control association studies. A disadvantage of standard maximum likelihood estimators of the genotype relative risk (GRR) is their strong dependence on outlier subjects, for example, patients diagnosed at unusually young age. Robust methods are available to constrain outlier influence, but they are scarcely used in genetic studies. This article provides a non-intimidating introduction to robust logistic regression, and investigates its benefits and limitations in genetic association studies. We applied the bounded Huber and extended the R package 'robustbase' with the re-descending Hampel functions to down-weight outlier influence. Computer simulations were carried out to assess the type I error rate, mean squared error (MSE) and statistical power according to major characteristics of the genetic study and investigated markers. Simulations were complemented with the analysis of real data. Both standard and robust estimation controlled type I error rates. Standard logistic regression showed the highest power but standard GRR estimates also showed the largest bias and MSE, in particular for associated rare and recessive variants. For illustration, a recessive variant with a true GRR=6.32 and a minor allele frequency=0.05 investigated in a 1000 case/1000 control study by standard logistic regression resulted in power=0.60 and MSE=16.5. The corresponding figures for Huber-based estimation were power=0.51 and MSE=0.53. Overall, Hampel- and Huber-based GRR estimates did not differ much. Robust logistic regression may represent a valuable alternative to standard maximum likelihood estimation when the focus lies on risk prediction rather than identification of susceptibility variants. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

CUSUM-Logistic Regression analysis for the rapid detection of errors in clinical laboratory test results.

PubMed

Sampson, Maureen L; Gounden, Verena; van Deventer, Hendrik E; Remaley, Alan T

2016-02-01

The main drawback of the periodic analysis of quality control (QC) material is that test performance is not monitored in time periods between QC analyses, potentially leading to the reporting of faulty test results. The objective of this study was to develop a patient based QC procedure for the more timely detection of test errors. Results from a Chem-14 panel measured on the Beckman LX20 analyzer were used to develop the model. Each test result was predicted from the other 13 members of the panel by multiple regression, which resulted in correlation coefficients between the predicted and measured result of >0.7 for 8 of the 14 tests. A logistic regression model, which utilized the measured test result, the predicted test result, the day of the week and time of day, was then developed for predicting test errors. The output of the logistic regression was tallied by a daily CUSUM approach and used to predict test errors, with a fixed specificity of 90%. The mean average run length (ARL) before error detection by CUSUM-Logistic Regression (CSLR) was 20 with a mean sensitivity of 97%, which was considerably shorter than the mean ARL of 53 (sensitivity 87.5%) for a simple prediction model that only used the measured result for error detection. A CUSUM-Logistic Regression analysis of patient laboratory data can be an effective approach for the rapid and sensitive detection of clinical laboratory errors. Published by Elsevier Inc.

Nonconvex Sparse Logistic Regression With Weakly Convex Regularization

NASA Astrophysics Data System (ADS)

Shen, Xinyue; Gu, Yuantao

2018-06-01

In this work we propose to fit a sparse logistic regression model by a weakly convex regularized nonconvex optimization problem. The idea is based on the finding that a weakly convex function as an approximation of the $\\ell_0$ pseudo norm is able to better induce sparsity than the commonly used $\\ell_1$ norm. For a class of weakly convex sparsity inducing functions, we prove the nonconvexity of the corresponding sparse logistic regression problem, and study its local optimality conditions and the choice of the regularization parameter to exclude trivial solutions. Despite the nonconvexity, a method based on proximal gradient descent is used to solve the general weakly convex sparse logistic regression, and its convergence behavior is studied theoretically. Then the general framework is applied to a specific weakly convex function, and a necessary and sufficient local optimality condition is provided. The solution method is instantiated in this case as an iterative firm-shrinkage algorithm, and its effectiveness is demonstrated in numerical experiments by both randomly generated and real datasets.

A comparative study on entrepreneurial attitudes modeled with logistic regression and Bayes nets.

PubMed

López Puga, Jorge; García García, Juan

2012-11-01

Entrepreneurship research is receiving increasing attention in our context, as entrepreneurs are key social agents involved in economic development. We compare the success of the dichotomic logistic regression model and the Bayes simple classifier to predict entrepreneurship, after manipulating the percentage of missing data and the level of categorization in predictors. A sample of undergraduate university students (N = 1230) completed five scales (motivation, attitude towards business creation, obstacles, deficiencies, and training needs) and we found that each of them predicted different aspects of the tendency to business creation. Additionally, our results show that the receiver operating characteristic (ROC) curve is affected by the rate of missing data in both techniques, but logistic regression seems to be more vulnerable when faced with missing data, whereas Bayes nets underperform slightly when categorization has been manipulated. Our study sheds light on the potential entrepreneur profile and we propose to use Bayesian networks as an additional alternative to overcome the weaknesses of logistic regression when missing data are present in applied research.

Comparison of cranial sex determination by discriminant analysis and logistic regression.

PubMed

Amores-Ampuero, Anabel; Alemán, Inmaculada

2016-04-05

Various methods have been proposed for estimating dimorphism. The objective of this study was to compare sex determination results from cranial measurements using discriminant analysis or logistic regression. The study sample comprised 130 individuals (70 males) of known sex, age, and cause of death from San José cemetery in Granada (Spain). Measurements of 19 neurocranial dimensions and 11 splanchnocranial dimensions were subjected to discriminant analysis and logistic regression, and the percentages of correct classification were compared between the sex functions obtained with each method. The discriminant capacity of the selected variables was evaluated with a cross-validation procedure. The percentage accuracy with discriminant analysis was 78.2% for the neurocranium (82.4% in females and 74.6% in males) and 73.7% for the splanchnocranium (79.6% in females and 68.8% in males). These percentages were higher with logistic regression analysis: 85.7% for the neurocranium (in both sexes) and 94.1% for the splanchnocranium (100% in females and 91.7% in males).

Work at older ages in Japan: variation by gender and employment status.

PubMed

Raymo, James M; Liang, Jersey; Sugisawa, Hidehiro; Kobayashi, Erika; Sugihara, Yoko

2004-05-01

This study describes the correlates of labor force participation among Japanese men and women aged 60-85 and examines differences by gender and employment status. Using four waves of data collected from a national sample of older Japanese between 1990 and 1999, we estimate multinomial logistic regression models for three measures of labor force participation (current labor force status, labor force exit, and labor force re-entry) as a function of individual and family characteristics measured 3 years earlier. Labor force participation is significantly associated with socioeconomic status, longest occupation, and family structure. The strength and nature of these relationships differ markedly for men and women and for wage employment and self-employment. The emphasis on life course experiences and work-family interdependence characterizing recent research on retirement in the United States is clearly relevant in Japan as well. To better understand later-life labor force participation in Japan, subsequent research should incorporate more direct measures of life course experiences and family relationships and attempt to make explicit cross-national comparisons of these relationships.

The relation of family violence, employment status, welfare benefits, and alcohol drinking in the United States

PubMed Central

Rodriguez, Eunice; Lasch, Kathryn E; Chandra, Pinky; Lee, Jennifer

2001-01-01

Objective To examine the contribution of employment status, welfare benefits, alcohol use, and other individual and contextual factors to physical aggression during marital conflict. Methods Logistic regression models were used to analyze panel data collected in the National Survey of Families and Households in 1987 and 1992. A total of 4,780 married or cohabiting persons reinterviewed in 1992 were included in the analysis. Domestic violence was defined as reporting that both partners were physically violent during arguments. Results Unemployed respondents are not at greater risk of family violence than employed respondents, after alcohol misuse, income, education, age, and other factors are controlled for; however, employed persons receiving welfare benefits are at significantly higher risk. Alcohol misuse, which remains a predictor of violence even after other factors are controlled for, increases the risk of family violence, and satisfaction with social support from family and friends is associated with its decrease. Conclusions Alcohol misuse has an important effect on domestic violence, and the potential impact of welfare reform on domestic violence needs to be monitored. PMID:11342506

Employment Benefit Receipt Among Ontario Public Disability Benefit Recipients with a Disability Related to a Mental Disorder.

PubMed

Dewa, Carolyn S

2016-02-01

Using administrative data from the public long-term disability support program in Ontario, Canada, this paper examines the factors related to receipt of a paid employment benefit. These analyses include only ODSP beneficiaries who were primary beneficiaries, who had active files in March 2011 and who were <65 years of age and had a disability-related primary diagnosis (n = 253,492). About 9 % of primary beneficiaries received the employment benefit. Logistic regression results suggest that compared to those who have a disability related to a physical disorder, those who have a psychotic disorder (OR 1.125), a mood disorder (OR 1.139) or a developmental disability (OR 1.618) are significantly more likely to receive the benefit while those who have a substance use disorder were significantly less likely (OR 0.540). These results indicate that a proportion of people who receives public disability benefits are employed. In addition, all things being equal, people with mental disorders are more likely to use this type of program than people with physical disorders.

Self-employment in joinery: an occupational risk facor?

PubMed

Lesage, Francois-Xavier; Salles, Julie; Deschamps, Frederic

2014-06-01

Only a few studies have analyzed the health of self-employed workers. This cross-sectional study is the first to compare health status among craftsmen joiners and paid joiners. Clinical and paraclinical data for self-employed craftsmen and employees were collected by occupational health doctors according to a standardized protocol and compared. Health data and professional status relationships were analyzed by logistic regression. A total of 171 craftsmen and 196 paid workers were included. Craftsmen had more dermatologic pathologies (odds ratio (OR) = 2.67, p < 0.05), ear/nose/throat symptoms (OR = 3.38, p < 0.001), pulmonary symptoms (OR = 2.46, p < 0.05), musculoskeletal symptoms (OR = 3.09, p < 0.001), and abnormal audiogram (OR = 3.50, p < 0.001). The FEV1 was significantly lower among craftsmen (p < 0.01), independently of tobacco smoke exposure. This survey high-lights a high morbidity rate among self-employed craftsmen, suggesting that among woodworkers, professional status can be a risk factor for health. The preventive medical system for craftsmen has to be rethought to guarantee better safety for this population.

Financial and employment problems in families of children with special health care needs: implications for research and practice.

PubMed

Looman, Wendy S; O'Conner-Von, Susan K; Ferski, Gabriela J; Hildenbrand, Debra A

2009-01-01

The purpose of this study was to identify factors related to financial burden among families of children with special needs and to identify specific provider-level activities associated with decreased risk for such burden. Data for secondary analysis are from the National Survey of Children with Special Health Care Needs (CSHCN). Logistic regression analysis of state-level data was conducted to identify significant predictors of financial and employment problems among families of children with SHCN in Minnesota. Children with more severe conditions and whose family members provided health care at home were more likely to have parents report financial and employment problems due to the child's condition. On the other hand, families whose health care providers communicated well with other service providers and who helped them feel like partners in their child's care were significantly less likely to report financial and employment problems. Pediatric nurses and nurse practitioners can use these findings as they work with families for optimal family outcomes. Advocacy and policy implications at state and federal levels also are discussed.

Employment and choice-making for adults with intellectual disability, autism, and down syndrome.

PubMed

Bush, Kelsey L; Tassé, Marc J

2017-06-01

Adults with disabilities are employed at a significantly lower rate than adults without disabilities. Of adults with disabilities in the workforce, more individuals work in a facility setting rather than a community setting, despite efforts to improve community inclusion. Choice-making has been proposed as a predictive factor for employment for individuals with disabilities. The purpose of this research was to examine the current state of employment for three groups of adults with intellectual disability (ID): individuals with autism spectrum disorder (ASD), individuals with Down syndrome (DS), and individuals with idiopathic ID. Choice-making and its relation to improved employment outcomes was explored. This study used National Core Indicator's Adult Consumer Survey datasets from years 2011-2012 and 2012-2013. Factor analyses revealed latent variables from six choice-making questions in the Adult Consumer Survey. Ordinal logistic regression was used to identify factors related to employment status. Adults with DS had the highest rates of paid community jobs, but adults with ID had the highest rates of choice-making. ID severity level and short-term choice-making had the greatest effects on employment status in all three groups. Employment rates remain low despite national efforts to find jobs for people with disabilities. Choice-making is a unique factor that was found to be associated with employment status and provides a target for interventions to increase employability. Copyright © 2017 Elsevier Ltd. All rights reserved.

Maternal employment and Mexican school-age children overweight in 2012: the importance of households features.

PubMed

Espinosa, Alejandro Martínez

2018-01-01

International evidence regarding the relationship between maternal employment and school-age children overweight and obesity shows divergent results. In Mexico, this relationship has not been confirmed by national data sets analysis. Consequently, the objective of this article was to evaluate the role of the mothers' participation in labor force related to excess body weight in Mexican school-age children (aged 5-11 years). A cross-sectional study was conducted on a sample of 17,418 individuals from the National Health and Nutrition Survey 2012, applying binomial logistic regression models. After controlling for individual, maternal and contextual features, the mothers' participation in labor force was associated with children body composition. However, when the household features (living arrangements, household ethnicity, size, food security and socioeconomic status) were incorporated, maternal employment was no longer statically significant. Household features are crucial factors for understanding the overweight and obesity prevalence levels in Mexican school-age children, despite the mother having a paid job. Copyright: © 2018 Permanyer.

Job frustration in substance abuse counselors working with offenders in prisons versus community settings.

PubMed

Perkins, Elizabeth B; Oser, Carrie B

2014-06-01

Substance abuse counselors who work with offenders are facing increasing caseloads, which puts them at higher risk of job frustration. The purpose of this study was to explore differences between substance abuse counselors employed in prison versus community settings in terms of level of organizational support and job frustration. This study also investigated whether organizational support was associated with job frustration after controlling for counselor characteristics and workplace setting. This was accomplished utilizing data that were collected from 267 counselors as part of the Criminal Justice Drug Abuse Treatment Studies research cooperative. Results indicated that counselors employed in community settings, as compared with those employed in prisons, are more likely to report higher levels of perceived organizational support. In addition, ordinal logistic regression results reveal that counselors who are non-White and have greater levels of organizational support have less job frustration, after controlling for counselor characteristics and workplace setting. The researches to practice implications are discussed.

Job Frustration in Substance Abuse Counselors Working with Offenders in Prisons Versus Community Settings

PubMed Central

Perkins, Elizabeth B.; Oser, Carrie B.

2014-01-01

Substance abuse counselors who work with offenders are facing increasing caseloads which puts them at higher risk for job frustration. The purpose of this study was to explore differences between substance abuse counselors employed in prison versus community settings in terms of level of organizational support and job frustration. This study also investigated whether organizational support was associated with job frustration after controlling for counselor characteristics and workplace setting. This was accomplished utilizing data that was collected from 267 counselors as part of the Criminal Justice Drug Abuse Treatment Studies (CJ-DATS) research cooperative. Results indicated that counselors employed in community settings, as compared to those employed in prisons, are more likely to report higher levels of perceived organizational support. In addition, ordinal logistic regression results reveal that counselors who are non-white and have greater levels of organizational support have less job frustration, after controlling for counselor characteristics and workplace setting. The research to practice implications are discussed. PMID:23525175

Health Insurance Coverage among Puerto Rican Adults in Same-Sex Relationships.

PubMed

Gonzales, Gilbert

2017-01-01

The primary objectives of this study were to measure and compare health insurance coverage between nonelderly Puerto Rican adults in cohabiting same-sex relationships and their counterparts in cohabiting different-sex relationships. This study used data from the 2008-2014 Puerto Rican Community Survey on nonelderly adults (18-64 years) in cohabiting same-sex (n=274) and different-sex (n=58,128) relationships. Multinomial logistic regression models estimated differences in primary source of health insurance while controlling for key demographic and socioeconomic characteristics. Compared with men in different-sex relationships, men in same-sex relationships were less likely to have employer-sponsored insurance (ESI). Women in same-sex relationships were less likely than others to have ESI, insurance purchased directly from an insurer, and public health insurance after controlling for socio-demographic factors. Employment-based discrimination and policy barriers may have prevented same-sex couples from enjoying the full benefits associated with marriage and cohabitation in Puerto Rico, including employer-sponsored health insurance.

Stress-related sickness absence and return to labour market in Sweden.

PubMed

Engström, Lars-Gunnar; Janson, Staffan

2007-03-15

To analyse factors influencing chances of returning to work after long-term sickness absence with a stress-related psychiatric diagnosis. Primary focus is on employer- and occupational categories as explanatory variables. Data was collected from the regional social insurance office in the county of Värmland for 911 individuals, all with stress-related sickness absences during November in the year 2000. Logistic regressions were carried out on outcome states from long-term sickness absence on two follow-up occasions after two and three years. The results indicate that the employer- and occupational categories only had a minor effect on return to work after the long-term sickness absence. Age and health-related factors together with time factors seem to be more relevant in explaining return to work. The findings suggest that individual labour market position, as occupation, employer, branch etc, seems to be less important than expected in explaining return to work from sickness absence due to stress-related psychiatric disorders.

Mental disorders and employment status in the São Paulo Metropolitan Area, Brazil: gender differences and use of health services.

PubMed

França, Mariane Henriques; Barreto, Sandhi Maria; Pereira, Flavia Garcia; Andrade, Laura Helena Silveira Guerra de; Paiva, Maria Cristina Alochio de; Viana, Maria Carmen

2017-10-09

Mental disorders are associated with employment status as significant predictors and as consequences of unemployment and early retirement. This study describes the estimates and associations of 12-month DSM-IV prevalence rates of mental disorders and use of health services with employment status by gender in the São Paulo Metropolitan Area, Brazil. Data from the São Paulo Megacity Mental Health Survey was analyzed (n = 5,037). This is a population-based study assessing the prevalence and determinants of mental disorders among adults, using the Composite International Diagnostic Interview. The associations were estimated by odds ratios obtained through binomial and multinomial logistic regression. This study demonstrates that having mental disorders, especially mood disorders, is associated with being inactive or unemployed among men and inactive among women, but only having a substance use disorder is associated with being unemployed among women. Among those with mental disorders, seeking health care services is less frequent within unemployed.

Stepwise Distributed Open Innovation Contests for Software Development: Acceleration of Genome-Wide Association Analysis

PubMed Central

Hill, Andrew; Loh, Po-Ru; Bharadwaj, Ragu B.; Pons, Pascal; Shang, Jingbo; Guinan, Eva; Lakhani, Karim; Kilty, Iain

2017-01-01

Abstract Background: The association of differing genotypes with disease-related phenotypic traits offers great potential to both help identify new therapeutic targets and support stratification of patients who would gain the greatest benefit from specific drug classes. Development of low-cost genotyping and sequencing has made collecting large-scale genotyping data routine in population and therapeutic intervention studies. In addition, a range of new technologies is being used to capture numerous new and complex phenotypic descriptors. As a result, genotype and phenotype datasets have grown exponentially. Genome-wide association studies associate genotypes and phenotypes using methods such as logistic regression. As existing tools for association analysis limit the efficiency by which value can be extracted from increasing volumes of data, there is a pressing need for new software tools that can accelerate association analyses on large genotype-phenotype datasets. Results: Using open innovation (OI) and contest-based crowdsourcing, the logistic regression analysis in a leading, community-standard genetics software package (PLINK 1.07) was substantially accelerated. OI allowed us to do this in <6 months by providing rapid access to highly skilled programmers with specialized, difficult-to-find skill sets. Through a crowd-based contest a combination of computational, numeric, and algorithmic approaches was identified that accelerated the logistic regression in PLINK 1.07 by 18- to 45-fold. Combining contest-derived logistic regression code with coarse-grained parallelization, multithreading, and associated changes to data initialization code further developed through distributed innovation, we achieved an end-to-end speedup of 591-fold for a data set size of 6678 subjects by 645 863 variants, compared to PLINK 1.07's logistic regression. This represents a reduction in run time from 4.8 hours to 29 seconds. Accelerated logistic regression code developed in this project has been incorporated into the PLINK2 project. Conclusions: Using iterative competition-based OI, we have developed a new, faster implementation of logistic regression for genome-wide association studies analysis. We present lessons learned and recommendations on running a successful OI process for bioinformatics. PMID:28327993

Stepwise Distributed Open Innovation Contests for Software Development: Acceleration of Genome-Wide Association Analysis.

PubMed

Hill, Andrew; Loh, Po-Ru; Bharadwaj, Ragu B; Pons, Pascal; Shang, Jingbo; Guinan, Eva; Lakhani, Karim; Kilty, Iain; Jelinsky, Scott A

2017-05-01

The association of differing genotypes with disease-related phenotypic traits offers great potential to both help identify new therapeutic targets and support stratification of patients who would gain the greatest benefit from specific drug classes. Development of low-cost genotyping and sequencing has made collecting large-scale genotyping data routine in population and therapeutic intervention studies. In addition, a range of new technologies is being used to capture numerous new and complex phenotypic descriptors. As a result, genotype and phenotype datasets have grown exponentially. Genome-wide association studies associate genotypes and phenotypes using methods such as logistic regression. As existing tools for association analysis limit the efficiency by which value can be extracted from increasing volumes of data, there is a pressing need for new software tools that can accelerate association analyses on large genotype-phenotype datasets. Using open innovation (OI) and contest-based crowdsourcing, the logistic regression analysis in a leading, community-standard genetics software package (PLINK 1.07) was substantially accelerated. OI allowed us to do this in <6 months by providing rapid access to highly skilled programmers with specialized, difficult-to-find skill sets. Through a crowd-based contest a combination of computational, numeric, and algorithmic approaches was identified that accelerated the logistic regression in PLINK 1.07 by 18- to 45-fold. Combining contest-derived logistic regression code with coarse-grained parallelization, multithreading, and associated changes to data initialization code further developed through distributed innovation, we achieved an end-to-end speedup of 591-fold for a data set size of 6678 subjects by 645 863 variants, compared to PLINK 1.07's logistic regression. This represents a reduction in run time from 4.8 hours to 29 seconds. Accelerated logistic regression code developed in this project has been incorporated into the PLINK2 project. Using iterative competition-based OI, we have developed a new, faster implementation of logistic regression for genome-wide association studies analysis. We present lessons learned and recommendations on running a successful OI process for bioinformatics. © The Author 2017. Published by Oxford University Press.

Easy and low-cost identification of metabolic syndrome in patients treated with second-generation antipsychotics: artificial neural network and logistic regression models.

PubMed

Lin, Chao-Cheng; Bai, Ya-Mei; Chen, Jen-Yeu; Hwang, Tzung-Jeng; Chen, Tzu-Ting; Chiu, Hung-Wen; Li, Yu-Chuan

2010-03-01

Metabolic syndrome (MetS) is an important side effect of second-generation antipsychotics (SGAs). However, many SGA-treated patients with MetS remain undetected. In this study, we trained and validated artificial neural network (ANN) and multiple logistic regression models without biochemical parameters to rapidly identify MetS in patients with SGA treatment. A total of 383 patients with a diagnosis of schizophrenia or schizoaffective disorder (DSM-IV criteria) with SGA treatment for more than 6 months were investigated to determine whether they met the MetS criteria according to the International Diabetes Federation. The data for these patients were collected between March 2005 and September 2005. The input variables of ANN and logistic regression were limited to demographic and anthropometric data only. All models were trained by randomly selecting two-thirds of the patient data and were internally validated with the remaining one-third of the data. The models were then externally validated with data from 69 patients from another hospital, collected between March 2008 and June 2008. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of all models. Both the final ANN and logistic regression models had high accuracy (88.3% vs 83.6%), sensitivity (93.1% vs 86.2%), and specificity (86.9% vs 83.8%) to identify MetS in the internal validation set. The mean +/- SD AUC was high for both the ANN and logistic regression models (0.934 +/- 0.033 vs 0.922 +/- 0.035, P = .63). During external validation, high AUC was still obtained for both models. Waist circumference and diastolic blood pressure were the common variables that were left in the final ANN and logistic regression models. Our study developed accurate ANN and logistic regression models to detect MetS in patients with SGA treatment. The models are likely to provide a noninvasive tool for large-scale screening of MetS in this group of patients. (c) 2010 Physicians Postgraduate Press, Inc.

Bayesian logistic regression in detection of gene-steroid interaction for cancer at PDLIM5 locus.

PubMed

Wang, Ke-Sheng; Owusu, Daniel; Pan, Yue; Xie, Changchun

2016-06-01

The PDZ and LIM domain 5 (PDLIM5) gene may play a role in cancer, bipolar disorder, major depression, alcohol dependence and schizophrenia; however, little is known about the interaction effect of steroid and PDLIM5 gene on cancer. This study examined 47 single-nucleotide polymorphisms (SNPs) within the PDLIM5 gene in the Marshfield sample with 716 cancer patients (any diagnosed cancer, excluding minor skin cancer) and 2848 noncancer controls. Multiple logistic regression model in PLINK software was used to examine the association of each SNP with cancer. Bayesian logistic regression in PROC GENMOD in SAS statistical software, ver. 9.4 was used to detect gene- steroid interactions influencing cancer. Single marker analysis using PLINK identified 12 SNPs associated with cancer (P< 0.05); especially, SNP rs6532496 revealed the strongest association with cancer (P = 6.84 × 10⁻³); while the next best signal was rs951613 (P = 7.46 × 10⁻³). Classic logistic regression in PROC GENMOD showed that both rs6532496 and rs951613 revealed strong gene-steroid interaction effects (OR=2.18, 95% CI=1.31-3.63 with P = 2.9 × 10⁻³ for rs6532496 and OR=2.07, 95% CI=1.24-3.45 with P = 5.43 × 10⁻³ for rs951613, respectively). Results from Bayesian logistic regression showed stronger interaction effects (OR=2.26, 95% CI=1.2-3.38 for rs6532496 and OR=2.14, 95% CI=1.14-3.2 for rs951613, respectively). All the 12 SNPs associated with cancer revealed significant gene-steroid interaction effects (P < 0.05); whereas 13 SNPs showed gene-steroid interaction effects without main effect on cancer. SNP rs4634230 revealed the strongest gene-steroid interaction effect (OR=2.49, 95% CI=1.5-4.13 with P = 4.0 × 10⁻⁴ based on the classic logistic regression and OR=2.59, 95% CI=1.4-3.97 from Bayesian logistic regression; respectively). This study provides evidence of common genetic variants within the PDLIM5 gene and interactions between PLDIM5 gene polymorphisms and steroid use influencing cancer.

Coping Styles in Heart Failure Patients with Depressive Symptoms

PubMed Central

Trivedi, Ranak B.; Blumenthal, James A.; O'Connor, Christopher; Adams, Kirkwood; Hinderliter, Alan; Sueta-Dupree, Carla; Johnson, Kristy; Sherwood, Andrew

2009-01-01

Objective Elevated depressive symptoms have been linked to poorer prognosis in heart failure (HF) patients. Our objective was to identify coping styles associated with depressive symptoms in HF patients. Methods 222 stable HF patients (32.75% female, 45.4% non-Hispanic Black) completed multiple questionnaires. Beck Depression Inventory (BDI) assessed depressive symptoms, Life Orientation Test (LOT-R) assessed optimism, ENRICHD Social Support Inventory (ESSI) and Perceived Social Support Scale (PSSS) assessed social support, and COPE assessed coping styles. Linear regression analyses were employed to assess the association of coping styles with continuous BDI scores. Logistic regression analyses were performed using BDI scores dichotomized into BDI<10 versus BDI≥10, to identify coping styles accompanying clinically significant depressive symptoms. Results In linear regression models, higher BDI scores were associated with lower scores on the acceptance (β=-.14), humor (β=-.15), planning (β=-.15), and emotional support (β=-.14) subscales of the COPE, and higher scores on the behavioral disengagement (β=.41), denial (β=.33), venting (β=.25), and mental disengagement (β=.22) subscales. Higher PSSS and ESSI scores were associated with lower BDI scores (β=-.32 and -.25, respectively). Higher LOT-R scores were associated with higher BDI scores (β=.39, p<.001). In logistical regression models, BDI≥10 was associated with greater likelihood of behavioral disengagement (OR=1.3), denial (OR=1.2), mental disengagement (OR=1.3), venting (OR=1.2), and pessimism (OR=1.2), and lower perceived social support measured by PSSS (OR=.92) and ESSI (OR=.92). Conclusion Depressive symptoms in HF patients are associated with avoidant coping, lower perceived social support, and pessimism. Results raise the possibility that interventions designed to improve coping may reduce depressive symptoms. PMID:19773027

Coping styles in heart failure patients with depressive symptoms.

PubMed

Trivedi, Ranak B; Blumenthal, James A; O'Connor, Christopher; Adams, Kirkwood; Hinderliter, Alan; Dupree, Carla; Johnson, Kristy; Sherwood, Andrew

2009-10-01

Elevated depressive symptoms have been linked to poorer prognosis in heart failure (HF) patients. Our objective was to identify coping styles associated with depressive symptoms in HF patients. A total of 222 stable HF patients (32.75% female, 45.4% non-Hispanic black) completed multiple questionnaires. Beck Depression Inventory (BDI) assessed depressive symptoms, Life Orientation Test (LOT-R) assessed optimism, ENRICHD Social Support Inventory (ESSI) and Perceived Social Support Scale (PSSS) assessed social support, and COPE assessed coping styles. Linear regression analyses were employed to assess the association of coping styles with continuous BDI scores. Logistic regression analyses were performed using BDI scores dichotomized into BDI<10 vs. BDI> or =10, to identify coping styles accompanying clinically significant depressive symptoms. In linear regression models, higher BDI scores were associated with lower scores on the acceptance (beta=-.14), humor (beta=-.15), planning (beta=-.15), and emotional support (beta=-.14) subscales of the COPE, and higher scores on the behavioral disengagement (beta=.41), denial (beta=.33), venting (beta=.25), and mental disengagement (beta=.22) subscales. Higher PSSS and ESSI scores were associated with lower BDI scores (beta=-.32 and -.25, respectively). Higher LOT-R scores were associated with higher BDI scores (beta=.39, P<.001). In logistical regression models, BDI> or =10 was associated with greater likelihood of behavioral disengagement (OR=1.3), denial (OR=1.2), mental disengagement (OR=1.3), venting (OR=1.2), and pessimism (OR=1.2), and lower perceived social support measured by PSSS (OR=.92) and ESSI (OR=.92). Depressive symptoms in HF patients are associated with avoidant coping, lower perceived social support, and pessimism. Results raise the possibility that interventions designed to improve coping may reduce depressive symptoms.

Deletion Diagnostics for Alternating Logistic Regressions

PubMed Central

Preisser, John S.; By, Kunthel; Perin, Jamie; Qaqish, Bahjat F.

2013-01-01

Deletion diagnostics are introduced for the regression analysis of clustered binary outcomes estimated with alternating logistic regressions, an implementation of generalized estimating equations (GEE) that estimates regression coefficients in a marginal mean model and in a model for the intracluster association given by the log odds ratio. The diagnostics are developed within an estimating equations framework that recasts the estimating functions for association parameters based upon conditional residuals into equivalent functions based upon marginal residuals. Extensions of earlier work on GEE diagnostics follow directly, including computational formulae for one-step deletion diagnostics that measure the influence of a cluster of observations on the estimated regression parameters and on the overall marginal mean or association model fit. The diagnostic formulae are evaluated with simulations studies and with an application concerning an assessment of factors associated with health maintenance visits in primary care medical practices. The application and the simulations demonstrate that the proposed cluster-deletion diagnostics for alternating logistic regressions are good approximations of their exact fully iterated counterparts. PMID:22777960

Does rectal indomethacin eliminate the need for prophylactic pancreatic stent placement in patients undergoing high-risk ERCP? Post hoc efficacy and cost-benefit analyses using prospective clinical trial data.

PubMed

Elmunzer, B Joseph; Higgins, Peter D R; Saini, Sameer D; Scheiman, James M; Parker, Robert A; Chak, Amitabh; Romagnuolo, Joseph; Mosler, Patrick; Hayward, Rodney A; Elta, Grace H; Korsnes, Sheryl J; Schmidt, Suzette E; Sherman, Stuart; Lehman, Glen A; Fogel, Evan L

2013-03-01

A recent large-scale randomized controlled trial (RCT) demonstrated that rectal indomethacin administration is effective in addition to pancreatic stent placement (PSP) for preventing post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) in high-risk cases. We performed a post hoc analysis of this RCT to explore whether rectal indomethacin can replace PSP in the prevention of PEP and to estimate the potential cost savings of such an approach. We retrospectively classified RCT subjects into four prevention groups: (1) no prophylaxis, (2) PSP alone, (3) rectal indomethacin alone, and (4) the combination of PSP and indomethacin. Multivariable logistic regression was used to adjust for imbalances in the prevalence of risk factors for PEP between the groups. Based on these adjusted PEP rates, we conducted an economic analysis comparing the costs associated with PEP prevention strategies employing rectal indomethacin alone, PSP alone, or the combination of both. After adjusting for risk using two different logistic regression models, rectal indomethacin alone appeared to be more effective for preventing PEP than no prophylaxis, PSP alone, and the combination of indomethacin and PSP. Economic analysis revealed that indomethacin alone was a cost-saving strategy in 96% of Monte Carlo trials. A prevention strategy employing rectal indomethacin alone could save approximately $150 million annually in the United States compared with a strategy of PSP alone, and $85 million compared with a strategy of indomethacin and PSP. This hypothesis-generating study suggests that prophylactic rectal indomethacin could replace PSP in patients undergoing high-risk ERCP, potentially improving clinical outcomes and reducing healthcare costs. A RCT comparing rectal indomethacin alone vs. indomethacin plus PSP is needed.

Work and family conflicts in employees with spinal cord injury and their caregiving partners.

PubMed

Fekete, C; Siegrist, J; Tough, H; Brinkhof, M W G

2018-01-01

Cross-sectional, observational. To investigate the association of conflicts between work and family life with indicators of health and to examine the antecedents of those conflicts in employees with spinal cord injury (SCI) and their caregiving partners. Community, Switzerland. Data from employed persons with SCI (n=79) and caregiving partners (n=93) who participated in the pro-WELL study were used. Logistic and tobit regressions were performed to assess the association of work-family and family-work conflicts with health indicators, namely mental health (36-item Short Form Health Survey (SF-36)), vitality (SF-36), well-being (WHOQoL BREF) and positive and negative affect (Positive and Negative Affect Scale short form (PANAS-S)). Own and partners' engagement in productive activities and socioeconomic circumstances were evaluated as potential antecedents of work-family and family-work conflicts using logistic regression. Work-family conflicts were related to reduced mental health (caregiving partners only), vitality and well-being. Family-work conflicts were linked to reduced mental health, vitality, well-being and positive affect in SCI and to reduced vitality in caregiving partners. Persons with lower income (SCI only) and lower subjective social position reported more conflicts than persons with higher income and higher subjective position. Higher workload increased work-family conflicts in caregiving partners and decreased family-work conflicts in SCI. Education, amount of caregiving, care-receiving and partners' employment status were not associated with the occurrence of conflicts. The optimal balance between work and family life is important to promote mental health, vitality and well-being in employees with SCI and their caregiving partners. This is especially true in employees perceiving their social position as low and in caregivers with a high workload.

Fluoride exposure and indicators of thyroid functioning in the Canadian population: implications for community water fluoridation.

PubMed

Barberio, Amanda M; Hosein, F Shaun; Quiñonez, Carlos; McLaren, Lindsay

2017-10-01

There are concerns that altered thyroid functioning could be the result of ingesting too much fluoride. Community water fluoridation (CWF) is an important source of fluoride exposure. Our objectives were to examine the association between fluoride exposure and (1) diagnosis of a thyroid condition and (2) indicators of thyroid functioning among a national population-based sample of Canadians. We analysed data from Cycles 2 and 3 of the Canadian Health Measures Survey (CHMS). Logistic regression was used to assess associations between fluoride from urine and tap water samples and the diagnosis of a thyroid condition. Multinomial logistic regression was used to examine the relationship between fluoride exposure and thyroid-stimulating hormone (TSH) level (low/normal/high). Other available variables permitted additional exploratory analyses among the subset of participants for whom we could discern some fluoride exposure from drinking water and/or dental products. There was no evidence of a relationship between fluoride exposure (from urine and tap water) and the diagnosis of a thyroid condition. There was no statistically significant association between fluoride exposure and abnormal (low or high) TSH levels relative to normal TSH levels. Rerunning the models with the sample constrained to the subset of participants for whom we could discern some source(s) of fluoride exposure from drinking water and/or dental products revealed no significant associations. These analyses suggest that, at the population level, fluoride exposure is not associated with impaired thyroid functioning in a time and place where multiple sources of fluoride exposure, including CWF, exist. © 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.

Preparing patients with cancer who work and treatment responsiveness.

PubMed

Kamau, Caroline

2017-03-01

Many patients with life-limiting illnesses continue to work because of financial reasons and because work provides good psychosocial support. A lack of appropriate advice/support through patient education could, however, make having a job detrimental to well-being (eg, symptom worsening). This study investigated the frequency with which patients received information that empowers their understanding of their condition, treatment, side effects of treatment and the likely impact on occupational functioning. A cross-sectional study. An analysis of survey data from 3457 patients with cancer in employment. Logistic regression showed that patients who received information about the impact of cancer on work life or education are 1.72 times more likely to have a positive treatment outcome. Patients who receive written information about the type of cancer are 1.99 times more likely to have a positive treatment outcome. Also, patients who receive written information before a cancer-related operation are 1.90 times more likely to have a positive treatment outcome. Information about the side effects of cancer treatment produces worse odds of a positive treatment outcome (0.65-1). A stepwise logistic regression analysing the effects irrespective of current employment status in 6710 patients showed that preparing them produces nearly twice better odds of cancer treatment responsiveness. Palliative care teams should consider ways of actively advising patients who work. Whereas the results showed evidence of good practice in cancer care, there is a need to ensure that all working patients with potentially life-limiting illnesses receive similar support. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Socio-demographic correlates of participation in mammography: a survey among women aged between 35- 69 in Tehran, Iran.

PubMed

Samah, Asnarulkhadi Abu; Ahmadian, Maryam

2012-01-01

The rates of breast cancer have increased over the past two decades, and this raises concern about physical, psychological and social well-being of women with breast cancer. Further, few women really want to do breast cancer screening. We here investigated the socio-demographic correlates of mammography participation among 400 asymptomatic Iranian women aged between 35 and 69. A cross-sectional survey was conducted at the four outpatient clinics of general hospitals in Tehran during the period from July through October, 2009. Bi-variate analyses and multi-variate binary logistic regression were employed to find the socio- demographic predictors of mammography utilization among participants. The rate of mammography participation was 21.5% and relatively high because of access to general hospital services. More women who had undergone mammography were graduates from university or college, had full-time or part-time employment, were insured whether public or private, reported a positive family history of breast cancer, and were in the middle income level (P <0.01).The largest number of participating women was in the age range of 41 to 50 years. The results of multivariate logistic regression further showed that education (95%CI: 0.131-0.622), monthly income (95%CI: 0.038-0.945), and family history of breast cancer (95%CI: 1.97-9.28) were significantly associated (all P <0.05)with mammography participation. The most important issue for a successful screening program is participation. Using a random sample, this study found that the potential predictor variables of mammography participation included a higher education level, a middle income level, and a positive family history of breast cancer for Iranian women after adjusting for all other demographic variables in the model.

Continuity of cannabis use and violent offending over the life course.

PubMed

Schoeler, T; Theobald, D; Pingault, J-B; Farrington, D P; Jennings, W G; Piquero, A R; Coid, J W; Bhattacharyya, S

2016-06-01

Although the association between cannabis use and violence has been reported in the literature, the precise nature of this relationship, especially the directionality of the association, is unclear. Young males from the Cambridge Study of Delinquent Development (n = 411) were followed up between the ages of 8 and 56 years to prospectively investigate the association between cannabis use and violence. A multi-wave (eight assessments, T1-T8) follow-up design was employed that allowed temporal sequencing of the variables of interest and the analysis of violent outcome measures obtained from two sources: (i) criminal records (violent conviction); and (ii) self-reports. A combination of analytic approaches allowing inferences as to the directionality of associations was employed, including multivariate logistic regression analysis, fixed-effects analysis and cross-lagged modelling. Multivariable logistic regression revealed that compared with never-users, continued exposure to cannabis (use at age 18, 32 and 48 years) was associated with a higher risk of subsequent violent behaviour, as indexed by convictions [odds ratio (OR) 7.1, 95% confidence interval (CI) 2.19-23.59] or self-reports (OR 8.9, 95% CI 2.37-46.21). This effect persisted after controlling for other putative risk factors for violence. In predicting violence, fixed-effects analysis and cross-lagged modelling further indicated that this effect could not be explained by other unobserved time-invariant factors. Furthermore, these analyses uncovered a bi-directional relationship between cannabis use and violence. Together, these results provide strong indication that cannabis use predicts subsequent violent offending, suggesting a possible causal effect, and provide empirical evidence that may have implications for public policy.

A cross-sectional study on the prevalence and associated risk factors for workplace violence against Chinese nurses.

PubMed

Shi, Lei; Zhang, Danyang; Zhou, Chenyu; Yang, Libin; Sun, Tao; Hao, Tianjun; Peng, Xiangwen; Gao, Lei; Liu, Wenhui; Mu, Yi; Han, Yuzhen; Fan, Lihua

2017-06-24

The purpose of the present study was to explore the characteristics of workplace violence that Chinese nurses at tertiary and county-level hospitals encountered in the 12 months from December 2014 to January 2016, to identify and analyse risk factors for workplace violence, and to establish the basis for future preventive strategies. A cross-sectional study. A total of 44 tertiary hospitals and 90 county-level hospitals in 16 provinces (municipalities or autonomous regions) in China. We used stratified random sampling to collect data from December 2014 to January 2016. We distributed 21 360 questionnaires, and 15 970 participants provided valid data (effective response rate=74.77%). We conducted binary logistic regression analyses on the risk factors for workplace violence among the nurses in our sample and analysed the reasons for aggression. The prevalence of workplace violence was 65.8%; of this, 64.9% was verbal violence, and physical violence and sexual harassment accounted for 11.8% and 3.9%, respectively. Frequent workplace violence occurred primarily in emergency and paediatric departments. Respondents reported that patients' relatives were the main perpetrators in tertiary and county-level hospitals. Logistic regression analysis showed that respondents' age, department, years of experience and direct contact with patients were common risk factors at different levels of hospitals. Workplace violence is frequent in China's tertiary and county-level hospitals; its occurrence is especially frequent in the emergency and paediatric departments. It is necessary to cope with workplace violence by developing effective control strategies at individual, hospital and national levels. © 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.

Risk factors for early disability pension in patients with epilepsy and vocational difficulties - Data from a specialized rehabilitation unit.

PubMed

Specht, Ulrich; Coban, Ingrid; Bien, Christian G; May, Theodor W

2015-10-01

The purpose of this study was to assess the risk factors for early disability pension (EDP) in adult patients with epilepsy in a specialized epilepsy rehabilitation setting. In a retrospective study, 246 patients with epilepsy and employment difficulties leading to referral to an inpatient rehabilitation unit were evaluated with a questionnaire on admission and after a mean of 2.5years after discharge. Patients already receiving EDP at baseline were excluded. Epilepsy-related, demographic, and employment-related data as well as cognitive functioning and psychiatric comorbidity were assessed as risk factors for EDP at follow-up and analyzed using logistic regression models. Seventy-six percent of the patients had uncontrolled epilepsy, and 66.7% had psychiatric comorbidity. At follow-up, 33.7% received an EDP. According to multivariate logistic regression analysis, age>50years (odds ratio (OR) 5.44, compared to age<30years), application for an EDP prior to admission (OR 3.7), sickness absence>3months in the previous year (OR 3.30, compared to sickness absence<3months), and psychiatric comorbidity (OR 2.79) were significant risk factors for an EDP at follow-up, while epilepsy-related factors and cognitive impairment showed an effect only in the univariate analyses. Potential risk factors for EDP in patients with epilepsy were evaluated using multivariate analysis. Knowledge of such factors may help to develop appropriate criteria for rehabilitation candidacy and interventions to reduce the risk for EDP. This might lead to an amelioration of both psychosocial burden of patients and economic burden on society. Copyright © 2015 Elsevier Inc. All rights reserved.

Work and family conflicts in employees with spinal cord injury and their caregiving partners

PubMed Central

Fekete, C; Siegrist, J; Tough, H; Brinkhof, M W G

2018-01-01

Study design: Cross-sectional, observational. Objectives: To investigate the association of conflicts between work and family life with indicators of health and to examine the antecedents of those conflicts in employees with spinal cord injury (SCI) and their caregiving partners. Setting: Community, Switzerland. Methods: Data from employed persons with SCI (n=79) and caregiving partners (n=93) who participated in the pro-WELL study were used. Logistic and tobit regressions were performed to assess the association of work–family and family–work conflicts with health indicators, namely mental health (36-item Short Form Health Survey (SF-36)), vitality (SF-36), well-being (WHOQoL BREF) and positive and negative affect (Positive and Negative Affect Scale short form (PANAS-S)). Own and partners’ engagement in productive activities and socioeconomic circumstances were evaluated as potential antecedents of work–family and family–work conflicts using logistic regression. Results: Work–family conflicts were related to reduced mental health (caregiving partners only), vitality and well-being. Family–work conflicts were linked to reduced mental health, vitality, well-being and positive affect in SCI and to reduced vitality in caregiving partners. Persons with lower income (SCI only) and lower subjective social position reported more conflicts than persons with higher income and higher subjective position. Higher workload increased work–family conflicts in caregiving partners and decreased family–work conflicts in SCI. Education, amount of caregiving, care-receiving and partners’ employment status were not associated with the occurrence of conflicts. Conclusion: The optimal balance between work and family life is important to promote mental health, vitality and well-being in employees with SCI and their caregiving partners. This is especially true in employees perceiving their social position as low and in caregivers with a high workload. PMID:28853447

Variation in hospital mortality in an Australian neonatal intensive care unit network.

PubMed

Abdel-Latif, Mohamed E; Nowak, Gen; Bajuk, Barbara; Glass, Kathryn; Harley, David

2018-07-01

Studying centre-to-centre (CTC) variation in mortality rates is important because inferences about quality of care can be made permitting changes in practice to improve outcomes. However, comparisons between hospitals can be misleading unless there is adjustment for population characteristics and severity of illness. We sought to report the risk-adjusted CTC variation in mortality among preterm infants born <32 weeks and admitted to all eight tertiary neonatal intensive care units (NICUs) in the New South Wales and the Australian Capital Territory Neonatal Network (NICUS), Australia. We analysed routinely collected prospective data for births between 2007 and 2014. Adjusted mortality rates for each NICU were produced using a multiple logistic regression model. Output from this model was used to construct funnel plots. A total of 7212 live born infants <32 weeks gestation were admitted consecutively to network NICUs during the study period. NICUs differed in their patient populations and severity of illness.The overall unadjusted hospital mortality rate for the network was 7.9% (n=572 deaths). This varied from 5.3% in hospital E to 10.4% in hospital C. Adjusted mortality rates showed little CTC variation. No hospital reached the +99.8% control limit level on adjusted funnel plots. Characteristics of infants admitted to NICUs differ, and comparing unadjusted mortality rates should be avoided. Logistic regression-derived risk-adjusted mortality rates plotted on funnel plots provide a powerful visual graphical tool for presenting quality performance data. CTC variation is readily identified, permitting hospitals to appraise their practices and start timely intervention. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Risk factors for falls in older patients with cancer.

PubMed

Zhang, Xiaotao; Sun, Ming; Liu, Suyu; Leung, Cheuk Hong; Pang, Linda; Popat, Uday R; Champlin, Richard; Holmes, Holly M; Valero, Vicente; Dinney, Colin P; Tripathy, Debu; Edwards, Beatrice J

2018-03-01

A rising number of patients with cancer are older adults (65 years of age and older), and this proportion will increase to 70% by the year 2020. Falls are a common condition in older adults. We sought to assess the prevalence and risk factors for falls in older patients with cancer. This is a single-site, retrospective cohort study. Patients who were receiving cancer care underwent a comprehensive geriatric assessments, including cognitive, functional, nutritional, physical, falls in the prior 6 months and comorbidity assessment. Vitamin D and bone densitometry were performed. Descriptive statistics and multivariable logistic regression. A total of 304 patients aged 65 or above were enrolled in this study. The mean age was 78.4±6.9 years. They had haematological, gastrointestinal, urological, breast, lung and gynaecological cancers. A total of 215 patients with available information about falls within the past 6 months were included for final analysis. Seventy-seven (35.8%) patients had at least one fall in the preceding 6 months. Functional impairment (p=0.048), frailty (p<0.001), dementia (p=0.021), major depression (p=0.010) and low social support (p=0.045) were significantly associated with the fall status in the univariate analysis. Multivariate logistic regression analysis identified frailty and functional impairment to be independent risk factors for falls. Falls are common in older patients with cancer and lead to adverse clinical outcomes. Major depression, functional impairment, frailty, dementia and low social support were risk factors for falls. Heightened awareness and targeted interventions can prevent falls in older patients with cancer. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Estimating interaction on an additive scale between continuous determinants in a logistic regression model.

PubMed

Knol, Mirjam J; van der Tweel, Ingeborg; Grobbee, Diederick E; Numans, Mattijs E; Geerlings, Mirjam I

2007-10-01

To determine the presence of interaction in epidemiologic research, typically a product term is added to the regression model. In linear regression, the regression coefficient of the product term reflects interaction as departure from additivity. However, in logistic regression it refers to interaction as departure from multiplicativity. Rothman has argued that interaction estimated as departure from additivity better reflects biologic interaction. So far, literature on estimating interaction on an additive scale using logistic regression only focused on dichotomous determinants. The objective of the present study was to provide the methods to estimate interaction between continuous determinants and to illustrate these methods with a clinical example. and results From the existing literature we derived the formulas to quantify interaction as departure from additivity between one continuous and one dichotomous determinant and between two continuous determinants using logistic regression. Bootstrapping was used to calculate the corresponding confidence intervals. To illustrate the theory with an empirical example, data from the Utrecht Health Project were used, with age and body mass index as risk factors for elevated diastolic blood pressure. The methods and formulas presented in this article are intended to assist epidemiologists to calculate interaction on an additive scale between two variables on a certain outcome. The proposed methods are included in a spreadsheet which is freely available at: http://www.juliuscenter.nl/additive-interaction.xls.

Socioeconomic and Cultural Correlates of Diet Quality in the Canadian Arctic: Results from the 2007-2008 Inuit Health Survey.

PubMed

Galloway, Tracey; Johnson-Down, Louise; Egeland, Grace M

2015-09-01

We examined the impact of socioeconomic and cultural factors on dietary quality in adult Inuit living in the Canadian Arctic. Interviews and a 24-h dietary recall were administered to 805 men and 1292 women from Inuit regions in the Canadian Arctic. We examined the effect of age, sex, education, income, employment, and cultural variables on respondents' energy, macronutrient intake, sodium/potassium ratio, and healthy eating index. Logistic regression was used to assess the impact of socioeconomic status (SES) on diet quality indicators. Age was positively associated with traditional food (TF) consumption and greater energy from protein but negatively associated with total energy and fibre intake. Associations between SES and diet quality differed considerably between men and women and there was considerable regional variability in diet quality measures. Age and cultural variables were significant predictors of diet quality in logistic regression. Increased age and use of the Inuit language in the home were the most significant predictors of TF consumption. Our findings are consistent with studies reporting a nutrition transition in circumpolar Inuit. We found considerable variability in diet quality and complex interaction between SES and cultural variables producing mixed effects that differ by age and gender.

A logistic regression approach to model the willingness of consumers to adopt renewable energy sources

NASA Astrophysics Data System (ADS)

Ulkhaq, M. M.; Widodo, A. K.; Yulianto, M. F. A.; Widhiyaningrum; Mustikasari, A.; Akshinta, P. Y.

2018-03-01

The implementation of renewable energy in this globalization era is inevitable since the non-renewable energy leads to climate change and global warming; hence, it does harm the environment and human life. However, in the developing countries, such as Indonesia, the implementation of the renewable energy sources does face technical and social problems. For the latter, renewable energy sources implementation is only effective if the public is aware of its benefits. This research tried to identify the determinants that influence consumers’ intention in adopting renewable energy sources. In addition, this research also tried to predict the consumers who are willing to apply the renewable energy sources in their houses using a logistic regression approach. A case study was conducted in Semarang, Indonesia. The result showed that only eight variables (from fifteen) that are significant statistically, i.e., educational background, employment status, income per month, average electricity cost per month, certainty about the efficiency of renewable energy project, relatives’ influence to adopt the renewable energy sources, energy tax deduction, and the condition of the price of the non-renewable energy sources. The finding of this study could be used as a basis for the government to set up a policy towards an implementation of the renewable energy sources.

[Diabetic Foot Neuropathy and Related Factors in Patients With Type 2 Diabetes Mellitus].

PubMed

Chen, Tzu-Yu; Lin, Chia-Huei; Chang, Yue-Cune; Wang, Chih-Hsin; Hung, Yi-Jen; Tzeng, Wen-Chii

2018-06-01

Patients with type 2 diabetes mellitus (T2DM) face a higher risk of diabetic foot neuropathy, which increases the risk of death. The early detection of factors that influence diabetic neuropathy reduces the risk of foot lesions, including foot ulcerations, lower extremity amputation, and mortality. To explore the demographic, disease-characteristic, health-literacy, and foot-self-care-behavior factors that affect diabetic foot neuropathy in patients with T2DM. A case-control study design was employed in which cases (Michigan Neuropathy Screening Instrument, MNSI) ≥ 2 were matched to controls based on age and gender in a medical center. A total of 114 patients diagnosed with T2DM in a medical center were recruited as participants. Data were collected using a structured questionnaire. The collected data were analyzed using Fisher's exact test, Mann-Whitney U test, and logistic regression. The results of multiple logistic regression showed that glycated hemoglobin (B = 1.696, p = .041) and communication and critical health literacy (B = -0.082, p = .034) were significant factors of diabetic foot neuropathy. The findings of this study suggest that nurses should assess the health literacy of patients with T2DM before providing health education and should develop a specific foot-care intervention for individuals with poor glycemic control.

Prediction of outcome in internet-delivered cognitive behaviour therapy for paediatric obsessive-compulsive disorder: A machine learning approach.

PubMed

Lenhard, Fabian; Sauer, Sebastian; Andersson, Erik; Månsson, Kristoffer Nt; Mataix-Cols, David; Rück, Christian; Serlachius, Eva

2018-03-01

There are no consistent predictors of treatment outcome in paediatric obsessive-compulsive disorder (OCD). One reason for this might be the use of suboptimal statistical methodology. Machine learning is an approach to efficiently analyse complex data. Machine learning has been widely used within other fields, but has rarely been tested in the prediction of paediatric mental health treatment outcomes. To test four different machine learning methods in the prediction of treatment response in a sample of paediatric OCD patients who had received Internet-delivered cognitive behaviour therapy (ICBT). Participants were 61 adolescents (12-17 years) who enrolled in a randomized controlled trial and received ICBT. All clinical baseline variables were used to predict strictly defined treatment response status three months after ICBT. Four machine learning algorithms were implemented. For comparison, we also employed a traditional logistic regression approach. Multivariate logistic regression could not detect any significant predictors. In contrast, all four machine learning algorithms performed well in the prediction of treatment response, with 75 to 83% accuracy. The results suggest that machine learning algorithms can successfully be applied to predict paediatric OCD treatment outcome. Validation studies and studies in other disorders are warranted. Copyright © 2017 John Wiley & Sons, Ltd.

Maternal employment and childhood overweight in low- and middle-income countries.

PubMed

Oddo, Vanessa M; Mueller, Noel T; Pollack, Keshia M; Surkan, Pamela J; Bleich, Sara N; Jones-Smith, Jessica C

2017-10-01

To investigate the association between maternal employment and childhood overweight in low- and middle-income countries (LMIC). Design/Setting We utilized cross-sectional data from forty-five Demographic and Health Surveys from 2010 to 2016 (n 268 763). Mothers were categorized as formally employed, informally employed or non-employed. We used country-specific logistic regression models to investigate the association between maternal employment and childhood overweight (BMI Z-score>2) and assessed heterogeneity in the association by maternal education with the inclusion of an interaction term. We used meta-analysis to pool the associations across countries. Sensitivity analyses included modelling BMI Z-score and normal weight (weight-for-age Z-score≥-2 to <2) as outcomes. Participants included children 0-5 years old and their mothers (aged 18-49 years). In most countries, neither formal nor informal employment was associated with childhood overweight. However, children of employed mothers, compared with children of non-employed mothers, had higher BMI Z-score and higher odds of normal weight. In countries where the association varied by education, children of formally employed women with high education, compared with children of non-employed women with high education, had higher odds of overweight (pooled OR=1·2; 95 % CI 1·0, 1·4). We find no clear association between employment and child overweight. However, maternal employment is associated with a modestly higher BMI Z-score and normal weight, suggesting that employment is currently associated with beneficial effects on children's weight status in most LMIC.

The relationship between employment and veteran status, disability and gender from 2004-2011 Behavioral Risk Factor Surveillance System (BRFSS).

PubMed

Smith, Diane L

2014-01-01

In 2011, about 1.8 million or 8 percent of the 22.2 million veterans were women in the US. The unemployment rate for female veterans of the wars in Iraq and Afghanistan rose to 13.5%, above the 8.4% for non-veteran adult women. To examine data from the Behavioral Risk Factor Surveillance System (BRFSS), from 2004-2011 to determine the relationship between employment and veteran status, disability and gender. Chi square analysis was used to determine if significant differences existed between the employment rate of female veterans with disabilities and female veterans without disabilities, female non-veterans with disabilities and male veterans with disabilities. Binomial logistic regression analysis was used to determine how veteran status, disability and gender affected the likelihood of not being employed. Significant differences were found in employment rate between female veterans with disabilities and female veterans without disabilities, but not when compared to female non-veterans with disabilities or male veterans with disabilities. Disability was the strongest factor increasing the likelihood of not being employed, though veteran status and female gender were also predictive. Female veterans with disabilities experience low levels of employment. Policies and programs are needed to address the unique needs of these veterans.

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.

Who gets fired, who gets re-hired: the role of workers' contract, age, health, work ability, performance, work satisfaction and employee investments.

PubMed

Wagenaar, Alfred F; Kompier, Michiel A J; Houtman, Irene L D; van den Bossche, Seth N J; Taris, Toon W

2015-04-01

Many workers have been dismissed in the past few years, either becoming unemployed or finding re-employment. The current study examined whether dismissal and its follow-up for the employee (re-employment versus unemployment) could be predicted from workers' employment contract and age, and their health status, work ability, work performance, work satisfaction and employee investments at baseline. Our sample comprised a selection of participants from the Netherlands Working Conditions Survey 2010 who participated in a follow-up questionnaire in 2012 (N = 2,644). We used logistic regression analyses to test our hypotheses. Temporary employment, low health status, low work ability, poor work performance, low work satisfaction and no employee investments in terms of training predicted future dismissal. Furthermore, older workers and workers reporting decreased work performance due to impaired health at baseline had a lower chance of re-employment after being dismissed. Interestingly, after taking into account all predictors, former temporary workers without permanent employment prospects had much better chances of re-employment after their dismissal than former permanent workers. Temporary, less healthy, low work ability, poor performing, dissatisfied and "under-invested" workers are at risk for dismissal, whereas older and less healthy workers are (also) at risk for long-term unemployment after being dismissed.

Logits and Tigers and Bears, Oh My! A Brief Look at the Simple Math of Logistic Regression and How It Can Improve Dissemination of Results

ERIC Educational Resources Information Center

Osborne, Jason W.

2012-01-01

Logistic regression is slowly gaining acceptance in the social sciences, and fills an important niche in the researcher's toolkit: being able to predict important outcomes that are not continuous in nature. While OLS regression is a valuable tool, it cannot routinely be used to predict outcomes that are binary or categorical in nature. These…

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

A Study Update of Mortality in Workers at a Phosphate Fertilizer Production Facility

PubMed Central

Yiin, James H.; Daniels, Robert D.; Kubale, Travis L.; Dunn, Kevin L.; Stayner, Leslie T.

2016-01-01

Objective To evaluate the mortality experience among 3,199 workers employed 1951–1976 at a phosphate fertilizer production plant in central Florida with follow-up through2011. Methods Cause-specific standardized mortality ratios (SMRs) for the full cohort were calculated with the U.S. population as referent. Lung cancer and leukemia risks were further analyzed using conditional logistic regression. Results The mortality due to all-causes (SMR = 1.07, 95% confidence interval [CI] 1.02–1.13, observed deaths [n] = 1,473), all-cancers (SMR = 1.16, 95%CI 1.06–1.28, n = 431), and a priori outcomes of interests including lung cancer (SMR = 1.32, 95%CI = 1.13–1.53, n = 168) and leukemia (SMR = 1.74, 95%CI = 1.11–2.62, n = 23) were statistically significantly elevated. Regression modeling on employment duration or estimated radiation scores did not show exposure–response relation with lung cancer or leukemia mortality. Conclusion SMR results showed increased lung cancer and leukemia mortality in a full cohort of the phosphate fertilizer production facility. There was, however, no exposure–response relation observed among cases and matched controls. PMID:26523937

Social participation after successful kidney transplantation.

PubMed

van der Mei, Sijrike F; van Sonderen, Eric L P; van Son, Willem J; de Jong, Paul E; Groothoff, Johan W; van den Heuvel, Wim J A

2007-03-30

To explore and describe the degree of social participation after kidney transplantation and to examine associated factors. A cross-sectional study on 239 adult patients 1-7.3 years after kidney transplantation was performed via in-home interviews on participation in obligatory activities (i.e., employment, education, household tasks) and leisure activities (volunteer work, assisting others, recreation, sports, clubs/associations, socializing, going out). Kidney transplantation patients had a lower educational level, spent less time on obligatory activities, had part-time jobs more often, and participated less in sports compared to a control group from the general population. No difference was found in socializing, church attendance, volunteer work and going out. Multivariate regression analysis showed a negative association of age and a positive association of educational status and time since transplantation with obligatory participation. Multivariate logistic regression showed positive associations of education and time since transplantation with volunteer work; age was negatively and education positively associated with sports and going out, whereas living arrangement was also associated with going out. Although kidney transplantation patients participate less in employment and sports, they do participate in household tasks, volunteer work, going out, socializing and other leisure activities. Participation is associated with factors as age, educational status and time since transplantation.

Intermediate and advanced topics in multilevel logistic regression analysis

PubMed Central

Merlo, Juan

2017-01-01

Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher‐level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within‐cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population‐average effect of covariates measured at the subject and cluster level, in contrast to the within‐cluster or cluster‐specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster‐level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28543517

Intermediate and advanced topics in multilevel logistic regression analysis.

PubMed

Austin, Peter C; Merlo, Juan

2017-09-10

Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Predictors of short-term treatment outcomes among California's Proposition 36 participants.

PubMed

Hser, Yih-Ing; Evans, Elizabeth; Teruya, Cheryl; Huang, David; Anglin, M Douglas

2007-05-01

California's voter-initiated Proposition 36 offers non-violent drug offenders community-based treatment as an alternative to incarceration or probation without treatment. This article reports short-term treatment outcomes subsequent to this major shift in drug policy. Data are from 1104 individuals randomly selected from all Proposition 36 participants assessed for treatment in five California counties during 2004. The overall study sample was 30% female, 51% white, 18% Black, 24% Hispanic, and 7% other racial/ethnic groups. The mean+/-SD age was 37+/-10 years. Counties varied considerably in participant characteristics, treatment service intensity, treatment duration, urine testing, and employment and recidivism outcomes, but not in drug use at 3-month follow-up. Controlling for county, logistic regression analysis showed that drug abstinence was predicted by gender (female), employment at baseline (full or part-time), residential (vs. outpatient) stay, low psychiatric severity, frequent urine testing by treatment facility, and more days in treatment. Recidivism was predicted only by shorter treatment duration. Employment predictors included age (younger), gender (male), baseline employment, and lower psychiatric severity. The study findings support drug testing to monitor abstinence and highlight the need to address employment and psychiatric problems among Proposition 36 participants.

Financial hardship, mastery and social support: Explaining poor mental health amongst the inadequately employed using data from the HILDA survey.

PubMed

Crowe, Laura; Butterworth, Peter; Leach, Liana

2016-12-01

This study analysed data from the Household Income and Labour Dynamics in Australia (HILDA) Survey to examine the relationship between employment status and mental health, and the mediating effects of financial hardship, mastery and social support. In addition, the study sought to explore the effects of duration of unemployment on mental health. The primary analysis used three waves of data from the HILDA Survey with 4965 young adult respondents. Longitudinal population-averaged logistic regression models assessed the association of employment status and mental health, including the contribution of mastery, financial hardship and social support in explaining this association between employment groups (unemployed vs. employed; under employed vs. employed). Sensitivity analyses utilised a fixed-effects approach and also considered the full-range of working-age respondents. Regression analysis was used to explore the effect of duration of unemployment on mental health. Respondents' who identified as unemployed or underemployed were at higher risk of poor mental health outcomes when compared to their employed counterparts. This association was ameliorated when accounting for mastery, financial hardship and social support for the unemployed, and was fully mediated for the underemployed. The fixed-effects models showed the transition to unemployment was associated with a decline in mental health and that mastery in particular contributed to that change. The same results were found with a broader age range of respondents. Finally, the relationship between duration of unemployment and mental health was not linear, with mental health showing marked decline across the first 9 weeks of unemployment. Mastery, social support and financial hardship are important factors in understanding the association of poor mental health with both unemployment and underemployment. Furthermore, the results suggest that the most deleterious effects on mental health may occur in the first two months of unemployment before plateauing. In order to prevent deterioration in mental health, these findings suggest intervention should commence immediately following job loss.

[Study on the correlation among adolescents' family function, negative life events stress amount and suicide ideation].

PubMed

Zhang, Dongdong; Chen, Ling; Yin, Dan; Miao, Jinping; Sun, Yehuan

2014-07-01

To explore the correlation between suicide ideation and family function & negative life events, as well as other influential factors in adolescents, thus present a theoretical base for clinicians and school staff to develop intervention for those problems. By adopting current situation random sampling method, Self-Rating Idea of Suicide Scale, Adolescent Self-Rating Life Events Check List and Family APGAR Index were used to assess adolescents at random in a hygiene vocational school in Changzhou City, Jiangsu Province and a collage in Wuhu City, Anhui Province. 3700 questionnaires were granted, 3675 questionnaires were collected, among which 3620 were valid. Chi-square test, t-test, and univariate logistic regression were employed in univariate analysis, multivariate logistic regression was used in multivariate analysis. The detection rate of suicide ideation is 7.0%, and the top five suicide ideation characteristics were: poor academic performance (33.6%), serious family functional impairment (25.8%), lower-middle academic performance (11.7%), bad economic conditions (10.8%) and study in Grade Three (9.9%). Multiple logistic regression showed that the following three high-level stress amount in negative life events are most crucial for suicide ideation. They are "relationships" (OR = 1.135, 95% CI 1.071 - 1. 202), "academic pressure" (OR = 1.169, 95% CI 1.101 - 1.241), and "external events" (OR = 1.278, 95% CI 1.187 - 1.376). What' s more, the stress of attending higher grades (OR = 1.980, 95% CI 1.302 - 3.008), poor academic performance (OR = 7.206, 95% CI 1.745 - 9.789), moderate family functional impairment (OR = 2.562, 95% CI 1.527 - 2.892) and its serious level (OR = 8.287, 95% CI 3.154 - 6.917) are also influential factors for suicide ideation. Severe family functional impairment and high-level stress amount of negative life events produced the main factors of suicide ideation. Therefore, necessary and sufficient support should be given to adolescents by families and schools.

The employment status of people with mental illness: National survey data from 2009 and 2010

PubMed Central

Luciano, Alison; Meara, Ellen

2014-01-01

Objective The aim of this study was to describe employment by mental illness severity in the U.S. during 2009-2010. Methods The sample included all working-age participants (age 18 to 64) from the 2009 and 2010 National Survey on Drug Use and Health (N = 77,326). Two well-established scales of mental health distinguished participants with none, mild, moderate, and serious mental illness. Analyses compared employment rate and income by mental illness severity and estimated logistic regression models of employment status controlling for demographic characteristics and substance use disorders. In secondary analyses, we assessed how the relationship between mental illness and employment varied by age and education status. Results Employment rates decreased with increasing mental illness severity (none = 75.9%, mild = 68.8%, moderate = 62.7%, serious = 54.5%, p<0.001). Over a third of people with serious mental illness, 39%, had incomes below $10,000 (compared to 23% among people without mental illness p<0.001). The gap in adjusted employment rates comparing serious to no mental illness was 1% among people 18-25 years old versus 21% among people 50-64 (p < .001). Conclusions More severe mental illness was associated with lower employment rates in 2009-2010. People with serious mental illness are less likely to be employed after age 49 than people with no, mild, or moderate mental illness. PMID:24933361

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

Participation in organized sports is positively associated with employment in adults with spinal cord injury.

PubMed

Blauwet, Cheri; Sudhakar, Supreetha; Doherty, Ashley L; Garshick, Eric; Zafonte, Ross; Morse, Leslie R

2013-05-01

The aim of this study was to determine the association between participation in organized sports programs and employment in adults with chronic spinal cord injury. This is a cross-sectional study of 149 adults with chronic spinal cord injury. Motor level and completeness of injury were confirmed by physical examination. Information related to demographics, employment, level of education, body mass index, duration of injury, participation in individually planned exercise, and participation in organized sports was obtained using a standardized questionnaire. Multivariable logistic regression analyses were used to assess factors associated with employment. In univariate analyses, employment was associated with younger age (P = 0.001) and a higher level of education (P = 0.01), whereas obesity decreased the likelihood of employment (P = 0.04). Participation in organized sports approached significance (P = 0.06). In the multivariable analysis and after adjusting for age, education, and body mass index, participation in organized sports was significantly associated with employment (odds ratio, 2.4; P = 0.04). Sex, duration of injury, wheelchair use, and participation in individually planned exercise were not significantly associated with employment (P = 0.16-0.94). In the adults with chronic spinal cord injury, participation in organized sports was positively associated with employment. Further studies are necessary to determine the causative nature of this association and how various factors related to sports participation may contribute.

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.

Predicting Social Trust with Binary Logistic Regression

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph; Hufstedler, Shirley

2015-01-01

This study used binary logistic regression to predict social trust with five demographic variables from a national sample of adult individuals who participated in The General Social Survey (GSS) in 2012. The five predictor variables were respondents' highest degree earned, race, sex, general happiness and the importance of personally assisting…

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.

Consistency in reporting condom use between husbands and wives in Bangladesh.

PubMed

Islam, Mohammad Amirul; Padmadas, Sabu S; Smith, Peter W F

2010-07-01

Consistency in reporting contraceptive use between spouses is little understood, especially in developing settings. This research challenges the accuracy of measuring contraceptive prevalence rate, which is traditionally calculated based on women's responses. Multinomial logistic regression techniques are employed on a couple dataset from the 1999-2000 Bangladesh Demographic and Health Survey (DHS) to investigate the consistency in reporting condom use between husbands and wives. The level of inconsistency in reporting condom use was about 46%, of which about 32% was explained by husbands reporting condom use while wives did not, and 14% by wives reporting condom use while husbands did not. Regression analysis showed that couple education and age difference between the spouses are significant determinants of inconsistent reporting behaviour. The findings suggest the need for alternative approaches (questions) in the DHS to ensure consistency in the collection of data related to use of family planning methods.

Employment outcomes of adults with cerebral palsy in Taiwan.

PubMed

Huang, I-Chun; Wang, Yun-Tung; Chan, Fong

2013-02-01

To examine the employment status and determinants of employability for adults with cerebral palsy (CP) in Taiwan. A cross-sectional survey was conducted. Participants were recruited from five main branches of the Cerebral Palsy Association. Two hundred and seventy-nine persons over the age of 18 (M = 26.4, SD = 7.7) with a diagnosis of cerebral palsy participated in the current study. Sixty-four of the 279 participants were employed with an employment rate of 22.9%. Of the 64 employed individuals, 67% worked in an integrated setting, 14% in supported employment, and 19% in sheltered employment. Hierarchical logistic regression analyses indicated that having an older age (odds ratio [OR] = 1.05; 95% confidence intervals [CI]: 1.01-1.10), a diagnosis of ataxia (OR = 3.44; 95% CI: 1.29-9.13), a higher educational attainment (OR = 1.86; 95% CI: 1.09-3.18), a higher mobility function in the community (OR = 1.48; 95% CI: 1.04-2.10), and a higher level of independence in daily activities (OR = 1.60; 95% CI: 1.23-2.09) were associated with an increased odds for employment. The employment rate for adults with CP in Taiwan is low. Age, CP diagnosis, educational attainment, and functional performance are important determinants related to employment outcomes for this group. Further research to validate effective medical and vocational rehabilitation interventions to improve the employability of people with CP in Taiwan is warranted.

Clustering performance comparison using K-means and expectation maximization algorithms.

PubMed

Jung, Yong Gyu; Kang, Min Soo; Heo, Jun

2014-11-14

Clustering is an important means of data mining based on separating data categories by similar features. Unlike the classification algorithm, clustering belongs to the unsupervised type of algorithms. Two representatives of the clustering algorithms are the K -means and the expectation maximization (EM) algorithm. Linear regression analysis was extended to the category-type dependent variable, while logistic regression was achieved using a linear combination of independent variables. To predict the possibility of occurrence of an event, a statistical approach is used. However, the classification of all data by means of logistic regression analysis cannot guarantee the accuracy of the results. In this paper, the logistic regression analysis is applied to EM clusters and the K -means clustering method for quality assessment of red wine, and a method is proposed for ensuring the accuracy of the classification results.

Racial/ethnic and educational differences in the estimated odds of recent nitrite use among adult household residents in the United States: an illustration of matching and conditional logistic regression.

PubMed

Delva, J; Spencer, M S; Lin, J K

2000-01-01

This article compares estimates of the relative odds of nitrite use obtained from weighted unconditional logistic regression with estimates obtained from conditional logistic regression after post-stratification and matching of cases with controls by neighborhood of residence. We illustrate these methods by comparing the odds associated with nitrite use among adults of four racial/ethnic groups, with and without a high school education. We used aggregated data from the 1994-B through 1996 National Household Survey on Drug Abuse (NHSDA). Difference between the methods and implications for analysis and inference are discussed.

Should the poor have no medicines to cure? A study on the association between social class and social security among the rural migrant workers in urban China.

PubMed

Guan, Ming

2017-11-07

The rampant urbanization and medical marketization in China have resulted in increased vulnerabilities to health and socioeconomic disparities among the rural migrant workers in urban China. In the Chinese context, the socioeconomic characteristics of rural migrant workers have attracted considerable research attention in the recent past years. However, to date, no previous studies have explored the association between the socioeconomic factors and social security among the rural migrant workers in urban China. This study aims to explore the association between socioeconomic inequity and social security inequity and the subsequent associations with medical inequity and reimbursement rejection. Data from a regionally representative sample of 2009 Survey of Migrant Workers in Pearl River Delta in China were used for analyses. Multiple logistic regressions were used to analyze the impacts of socioeconomic factors on the eight dimensions of social security (sick pay, paid leave, maternity pay, medical insurance, pension insurance, occupational injury insurance, unemployment insurance, and maternity insurance) and the impacts of social security on medical reimbursement rejection. The zero-inflated negative binomial regression model (ZINB regression) was adopted to explore the relationship between socioeconomic factors and hospital visits among the rural migrant workers with social security. The study population consisted of 848 rural migrant workers with high income who were young and middle-aged, low-educated, and covered by social security. Reimbursement rejection and abusive supervision for the rural migrant workers were observed. Logistic regression analysis showed that there were significant associations between socioeconomic factors and social security. ZINB regression showed that there were significant associations between socioeconomic factors and hospital visits among the rural migrant workers. Also, several dimensions of social security had significant associations with reimbursement rejections. This study showed that social security inequity, medical inequity, and reimbursement inequity happened to the rural migrant workers simultaneously. Future policy should strengthen health justice and enterprises' medical responsibilities to the employed rural migrant workers.

Hospital compliance with a state unfunded mandate: the case of California's Earthquake Safety Law.

PubMed

McCue, Michael J; Thompson, Jon M

2012-01-01

Abstract In recent years, community hospitals have experienced heightened regulation with many unfunded mandates. The authors assessed the market, organizational, operational, and financial characteristics of general acute care hospitals in California that have a main acute care hospital building that is noncompliant with state requirements and at risk of major structural collapse from earthquakes. Using California hospital data from 2007 to 2009, and employing logistic regression analysis, the authors found that hospitals having buildings that are at the highest risk of collapse are located in larger population markets, possess smaller market share, have a higher percentage of Medicaid patients, and have less liquidity.

Immigrants from Mexico experience serious behavioral and psychiatric problems at far lower rates than US-born Americans.

PubMed

Salas-Wright, Christopher P; Vaughn, Michael G; Goings, Trenette Clark

2017-10-01

To examine the prevalence of self-reported criminal and violent behavior, substance use disorders, and mental disorders among Mexican immigrants vis-à-vis the US born. Study findings are based on national data collected between 2012 and 2013. Binomial logistic regression was employed to examine the relationship between immigrant status and behavioral/psychiatric outcomes. Mexican immigrants report substantially lower levels of criminal and violent behaviors, substance use disorders, and mental disorders compared to US-born individuals. While some immigrants from Mexico have serious behavioral and psychiatric problems, Mexican immigrants in general experience such problems at far lower rates than US-born individuals.

Why do they leave? Factors associated with job termination among personal assistant workers in home care.

PubMed

Butler, Sandra S; Simpson, Nan; Brennan, Mark; Turner, Winston

2010-11-01

Recruiting and retaining an adequate number of personal support workers in home care is both challenging and essential to allowing elders to age in place. A mixed-method, longitudinal study examined turnover in a sample of 261 personal support workers in Maine; 70 workers (26.8%) left their employment in the first year of the study. Logistic regression analysis indicated that younger age and lack of health insurance were significant predictors of turnover. Analysis of telephone interviews revealed three overarching themes related to termination: job not worthwhile, personal reasons, and burnout. Implications of study findings for gerontological social workers are outlined.

Regression trees for predicting mortality in patients with cardiovascular disease: What improvement is achieved by using ensemble-based methods?

PubMed Central

Austin, Peter C; Lee, Douglas S; Steyerberg, Ewout W; Tu, Jack V

2012-01-01

In biomedical research, the logistic regression model is the most commonly used method for predicting the probability of a binary outcome. While many clinical researchers have expressed an enthusiasm for regression trees, this method may have limited accuracy for predicting health outcomes. We aimed to evaluate the improvement that is achieved by using ensemble-based methods, including bootstrap aggregation (bagging) of regression trees, random forests, and boosted regression trees. We analyzed 30-day mortality in two large cohorts of patients hospitalized with either acute myocardial infarction (N = 16,230) or congestive heart failure (N = 15,848) in two distinct eras (1999–2001 and 2004–2005). We found that both the in-sample and out-of-sample prediction of ensemble methods offered substantial improvement in predicting cardiovascular mortality compared to conventional regression trees. However, conventional logistic regression models that incorporated restricted cubic smoothing splines had even better performance. We conclude that ensemble methods from the data mining and machine learning literature increase the predictive performance of regression trees, but may not lead to clear advantages over conventional logistic regression models for predicting short-term mortality in population-based samples of subjects with cardiovascular disease. PMID:22777999

Substance Use, Symptom, and Employment Outcomes of Persons With a Workplace Mandate for Chemical Dependency Treatment

PubMed Central

Weisner, Constance; Lu, Yun; Hinman, Agatha; Monahan, John; Bonnie, Richard J.; Moore, Charles D.; Chi, Felicia W.; Appelbaum, Paul S.

2010-01-01

Objective This study examined the role of workplace mandates to chemical dependency treatment in treatment adherence, alcohol and drug abstinence, severity of employment problems, and severity of psychiatric problems. Methods The sample included 448 employed members of a private, nonprofit U.S. managed care health plan who entered chemical dependency treatment with a workplace mandate (N=75) or without one (N=373); 405 of these individuals were followed up at one year (N=70 and N=335, respectively), and 362 participated in a five-year follow up (N=60 and N=302, respectively). Propensity scores predicting receipt of a workplace mandate were calculated. Logistic regression and ordinary least-squares regression were used to predict length of stay in chemical dependency treatment, alcohol and drug abstinence, and psychiatric and employment problem severity at one and five years. Results Overall, participants with a workplace mandate had one- and five-year outcomes similar to those without such a mandate. Having a workplace mandate also predicted longer treatment stays and improvement in employment problems. When other factors related to outcomes were controlled for, having a workplace mandate predicted abstinence at one year, with length of stay as a mediating variable. Conclusions Workplace mandates can be an effective mechanism for improving work performance and other outcomes. Study participants who had a workplace mandate were more likely than those who did not have a workplace mandate to be abstinent at follow-up, and they did as well in treatment, both short and long term. Pressure from the workplace likely gets people to treatment earlier and provides incentives for treatment adherence. PMID:19411353

Family violence, employment status, welfare benefits, and alcohol drinking in the United States: what is the relation?

PubMed Central

Rodriguez, E; Lasch, K; Chandra, P; Lee, J

2001-01-01

OBJECTIVES—This study examined the contribution of employment status, welfare benefits, alcohol use, and other individual, and contextual factors to physical aggression during marital conflict.
METHODS—Logistic regression models were used to analyse panel data collected in the National Survey of Families and Households in 1987 and 1992. A total of 4780 married or cohabiting persons re-interviewed in 1992 were included in the analysis. Domestic violence was defined as reporting that both partners were physically violent during arguments.
RESULTS—It was found that non-employed respondents are not at greater risk of family violence in comparison with employed respondents, after controlling for alcohol misuse, income, education, age, and other factors; however, employed persons receiving welfare benefits are at significantly higher risk. Alcohol misuse, which remains a predictor of violence even after controlling for other factors, increases the risk of family violence while satisfaction with social support from family and friends decreases it.
CONCLUSION—These results underscore the important effect of alcohol misuse on domestic violence, and the need to monitor the potential impact of welfare reform on domestic violence.


Keywords: family violence; alcohol misuse; employment status; welfare benefits PMID:11160171

GP consultations for common mental disorders and subsequent sickness certification: register-based study of the employed population in Norway

PubMed Central

Gjesdal, Sturla; Holmaas, Tor Helge; Monstad, Karin; Hetlevik, Øystein

2016-01-01

Background. Challenges related to work are in focus when employed people with common mental disorders (CMDs) consult their GPs. Many become sickness certified and remain on sick leave over time. Objectives. To investigate the frequency of new CMD episodes among employed patients in Norwegian general practice and subsequent sickness certification. Methods. Using a national claims register, employed persons with a new episode of CMD were included. Sickness certification, sick leave over 16 days and length of absences were identified. Patient- and GP-related predictors for the different outcomes were assessed by means of logistic regression. Results. During 1 year 2.6% of employed men and 4.2% of employed women consulted their GP with a new episode of CMD. Forty-five percent were sickness certified, and 24 percent were absent over 16 days. Thirty-eight percent had depression and 19% acute stress reaction, which carried the highest risk for initial sickness certification, 75%, though not for prolonged absence. Men and older patients had lower risk for sickness certification, but higher risk for long-term absence. Conclusion. Better knowledge of factors at the workplace detrimental to mental health, and better treatment for depression and stress reactions might contribute to timely return of sickness absentees. PMID:27535329

Employment conditions and maternal postpartum mental health: results from the Longitudinal Study of Australian Children.

PubMed

Cooklin, Amanda R; Canterford, Louise; Strazdins, Lyndall; Nicholson, Jan M

2011-06-01

Maternal postpartum mental health is influenced by a broad range of risk and protective factors including social circumstances. Forty percent of Australian women resume employment in the first year postpartum, yet poor quality employment (without security, control, flexibility or leave) has not been investigated as a potential social determinant of maternal psychological distress. This paper examines whether poor quality jobs are associated with an increased risk of maternal postpartum psychological distress. Data were collected from employed mothers of infants ≤12 months (n = 1,300) participating in the Longitudinal Study of Australian Children. Logistic regression analyses estimated the association between job quality and maternal psychological distress, adjusting for prior depression, social support, quality of partner relationship, adverse life events and sociodemographic characteristics. Only 21% of women reported access to all four optimal job conditions. After adjustment for known risk factors for poor maternal mood, mothers were significantly more likely to report psychological distress (adjusted OR = 1.39, 95% CI 1.09, 1.77) with each reduction in the number of optimal employment conditions. Interventions for maternal postpartum affective disorders are unlikely to be successful if major risk factors are not addressed. These results provide strong evidence that employment conditions are associated with maternal postpartum mood, and warrant consideration in psychosocial risk assessments and interventions.

Employment benefits and job retention: evidence among patients with colorectal cancer.

PubMed

Veenstra, Christine M; Abrahamse, Paul; Wagner, Todd H; Hawley, Sarah T; Banerjee, Mousumi; Morris, Arden M

2018-03-01

A "health shock," that is, a large, unanticipated adverse health event, can have long-term financial implications for patients and their families. Colorectal cancer is the third most commonly diagnosed cancer among men and women and is an example of a specific health shock. We examined whether specific benefits (employer-based health insurance, paid sick leave, extended sick leave, unpaid time off, disability benefits) are associated with job retention after diagnosis and treatment of colorectal cancer. In 2011-14, we surveyed patients with Stage III colorectal cancer from two representative SEER registries. The final sample was 1301 patients (68% survey response rate). For this study, we excluded 735 respondents who were not employed and 20 with unknown employment status. The final analytic sample included 546 respondents. Job retention in the year following diagnosis was assessed, and multivariable logistic regression was used to evaluate associations between job retention and access to specific employment benefits. Employer-based health insurance (OR = 2.97; 95% CI = 1.56-6.01; P = 0.003) and paid sick leave (OR = 2.93; 95% CI = 1.23-6.98; P = 0.015) were significantly associated with job retention, after adjusting for sociodemographic, clinical, geographic, and job characteristics. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

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.

Strategies for Testing Statistical and Practical Significance in Detecting DIF with Logistic Regression Models

ERIC Educational Resources Information Center

Fidalgo, Angel M.; Alavi, Seyed Mohammad; Amirian, Seyed Mohammad Reza

2014-01-01

This study examines three controversial aspects in differential item functioning (DIF) detection by logistic regression (LR) models: first, the relative effectiveness of different analytical strategies for detecting DIF; second, the suitability of the Wald statistic for determining the statistical significance of the parameters of interest; and…

Iterative Purification and Effect Size Use with Logistic Regression for Differential Item Functioning Detection

ERIC Educational Resources Information Center

French, Brian F.; Maller, Susan J.

2007-01-01

Two unresolved implementation issues with logistic regression (LR) for differential item functioning (DIF) detection include ability purification and effect size use. Purification is suggested to control inaccuracies in DIF detection as a result of DIF items in the ability estimate. Additionally, effect size use may be beneficial in controlling…

A Note on Three Statistical Tests in the Logistic Regression DIF Procedure

ERIC Educational Resources Information Center

Paek, Insu

2012-01-01

Although logistic regression became one of the well-known methods in detecting differential item functioning (DIF), its three statistical tests, the Wald, likelihood ratio (LR), and score tests, which are readily available under the maximum likelihood, do not seem to be consistently distinguished in DIF literature. This paper provides a clarifying…

"Let Me Count the Ways:" Fostering Reasons for Living among Low-Income, Suicidal, African American Women

ERIC Educational Resources Information Center

West, Lindsey M.; Davis, Telsie A.; Thompson, Martie P.; Kaslow, Nadine J.

2011-01-01

Protective factors for fostering reasons for living were examined among low-income, suicidal, African American women. Bivariate logistic regressions revealed that higher levels of optimism, spiritual well-being, and family social support predicted reasons for living. Multivariate logistic regressions indicated that spiritual well-being showed…

Comparison of Two Approaches for Handling Missing Covariates in Logistic Regression

ERIC Educational Resources Information Center

Peng, Chao-Ying Joanne; Zhu, Jin

2008-01-01

For the past 25 years, methodological advances have been made in missing data treatment. Most published work has focused on missing data in dependent variables under various conditions. The present study seeks to fill the void by comparing two approaches for handling missing data in categorical covariates in logistic regression: the…

Comparison of IRT Likelihood Ratio Test and Logistic Regression DIF Detection Procedures

ERIC Educational Resources Information Center

Atar, Burcu; Kamata, Akihito

2011-01-01

The Type I error rates and the power of IRT likelihood ratio test and cumulative logit ordinal logistic regression procedures in detecting differential item functioning (DIF) for polytomously scored items were investigated in this Monte Carlo simulation study. For this purpose, 54 simulation conditions (combinations of 3 sample sizes, 2 sample…

Multiple Logistic Regression Analysis of Cigarette Use among High School Students

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph

2011-01-01

A binary logistic regression analysis was performed to predict high school students' cigarette smoking behavior from selected predictors from 2009 CDC Youth Risk Behavior Surveillance Survey. The specific target student behavior of interest was frequent cigarette use. Five predictor variables included in the model were: a) race, b) frequency of…

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…

Propensity Score Estimation with Data Mining Techniques: Alternatives to Logistic Regression

ERIC Educational Resources Information Center

Keller, Bryan S. B.; Kim, Jee-Seon; Steiner, Peter M.

2013-01-01

Propensity score analysis (PSA) is a methodological technique which may correct for selection bias in a quasi-experiment by modeling the selection process using observed covariates. Because logistic regression is well understood by researchers in a variety of fields and easy to implement in a number of popular software packages, it has…

Two-factor logistic regression in pediatric liver transplantation

NASA Astrophysics Data System (ADS)

Uzunova, Yordanka; Prodanova, Krasimira; Spasov, Lyubomir

2017-12-01

Using a two-factor logistic regression analysis an estimate is derived for the probability of absence of infections in the early postoperative period after pediatric liver transplantation. The influence of both the bilirubin level and the international normalized ratio of prothrombin time of blood coagulation at the 5th postoperative day is studied.

Predictors of Placement Stability at the State Level: The Use of Logistic Regression to Inform Practice

ERIC Educational Resources Information Center

Courtney, Jon R.; Prophet, Retta

2011-01-01

Placement instability is often associated with a number of negative outcomes for children. To gain state level contextual knowledge of factors associated with placement stability/instability, logistic regression was applied to selected variables from the New Mexico Adoption and Foster Care Administrative Reporting System dataset. Predictors…

Classifying machinery condition using oil samples and binary logistic regression

NASA Astrophysics Data System (ADS)

Phillips, J.; Cripps, E.; Lau, John W.; Hodkiewicz, M. R.

2015-08-01

The era of big data has resulted in an explosion of condition monitoring information. The result is an increasing motivation to automate the costly and time consuming human elements involved in the classification of machine health. When working with industry it is important to build an understanding and hence some trust in the classification scheme for those who use the analysis to initiate maintenance tasks. Typically "black box" approaches such as artificial neural networks (ANN) and support vector machines (SVM) can be difficult to provide ease of interpretability. In contrast, this paper argues that logistic regression offers easy interpretability to industry experts, providing insight to the drivers of the human classification process and to the ramifications of potential misclassification. Of course, accuracy is of foremost importance in any automated classification scheme, so we also provide a comparative study based on predictive performance of logistic regression, ANN and SVM. A real world oil analysis data set from engines on mining trucks is presented and using cross-validation we demonstrate that logistic regression out-performs the ANN and SVM approaches in terms of prediction for healthy/not healthy engines.

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

PubMed

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

2012-01-01

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

Matched samples logistic regression in case-control studies with missing values: when to break the matches.

PubMed

Hansson, Lisbeth; Khamis, Harry J

2008-12-01

Simulated data sets are used to evaluate conditional and unconditional maximum likelihood estimation in an individual case-control design with continuous covariates when there are different rates of excluded cases and different levels of other design parameters. The effectiveness of the estimation procedures is measured by method bias, variance of the estimators, root mean square error (RMSE) for logistic regression and the percentage of explained variation. Conditional estimation leads to higher RMSE than unconditional estimation in the presence of missing observations, especially for 1:1 matching. The RMSE is higher for the smaller stratum size, especially for the 1:1 matching. The percentage of explained variation appears to be insensitive to missing data, but is generally higher for the conditional estimation than for the unconditional estimation. It is particularly good for the 1:2 matching design. For minimizing RMSE, a high matching ratio is recommended; in this case, conditional and unconditional logistic regression models yield comparable levels of effectiveness. For maximizing the percentage of explained variation, the 1:2 matching design with the conditional logistic regression model is recommended.

Label-noise resistant logistic regression for functional data classification with an application to Alzheimer's disease study.

PubMed

Lee, Seokho; Shin, Hyejin; Lee, Sang Han

2016-12-01

Alzheimer's disease (AD) is usually diagnosed by clinicians through cognitive and functional performance test with a potential risk of misdiagnosis. Since the progression of AD is known to cause structural changes in the corpus callosum (CC), the CC thickness can be used as a functional covariate in AD classification problem for a diagnosis. However, misclassified class labels negatively impact the classification performance. Motivated by AD-CC association studies, we propose a logistic regression for functional data classification that is robust to misdiagnosis or label noise. Specifically, our logistic regression model is constructed by adopting individual intercepts to functional logistic regression model. This approach enables to indicate which observations are possibly mislabeled and also lead to a robust and efficient classifier. An effective algorithm using MM algorithm provides simple closed-form update formulas. We test our method using synthetic datasets to demonstrate its superiority over an existing method, and apply it to differentiating patients with AD from healthy normals based on CC from MRI. © 2016, The International Biometric Society.

The Effect of Latent Binary Variables on the Uncertainty of the Prediction of a Dichotomous Outcome Using Logistic Regression Based Propensity Score Matching.

PubMed

Szekér, Szabolcs; Vathy-Fogarassy, Ágnes

2018-01-01

Logistic regression based propensity score matching is a widely used method in case-control studies to select the individuals of the control group. This method creates a suitable control group if all factors affecting the output variable are known. However, if relevant latent variables exist as well, which are not taken into account during the calculations, the quality of the control group is uncertain. In this paper, we present a statistics-based research in which we try to determine the relationship between the accuracy of the logistic regression model and the uncertainty of the dependent variable of the control group defined by propensity score matching. Our analyses show that there is a linear correlation between the fit of the logistic regression model and the uncertainty of the output variable. In certain cases, a latent binary explanatory variable can result in a relative error of up to 70% in the prediction of the outcome variable. The observed phenomenon calls the attention of analysts to an important point, which must be taken into account when deducting conclusions.

Postsecondary education and employment among youth with an autism spectrum disorder.

PubMed

Shattuck, Paul T; Narendorf, Sarah Carter; Cooper, Benjamin; Sterzing, Paul R; Wagner, Mary; Taylor, Julie Lounds

2012-06-01

We examined the prevalence and correlates of postsecondary education and employment among youth with an autism spectrum disorder (ASD). Data were from a nationally representative survey of parents, guardians, and young adults with an ASD. Participation in postsecondary employment, college, or vocational education and lack of participation in any of these activities were examined. Rates were compared with those of youth in 3 other eligibility categories: speech/language impairment, learning disability, and mental retardation. Logistic regression was used to examine correlates of each outcome. For youth with an ASD, 34.7% had attended college and 55.1% had held paid employment during the first 6 years after high school. More than 50% of youth who had left high school in the past 2 years had no participation in employment or education. Youth with an ASD had the lowest rates of participation in employment and the highest rates of no participation compared with youth in other disability categories. Higher income and higher functional ability were associated with higher adjusted odds of participation in postsecondary employment and education. Youth with an ASD have poor postsecondary employment and education outcomes, especially in the first 2 years after high school. Those from lower-income families and those with greater functional impairments are at heightened risk for poor outcomes. Further research is needed to understand how transition planning before high school exit can facilitate a better connection to productive postsecondary activities.

The relation between indicators of low employment quality and attendance behavior in countries of the European Union.

PubMed

Janssens, Heidi; Braeckman, Lutgart; De Clercq, Bart; De Bacquer, Dirk; Clays, Els

2017-12-01

Previous research demonstrated an association between low employment quality and lower sickness absence, which may be explained by presenteeism. Therefore, this study aimed exploring the relation between three indicators of employment quality (long working hours, precarious employment, job insecurity) and attendance behavior. The association between employment quality and attendance behavior was investigated in 28.999 workers (mean age: 40.0 years, 53% males) of the fifth wave of the European Working Conditions Survey, using multilevel multinomial logistic regression analysis. Attendance behavior was operationalized as different combinations of sickness absence and presenteeism. Those working >48 h/week, had a higher risk to report presenteeism (with or without sickness absence). They had a lower risk to report sickness absence without presenteeism. Workers with a precarious contract had a lower risk to report absenteeism without presenteeism and the combination of both presenteeism and absenteeism. Finally, for workers perceiving job insecurity, the risk for presenteeism without sickness absence was significantly higher. Several indicators of low employment quality were associated with attendance behavior, suggesting a complex behavioral mechanism in workers facing low job quality employment. Therefore, policy makers are recommended to re-establish the indefinite contractual employment as the standard, avoiding long working hours. © The Author 2016. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Employment Implications of Informal Cancer Caregiving

PubMed Central

de Moor, Janet S.; Dowling, Emily C.; Ekwueme, Donatus U.; Guy, Gery P.; Rodriguez, Juan; Virgo, Katherine S.; Han, Xuesong; Kent, Erin E.; Li, Chunyu; Litzelman, Kristen; McNeel, Timothy S.; Liu, Benmei; Yabroff, K. Robin

2016-01-01

Purpose Previous research describing how informal cancer caregiving impacts employment has been conducted in small samples or a single disease site. This paper provides population-based estimates of the effect of cancer caregiving on employment and characterizes the employment changes made by caregivers. Methods The sample comprised cancer survivors with a friend or family caregiver, participating in either the Medical Expenditure Panel Survey Experiences with Cancer Survivorship Survey (ECSS) (n=458) or the LIVESTRONG 2012 Survey for People Affected by Cancer (SPAC) (n=4,706). Descriptive statistics characterized the sample of survivors and their caregivers’ employment changes. Multivariable logistic regression identified predictors of caregivers’ extended employment changes, comprising time off and changes to hours, duties or employment status. Results Among survivors with an informal caregiver, 25% from the ECSS and 29% from the SPAC reported their caregivers made extended employment changes. Approximately 8% of survivors had caregivers who took time off from work lasting ≥ 2 months. Caregivers who made extended employment changes were more likely to care for survivors treated with chemotherapy or transplant; closer to diagnosis or end of treatment; who experienced functional limitations; and made work changes due to cancer themselves compared to caregivers who did not make extended employment changes. Conclusions Many informal cancer caregivers make employment changes to provide care during survivors’ treatment and recovery. Implications for cancer survivors This study describes cancer caregiving in a prevalent sample of cancer survivors, thereby reflecting the experiences of individuals with many different cancer types and places in the cancer treatment trajectory. PMID:27423439

Examination of Veterans Affairs disability compensation as a disincentive for employment in a population-based sample of Veterans under age 65.

PubMed

Tsai, Jack; Rosenheck, Robert A

2013-12-01

Concerns that disability benefits may create disincentives for employment may be especially relevant for young American military veterans, particularly veterans of the recent wars in Iraq and Afghanistan who are facing a current economic recession and turning in large numbers to the Department of Veterans Affairs (VA) for disability compensation. This study describes the rate of employment and VA disability compensation among a nationally representative sample of veterans under the age of 65 and examines the association between levels of VA disability compensation and employment, adjusting for sociodemographics and health status. Data on a total of 4,787 veterans from the 2010 National Survey of Veterans were analyzed using multinomial logistic regressions to compare employed veterans with two groups that were not employed. Two-thirds of veterans under the age of 65 were employed, although only 36 % of veterans with a VA service-connected disability rating of 50 % or higher were employed. Veterans who received no VA disability compensation or who were service-connected 50 % or more were more likely to be unemployed and not looking for employment than veterans who were not service-connected or were service-connected less than 50 %, suggesting high but not all levels of VA disability compensation create disincentives for employment. Results were similar when analyses were limited to veterans who served in Iraq and Afghanistan. Education and vocational rehabilitation interventions, as well as economic work incentives, may be needed to maximize employment among veterans with disabilities.

Employment implications of informal cancer caregiving.

PubMed

de Moor, Janet S; Dowling, Emily C; Ekwueme, Donatus U; Guy, Gery P; Rodriguez, Juan; Virgo, Katherine S; Han, Xuesong; Kent, Erin E; Li, Chunyu; Litzelman, Kristen; McNeel, Timothy S; Liu, Benmei; Yabroff, K Robin

2017-02-01

Previous research describing how informal cancer caregiving impacts employment has been conducted in small samples or a single disease site. This paper provides population-based estimates of the effect of informal cancer caregiving on employment and characterizes employment changes made by caregivers. The samples included cancer survivors with a friend or family caregiver, participating in either the Medical Expenditure Panel Survey Experiences with Cancer Survivorship Survey (ECSS) (n = 458) or the LIVESTRONG 2012 Survey for People Affected by Cancer (SPAC) (n = 4706). Descriptive statistics characterized the sample of survivors and their caregivers' employment changes. Multivariable logistic regression identified predictors of caregivers' extended employment changes, comprising time off and changes to hours, duties, or employment status. Among survivors with an informal caregiver, 25 % from the ECSS and 29 % from the SPAC reported that their caregivers made extended employment changes. Approximately 8 % of survivors had caregivers who took time off from work lasting ≥2 months. Caregivers who made extended employment changes were more likely to care for survivors: treated with chemotherapy or transplant; closer to diagnosis or end of treatment; who experienced functional limitations; and made work changes due to cancer themselves compared to caregivers who did not make extended employment changes. Many informal cancer caregivers make employment changes to provide care during survivors' treatment and recovery. This study describes cancer caregiving in a prevalent sample of cancer survivors, thereby reflecting the experiences of individuals with many different cancer types and places in the cancer treatment trajectory.

The association between chronological age, age at injury and employment: Is there a mediating effect of secondary health conditions?

PubMed

Marti, A; Boes, S; Lay, V; Escorpizo, R; Reuben Escorpizo, P T; Trezzini, B

2016-03-01

Cross-sectional observational study with data from the 2012 community-based survey of the Swiss Spinal Cord Injury Cohort Study. To examine the relationships between chronological age, age at injury, secondary health conditions (SHCs) and paid employment. Community setting in Switzerland. A total of 1159 individuals of working age (16-63 years for women and 64 years for men) with traumatic or non-traumatic spinal cord injury (SCI) were included in the study. Direct and indirect (via SHCs) effects of chronological age and age at injury on paid employment were tested using a decomposition method for logistic regression models. Both chronological age groups (age 35-49 and 50-63/64 years) and the group with age at injury beyond 40 years showed negative direct effects on employment status. A partial indirect effect (mediation) via chronic pain was found in the group with the highest chronological age (>50 years). Furthermore, pressure ulcer, pain and urinary tract infection were negatively related with employment in both models, that is, chronological age and employment and age at injury and employment. Being older and having a higher age at injury directly affects whether an individual is employed. Pain is mediating the relation between chronological age and employment. Furthermore, pressure ulcer, chronic pain and urinary tract infection directly reduce the likelihood to be employed and, therefore, represent important intervention targets in efforts to maintain or engage in employment of individuals with SCI.

Naval Research Logistics Quarterly. Volume 28. Number 3,

DTIC Science & Technology

1981-09-01

denotes component-wise maximum. f has antone (isotone) differences on C x D if for cl < c2 and d, < d2, NAVAL RESEARCH LOGISTICS QUARTERLY VOL. 28...or negative correlations and linear or nonlinear regressions. Given are the mo- ments to order two and, for special cases, (he regression function and...data sets. We designate this bnb distribution as G - B - N(a, 0, v). The distribution admits only of positive correlation and linear regressions

Regression approaches in the test-negative study design for assessment of influenza vaccine effectiveness.

PubMed

Bond, H S; Sullivan, S G; Cowling, B J

2016-06-01

Influenza vaccination is the most practical means available for preventing influenza virus infection and is widely used in many countries. Because vaccine components and circulating strains frequently change, it is important to continually monitor vaccine effectiveness (VE). The test-negative design is frequently used to estimate VE. In this design, patients meeting the same clinical case definition are recruited and tested for influenza; those who test positive are the cases and those who test negative form the comparison group. When determining VE in these studies, the typical approach has been to use logistic regression, adjusting for potential confounders. Because vaccine coverage and influenza incidence change throughout the season, time is included among these confounders. While most studies use unconditional logistic regression, adjusting for time, an alternative approach is to use conditional logistic regression, matching on time. Here, we used simulation data to examine the potential for both regression approaches to permit accurate and robust estimates of VE. In situations where vaccine coverage changed during the influenza season, the conditional model and unconditional models adjusting for categorical week and using a spline function for week provided more accurate estimates. We illustrated the two approaches on data from a test-negative study of influenza VE against hospitalization in children in Hong Kong which resulted in the conditional logistic regression model providing the best fit to the data.

Interstitial lung abnormalities and self-reported health and functional status.

PubMed

Axelsson, Gisli Thor; Putman, Rachel K; Araki, Tetsuro; Sigurdsson, Sigurdur; Gudmundsson, Elias Freyr; Eiriksdottir, Gudny; Aspelund, Thor; Miller, Ezra R; Launer, Lenore J; Harris, Tamara B; Hatabu, Hiroto; Gudnason, Vilmundur; Hunninghake, Gary Matt; Gudmundsson, Gunnar

2018-01-09

We investigated the association between interstitial lung abnormalities (ILA) and self-reported measures of health and functional status in 5764 participants from the Age, Gene/Environment Susceptibility-Reykjavik study. The associations of ILA to activities of daily living (ADLs), general health status and physical activity were explored using logistic regression models. Participants with ILA were less likely to be independent in ADLs (OR 0.70; 95% CI 0.55 to 0.90) to have good or better self-reported health (OR 0.66; 95% CI 0.52 to 0.82) and to participate in physical activity (OR 0.72; CI 0.56 to 0.91). The results demonstrate ILA's association with worsening self-reported health and functional status. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Turnover and Associated Factors in Asian Foreign-Educated Nurses.

PubMed

Geun, Hyo Geun; Redman, Richard W; McCullagh, Marjorie C

2016-05-01

The purposes of this study are to (1) describe the gap between expected and perceived organizational experiences among Asian foreign-educated nurses (FENs) in the United States and (2) to examine factors associated with turnover in their 1st year of employment. Little is known about factors associated with turnover among Asian FENs. A cross-sectional design with a convenience sampling was conducted. Subjects (n = 201) responded either via Web-based or mail survey. A series of simple and multivariable logistic regressions were used. Expectations of FENs before organizational entry were significantly higher than their experiences. The FENs who reported less organizational responsibility than expected were more likely to leave their 1st employment to move to another organization or unit. This study may contribute to our understanding of the potential factors that assist or interfere with the organization's administrative retention plan for Asian FENs.

Outcome-based and Participation-based Wellness Incentives

PubMed Central

Barleen, Nathan A.; Marzec, Mary L.; Boerger, Nicholas L.; Moloney, Daniel P.; Zimmerman, Eric M.; Dobro, Jeff

2017-01-01

Objective: This study examined whether worksite wellness program participation or achievement of health improvement targets differed according to four incentive types (participation-based, hybrid, outcome-based, and no incentive). Methods: The study included individuals who completed biometric health screenings in both 2013 and 2014 and had elevated metrics in 2013 (baseline year). Multivariate logistic regression modeling tested for differences in odds of participation and achievement of health improvement targets between incentive groups; controlling for demographics, employer characteristics, incentive amounts, and other factors. Results: No statistically significant differences between incentive groups occurred for odds of participation or achievement of health improvement target related to body mass index, blood pressure, or nonhigh-density lipoprotein cholesterol. Conclusions: Given the null findings of this study, employers cannot assume that outcome-based incentives will result in either increased program participation or greater achievement of health improvement targets than participation-based incentives. PMID:28146041

Type of Insurance and Use of Preventive Health Services Among Older Adults in Mexico.

PubMed

Rivera-Hernandez, Maricruz; Galarraga, Omar

2015-09-01

The main purpose of this article was to assess the differences between Seguro Popular (SP) and employer-based health insurance in the use of preventive services, including screening tests for diabetes, cholesterol, hypertension, cervical cancer, and prostate cancer among older adults at more than a decade of health care reform in Mexico. Logistic regression models were used with data from the Mexican Health and Nutrition Survey, 2012. After adjusting for other factors influencing preventive service utilization, SP enrollees were more likely to use screening tests for diabetes, cholesterol, hypertension, and cervical cancer than the uninsured; however, those in employment-based and private insurances had higher odds of using preventive care for most of these services, except Pap smears. Despite all the evidence that suggests that SP has increased access to health insurance for the poor, inequalities in health care access and utilization still exist in Mexico. © The Author(s) 2015.

Maternal occupation and risk for low birth weight delivery: assessment using state birth registry data.

PubMed

Meyer, John D; Nichols, Ginger H; Warren, Nicholas; Reisine, Susan

2008-03-01

To determine the effects of employment on low birth weight (LBW) in a service-based economy, we evaluated the association of LBW delivery with occupational data collected in a state birth registry. Occupational data in the 2000 Connecticut birth registry were coded for 41,009 singleton births. Associations between employment and LBW delivery were analyzed using logistic regression controlling for covariates in the registry data set. Evidence for improved LBW outcomes in working mothers did not persist when adjusted for maternal covariates. Among working mothers, elevated risk of LBW was seen in textile, food service, personal appearance, material dispatching or distributing, and retail sales workers. Improved overall birth outcomes seen in working mothers may arise from favorable demographic and health attributes. Higher LBW risk was seen in several types of service sector jobs and in textile work.

Type of insurance and use of preventive health services among older adults in Mexico

PubMed Central

Rivera-Hernandez, Maricruz; Galarraga, Omar

2016-01-01

Objectives The main purpose of this paper was to assess the differences between Seguro Popular (SP) and employer-based health insurance in the use of preventive services, including screening tests for diabetes, cholesterol, hypertension, cervical cancer and prostate cancer among older adults at more than a decade of health care reform in Mexico. Methods Logistic regression models were used with data from the Mexican Health and Nutrition Survey 2012. Results After adjusting for other factors influencing preventive service utilization, SP enrollees were more likely to use screening tests for diabetes, cholesterol, hypertension and cervical cancer than the uninsured; however, those in employment-based and private insurances had higher odds of using preventive care for most of these services, except Pap smears. Discussion Despite all the evidence that suggests that Seguro Popular has increased access to health insurance for the poor, inequalities in healthcare access still exist in Mexico. PMID:25804897

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network

PubMed Central

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins. PMID:27418910

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network.

PubMed

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins.

Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis.

PubMed

Armstrong, Ben G; Gasparrini, Antonio; Tobias, Aurelio

2014-11-24

The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression on data expanded to case-control (case crossover) format, but this has some limitations. In particular adjusting for overdispersion and auto-correlation in the counts is not possible. It has been established that a Poisson model for counts with stratum indicators gives identical estimates to those from conditional logistic regression and does not have these limitations, but it is little used, probably because of the overheads in estimating many stratum parameters. The conditional Poisson model avoids estimating stratum parameters by conditioning on the total event count in each stratum, thus simplifying the computing and increasing the number of strata for which fitting is feasible compared with the standard unconditional Poisson model. Unlike the conditional logistic model, the conditional Poisson model does not require expanding the data, and can adjust for overdispersion and auto-correlation. It is available in Stata, R, and other packages. By applying to some real data and using simulations, we demonstrate that conditional Poisson models were simpler to code and shorter to run than are conditional logistic analyses and can be fitted to larger data sets than possible with standard Poisson models. Allowing for overdispersion or autocorrelation was possible with the conditional Poisson model but when not required this model gave identical estimates to those from conditional logistic regression. Conditional Poisson regression models provide an alternative to case crossover analysis of stratified time series data with some advantages. The conditional Poisson model can also be used in other contexts in which primary control for confounding is by fine stratification.

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

PubMed

Agga, Getahun E; Scott, H Morgan

2015-10-01

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

Essential neonatal care utilization and associated factors among mothers in public health facilities of Aksum Town, North Ethiopia, 2016.

PubMed

Berhe, Megbey; Medhaniye, Araya Abraha; Kahsay, Gizienesh; Birhane, Ermyas; Abay, Mebrahtu

2017-01-01

Globally, neonatal death accounts about 44% of child death in 2013. Ethiopia is one of the ten countries with the highest number of neonatal death. Worldwide, more than 43% of deaths among under five year children is contributed by neonates. Half of the neonatal death occur in the first day of life. Recommendations about newborn care practices may conflict with local beliefs and practices. So, it is important to understand the existing newborn care practice and factors affecting it in order to take interventions so as to decrease neonatal death. To assess magnitude of essential neonatal care utilization and associated factors among women visiting public health facilities in Aksum Town, Tigray, Northern Ethiopia, 2015. Facility based cross sectional study was conducted from December 30, 2015 to January 31, 2016.The sampled population are 423 women who gave live births within the last 6 months prior to data collection. Systematic random sampling technique was employed. Data were entered, coded and cleaned using Epi info version 7, and SPSS Version 21 software was used for analysis. Both bivariable and multivariable logistic regression models were used to determine factors associated with essential neonatal care utilization. Variables with P-value <0.2 in the bivariable logistic regression model were included in to multivariable logistic regression model, and finally variables with P-value <0.05 were considered as independent factors. Odds ratio was used to measure strength of association at 95% confidence level. A total of 423 mothers included in the study. Prevalence of safe cord care, optimal breast feeding, thermal care and baby received Tetracycline eye ointment and vaccine at birth were 42.8%, 63.1%, 32.6% and 44.7% among the respondents respectively. Only 113(26.7%) of the participants fulfilled essential new born care practice. Occupation, parity and counseling on essential new born care during delivery were significantly associated with utilization of essential new born care. Employed women (AOR = 7.08; 95% CI (2.21, 12.72), 2-3 number of deliveries (AOR = 1.84; 95% CI (1.04, 3.26) and received counseling about essential new born car during delivery (AOR = 3.36; 95% CI (1.86, 6.08) were more likely to practice essential neonatal care practice than their counterparts. Around three-fourth of mothers were not practicing Essential Newborn Care (ENC). Occupation, parity and essential new born care counseling during delivery were significantly associated with utilization of ENC. Promotion of information at community level, women empowerment and staff training is recommended.

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.

The use of machine learning for the identification of peripheral artery disease and future mortality risk.

PubMed

Ross, Elsie Gyang; Shah, Nigam H; Dalman, Ronald L; Nead, Kevin T; Cooke, John P; Leeper, Nicholas J

2016-11-01

A key aspect of the precision medicine effort is the development of informatics tools that can analyze and interpret "big data" sets in an automated and adaptive fashion while providing accurate and actionable clinical information. The aims of this study were to develop machine learning algorithms for the identification of disease and the prognostication of mortality risk and to determine whether such models perform better than classical statistical analyses. Focusing on peripheral artery disease (PAD), patient data were derived from a prospective, observational study of 1755 patients who presented for elective coronary angiography. We employed multiple supervised machine learning algorithms and used diverse clinical, demographic, imaging, and genomic information in a hypothesis-free manner to build models that could identify patients with PAD and predict future mortality. Comparison was made to standard stepwise linear regression models. Our machine-learned models outperformed stepwise logistic regression models both for the identification of patients with PAD (area under the curve, 0.87 vs 0.76, respectively; P = .03) and for the prediction of future mortality (area under the curve, 0.76 vs 0.65, respectively; P = .10). Both machine-learned models were markedly better calibrated than the stepwise logistic regression models, thus providing more accurate disease and mortality risk estimates. Machine learning approaches can produce more accurate disease classification and prediction models. These tools may prove clinically useful for the automated identification of patients with highly morbid diseases for which aggressive risk factor management can improve outcomes. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Artificial neural networks predict the incidence of portosplenomesenteric venous thrombosis in patients with acute pancreatitis.

PubMed

Fei, Y; Hu, J; Li, W-Q; Wang, W; Zong, G-Q

2017-03-01

Essentials Predicting the occurrence of portosplenomesenteric vein thrombosis (PSMVT) is difficult. We studied 72 patients with acute pancreatitis. Artificial neural networks modeling was more accurate than logistic regression in predicting PSMVT. Additional predictive factors may be incorporated into artificial neural networks. Objective To construct and validate artificial neural networks (ANNs) for predicting the occurrence of portosplenomesenteric venous thrombosis (PSMVT) and compare the predictive ability of the ANNs with that of logistic regression. Methods The ANNs and logistic regression modeling were constructed using simple clinical and laboratory data of 72 acute pancreatitis (AP) patients. The ANNs and logistic modeling were first trained on 48 randomly chosen patients and validated on the remaining 24 patients. The accuracy and the performance characteristics were compared between these two approaches by SPSS17.0 software. Results The training set and validation set did not differ on any of the 11 variables. After training, the back propagation network training error converged to 1 × 10 -20 , and it retained excellent pattern recognition ability. When the ANNs model was applied to the validation set, it revealed a sensitivity of 80%, specificity of 85.7%, a positive predictive value of 77.6% and negative predictive value of 90.7%. The accuracy was 83.3%. Differences could be found between ANNs modeling and logistic regression modeling in these parameters (10.0% [95% CI, -14.3 to 34.3%], 14.3% [95% CI, -8.6 to 37.2%], 15.7% [95% CI, -9.9 to 41.3%], 11.8% [95% CI, -8.2 to 31.8%], 22.6% [95% CI, -1.9 to 47.1%], respectively). When ANNs modeling was used to identify PSMVT, the area under receiver operating characteristic curve was 0.849 (95% CI, 0.807-0.901), which demonstrated better overall properties than logistic regression modeling (AUC = 0.716) (95% CI, 0.679-0.761). Conclusions ANNs modeling was a more accurate tool than logistic regression in predicting the occurrence of PSMVT following AP. More clinical factors or biomarkers may be incorporated into ANNs modeling to improve its predictive ability. © 2016 International Society on Thrombosis and Haemostasis.

PREDICTION OF MALIGNANT BREAST LESIONS FROM MRI FEATURES: A COMPARISON OF ARTIFICIAL NEURAL NETWORK AND LOGISTIC REGRESSION TECHNIQUES

PubMed Central

McLaren, Christine E.; Chen, Wen-Pin; Nie, Ke; Su, Min-Ying

2009-01-01

Rationale and Objectives Dynamic contrast enhanced MRI (DCE-MRI) is a clinical imaging modality for detection and diagnosis of breast lesions. Analytical methods were compared for diagnostic feature selection and performance of lesion classification to differentiate between malignant and benign lesions in patients. Materials and Methods The study included 43 malignant and 28 benign histologically-proven lesions. Eight morphological parameters, ten gray level co-occurrence matrices (GLCM) texture features, and fourteen Laws’ texture features were obtained using automated lesion segmentation and quantitative feature extraction. Artificial neural network (ANN) and logistic regression analysis were compared for selection of the best predictors of malignant lesions among the normalized features. Results Using ANN, the final four selected features were compactness, energy, homogeneity, and Law_LS, with area under the receiver operating characteristic curve (AUC) = 0.82, and accuracy = 0.76. The diagnostic performance of these 4-features computed on the basis of logistic regression yielded AUC = 0.80 (95% CI, 0.688 to 0.905), similar to that of ANN. The analysis also shows that the odds of a malignant lesion decreased by 48% (95% CI, 25% to 92%) for every increase of 1 SD in the Law_LS feature, adjusted for differences in compactness, energy, and homogeneity. Using logistic regression with z-score transformation, a model comprised of compactness, NRL entropy, and gray level sum average was selected, and it had the highest overall accuracy of 0.75 among all models, with AUC = 0.77 (95% CI, 0.660 to 0.880). When logistic modeling of transformations using the Box-Cox method was performed, the most parsimonious model with predictors, compactness and Law_LS, had an AUC of 0.79 (95% CI, 0.672 to 0.898). Conclusion The diagnostic performance of models selected by ANN and logistic regression was similar. The analytic methods were found to be roughly equivalent in terms of predictive ability when a small number of variables were chosen. The robust ANN methodology utilizes a sophisticated non-linear model, while logistic regression analysis provides insightful information to enhance interpretation of the model features. PMID:19409817

Rank-Optimized Logistic Matrix Regression toward Improved Matrix Data Classification.

PubMed

Zhang, Jianguang; Jiang, Jianmin

2018-02-01

While existing logistic regression suffers from overfitting and often fails in considering structural information, we propose a novel matrix-based logistic regression to overcome the weakness. In the proposed method, 2D matrices are directly used to learn two groups of parameter vectors along each dimension without vectorization, which allows the proposed method to fully exploit the underlying structural information embedded inside the 2D matrices. Further, we add a joint [Formula: see text]-norm on two parameter matrices, which are organized by aligning each group of parameter vectors in columns. This added co-regularization term has two roles-enhancing the effect of regularization and optimizing the rank during the learning process. With our proposed fast iterative solution, we carried out extensive experiments. The results show that in comparison to both the traditional tensor-based methods and the vector-based regression methods, our proposed solution achieves better performance for matrix data classifications.

The importance of identifying and modifying unemployment predictor variables in the evolution of a novel model of care for low back pain in the general population.

PubMed

Harris, Simon A; Rampersaud, Y Raja

2016-01-01

Care for low back pain (LBP) is costly, fragmented and, in non-compensation populations, rarely specifically addresses factors associated with maintaining employment status or return to work (RTW). This study aimed to identify modifiable independent risk factors for (1) a negative work status at presentation and (2) a change in work status during treatment in a cohort of LBP patients. The results are intended to inform improvement in best-evidence care pathways to maximize societal outcomes and overall value of a new model of care. A prospective observational study was carried out. Work-eligible, non-workers compensation patients with recurrent or persistent LBP ≥6 weeks and ≤12 months. The Inter-professional Spine Assessment and Education Clinics (ISAEC)-a novel Government-funded shared-care model of management for LBP. This study used the following methods: (1) Cross-sectional analysis of baseline data from the initial ISAEC consultation (t0) from December 2012 to April 2014. Work status at t0 was dichotomized as employed (E) or underemployed (UE; unemployed, modified work duty, or disability). Multivariate logistic regression modeling was used to determine independent predictors of UE status at t0. (2) Bivariate analysis of longitudinal data from t0 to 6 months (t1) to identify risk factors for work status change. Employment journey categorized into four groups: Et0/Et1-employed at t0 and employed at t1; Et0/UEt1-employed at t0 and underemployed at t1; UEt0/Et1-underemployed at t0 and employed at t1; UEt0/UEt1-underemployed at t0 and underemployed at t1. This study yielded the following results: (1) Initial consultation data on 462 consecutive patients (Et0=344, UEt0=118). Multivariate logistic regression identified legal claim, depression, smoking, and higher STarT Back (or Oswestry Disability Index [ODI]) score as independent risk factors for UEt0. (2) Overall UE rate did not significantly change during longitudinal analysis (n=178, UEt0=25.5%, UEt1=22.9%). However, 10.5% of Et0 became UEt1 (Et0/Et1=102, Et0/UEt1=12). Bivariate analysis identified elevated baseline ODI score as the only significant predictor variable for UEt1 in Et0 cohort (p=.0101). Conversely, ISAEC improved the employment status in 41% of UEt0 to Et1 (UEt0/Et1=16, UEt0/UEt1=23), and the absence of depression was significant for predicting RTW (p=.0001). From a societal perspective, employment status as an outcome measure is paramount in assessing the value of a new model of care for LBP. Mitigation strategies for the predictor variables identified will be included in ISAEC pathways to translate clinical improvement into societal added value. Copyright © 2015 Elsevier Inc. All rights reserved.

Detecting DIF in Polytomous Items Using MACS, IRT and Ordinal Logistic Regression

ERIC Educational Resources Information Center

Elosua, Paula; Wells, Craig

2013-01-01

The purpose of the present study was to compare the Type I error rate and power of two model-based procedures, the mean and covariance structure model (MACS) and the item response theory (IRT), and an observed-score based procedure, ordinal logistic regression, for detecting differential item functioning (DIF) in polytomous items. A simulation…

Accuracy of Bayes and Logistic Regression Subscale Probabilities for Educational and Certification Tests

ERIC Educational Resources Information Center

Rudner, Lawrence

2016-01-01

In the machine learning literature, it is commonly accepted as fact that as calibration sample sizes increase, Naïve Bayes classifiers initially outperform Logistic Regression classifiers in terms of classification accuracy. Applied to subtests from an on-line final examination and from a highly regarded certification examination, this study shows…

Comparing Linear Discriminant Function with Logistic Regression for the Two-Group Classification Problem.

ERIC Educational Resources Information Center

Fan, Xitao; Wang, Lin

The Monte Carlo study compared the performance of predictive discriminant analysis (PDA) and that of logistic regression (LR) for the two-group classification problem. Prior probabilities were used for classification, but the cost of misclassification was assumed to be equal. The study used a fully crossed three-factor experimental design (with…

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

ERIC Educational Resources Information Center

Nguyen, Phuong L.

2006-01-01

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

School Exits in the Milwaukee Parental Choice Program: Evidence of a Marketplace?

ERIC Educational Resources Information Center

Ford, Michael

2011-01-01

This article examines whether the large number of school exits from the Milwaukee school voucher program is evidence of a marketplace. Two logistic regression and multinomial logistic regression models tested the relation between the inability to draw large numbers of voucher students and the ability for a private school to remain viable. Data on…

Hierarchical Bayesian Logistic Regression to forecast metabolic control in type 2 DM patients.

PubMed

Dagliati, Arianna; Malovini, Alberto; Decata, Pasquale; Cogni, Giulia; Teliti, Marsida; Sacchi, Lucia; Cerra, Carlo; Chiovato, Luca; Bellazzi, Riccardo

2016-01-01

In this work we present our efforts in building a model able to forecast patients' changes in clinical conditions when repeated measurements are available. In this case the available risk calculators are typically not applicable. We propose a Hierarchical Bayesian Logistic Regression model, which allows taking into account individual and population variability in model parameters estimate. The model is used to predict metabolic control and its variation in type 2 diabetes mellitus. In particular we have analyzed a population of more than 1000 Italian type 2 diabetic patients, collected within the European project Mosaic. The results obtained in terms of Matthews Correlation Coefficient are significantly better than the ones gathered with standard logistic regression model, based on data pooling.

An empirical study of statistical properties of variance partition coefficients for multi-level logistic regression models

USGS Publications Warehouse

Li, Ji; Gray, B.R.; Bates, D.M.

2008-01-01

Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.

Model building strategy for logistic regression: purposeful selection.

PubMed

Zhang, Zhongheng

2016-03-01

Logistic regression is one of the most commonly used models to account for confounders in medical literature. The article introduces how to perform purposeful selection model building strategy with R. I stress on the use of likelihood ratio test to see whether deleting a variable will have significant impact on model fit. A deleted variable should also be checked for whether it is an important adjustment of remaining covariates. Interaction should be checked to disentangle complex relationship between covariates and their synergistic effect on response variable. Model should be checked for the goodness-of-fit (GOF). In other words, how the fitted model reflects the real data. Hosmer-Lemeshow GOF test is the most widely used for logistic regression model.

Research on simulation based material delivery system for an automobile company with multi logistics center

NASA Astrophysics Data System (ADS)

Luo, D.; Guan, Z.; Wang, C.; Yue, L.; Peng, L.

2017-06-01

Distribution of different parts to the assembly lines is significant for companies to improve production. Current research investigates the problem of distribution method optimization of a logistics system in a third party logistic company that provide professional services to an automobile manufacturing case company in China. Current research investigates the logistics leveling the material distribution and unloading platform of the automobile logistics enterprise and proposed logistics distribution strategy, material classification method, as well as logistics scheduling. Moreover, the simulation technology Simio is employed on assembly line logistics system which helps to find and validate an optimization distribution scheme through simulation experiments. Experimental results indicate that the proposed scheme can solve the logistic balance and levels the material problem and congestion of the unloading pattern in an efficient way as compared to the original method employed by the case company.

LOTS of LTA applications

NASA Technical Reports Server (NTRS)

Brown, J. S.

1975-01-01

Current problems facing the logistical planner in utilizing the new ships of the modern, intermodal sea transportation systems in a logistics-over-the-shore (undeveloped) environment are described. Then the employment of two potential LTA vehicle systems are described and discussed as significant parts of possible solutions to this range of logistical problems. Vulnerability aspects of these LTA vehicles are also briefly addressed because of their possible employment near combat areas.

An Evaluation of One- and Three-Parameter Logistic Tailored Testing Procedures for Use with Small Item Pools.

ERIC Educational Resources Information Center

McKinley, Robert L.; Reckase, Mark D.

A two-stage study was conducted to compare the ability estimates yielded by tailored testing procedures based on the one-parameter logistic (1PL) and three-parameter logistic (3PL) models. The first stage of the study employed real data, while the second stage employed simulated data. In the first stage, response data for 3,000 examinees were…

Maternal depressive symptoms, employment, and social support.

PubMed

Gjerdingen, Dwenda; McGovern, Patricia; Attanasio, Laura; Johnson, Pamela Jo; Kozhimannil, Katy Backes

2014-01-01

The purpose of this study was to characterize the relationship between maternal depressive symptoms and employment and whether it is mediated by social support. We used data from a nationally representative sample of 700 US women who gave birth in 2005 and completed 2 surveys in the Listening to Mothers series, the first in early 2006, an average of 7.3 months postpartum, and the second an average of 13.4 months postpartum. A dichotomous measure of depressive symptoms was calculated from the 2-item Patient Health Questionnaire, and women reported their employment status and levels of social support from partners and others. We modeled the association between maternal employment and depressive symptoms using multivariate logistic regression, including social support and other control variables. Maternal employment and high support from a nonpartner source were both independently associated with significantly lower odds of depressive symptoms (adjusted odds ratio [AOR], 0.35 and P = .011, and AOR, 0.40, P = .011, respectively). These relationships remained significant after controlling for mothers' baseline mental and physical health, babies' health, and demographic characteristics (AOR, 0.326 and P = .015, and AOR, 0.267 and P = .025, respectively). Maternal employment and strong social support, particularly nonpartner support, were independently associated with fewer depressive symptoms. Clinicians should encourage mothers of young children who are at risk for depression to consider ways to optimize their employment circumstances and "other" social support.

Comparing exposure assessment methods for traffic-related air pollution in an adverse pregnancy outcome study.

PubMed

Wu, Jun; Wilhelm, Michelle; Chung, Judith; Ritz, Beate

2011-07-01

Previous studies reported adverse impacts of traffic-related air pollution exposure on pregnancy outcomes. Yet, little information exists on how effect estimates are impacted by the different exposure assessment methods employed in these studies. To compare effect estimates for traffic-related air pollution exposure and preeclampsia, preterm birth (gestational age less than 37 weeks), and very preterm birth (gestational age less than 30 weeks) based on four commonly used exposure assessment methods. We identified 81,186 singleton births during 1997-2006 at four hospitals in Los Angeles and Orange Counties, California. Exposures were assigned to individual subjects based on residential address at delivery using the nearest ambient monitoring station data [carbon monoxide (CO), nitrogen dioxide (NO(2)), nitric oxide (NO), nitrogen oxides (NO(x)), ozone (O(3)), and particulate matter less than 2.5 (PM(2.5)) or less than 10 (PM(10))μm in aerodynamic diameter], both unadjusted and temporally adjusted land-use regression (LUR) model estimates (NO, NO(2), and NO(x)), CALINE4 line-source air dispersion model estimates (NO(x) and PM(2.5)), and a simple traffic-density measure. We employed unconditional logistic regression to analyze preeclampsia in our birth cohort, while for gestational age-matched risk sets with preterm and very preterm birth we employed conditional logistic regression. We observed elevated risks for preeclampsia, preterm birth, and very preterm birth from maternal exposures to traffic air pollutants measured at ambient stations (CO, NO, NO(2), and NO(x)) and modeled through CALINE4 (NO(x) and PM(2.5)) and LUR (NO(2) and NO(x)). Increased risk of preterm birth and very preterm birth were also positively associated with PM(10) and PM(2.5) air pollution measured at ambient stations. For LUR-modeled NO(2) and NO(x) exposures, elevated risks for all the outcomes were observed in Los Angeles only--the region for which the LUR models were initially developed. Unadjusted LUR models often produced odds ratios somewhat larger in size than temporally adjusted models. The size of effect estimates was smaller for exposures based on simpler traffic density measures than the other exposure assessment methods. We generally confirmed that traffic-related air pollution was associated with adverse reproductive outcomes regardless of the exposure assessment method employed, yet the size of the estimated effect depended on how both temporal and spatial variations were incorporated into exposure assessment. The LUR model was not transferable even between two contiguous areas within the same large metropolitan area in Southern California. Copyright © 2011 Elsevier Inc. All rights reserved.

Assessing landslide susceptibility by statistical data analysis and GIS: the case of Daunia (Apulian Apennines, Italy)

NASA Astrophysics Data System (ADS)

Ceppi, C.; Mancini, F.; Ritrovato, G.

2009-04-01

This study aim at the landslide susceptibility mapping within an area of the Daunia (Apulian Apennines, Italy) by a multivariate statistical method and data manipulation in a Geographical Information System (GIS) environment. Among the variety of existing statistical data analysis techniques, the logistic regression was chosen to produce a susceptibility map all over an area where small settlements are historically threatened by landslide phenomena. By logistic regression a best fitting between the presence or absence of landslide (dependent variable) and the set of independent variables is performed on the basis of a maximum likelihood criterion, bringing to the estimation of regression coefficients. The reliability of such analysis is therefore due to the ability to quantify the proneness to landslide occurrences by the probability level produced by the analysis. The inventory of dependent and independent variables were managed in a GIS, where geometric properties and attributes have been translated into raster cells in order to proceed with the logistic regression by means of SPSS (Statistical Package for the Social Sciences) package. A landslide inventory was used to produce the bivariate dependent variable whereas the independent set of variable concerned with slope, aspect, elevation, curvature, drained area, lithology and land use after their reductions to dummy variables. The effect of independent parameters on landslide occurrence was assessed by the corresponding coefficient in the logistic regression function, highlighting a major role played by the land use variable in determining occurrence and distribution of phenomena. Once the outcomes of the logistic regression are determined, data are re-introduced in the GIS to produce a map reporting the proneness to landslide as predicted level of probability. As validation of results and regression model a cell-by-cell comparison between the susceptibility map and the initial inventory of landslide events was performed and an agreement at 75% level achieved.

Prevalence, sociodemographic factors, psychological distress, and coping strategies related to compulsive buying: a cross sectional study in Galicia, Spain.

PubMed

Otero-López, José Manuel; Villardefrancos, Estíbaliz

2014-04-05

Compulsive buying has become a serious problem affecting a growing number of people in contemporary consumer societies. Nevertheless, research examining its prevalence in representative samples from the general population is still scarce and mainly focused on the exploration of sociodemographic factors, neglecting other aspects like psychological distress and coping styles. Therefore, this study intends to contribute to the cumulative knowledge by assessing compulsive buying prevalence in a representative sample from the general population in the region of Galicia, in Spain. Sociodemographic determinants, psychological symptoms, and coping strategies are also analyzed to clarify their role in this phenomenon. A random routes procedure was employed in the recruitment of the sample which was comprised of 2159 participants who were classified as either compulsive buyers or non-compulsive buyers. Both groups were compared regarding sociodemographic determinants, symptoms, and coping strategies through chi-square tests or analyses of variance. A multivariate logistic regression analysis was conducted to determine which of these determinants might play a part in the make up of a risk profile for compulsive buying. Estimated prevalence of compulsive buying was 7.1%. Compulsive buyers and non-compulsive buyers differed significantly in sex and age, with women and younger people showing a higher propensity for this phenomenon. Individuals with compulsive buying presented significantly higher scores on all the psychological symptoms considered. They also employed passive-avoidance coping strategies much more frequently and active strategies of problem solving and cognitive restructuring much less frequently. The logistic regression analysis results confirmed that being female, experiencing symptoms of anxiety, depression, and obsession-compulsion, and employing the passive-avoidance coping strategies of problem avoidance, wishful thinking, and self-criticism, all constituted risk factors for compulsive buying, whilst the increased age and the use of the active coping strategies of problem solving and cognitive restructuring were protection factors. Our findings revealed a substantial prevalence of compulsive buying. Additionally, the relevance of sociodemographic determinants, psychological distress, and coping strategies in this problem was confirmed. The establishment of a risk profile for compulsive buying based on these different sets of determinants would likely contribute to the development of more effective intervention programs.

Impact of Coal Mining on Self-Rated Health among Appalachian Residents

PubMed Central

Woolley, Shannon M.; Bear, Todd M.; Balmert, Lauren C.; Talbott, Evelyn O.; Buchanich, Jeanine M.

2015-01-01

Objective. To determine the impact of coal mining, measured as the number of coal mining-related facilities nearby one's residence or employment in an occupation directly related to coal mining, on self-rated health in Appalachia. Methods. Unadjusted and adjusted ordinal logistic regression models calculated odds ratio estimates and associated 95% confidence intervals for the probability of having an excellent self-rated health response versus another response. Covariates considered in the analyses included number of coal mining-related facilities nearby one's residence and employment in an occupation directly related to coal mining, as well as potential confounders age, sex, BMI, smoking status, income, and education. Results. The number of coal mining facilities near the respondent's residence was not a statistically significant predictor of self-rated health. Employment in a coal-related occupation was a statistically significant predictor of self-rated health univariably; however, after adjusting for potential confounders, it was no longer a significant predictor. Conclusions. Self-rated health does not seem to be associated with residential proximity to coal mining facilities or employment in the coal industry. Future research should consider additional measures for the impact of coal mining. PMID:26240577

Do Italian surgeons use antibiotic prophylaxis in thyroid surgery? Results from a national study (UEC--Italian Endocrine Surgery Units Association).

PubMed

Gentile, Ivan; Rosato, Lodovico; Avenia, Nicola; Testini, Mario; D'Ajello, Michele; Antonino, Antonio; De Palma, Maurizio

2014-01-01

Thyroid surgery is a clean procedure and therefore antibiotic prophylaxis is not routinely recommended by most international guidelines. However, antibiotics are often used in clinical practice. We enrolled 2926 patients who performed a thyroid surgical operation between the years 2009 and 2011 in the 38 centers of endocrine surgery that joined the UEC--Italian Endocrine Surgery Units Association. Antibiotic prophylaxis was used in 1132 interventions (38.7%). In case of antibiotic prophylaxis, cephalosporins or aminopenicillins ± beta lactamase inhibitors were employed. At logistic regression analysis the use of drainage or device and the presence of malignancy were independent predictors of antibiotic prophylaxis employment. In conclusion our study shows that antibiotic prophylaxis was not rarely used in clinical practice in the setting of thyroid surgery. Drainage apposition, use of device, and malignant disease were independent predictors for antibiotic prophylaxis employment. More data on everyday practice and infection rate in well-designed studies are warranted to provide definitive recommendations on the utility of antibiotic prophylaxis in this setting. According to our experience, we don't consider to be strictly necessary the antibiotic prophylaxis employment in order to reduce infection rate in thyroid surgery.

Utilization of assistive technology by persons with physical disabilities: an examination of predictive factors by race.

PubMed

Loggins, Shondra; Alston, Reginald; Lewis, Allen

2014-11-01

Examine the relationship between race, use of assistive technology (AT), gender, educational attainment, income, employment status and access to health care. Data were analyzed from the national Behavioral Risk Factor Surveillance System (BRFSS) collected in USA in 2007. Descriptive statistics and logistic regression were performed. Among those who used AT, more European Americans (EAs) were educated, employed, made >$25,000 per year and had better access to health coverage. In contrast, more African Americans (AAs) who used AT were less educated, unemployed, made <$25,000 per year and had worse health coverage. Overall, AAs used AT more than EAs. The trend was consistent with predictive factors. AAs were 29% more likely to use AT compared to EAs. For EAs and AAs, predictors for use of AT were age, gender, education, employment status, income, health coverage and medical costs. Racial differences between AAs and EAs were observed in the use of AT by persons with physical disabilities based on age, gender, education, employment status, income levels, health care coverage and medical costs. Even though EAs and AAs had the same predictors, there were racial differences in the magnitude of the predictors.

Risk selection into consumer-directed health plans: an analysis of family choices within large employers.

PubMed

McDevitt, Roland D; Haviland, Amelia M; Lore, Ryan; Laudenberger, Laura; Eisenberg, Matthew; Sood, Neeraj

2014-04-01

To identify the degree of selection into consumer-directed health plans (CDHPs) versus traditional plans over time, and factors that influence choice and temper risk selection. Sixteen large employers offering both CDHP and traditional plans during the 2004–2007 period, more than 200,000 families. We model CDHP choice with logistic regression; predictors include risk scores, in addition to family, choice setting, and plan characteristics. Additional models stratify by account type or single enrollee versus family. Risk scores, family characteristics, and enrollment decisions are derived from medical claims and enrollment files. Interviews with human resources executives provide additional data. CDHP risk scores were 74 percent of traditional plan scores in the first year, and this difference declined over time. Employer contributions to accounts and employee premium savings fostered CDHP enrollment and reduced risk selection. Having to make an active choice of plan increased CDHP enrollment but also increased risk selection. Risk selection was greater for singles than families and did not differ between HRA and HSA-based CDHPs. Risk selection was not severe and it was well managed. Employers have effective methods to encourage CDHP enrollment and temper selection against traditional plans.

Determination of riverbank erosion probability using Locally Weighted Logistic Regression

NASA Astrophysics Data System (ADS)

Ioannidou, Elena; Flori, Aikaterini; Varouchakis, Emmanouil A.; Giannakis, Georgios; Vozinaki, Anthi Eirini K.; Karatzas, George P.; Nikolaidis, Nikolaos

2015-04-01

Riverbank erosion is a natural geomorphologic process that affects the fluvial environment. The most important issue concerning riverbank erosion is the identification of the vulnerable locations. An alternative to the usual hydrodynamic models to predict vulnerable locations is to quantify the probability of erosion occurrence. This can be achieved by identifying the underlying relations between riverbank erosion and the geomorphological or hydrological variables that prevent or stimulate erosion. Thus, riverbank erosion can be determined by a regression model using independent variables that are considered to affect the erosion process. The impact of such variables may vary spatially, therefore, a non-stationary regression model is preferred instead of a stationary equivalent. Locally Weighted Regression (LWR) is proposed as a suitable choice. This method can be extended to predict the binary presence or absence of erosion based on a series of independent local variables by using the logistic regression model. It is referred to as Locally Weighted Logistic Regression (LWLR). Logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable (e.g. binary response) based on one or more predictor variables. The method can be combined with LWR to assign weights to local independent variables of the dependent one. LWR allows model parameters to vary over space in order to reflect spatial heterogeneity. The probabilities of the possible outcomes are modelled as a function of the independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. erosion presence or absence) for any value of the independent variables. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested. The most straightforward measure for goodness of fit is the G statistic. It is a simple and effective way to study and evaluate the Logistic Regression model efficiency and the reliability of each independent variable. The developed statistical model is applied to the Koiliaris River Basin on the island of Crete, Greece. Two datasets of river bank slope, river cross-section width and indications of erosion were available for the analysis (12 and 8 locations). Two different types of spatial dependence functions, exponential and tricubic, were examined to determine the local spatial dependence of the independent variables at the measurement locations. The results show a significant improvement when the tricubic function is applied as the erosion probability is accurately predicted at all eight validation locations. Results for the model deviance show that cross-section width is more important than bank slope in the estimation of erosion probability along the Koiliaris riverbanks. The proposed statistical model is a useful tool that quantifies the erosion probability along the riverbanks and can be used to assist managing erosion and flooding events. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

Do changes in spousal employment status lead to domestic violence? Insights from a prospective study in Bangalore, India.

PubMed

Krishnan, Suneeta; Rocca, Corinne H; Hubbard, Alan E; Subbiah, Kalyani; Edmeades, Jeffrey; Padian, Nancy S

2010-01-01

The prevalence of physical domestic violence--violence against women perpetrated by husbands--is staggeringly high across the Indian subcontinent. Although gender-based power dynamics are thought to underlie women's vulnerability, relatively little is known about risk and protective factors. This prospective study in southern India examined the association between key economic aspects of gender-based power, namely spousal employment status, and physical domestic violence. In 2005-2006, 744 married women, aged 16-25, residing in low-income communities in Bangalore, India were enrolled in the study. Data were collected at enrollment, 12 and 24 months. Multivariable logistic regression models were used to examine the prospective association between women's employment status, their perceptions of their husband's employment stability, and domestic violence. Women who were unemployed at one visit and began employment by the next visit had an 80% higher odds of violence, as compared to women who maintained their unemployed status. Similarly, women whose husbands had stable employment at one visit and newly had difficulty with employment had 1.7 times the odds of violence, as compared to women whose husbands maintained their stable employment. To our knowledge, this study is the first from a developing country to confirm that changes in spousal employment status are associated with subsequent changes in violence risk. It points to the complex challenges of violence prevention, including the need for interventions among men and gender-transformative approaches to promote gender-equitable attitudes, practices and norms among men and women.

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.

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

Modifiable risk factors predicting major depressive disorder at four year follow-up: a decision tree approach.

PubMed

Batterham, Philip J; Christensen, Helen; Mackinnon, Andrew J

2009-11-22

Relative to physical health conditions such as cardiovascular disease, little is known about risk factors that predict the prevalence of depression. The present study investigates the expected effects of a reduction of these risks over time, using the decision tree method favoured in assessing cardiovascular disease risk. The PATH through Life cohort was used for the study, comprising 2,105 20-24 year olds, 2,323 40-44 year olds and 2,177 60-64 year olds sampled from the community in the Canberra region, Australia. A decision tree methodology was used to predict the presence of major depressive disorder after four years of follow-up. The decision tree was compared with a logistic regression analysis using ROC curves. The decision tree was found to distinguish and delineate a wide range of risk profiles. Previous depressive symptoms were most highly predictive of depression after four years, however, modifiable risk factors such as substance use and employment status played significant roles in assessing the risk of depression. The decision tree was found to have better sensitivity and specificity than a logistic regression using identical predictors. The decision tree method was useful in assessing the risk of major depressive disorder over four years. Application of the model to the development of a predictive tool for tailored interventions is discussed.

Effect of expressions of tumor necrosis factor α and interleukin 1B on peritoneal metastasis of gastric cancer.

PubMed

Guo, Lin; Ou, Jin-Lei; Zhang, Tong; Ma, Liang; Qu, Long-Fei

2015-11-01

Our study aimed to investigate effect of expressions of tumor necrosis factor α (TNF-α) and interleukin 1B (IL-1B) on peritoneal metastasis of gastric cancer (GC). From June 2012 to June 2014, a total of 60 patients with advanced peritoneal metastasis from GC were collected from Department of Gastrointestinal and Nutriology Surgery at Shengjing Hospital of China Medical University. Furthermore, 60 GC patients without peritoneal metastasis were enrolled as controls. Immunohistochemistry was performed to test TNF-α and IL-1B expression, and logistic regression analysis was employed for evaluating risk factors for peritoneal metastasis of GC. Our results showed that TNF-α expression in metastatic group and non-metastatic group was significantly different (P = 0.043), but no significant difference was found in IL-1B expression between two groups (P = 0.261). In addition, TNF-α expression in metastatic group and non-metastatic group was associated with tumor size, depth of invasion, the degree of differentiation (all P < 0.05). Logistic regression analysis indicated that tumor size, depth of invasion, the degree of differentiation and TNF-α expression were risk factors for peritoneal metastasis of GC (all P < 0.05). Our study found that TNF-α expression may play a vital role in peritoneal metastasis of GC, while IL-1B expression might not be correlated with peritoneal metastasis.

Socio-economic Correlates of Malnutrition among Married Women in Bangladesh.

PubMed

Mostafa Kamal, S M; Md Aynul, Islam

2010-12-01

This paper examines the prevalence and socio-economic correlates of malnutrition among ever married non-pregnant women of reproductive age of Bangladesh using a nationally representative weighted sample of 10,145. Body mass index was used to measure nutritional status. Both bivariate and multivariate statistical analyses were employed to assess the relationship between socio-economic characteristics and women's nutritional status. Overall, 28.5% of the women were found to be underweight. The fixed effect multivariate binary logistic regression analysis yielded significantly increased risk of underweight for the young, currently working, non-Muslim, rural residents, widowed, divorced or separated women. Significant wide variations of malnourishment prevailed in the administrative regions of the country. Wealth index and women's education were the most important determinants of underweight. The multivariate logistic regression analysis revealed that the risk of being underweight was almost seven times higher (OR=6.76, 95% CI=5.20-8.80) among women with no formal education as compared to those with higher education and the likelihood of underweight was significantly (p<0.001) 5.2 times (OR=5.23, 95% CI=4.51-6.07) in the poorest as compared to their richest counterparts. Poverty alleviation programmes should be strengthened targeting the poor. Effective policies, information and health education programmes for women are required to ensure adequate access to health services and for them to understand the components of a healthy diet.

National health insurance subscription and maternal healthcare utilisation across mothers' wealth status in Ghana.

PubMed

Ameyaw, Edward Kwabena; Kofinti, Raymond Elikplim; Appiah, Francis

2017-12-01

This study is against the backdrop that despite the forty-nine percent decline in Maternal Mortality Rate in Ghana, the situation still remains high averaging 319 per 100,000 live births between 2011 and 2015. To examine the relationship between National Health Insurance and maternal healthcare utilisation across three main wealth quintiles (Poor, Middle and Rich). The study employed data from the 2014 Ghana Demographic and Health Survey. Both descriptive analysis and binary logistic regression were conducted. Descriptively, rich women had high antenatal attendance and health facility deliveries represented by 96.5% and 95.6% respectively. However, the binary logistic regression results revealed that poor women owning NHIS are 7% (CI = 1.76-2.87) more likely to make at least four antenatal care visits compared to women in the middle wealth quintile (5%, CI = 2.12-4.76) and rich women (2%, CI = 1.14-4.14). Similarly, poor women who owned the NHIS are 14% (CI = 1.42-2.13) likely to deliver in health facility than women in the middle and rich wealth quintile. The study has vindicated the claim that NHIS Scheme is pro-poor in Ghana. The Ministry of Health should target women in the rural area to be enrolled on the NHIS to improve maternal healthcare utilisation since poverty is principally a rural phenomenon in Ghana.

Predictors of certification in infection prevention and control among infection preventionists: APIC MegaSurvey findings.

PubMed

Kalp, Ericka L; Harris, Jeanette J; Zawistowski, Grace

2018-06-06

The 2015 APIC MegaSurvey was completed by 4,078 members to assess infection prevention practices. This study's purpose was to examine MegaSurvey results to relate infection preventionist (IP) certification status with demographic characteristics, organizational structure, compensation benefits, and practice and competency factors. Descriptive statistics were used to examine population characteristics and certification status. Bivariate logistic regression was performed to evaluate relationships between independent variables and certification status. Variables demonstrating statistical significance (P <.05) were included in multivariable logistic regression analyses. Forty-seven percent of survey respondents had their CIC. IPs were less likely certified if their educational attainment was less than a bachelor's degree, they were aged 18-45 years, they worked in rural facilities, they had <16 years' experience in health care before becoming an IP, and the percentage of job dedicated to infection prevention was <75%. However, certification was associated with CIC benefit paid fully by employer, self-rating as proficient and expert-advanced, and surveillance and epidemiologic investigation competency obtained via professional development and training. CIC attainment was associated with IP characteristics. Additional research should focus on identifying strategies to increase certification among noncertified IPs because CIC is a measure of proficiency that should be a goal for all IPs. Copyright © 2018 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Prevalence and occupational predictors of psychological distress in the offshore petroleum industry: a prospective study.

PubMed

Nielsen, Morten Birkeland; Tvedt, Sturle Danielsen; Matthiesen, Stig Berge

2013-11-01

This study investigates the prevalence of psychological distress and stressors in the work environment as prospective predictors of distress, among employees in the offshore petroleum industry. Correlation and logistic regression analyses were employed to examine longitudinal relationships between stressors and distress in a randomly drawn sample of 741 employees from the Norwegian petroleum offshore industry. Time lag between baseline and follow-up was 6 months. Work environment stressors included safety factors, leadership, and job characteristics. The prevalence of psychological distress was 9 % at baseline and 8 % at follow-up. All investigated work environment factors correlated with subsequent distress. In bivariate logistic regression analyses, caseness of distress was predicted by baseline distress, near miss accidents, risk perception, poor safety climate, tyrannical leadership, laissez-faire leadership, job demands, and workplace bullying. After adjustment for baseline distress, control variables, and other predictors, laissez-faire leadership (OR = 1.69; 95 % CI: 1.12-2.54) and exposure to bullying (OR = 1.49; 95 % CI: 1.07-2.10) emerged as the most robust predictors of subsequent distress. The findings show that the prevalence of psychological distress is lower among offshore employees than in the general population. Although offshore workers operate in a physically challenging context, their mental health is mainly influenced by stressors in the psychosocial work environment. This highlights the importance of developing and implementing psychosocial safety interventions within the offshore industry.

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.

Patterns and correlates of illicit drug selling among youth in the USA

PubMed Central

Vaughn, Michael G; Shook, Jeffrey J; Perron, Brian E; Abdon, Arnelyn; Ahmedani, Brian

2011-01-01

Purpose Despite the high rates of drug selling among youth in juvenile justice and youth residing in disadvantage neighborhoods, relatively little is known about the patterns of illicit drug selling among youth in the general population. Methods Using the public-use data file from the adolescent sample (N = 17 842) in the 2008 National Survey on Drug Use and Health (NSDUH), this study employed multiple logistic regression to compare the behavioral, parental involvement, and prevention experiences of youth who sold and did not sell illicit drugs in the past year. Results Findings from a series of logistic regression models indicated youth who sold drugs were far more likely to use a wide variety of drugs and engage in delinquent acts. Drug-selling youth were significantly less likely to report having a parent involved in their life and have someone to talk to about serious problems but were more likely to report exposure to drug prevention programming. Conclusion Selling of drugs by youth appears to be a byproduct of substance abuse and deviance proneness, and the prevention programs these youth experience are likely a result of mandated exposure derived from contact with the criminal justice system. Assuming no major drug supply side reductions, policies, and practices associated with increasing drug abuse treatment, parental involvement and supervision, and school engagement are suggested. PMID:22375100

Determinants of physician utilization, emergency room use, and hospitalizations among populations with multiple health vulnerabilities.

PubMed

Small, La Fleur F

2011-09-01

Understanding the factors that influence differing types of health care utilization within vulnerable groups can serve as a basis for projecting future health care needs, forecasting future health care expenditures, and influencing social policy. In this article the Behavioral Model for Vulnerable Populations is used to evaluate discretionary (physician visits) and non-discretionary (emergency room visits, and hospitalizations) health utilization patterns of a sample of 1466 respondents with one or more vulnerable health classification. Reported vulnerabilities include: (1) persons with substance disorders; (2) homeless persons; (3) persons with mental health problems; (4) victims of violent crime; (5) persons diagnosed with HIV/AIDS; (6) and persons in receipt of public benefits. Hierarchical logistic regression is used on three nested models to model factors that influence physician visits, emergency room visits, and hospitalizations. Additionally, bivariate logistic regression analyses are completed using a vulnerability index to evaluate the impact of increased numbers of vulnerability on all three forms of health care utilization. Findings from this study suggest the Behavioral Model of Vulnerable Populations be employed in future research regarding health care utilization patterns among vulnerable populations. This article encourages further research investigating the cumulative effect of health vulnerabilities on the use of non-discretionary services so that this behavior could be better understood and appropriate social policies and behavioral interventions implemented.

Negative mood states and related factors in a sample of adolescent secondary-school students in Barcelona (Spain).

PubMed

Ahonen, Emily Q; Nebot, Manel; Giménez, Emmanuel

2007-01-01

Poor mental health is a common problem in adolescence. Little information is available, however, about the factors influencing negative mood states in otherwise healthy adolescents. We aimed to describe the mood states and related factors in a sample of adolescents in the city of Barcelona (Spain). We administered a health survey to a sample of 2,727 students from public, subsidized, and private schools in Barcelona, aged approximately 14, 16, and 18 years old. To analyze the associations among moods and related factors, we used bivariate logistic regression, and fitted multivariate logistic regressions using the statistically significant variables from the bivariate analysis. To examine the possible group effects of the school on individual students, we employed multilevel analysis. The frequencies of negative mood states increased with age, with girls consistently reporting more frequent negative mood states than boys. The factors associated with negative mood states were problematic alcohol use, perceived mistreatment or abuse, antisocial behavior, intention to use or current use of illegal drugs (not including cannabis), lower perceived academic performance, and feeling isolated. Mood states are influenced by lifestyle and social factors, about which there is little local information. To plan and implement appropriate public health interventions, more complete information about the possible areas of influence is required. To complement the information obtained from studies such as the present study, longitudinal and qualitative studies would be desirable.

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.

Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat—Turkey)

NASA Astrophysics Data System (ADS)

Yilmaz, Işık

2009-06-01

The purpose of this study is to compare the landslide susceptibility mapping methods of frequency ratio (FR), logistic regression and artificial neural networks (ANN) applied in the Kat County (Tokat—Turkey). Digital elevation model (DEM) was first constructed using GIS software. Landslide-related factors such as geology, faults, drainage system, topographical elevation, slope angle, slope aspect, topographic wetness index (TWI) and stream power index (SPI) were used in the landslide susceptibility analyses. Landslide susceptibility maps were produced from the frequency ratio, logistic regression and neural networks models, and they were then compared by means of their validations. The higher accuracies of the susceptibility maps for all three models were obtained from the comparison of the landslide susceptibility maps with the known landslide locations. However, respective area under curve (AUC) values of 0.826, 0.842 and 0.852 for frequency ratio, logistic regression and artificial neural networks showed that the map obtained from ANN model is more accurate than the other models, accuracies of all models can be evaluated relatively similar. The results obtained in this study also showed that the frequency ratio model can be used as a simple tool in assessment of landslide susceptibility when a sufficient number of data were obtained. Input process, calculations and output process are very simple and can be readily understood in the frequency ratio model, however logistic regression and neural networks require the conversion of data to ASCII or other formats. Moreover, it is also very hard to process the large amount of data in the statistical package.

Early retirement and non-employment after breast cancer.

PubMed

Lindbohm, M-L; Kuosma, E; Taskila, T; Hietanen, P; Carlsen, K; Gudbergsson, S; Gunnarsdottir, H

2014-06-01

This study examined whether workplace support, sociodemographic factors and co-morbidity are associated with early retirement or non-employment due to other reasons among breast cancer survivors. We also compared quality of life and chronic symptoms (pain, fatigue, anxiety and depression) among employed, retired and other non-employed breast cancer survivors. We identified breast cancer survivors diagnosed between 1997 and 2002 from either a hospital or a cancer registry in Denmark, Finland, Iceland and Norway (NOCWO study). All patients had been treated with curative intent. Information on employment, co-morbidity and support was collected via a questionnaire. The sample included 1111 working-aged cancer-free survivors who had been employed at the time of diagnosis. We used multinomial logistic regression models to analyse the association of various determinants with early retirement and other non-employment (due to unemployment, subsidized employment or being a homemaker). Low education, low physical quality of life, co-morbidity and pain were associated with both early retirement and other non-employment after cancer. Other non-employed survivors also rated their mental quality of life as lower and experienced anxiety and fatigue more often than all the other survivors. Moreover, they reported a lower level of supervisor support after their diagnosis than the employed survivors. Retired survivors more often reported weak support from colleagues. Differences in ill health and functional status between various groups of non-employed cancer survivors need to be considered when planning policy measures for improving the labour market participation of this population and preventing their early withdrawal from working life. Copyright © 2013 John Wiley & Sons, Ltd.

The impact of ill health on exit from paid employment in Europe among older workers.

PubMed

van den Berg, Tilja; Schuring, Merel; Avendano, Mauricio; Mackenbach, Johan; Burdorf, Alex

2010-12-01

To determine the impact of ill health on exit from paid employment in Europe among older workers. Participants of the Survey on Health and Ageing in Europe (SHARE) in 11 European countries in 2004 and 2006 were selected when 50-63 years old and in paid employment at baseline (n=4611). Data were collected on self-rated health, chronic diseases, mobility limitations, obesity, smoking, alcohol use, physical activity and work characteristics. Participants were classified into employed, retired, unemployed and disabled at the end of the 2-year follow-up. Multinomial logistic regression was used to estimate the effect of different measures of ill health on exit from paid employment. During the 2-year follow-up, 17% of employed workers left paid employment, mainly because of early retirement. Controlling for individual and work related characteristics, poor self-perceived health was strongly associated with exit from paid employment due to retirement, unemployment or disability (ORs from 1.32 to 4.24). Adjustment for working conditions and lifestyle reduced the significant associations between ill health and exit from paid employment by 0-18.7%. Low education, obesity, low job control and effort-reward imbalance were associated with measures of ill health, but also risk factors for exit from paid employment after adjustment for ill health. Poor self-perceived health was strongly associated with exit from paid employment among European workers aged 50-63 years. This study suggests that the influence of ill health on exit from paid employment could be lessened by measures targeting obesity, problematic alcohol use, job control and effort-reward balance.

A Comparison of Logistic Regression, Neural Networks, and Classification Trees Predicting Success of Actuarial Students

ERIC Educational Resources Information Center

Schumacher, Phyllis; Olinsky, Alan; Quinn, John; Smith, Richard

2010-01-01

The authors extended previous research by 2 of the authors who conducted a study designed to predict the successful completion of students enrolled in an actuarial program. They used logistic regression to determine the probability of an actuarial student graduating in the major or dropping out. They compared the results of this study with those…

Logistic regression accuracy across different spatial and temporal scales for a wide-ranging species, the marbled murrelet

Treesearch

Carolyn B. Meyer; Sherri L. Miller; C. John Ralph

2004-01-01

The scale at which habitat variables are measured affects the accuracy of resource selection functions in predicting animal use of sites. We used logistic regression models for a wide-ranging species, the marbled murrelet, (Brachyramphus marmoratus) in a large region in California to address how much changing the spatial or temporal scale of...

A Generalized Logistic Regression Procedure to Detect Differential Item Functioning among Multiple Groups

ERIC Educational Resources Information Center

Magis, David; Raiche, Gilles; Beland, Sebastien; Gerard, Paul

2011-01-01

We present an extension of the logistic regression procedure to identify dichotomous differential item functioning (DIF) in the presence of more than two groups of respondents. Starting from the usual framework of a single focal group, we propose a general approach to estimate the item response functions in each group and to test for the presence…

Risk Factors of Falls in Community-Dwelling Older Adults: Logistic Regression Tree Analysis

ERIC Educational Resources Information Center

Yamashita, Takashi; Noe, Douglas A.; Bailer, A. John

2012-01-01

Purpose of the Study: A novel logistic regression tree-based method was applied to identify fall risk factors and possible interaction effects of those risk factors. Design and Methods: A nationally representative sample of American older adults aged 65 years and older (N = 9,592) in the Health and Retirement Study 2004 and 2006 modules was used.…

Estimation of Logistic Regression Models in Small Samples. A Simulation Study Using a Weakly Informative Default Prior Distribution

ERIC Educational Resources Information Center

Gordovil-Merino, Amalia; Guardia-Olmos, Joan; Pero-Cebollero, Maribel

2012-01-01

In this paper, we used simulations to compare the performance of classical and Bayesian estimations in logistic regression models using small samples. In the performed simulations, conditions were varied, including the type of relationship between independent and dependent variable values (i.e., unrelated and related values), the type of variable…

Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA

USGS Publications Warehouse

Ohlmacher, G.C.; Davis, J.C.

2003-01-01

Landslides in the hilly terrain along the Kansas and Missouri rivers in northeastern Kansas have caused millions of dollars in property damage during the last decade. To address this problem, a statistical method called multiple logistic regression has been used to create a landslide-hazard map for Atchison, Kansas, and surrounding areas. Data included digitized geology, slopes, and landslides, manipulated using ArcView GIS. Logistic regression relates predictor variables to the occurrence or nonoccurrence of landslides within geographic cells and uses the relationship to produce a map showing the probability of future landslides, given local slopes and geologic units. Results indicated that slope is the most important variable for estimating landslide hazard in the study area. Geologic units consisting mostly of shale, siltstone, and sandstone were most susceptible to landslides. Soil type and aspect ratio were considered but excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression. Soil types were highly correlated with the geologic units, and no significant relationships existed between landslides and slope aspect. ?? 2003 Elsevier Science B.V. All rights reserved.

A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test

NASA Technical Reports Server (NTRS)

Messer, Bradley

2007-01-01

Propulsion ground test facilities face the daily challenge of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Over the last decade NASA s propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and exceeded the capabilities of numerous test facility and test article components. A logistic regression mathematical modeling technique has been developed to predict the probability of successfully completing a rocket propulsion test. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),.., X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure of accomplishing a full duration test. The use of logistic regression modeling is not new; however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from this type of model provide project managers with insight and confidence into the effectiveness of rocket propulsion ground testing.

Predicting risk for portal vein thrombosis in acute pancreatitis patients: A comparison of radical basis function artificial neural network and logistic regression models.

PubMed

Fei, Yang; Hu, Jian; Gao, Kun; Tu, Jianfeng; Li, Wei-Qin; Wang, Wei

2017-06-01

To construct a radical basis function (RBF) artificial neural networks (ANNs) model to predict the incidence of acute pancreatitis (AP)-induced portal vein thrombosis. The analysis included 353 patients with AP who had admitted between January 2011 and December 2015. RBF ANNs model and logistic regression model were constructed based on eleven factors relevant to AP respectively. Statistical indexes were used to evaluate the value of the prediction in two models. The predict sensitivity, specificity, positive predictive value, negative predictive value and accuracy by RBF ANNs model for PVT were 73.3%, 91.4%, 68.8%, 93.0% and 87.7%, respectively. There were significant differences between the RBF ANNs and logistic regression models in these parameters (P<0.05). In addition, a comparison of the area under receiver operating characteristic curves of the two models showed a statistically significant difference (P<0.05). The RBF ANNs model is more likely to predict the occurrence of PVT induced by AP than logistic regression model. D-dimer, AMY, Hct and PT were important prediction factors of approval for AP-induced PVT. Copyright © 2017 Elsevier Inc. All rights reserved.

Biomechanical and organisational stressors and associations with employment withdrawal among pregnant workers: evidence and implications.

PubMed

Guendelman, Sylvia; Gemmill, Alison; MacDonald, Leslie A

2016-12-01

The distribution of exposure to biomechanical and organisational job stressors (BOJS) and associations with employment withdrawal (antenatal leave, unemployment) was examined in a case-control study of 1114 pregnant workers in California. We performed descriptive and multivariate logistic and multinomial regression analyses. At pregnancy onset, 57% were exposed to one or more biomechanical stressors, including frequent bending, heavy lifting and prolonged standing. One-third were simultaneously exposed to BOJS. Exposure to biomechanical stressors declined as pregnancy progressed and cessation often (41%) coincided with employment withdrawal (antenatal leave and unemployment). In multivariate modelling, whether we adjusted for or considered organisational stressors as coincident exposures, results showed that pregnant workers exposed to biomechanical stressors had increased employment withdrawal compared to the unexposed. Work schedule accommodations moderate this association. Paid antenatal leave, available to few US women, was an important strategy for mitigating exposure to BOJS. Implications for science and policy are discussed. Practitioner Summary: This case-control study showed that exposure to biomechanical stressors decline throughout pregnancy. Antenatal leave was an important strategy used for mitigating exposure among sampled California women with access to paid benefits. Employment withdrawal among workers exposed to BJOS may be reduced by proactive administrative and engineering efforts applied early in pregnancy.

Factors affecting vocational outcomes of people with chronic illness participating in a supported competitive open employment program in Hong Kong.

PubMed

Lee, Rosalia K Y; Chan, Chetwyn C H

2005-01-01

This study aimed to analyze the ability of the Patient Retraining and Vocational Resettlement (PRAVR) program to enhance the vocational outcomes of individuals with chronic illness, and to study the socio-demographic factors associated with successful vocational outcome. A retrospective study of 548 individuals with various types of chronic illness who enrolled in the program between 1995 and 2003. Their socio-demographic data and their employment outcome after a six-month job skills retraining and job settlement service were collected for analysis. The program was found to enhance the vocational outcomes of patients who completed the program. Logistic regression identified significant factors predicting successful vocational outcomes. For the male patients, the chances of employment were higher if the onset of illness had occurred at least 10 years before (odd ratios = 0.326). For the female patients, the chances of employment were higher if they had been unemployed for less than 1 year (odd ratio = 3.8). The PRAVR program is able to enhance the vocational outcomes of people with chronic illness in Hong Kong. The factors which were found to relate to successful employment were unique to the local situation. Further studies should explore these factors in a more in-depth manner.

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.

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.

Regional and Gender Differences and Trends in the Anesthesiologist Workforce.

PubMed

Baird, Matthew; Daugherty, Lindsay; Kumar, Krishna B; Arifkhanova, Aziza

2015-11-01

Concerns have long existed about potential shortages in the anesthesiologist workforce. In addition, many changes have occurred in the economy, demographics, and the healthcare sector in the last few years, which may impact the workforce. The authors documented workforce trends by region of the United States and gender, trends that may have implications for the supply and demand of anesthesiologists. The authors conducted a national survey of American Society of Anesthesiologists members (accounting for >80% of all practicing anesthesiologists in the United States) in 2007 and repeated it in 2013. The authors used logistic regression analysis and Seemingly Unrelated Regression to test across several indicators under an overarching hypothesis. Anesthesiologists in Western states had markedly different patterns of practice relative to anesthesiologists in other regions in 2007 and 2013, including differences in employer type, the composition of anesthesia teams, and the time spent on monitored anesthesia care. The number and proportion of female anesthesiologists in the workforce increased between 2007 and 2013, and females differed from males in employment arrangements, compensation, and work hours. Regional differences remained stable during this time period although the reasons for these differences are speculative. Similarly, how and whether the gender difference in work hours and shift to younger anesthesiologists during this period will impact workforce needs is uncertain.

EXpectation Propagation LOgistic REgRession (EXPLORER): Distributed Privacy-Preserving Online Model Learning

PubMed Central

Wang, Shuang; Jiang, Xiaoqian; Wu, Yuan; Cui, Lijuan; Cheng, Samuel; Ohno-Machado, Lucila

2013-01-01

We developed an EXpectation Propagation LOgistic REgRession (EXPLORER) model for distributed privacy-preserving online learning. The proposed framework provides a high level guarantee for protecting sensitive information, since the information exchanged between the server and the client is the encrypted posterior distribution of coefficients. Through experimental results, EXPLORER shows the same performance (e.g., discrimination, calibration, feature selection etc.) as the traditional frequentist Logistic Regression model, but provides more flexibility in model updating. That is, EXPLORER can be updated one point at a time rather than having to retrain the entire data set when new observations are recorded. The proposed EXPLORER supports asynchronized communication, which relieves the participants from coordinating with one another, and prevents service breakdown from the absence of participants or interrupted communications. PMID:23562651

Ex-post-facto analysis of competitive employment outcomes for individuals with mental retardation: national perspective.

PubMed

Moore, Corey L; Harley, Debra A; Gamble, David

2004-08-01

Disparities in proportions of competitive job placements and provision of vocational rehabilitation services by level of mental retardation were identified for 28,565 individuals. Chi-square results reveal that consumers with mild mental retardation are significantly more likely to achieve competitive jobs compared to those with more severe levels. Logistic regression indicated that the odds of achieving a competitive job for consumers receiving job placement services, business/vocational training, and counseling were nearly two times that of individuals not receiving such services. Findings suggest that a significantly lower proportion of these services were provided to consumers with severe/profound mental retardation. Implications of findings for service, research, and policy are discussed.

Religious coping, spirituality, and substance use and abuse among youth in high-risk communities in San Salvador, El Salvador.

PubMed

Salas-Wright, Christopher P; Olate, Rene; Vaughn, Michael G

2013-06-01

Little is known about the relationship between religious coping, spirituality, and substance use in developing nations such as El Salvador. Collected in 2011, the sample consists of 290 high-risk and gang-involved adolescents (11-17 years) and young adults (18-25 years) in San Salvador, El Salvador. Structural equation modeling and logistic regression are employed to examine the associations between the Measure of Religious Coping (RCOPE), the Intrinsic Spirituality Scale, and substance use and abuse. Results suggest that spirituality and, to a far lesser degree, religious coping may serve to protect for substance use and abuse among this high-risk population of Salvadoran youth.

[Application of Mass Spectrometry to the Diagnosis of Cancer--Chairman's Introductory Remarks].

PubMed

Yatomi, Yutaka

2015-09-01

In this symposium, the latest application of mass spectrometry to laboratory medicine, i.e., to the early diagnosis of cancer, was introduced. Dr. Masaru YOSHIDA, who has been using metabolome analysis to discover biomarker candidates for gastroenterological diseases, presented an automated early diagnosis system for early stages of colon cancer based on metabolome analysis and using a minute amount of blood. On the other hand, Dr. Sen TAKEDA, who has developed a new approach by employing both mass spectrometry and machine-learning for cancer diagnosis, presented a device for the clinical diagnosis of cancer using probe electrospray ionization (PESI) and machine-learning called the dual penalized logistic regression machine (dPLRM).

Team versus individual sport participation as a modifying factor in the development of post-concussion syndrome after first concussion: A pilot study.

PubMed

Jeckell, Aaron S; Brett, Benjamin L; Totten, Douglas J; Solomon, Gary S

2018-01-19

Identification of modifying factors that influence the development of post-concussion syndrome (PCS) following sport-related concussion (SRC) has drawn considerable interest. In this pilot study, we investigate the effect of team vs. individual sport participation on the development of PCS in a sample of 136 high school and college student-athletes. Controlling for several confounding variables, we employed a binary logistic regression and chi-squared test. Results of this pilot study indicate that participation in team versus individual sport is not a significant factor in the development of PCS. The identification of other forms of protective mechanisms is discussed.

Constructing a consumption model of fine dining from the perspective of behavioral economics

PubMed Central

Tsai, Sang-Bing

2018-01-01

Numerous factors affect how people choose a fine dining restaurant, including food quality, service quality, food safety, and hedonic value. A conceptual framework for evaluating restaurant selection behavior has not yet been developed. This study surveyed 150 individuals with fine dining experience and proposed the use of mental accounting and axiomatic design to construct a consumer economic behavior model. Linear and logistic regressions were employed to determine model correlations and the probability of each factor affecting behavior. The most crucial factor was food quality, followed by service and dining motivation, particularly regarding family dining. Safe ingredients, high cooking standards, and menu innovation all increased the likelihood of consumers choosing fine dining restaurants. PMID:29641554

Constructing a consumption model of fine dining from the perspective of behavioral economics.

PubMed

Hsu, Sheng-Hsun; Hsiao, Cheng-Fu; Tsai, Sang-Bing

2018-01-01

Numerous factors affect how people choose a fine dining restaurant, including food quality, service quality, food safety, and hedonic value. A conceptual framework for evaluating restaurant selection behavior has not yet been developed. This study surveyed 150 individuals with fine dining experience and proposed the use of mental accounting and axiomatic design to construct a consumer economic behavior model. Linear and logistic regressions were employed to determine model correlations and the probability of each factor affecting behavior. The most crucial factor was food quality, followed by service and dining motivation, particularly regarding family dining. Safe ingredients, high cooking standards, and menu innovation all increased the likelihood of consumers choosing fine dining restaurants.

Study on optimization method of test conditions for fatigue crack detection using lock-in vibrothermography

NASA Astrophysics Data System (ADS)

Min, Qing-xu; Zhu, Jun-zhen; Feng, Fu-zhou; Xu, Chao; Sun, Ji-wei

2017-06-01

In this paper, the lock-in vibrothermography (LVT) is utilized for defect detection. Specifically, for a metal plate with an artificial fatigue crack, the temperature rise of the defective area is used for analyzing the influence of different test conditions, i.e. engagement force, excitation intensity, and modulated frequency. The multivariate nonlinear and logistic regression models are employed to estimate the POD (probability of detection) and POA (probability of alarm) of fatigue crack, respectively. The resulting optimal selection of test conditions is presented. The study aims to provide an optimized selection method of the test conditions in the vibrothermography system with the enhanced detection ability.

Dietary consumption patterns and laryngeal cancer risk.

PubMed

Vlastarakos, Petros V; Vassileiou, Andrianna; Delicha, Evie; Kikidis, Dimitrios; Protopapas, Dimosthenis; Nikolopoulos, Thomas P

2016-06-01

We conducted a case-control study to investigate the effect of diet on laryngeal carcinogenesis. Our study population was made up of 140 participants-70 patients with laryngeal cancer (LC) and 70 controls with a non-neoplastic condition that was unrelated to diet, smoking, or alcohol. A food-frequency questionnaire determined the mean consumption of 113 different items during the 3 years prior to symptom onset. Total energy intake and cooking mode were also noted. The relative risk, odds ratio (OR), and 95% confidence interval (CI) were estimated by multiple logistic regression analysis. We found that the total energy intake was significantly higher in the LC group (p < 0.001), and that the difference remained statistically significant after logistic regression analysis (p < 0.001; OR: 118.70). Notably, meat consumption was higher in the LC group (p < 0.001), and the difference remained significant after logistic regression analysis (p = 0.029; OR: 1.16). LC patients also consumed significantly more fried food (p = 0.036); this difference also remained significant in the logistic regression model (p = 0.026; OR: 5.45). The LC group also consumed significantly more seafood (p = 0.012); the difference persisted after logistic regression analysis (p = 0.009; OR: 2.48), with the consumption of shrimp proving detrimental (p = 0.049; OR: 2.18). Finally, the intake of zinc was significantly higher in the LC group before and after logistic regression analysis (p = 0.034 and p = 0.011; OR: 30.15, respectively). Cereal consumption (including pastas) was also higher among the LC patients (p = 0.043), with logistic regression analysis showing that their negative effect was possibly associated with the sauces and dressings that traditionally accompany pasta dishes (p = 0.006; OR: 4.78). Conversely, a higher consumption of dairy products was found in controls (p < 0.05); logistic regression analysis showed that calcium appeared to be protective at the micronutrient level (p < 0.001; OR: 0.27). We found no difference in the overall consumption of fruits and vegetables between the LC patients and controls; however, the LC patients did have a greater consumption of cooked tomatoes and cooked root vegetables (p = 0.039 for both), and the controls had more consumption of leeks (p = 0.042) and, among controls younger than 65 years, cooked beans (p = 0.037). Lemon (p = 0.037), squeezed fruit juice (p = 0.032), and watermelon (p = 0.018) were also more frequently consumed by the controls. Other differences at the micronutrient level included greater consumption by the LC patients of retinol (p = 0.044), polyunsaturated fats (p = 0.041), and linoleic acid (p = 0.008); LC patients younger than 65 years also had greater intake of riboflavin (p = 0.045). We conclude that the differences in dietary consumption patterns between LC patients and controls indicate a possible role for lifestyle modifications involving nutritional factors as a means of decreasing the risk of laryngeal cancer.

Childbirth or termination of pregnancy: does paid employment matter? A population study of women in reproductive age in Norway.

PubMed

Eskild, Anne; Herdlevaer, Ida E; Strøm-Roum, Ellen M; Monkerud, Lars; Grytten, Jostein

2016-05-01

We studied whether female paid employment is associated with pregnancy outcome; childbirth or pregnancy termination. All women in Norway, 16-54 years of age, during the years 2007-10 were included. Data sources were; the Norwegian Central Person Registry, the Medical Birth Registry of Norway, and the Registry of Pregnancy Termination. We compared the proportion without paid employment among all women, women who gave birth, and among women who requested termination of pregnancy. Thereafter, and among pregnant women, we estimated the odds ratio for pregnancy termination request for women without paid employment by applying logistic regression analyses, using women with paid employment as reference. Among all women 16-54 years of age, 23.5% were without paid employment. Among women who gave birth, 15.8% were without paid employment, whereas this proportion was 46.4% among women who requested pregnancy termination (p < 0.05). Among the 307 512 women who were pregnant, 60 734 (19.4%) requested pregnancy termination. The odds ratio for pregnancy termination request was 3.18 (95% CI 3.11-3.25) for women without paid employment. Adjustments were made for age, number of children, and region of residence in Norway. Being without paid employment was more common among women in the general population and among women requesting pregnancy termination than among women who gave birth. Hence, women seem to have children when they are in paid employment. The role of women's paid employment for reproductive choices should be further investigated. © 2016 Nordic Federation of Societies of Obstetrics and Gynecology.

Association of rheumatic diseases with early exit from paid employment in Portugal.

PubMed

Laires, Pedro A; Gouveia, Miguel

2014-04-01

To examine the association between rheumatic diseases (RD) and other chronic morbidity with early exit from paid employment in the Portuguese population. The study population consisted of all people between 50 and 64 years of age (3,762 men and 4,241 women) who participated in the Portuguese National Health Survey, conducted in 2005/2006. Data were collected on demographics, ill-health, lifestyle, and socioeconomic factors. Logistic regression was used to estimate the isolated effect of rheumatic diseases and other chronic diseases on the likelihood of exit from paid employment. At the time of the survey, 45.1 % of the Portuguese population with ages between 50 and 64 years old were not employed. In the nonemployed population, 31.6 % self-reported "poor" to "very poor" health, whereas 16.4 % did so in the employed population. A larger average number of major chronic diseases per capita were also found in those not employed (1.9 vs. 1.4, p < 0.001). In the multivariate models, chronic diseases were associated with early exit from paid employment. In particular, rheumatic diseases were more prevalent (43.4 vs. 32.1 %) and associated with early exit from work (OR 1.31; CI 1.12-1.52, p = 0.001). This study suggests an association between RD and other major chronic diseases with early exit from paid employment in Portugal. Thus, health and social protection policies should target these chronic disorders in order to better address sustainability issues and social protection effectiveness.

Breastfeeding and maternal employment: results from three national nutritional surveys in Mexico.

PubMed

Rivera-Pasquel, Marta; Escobar-Zaragoza, Leticia; González de Cosío, Teresita

2015-05-01

To evaluate the association between maternal employment and breastfeeding (both duration and status) in Mexican mothers using data from three National Health and Nutrition Surveys conducted in 1999, 2006 and 2012. We analyzed data from the 1999 National Nutrition Survey, the 2006 National Nutrition and Health Survey, and the 2012 National Nutrition and Health Survey (NNS-1999, NHNS-2006 and NHNS-2012) on 5,385 mothers aged 12-49 years, with infants under 1 year. Multivariate logistic regression models were used to analyze the association between breastfeeding and maternal employment adjusted for maternal and infant's socio-demographic covariates. Maternal formal employment was negatively associated with breastfeeding in Mexican mothers with infants under 1 year. Formally employed mothers were 20 % less likely to breastfeed compared to non-formally employed mothers and 27 % less likely to breastfeed compared to unemployed mothers. Difference in median duration of breastfeeding between formally employed and unemployed mothers was 5.7 months for NNS-1999, 4.7 months for NNHS-2006 and 6.7 months for NNHS-2012 respectively (p < 0.05). In NHNS-2006 and NHNS-2012, health care access was associated with longer breastfeeding duration. Maternal employment has been negatively associated with breastfeeding in Mexican mothers of <1 year infants at least for the last 15 years. For Mexicans involved in policy design, implementation or modification, these data might offer robust evidence on this negative association, and can be used confidently as basis for conceiving a more just legislation for working lactating women.

Postsecondary Education and Employment Among Youth With an Autism Spectrum Disorder

PubMed Central

Narendorf, Sarah Carter; Cooper, Benjamin; Sterzing, Paul R.; Wagner, Mary; Taylor, Julie Lounds

2012-01-01

OBJECTIVES: We examined the prevalence and correlates of postsecondary education and employment among youth with an autism spectrum disorder (ASD). METHODS: Data were from a nationally representative survey of parents, guardians, and young adults with an ASD. Participation in postsecondary employment, college, or vocational education and lack of participation in any of these activities were examined. Rates were compared with those of youth in 3 other eligibility categories: speech/language impairment, learning disability, and mental retardation. Logistic regression was used to examine correlates of each outcome. RESULTS: For youth with an ASD, 34.7% had attended college and 55.1% had held paid employment during the first 6 years after high school. More than 50% of youth who had left high school in the past 2 years had no participation in employment or education. Youth with an ASD had the lowest rates of participation in employment and the highest rates of no participation compared with youth in other disability categories. Higher income and higher functional ability were associated with higher adjusted odds of participation in postsecondary employment and education. CONCLUSIONS: Youth with an ASD have poor postsecondary employment and education outcomes, especially in the first 2 years after high school. Those from lower-income families and those with greater functional impairments are at heightened risk for poor outcomes. Further research is needed to understand how transition planning before high school exit can facilitate a better connection to productive postsecondary activities. PMID:22585766

Employment status and work-related difficulties in lung cancer survivors compared with the general population.

PubMed

Kim, Young Ae; Yun, Young Ho; Chang, Yoon Jung; Lee, Jongmog; Kim, Moon Soo; Lee, Hyun-Sung; Zo, Jae Ill; Kim, Jhingook; Choi, Yong Soo; Shim, Young Mog; Yoon, Seok-Jun

2014-03-01

To investigate the employment status of lung cancer survivors and the work-related problems they face. Although the number of lung cancer survivors is increasing, little is known about their employment and work-related issues. We enrolled 830 lung cancer survivors 12 months after lung cancer curative surgery (median time after diagnosis, 4.11 years) and 1000 volunteers from the general population. All participants completed the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, Core 30-item and a questionnaire that included items relating to their jobs. We used logistic regression analysis to identify independent predictors of unemployment. The employment rate of lung cancer survivors decreased from 68.6% at the time of diagnosis to 38.8% after treatment, which was significantly lower than the employment rate of the general population (63.5%; adjusted odds ratio = 2.31, 95% confidence interval: 1.66-3.22). The posttreatment unemployment rate was higher for women than for men. Among survivors, employment was inversely associated with older age, household income, number of comorbidities, and poor social functioning. Fatigue (78.6%) was the most common work-related problem reported by survivors. Lung cancer survivors experienced more difficulties in employment than did the general population. Age, monthly household income, number of comorbidities, and social functioning appear to be important factors influencing employment status. These findings suggest that lung cancer survivors need support to cope with the financial impact of cancer.

Determinants for employer-paid health insurance coverage: a population-based study of the Danish labour force.

PubMed

Christensen, Ann; Søgaard, Rikke

2013-08-01

In 2002, the Danish tax law was changed, giving employees a tax exemption on supplemental, employer-paid health insurance. This might have conflicted with one of the key foundations of the healthcare system, namely equal access for equal needs. The aim of this study was to investigate determinants for employer-paid health insurance coverage. Because the policy change affected only people who were part of the labour force and because the public sector at that time had no tradition of providing fringe benefits, the analysis was restricted to the private labour force. The analysis was based on data from a range of Danish person-level and company-level registers (explanatory variables). These data were combined with information on insurance status obtained from the trade organisation for insurance (dependent variable). A logistic regression was performed to estimate the odds of having employer-paid health insurance coverage. The individuals who were most likely to be insured were those employed in foreign companies as mid-level managers within the field of building and construction. Other important variables were the number of persons employed in a company, gender, ethnicity, region of residence, years of education, and annual income. Both company and individual characteristics were found to be important and significant predictors for employer-paid health insurance coverage. The Danish tax exemption on private health insurance in the years 2002-12 thus seems to have led to inequality in employer-paid health insurance coverage.

Assessing the oral health of an ageing population: methods, challenges and predictors of survey participation.

PubMed

Matthews, Debora C; Brillant, Martha G S; Clovis, Joanne B; McNally, Mary E; Filiaggi, Mark J; Kotzer, Robert D; Lawrence, Herenia P

2012-06-01

To examine predictors of participation and to describe the methodological considerations of conducting a two-stage population-based oral health survey. An observational, cross-sectional survey (telephone interview and clinical oral examination) of community-dwelling adults aged 45-64 and ≥65 living in Nova Scotia, Canada was conducted. The survey response rate was 21% for the interview and 13.5% for the examination. A total of 1141 participants completed one or both components of the survey. Both age groups had higher levels of education than the target population; the age 45-64 sample also had a higher proportion of females and lower levels of employment than the target population. Completers (participants who completed interview and examination) were compared with partial completers (who completed only the interview), and stepwise logistic regression was performed to examine predictors of completion. Identified predictors were as follows: not working, post-secondary education and frequent dental visits. Recruitment, communications and logistics present challenges in conducting a province-wide survey. Identification of employment, education and dental visit frequency as predictors of survey participation provide insight into possible non-response bias and suggest potential for underestimation of oral disease prevalence in this and similar surveys. This potential must be considered in analysis and in future recruitment strategies. © 2011 The Gerodontology Society and John Wiley & Sons A/S.

A Comparison of the Logistic Regression and Contingency Table Methods for Simultaneous Detection of Uniform and Nonuniform DIF

ERIC Educational Resources Information Center

Guler, Nese; Penfield, Randall D.

2009-01-01

In this study, we investigate the logistic regression (LR), Mantel-Haenszel (MH), and Breslow-Day (BD) procedures for the simultaneous detection of both uniform and nonuniform differential item functioning (DIF). A simulation study was used to assess and compare the Type I error rate and power of a combined decision rule (CDR), which assesses DIF…

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…

Predicting Student Success on the Texas Chemistry STAAR Test: A Logistic Regression Analysis

ERIC Educational Resources Information Center

Johnson, William L.; Johnson, Annabel M.; Johnson, Jared

2012-01-01

Background: The context is the new Texas STAAR end-of-course testing program. Purpose: The authors developed a logistic regression model to predict who would pass-or-fail the new Texas chemistry STAAR end-of-course exam. Setting: Robert E. Lee High School (5A) with an enrollment of 2700 students, Tyler, Texas. Date of the study was the 2011-2012…

Using ROC curves to compare neural networks and logistic regression for modeling individual noncatastrophic tree mortality

Treesearch

Susan L. King

2003-01-01

The performance of two classifiers, logistic regression and neural networks, are compared for modeling noncatastrophic individual tree mortality for 21 species of trees in West Virginia. The output of the classifier is usually a continuous number between 0 and 1. A threshold is selected between 0 and 1 and all of the trees below the threshold are classified as...