Multilevel nonlinear mixed-effects models for the modeling of earlywood and latewood microfibril angle

Treesearch

Lewis Jordon; Richard F. Daniels; Alexander Clark; Rechun He

2005-01-01

Earlywood and latewood microfibril angle (MFA) was determined at I-millimeter intervals from disks at 1.4 meters, then at 3-meter intervals to a height of 13.7 meters, from 18 loblolly pine (Pinus taeda L.) trees grown in southeastern Texas. A modified three-parameter logistic function with mixed effects is used for modeling earlywood and latewood...

School Health Promotion Policies and Adolescent Risk Behaviors in Israel: A Multilevel Analysis

ERIC Educational Resources Information Center

Tesler, Riki; Harel-Fisch, Yossi; Baron-Epel, Orna

2016-01-01

Background: Health promotion policies targeting risk-taking behaviors are being implemented across schools in Israel. This study identified the most effective components of these policies influencing cigarette smoking and alcohol consumption among adolescents. Methods: Logistic hierarchical linear model (HLM) analysis of data for 5279 students in…

Risk Factors for Child Malnutrition in Bangladesh: A Multilevel Analysis of a Nationwide Population-Based Survey.

PubMed

Chowdhury, Mohammad Rocky Khan; Rahman, Mohammad Shafiur; Khan, Mohammad Mubarak Hossain; Mondal, Mohammad Nazrul Islam; Rahman, Mohammad Mosiur; Billah, Baki

2016-05-01

To identify the prevalence and risk factors of child malnutrition in Bangladesh. Data was extracted from the Bangladesh Demographic Health Survey (2011). The outcome measures were stunting, wasting, and underweight. χ(2) analysis was performed to find the association of outcome variables with selected factors. Multilevel logistic regression models with a random intercept at each of the household and community levels were used to identify the risk factors of stunting, wasting, and underweight. From the 2011 survey, 7568 children less than 5 years of age were included in the current analysis. The overall prevalence of stunting, wasting, and underweight was 41.3% (95% CI 39.0-42.9). The χ(2) test and multilevel logistic regression analysis showed that the variables age, sex, mother's body mass index, mother's educational status, father's educational status, place of residence, socioeconomic status, community status, religion, region of residence, and food security are significant factors of child malnutrition. Children with poor socioeconomic and community status were at higher risk of malnutrition. Children from food insecure families were more likely to be malnourished. Significant community- and household-level variations were found. The prevalence of child malnutrition is still high in Bangladesh, and the risk was assessed at several multilevel factors. Therefore, prevention of malnutrition should be given top priority as a major public health intervention. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Assessing a multilevel model of young children’s oral health with national survey data

PubMed Central

Bramlett, Matthew D.; Soobader, Mah-J; Fisher-Owens, Susan A.; Weintraub, Jane A.; Gansky, Stuart A.; Platt, Larry J.; Newacheck, Paul W.

2010-01-01

Objectives To empirically test a multilevel conceptual model of children’s oral health incorporating 22 domains of children’s oral health across four levels: child, family, neighborhood and state. Data source The 2003 National Survey of Children’s Health, a module of the State and Local Area Integrated Telephone Survey conducted by the Centers for Disease Control and Prevention’s National Center for Health Statistics, is a nationally representative telephone survey of caregivers of children. Study design We examined child-, family-, neighborhood-, and state-level factors influencing parent’s report of children’s oral health using a multilevel logistic regression model, estimated for 26 736 children ages 1–5 years. Principal findings Factors operating at all four levels were associated with the likelihood that parents rated their children’s oral health as fair or poor, although most significant correlates are represented at the child or family level. Of 22 domains identified in our conceptual model, 15 domains contained factors significantly associated with young children’s oral health. At the state level, access to fluoridated water was significantly associated with favorable oral health for children. Conclusions Our results suggest that efforts to understand or improve children’s oral health should consider a multilevel approach that goes beyond solely child-level factors. PMID:20370808

Freshman Year Dropouts: Interactions between Student and School Characteristics and Student Dropout Status

ERIC Educational Resources Information Center

Zvoch, Keith

2006-01-01

Data from a large school district in the southwestern United States were analyzed to investigate relations between student and school characteristics and high school freshman dropout patterns. Application of a multilevel logistic regression model to student dropout data revealed evidence of school-to-school differences in student dropout rates and…

Preferences for the sex-composition of children in Europe: a multilevel examination of its effect on progression to a third child.

PubMed

Mills, Melinda; Begall, Katia

2010-03-01

Comparative research on the preferred sex of children in Western societies has generally focused on women only and ignored the role of gender equity and the need for children's economic support in old age. A multilevel analysis extends existing research by examining, for both men and women and across 24 European countries, the effect of the preferred sex-composition of offspring on whether parents have or intend to have a third child. Using the European Social Survey (2004/5), a multilevel (random coefficient) ordered logit regression of that intention (N = 3,323) and a binary logistic multilevel model of the transition to a third child (N = 6,502) demonstrate the presence of a mixed-sex preference. In countries with a high risk of poverty in old age, a preference for sons is found, particularly for men. In societies where there is lower gender equity, both men and women have a significant preference for boys.

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…

Associations between Responsible Beverage Service Laws and Binge Drinking and Alcohol-Impaired Driving

ERIC Educational Resources Information Center

Linde, Ann C.; Toomey, Traci L.; Wolfson, Julian; Lenk, Kathleen M.; Jones-Webb, Rhonda; Erickson, Darin J.

2016-01-01

We explored potential associations between the strength of state Responsible Beverage Service (RBS) laws and self-reported binge drinking and alcohol-impaired driving in the U.S. A multi-level logistic mixed-effects model was used, adjusting for potential confounders. Analyses were conducted on the overall BRFSS sample and drinkers only. Seven…

Stages of syphilis in South China - a multilevel analysis of early diagnosis.

PubMed

Wong, Ngai Sze; Huang, Shujie; Zheng, Heping; Chen, Lei; Zhao, Peizhen; Tucker, Joseph D; Yang, Li Gang; Goh, Beng Tin; Yang, Bin

2017-01-31

Early diagnosis of syphilis and timely treatment can effectively reduce ongoing syphilis transmission and morbidity. We examined the factors associated with the early diagnosis of syphilis to inform syphilis screening strategic planning. In an observational study, we analyzed reported syphilis cases in Guangdong Province, China (from 2014 to mid-2015) accessed from the national case-based surveillance system. We categorized primary and secondary syphilis cases as early diagnosis and categorized latent and tertiary syphilis as delayed diagnosis. Univariate analyses and multivariable logistic regressions were performed to identify the factors associated with early diagnosis. We also examined the factors associated with early diagnosis at the individual and city levels in multilevel logistic regression models with cases nested by city (n = 21), adjusted for age at diagnosis and gender. Among 83,944 diagnosed syphilis cases, 22% were early diagnoses. The city-level early diagnosis rate ranged from 7 to 46%, consistent with substantial geographic variation as shown in the multilevel model. Early diagnosis was associated with cases presenting to specialist clinics for screening, being male and attaining higher education level. Cases received syphilis testing in institutions and hospitals, and diagnosed in hospitals were less likely to be in early diagnosis. At the city-level, cases living in a city equipped with more hospitals per capita were less likely to be early diagnosis. To enhance early diagnosis of syphilis, city-specific syphilis screening strategies with a mix of passive and client/provider-initiated testing might be a useful approach.

Regional contextual influences on short sleep duration: a 50 universities population-based multilevel study in China.

PubMed

Yang, Tingzhong; Peng, Sihui; Barnett, Ross; Zhang, Chichen

2018-01-01

Ecological models have emphasized that short sleep duration (SSD) is influenced by both individual and environmental variables. However, few studies have considered the latter. The present study explores the influence of urban and regional contextual factors, net of individual characteristics, on the prevalence of SSD among university students in China. Participants were 11,954 students, who were identified through a multistage survey sampling process conducted in 50 universities. Individual data were obtained through a self-administered questionnaire, and contextual variables were retrieved from a national database. Multilevel logistic regression models were used to examine urban and regional variations in high and moderate levels of SSD. Overall the prevalence of high SSD (<6 hours sleep duration) was 2.8% (95% CI: 1.7%,3.9%) and moderate SSD (<7 hours) 24.7% (95% CI: 19.5%, 29.8%). Multilevel logistic regressions confirmed that home region gross domestic product (GDP) and the university regional unemployment rate were associated with SSD, net of other individual- and city-level covariates. Students attending high-level universities also recorded the highest levels of SSD. Of the individual characteristcs, only mother's occupation and student mental health status were related to SSD. The results of this study add important insights about the role of contextual factors affecting SSD among young adults and indicate the need to take into account both past, as well as present, environmental influences to control SSD.

Smoking in young adolescents: an approach with multilevel discrete choice models

PubMed Central

Pinilla, J; Gonzalez, B; Barber, P; Santana, Y

2002-01-01

Design: Cross sectional analysis performed by multilevel logistic regression with pupils at the first level and schools at the second level. The data came from a stratified sample of students surveyed on their own, their families' and their friends' smoking habits, their schools, and their awareness of cigarette prices and advertising. Setting: The study was performed in the Island of Gran Canaria, Spain. Participants: 1877 students from 30 secondary schools in spring of 2000 (model's effective sample sizes 1697 and 1738) . Main results: 14.2% of the young teenagers surveyed use tobacco, almost half of them (6.3% of the total surveyed) on a daily basis. According to the ordered logistic regression model, to have a smoker as the best friend increases significantly the probability of smoking (odds ratio: 6.96, 95% confidence intervals (CI) (4.93 to 9.84), and the same stands for one smoker living at home compared with a smoking free home (odds ratio: 2.03, 95% CI 1.22 to 3.36). Girls smoke more (odds ratio: 1.85, 95% CI 1.33 to 2.59). Experience with alcohol, and lack of interest in studies are also significant factors affecting smoking. Multilevel models of logistic regression showed that factors related to the school affect the smoking behaviour of young teenagers. More specifically, whether a school complies with antismoking rules or not is the main factor to predict smoking prevalence in schools. The remainder of the differences can be attributed to individual and family characteristics, tobacco consumption by parents or other close relatives, and peer group. Conclusions: A great deal of the individual differences in smoking are explained by factors at the school level, therefore the context is very relevant in this case. The most relevant predictors for smoking in young adolescents include some factors related to the schools they attend. One variable stood out in accounting for the school to school differences: how well they enforced the no smoking rule. Therefore we can prevent or delay tobacco smoking in adolescents not only by publicising health risks, but also by better enforcing no smoking rules in schools. PMID:11854347

The median hazard ratio: a useful measure of variance and general contextual effects in multilevel survival analysis.

PubMed

Austin, Peter C; Wagner, Philippe; Merlo, Juan

2017-03-15

Multilevel data occurs frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models (MLRM). MLRM incorporate cluster-specific random effects which allow one to partition the total individual variance into between-cluster variation and between-individual variation. Statistically, MLRM account for the dependency of the data within clusters and provide correct estimates of uncertainty around regression coefficients. Substantively, the magnitude of the effect of clustering provides a measure of the General Contextual Effect (GCE). When outcomes are binary, the GCE can also be quantified by measures of heterogeneity like the Median Odds Ratio (MOR) calculated from a multilevel logistic regression model. Time-to-event outcomes within a multilevel structure occur commonly in epidemiological and medical research. However, the Median Hazard Ratio (MHR) that corresponds to the MOR in multilevel (i.e., 'frailty') Cox proportional hazards regression is rarely used. Analogously to the MOR, the MHR is the median relative change in the hazard of the occurrence of the outcome when comparing identical subjects from two randomly selected different clusters that are ordered by risk. We illustrate the application and interpretation of the MHR in a case study analyzing the hazard of mortality in patients hospitalized for acute myocardial infarction at hospitals in Ontario, Canada. We provide R code for computing the MHR. The MHR is a useful and intuitive measure for expressing cluster heterogeneity in the outcome and, thereby, estimating general contextual effects in multilevel survival analysis. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

The median hazard ratio: a useful measure of variance and general contextual effects in multilevel survival analysis

PubMed Central

Wagner, Philippe; Merlo, Juan

2016-01-01

Multilevel data occurs frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models (MLRM). MLRM incorporate cluster‐specific random effects which allow one to partition the total individual variance into between‐cluster variation and between‐individual variation. Statistically, MLRM account for the dependency of the data within clusters and provide correct estimates of uncertainty around regression coefficients. Substantively, the magnitude of the effect of clustering provides a measure of the General Contextual Effect (GCE). When outcomes are binary, the GCE can also be quantified by measures of heterogeneity like the Median Odds Ratio (MOR) calculated from a multilevel logistic regression model. Time‐to‐event outcomes within a multilevel structure occur commonly in epidemiological and medical research. However, the Median Hazard Ratio (MHR) that corresponds to the MOR in multilevel (i.e., ‘frailty’) Cox proportional hazards regression is rarely used. Analogously to the MOR, the MHR is the median relative change in the hazard of the occurrence of the outcome when comparing identical subjects from two randomly selected different clusters that are ordered by risk. We illustrate the application and interpretation of the MHR in a case study analyzing the hazard of mortality in patients hospitalized for acute myocardial infarction at hospitals in Ontario, Canada. We provide R code for computing the MHR. The MHR is a useful and intuitive measure for expressing cluster heterogeneity in the outcome and, thereby, estimating general contextual effects in multilevel survival analysis. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:27885709

Another Way out: The Impact of Juvenile Arrests on High School Dropout

ERIC Educational Resources Information Center

Hirschfield, Paul

2009-01-01

This article suggests that contact with the legal system increased school dropout in a Chicago sample of 4,844 inner-city students. According to multilevel multivariate logistic models, students who were first arrested during the 9th or 10th grade were six to eight times more likely than were nonarrested students ever to dropout of high school and…

A Comparison of Individual-Level and Community-Level Predictors of Marijuana and Cocaine Use among a Sample of Newly Arrested Juvenile Offenders

ERIC Educational Resources Information Center

Childs, Kristina; Dembo, Richard; Belenko, Steven; Wareham, Jennifer; Schmeidler, James

2011-01-01

Variations in drug use have been found across individual-level factors and community characteristics, and by type of drug used. Relatively little research, however, has examined this variation among juvenile offenders. Based on a sample of 924 newly arrested juvenile offenders, two multilevel logistic regression models predicting marijuana test…

Anorexia nervosa, depression and suicidal thoughts among Chinese adolescents: a national school-based cross-sectional study.

PubMed

Lian, Qiguo; Zuo, Xiayun; Mao, Yanyan; Luo, Shan; Zhang, Shucheng; Tu, Xiaowen; Lou, Chaohua; Zhou, Weijin

2017-04-04

Although there is much literature on adolescent suicide, combined effects of depression and anorexia nervosa on suicide were rarely investigated. The aims of this study are to examine the association between anorexia nervosa and suicidal thoughts and explore the interaction between anorexia nervosa and depression. This is a cross-sectional study, in the study, a sample of 8,746 Chinese adolescents was selected by multistage stratified method in 2012/2013 from 20 middle schools in 7 provinces across China Mainland. Multilevel logistic model was introduced to explore association between anorexia nervosa and suicidal thoughts. And subgroup analyses were conducted on participants with or without depression. Multilevel logistic model revealed that demographic variables, including academic achievement, were not the predictive risk factors of suicidal thoughts. Those who suffered from worse severity of perceived anorexia nervosa were at increased risk of thinking about suicide. The interaction between depression and anorexia nervosa was significant, however, subgroup analyses showed that the associations were significant only among the adolescents without depression. Our results indicate that all levels of anorexia nervosa serve as predictable indicators of suicidal thoughts in Chinese adolescents, and the effects of anorexia nervosa are modified by depression status.

Multilevel joint competing risk models

NASA Astrophysics Data System (ADS)

Karunarathna, G. H. S.; Sooriyarachchi, M. R.

2017-09-01

Joint modeling approaches are often encountered for different outcomes of competing risk time to event and count in many biomedical and epidemiology studies in the presence of cluster effect. Hospital length of stay (LOS) has been the widely used outcome measure in hospital utilization due to the benchmark measurement for measuring multiple terminations such as discharge, transferred, dead and patients who have not completed the event of interest at the follow up period (censored) during hospitalizations. Competing risk models provide a method of addressing such multiple destinations since classical time to event models yield biased results when there are multiple events. In this study, the concept of joint modeling has been applied to the dengue epidemiology in Sri Lanka, 2006-2008 to assess the relationship between different outcomes of LOS and platelet count of dengue patients with the district cluster effect. Two key approaches have been applied to build up the joint scenario. In the first approach, modeling each competing risk separately using the binary logistic model, treating all other events as censored under the multilevel discrete time to event model, while the platelet counts are assumed to follow a lognormal regression model. The second approach is based on the endogeneity effect in the multilevel competing risks and count model. Model parameters were estimated using maximum likelihood based on the Laplace approximation. Moreover, the study reveals that joint modeling approach yield more precise results compared to fitting two separate univariate models, in terms of AIC (Akaike Information Criterion).

Transition and protective agency of early childhood learning behaviors as portents of later school attendance and adjustment.

PubMed

McDermott, Paul A; Rikoon, Samuel H; Fantuzzo, John W

2016-02-01

This article reports on the study of differential change trajectories for early childhood learning behaviors as they relate to future classroom adjustment and school attendance. A large sample (N=2152) of Head Start children was followed through prekindergarten, kindergarten, and 1st grade. Classroom learning behaviors were assessed twice each year by teachers who observed gradual declines in Competence Motivation and Attentional Persistence as children transitioned through schooling. Cross-classified multilevel growth models revealed distinct transitional pathways for future adjustment versus maladjustment and sporadic versus chronic absenteeism. Generalized multilevel logistic modeling and receiver operating characteristic curve analyses showed that teachers' earliest assessments were substantially predictive of eventual good classroom adjustment and school attendance, with increasing accuracy for prediction of future sociobehavioral adjustment as time progressed. Copyright © 2015 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Migration and Remittances: Evidence from a Poor Province in China*

PubMed Central

Liang, Zai; Li, Jiejin; Ma, Zhongdong

2014-01-01

This paper examines patterns of remittances among migrants from Guizhou province of China. Our research is motivated by three lines of theoretical arguments, namely the new economics of migration, a translocal perspective linking remittances and development, and the culture of remittances. Taking individual, household, and village-level characteristics into account, we estimated multilevel logistic models of the decision to remit and multilevel models of the amount of remittances. Our results show that migrant remittance behaviour is responsive to family needs as well as household economic position in the village.. Migrants who come from entrepreneurial households are more likely to remit a large amount than other types of households. We find some evidence of “culture of remittances” in these villages. Consistent with our expectations, migrants who are from villages with higher amount of average remittances are likely to remit a larger amount than otherwise. PMID:26146509

The Association between Overweight and School Policies on Physical Activity: A Multilevel Analysis among Elementary School Youth in the PLAY-On Study

ERIC Educational Resources Information Center

Leatherdale, Scott T.

2010-01-01

The objective is to examine school-level program and policy characteristics and student-level behavioural characteristics associated with being overweight. Multilevel logistic regression analysis were used to examine the school- and student-level characteristics associated with the odds of a student being overweight among 1264 Grade 5-8 students…

The mathematical and theoretical biology institute--a model of mentorship through research.

PubMed

Camacho, Erika T; Kribs-Zaleta, Christopher M; Wirkus, Stephen

2013-01-01

This article details the history, logistical operations, and design philosophy of the Mathematical and Theoretical Biology Institute (MTBI), a nationally recognized research program with an 18-year history of mentoring researchers at every level from high school through university faculty, increasing the number of researchers from historically underrepresented minorities, and motivating them to pursue research careers by allowing them to work on problems of interest to them and supporting them in this endeavor. This mosaic profile highlights how MTBI provides a replicable multi-level model for research mentorship.

Risk factors for the incidence of dengue virus infection in preschool children.

PubMed

Teixeira, Maria G; Morato, Vanessa; Barreto, Florisneide R; Mendes, Carlos M C; Barreto, Maurício L; Costa, Maria da Conceição N

2012-11-01

To estimate the seroincidence of dengue in children living in Salvador, Bahia, Brazil and to evaluate the factors associated.   A prospective serological survey was carried out in a sample of children 0-3 years of age. A multilevel logistic model was used to identify the determinants of seroincidence. The seroprevalence of dengue was 26.6% in the 625 children evaluated. A second survey detected an incidence of 33.2%. Multilevel logistic regression showed a statistically significant association between the seroincidence of dengue and age and the premises index. In Salvador, the dengue virus is in active circulation during early childhood; consequently, children have heterotypic antibodies and run a high risk of developing dengue haemorrhagic fever, because the sequence and intensity of the three dengue virus serotypes currently circulating in this city are very similar to those that were circulating in Rio de Janeiro, Brazil, in 2008. Therefore, the authors strongly recommend that the health authorities in cities with a similar epidemiological scenario be aware of this risk and implement improvements in health care, particularly targeting the paediatric age groups. In addition, information should be provided to the population and actions should be implemented to combat this vector. © 2012 Blackwell Publishing Ltd.

Retrospective analysis of Bluetongue farm risk profile definition, based on biology, farm management practices and climatic data.

PubMed

Cappai, Stefano; Loi, Federica; Coccollone, Annamaria; Contu, Marino; Capece, Paolo; Fiori, Michele; Canu, Simona; Foxi, Cipriano; Rolesu, Sandro

2018-07-01

Bluetongue (BT) is a vector-borne disease transmitted by species of Culicoides midges (Diptera: Ceratopogonidae). Many studies have contributed to clarifying various aspects of its aetiology, epidemiology and vector dynamic; however, BT remains a disease of epidemiological and economic importance that affects ruminants worldwide. Since 2000, the Sardinia region has been the most affected area of the Mediterranean basin. The region is characterised by wide pastoral areas for sheep and represents the most likely candidate region for the study of Bluetongue virus (BTV) distribution and prevalence in Italy. Furthermore, specific information on the farm level and epidemiological studies needs to be provided to increase the knowledge on the disease's spread and to provide valid mitigation strategies in Sardinia. This study conducted a punctual investigation into the spatial patterns of BTV transmission to define a risk profile for all Sardinian farmsby using a logistic multilevel mixed model that take into account agro-meteorological aspects, as well as farm characteristics and management. Data about animal density (i.e. sheep, goats and cattle), vaccination, previous outbreaks, altitude, land use, rainfall, evapotranspiration, water surface, and farm management practices (i.e. use of repellents, treatment against insect vectors, storage of animals in shelter overnight, cleaning, presence of mud and manure) were collected for 12,277 farms for the years 2011-2015. The logistic multilevel mixed model showed the fundamental role of climatic factors in disease development and the protective role of good management, vaccination, outbreak in the previous year and altitude. Regional BTV risk maps were developed, based on the predictor values of logistic model results, and updated every 10 days. These maps were used to identify, 20 days in advance, the areas at highest risk. The risk farm profile, as defined by the model, would provide specific information about the role of each factor for all Sardinian institutions involved in devising BT prevention and control strategies. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

[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.

Elder abuse and socioeconomic inequalities: a multilevel study in 7 European countries.

PubMed

Fraga, Sílvia; Lindert, Jutta; Barros, Henrique; Torres-González, Francisco; Ioannidi-Kapolou, Elisabeth; Melchiorre, Maria Gabriella; Stankunas, Mindaugas; Soares, Joaquim F

2014-04-01

To compare the prevalence of elder abuse using a multilevel approach that takes into account the characteristics of participants as well as socioeconomic indicators at city and country level. In 2009, the project on abuse of elderly in Europe (ABUEL) was conducted in seven cities (Stuttgart, Germany; Ancona, Italy; Kaunas, Lithuania, Stockholm, Sweden; Porto, Portugal; Granada, Spain; Athens, Greece) comprising 4467 individuals aged 60-84 years. We used a 3-level hierarchical structure of data: 1) characteristics of participants; 2) mean of tertiary education of each city; and 3) country inequality indicator (Gini coefficient). Multilevel logistic regression was used and proportional changes in Intraclass Correlation Coefficient (ICC) were inspected to assert explained variance between models. The prevalence of elder abuse showed large variations across sites. Adding tertiary education to the regression model reduced the country level variance for psychological abuse (ICC=3.4%), with no significant decrease in the explained variance for the other types of abuse. When the Gini coefficient was considered, the highest drop in ICC was observed for financial abuse (from 9.5% to 4.3%). There is a societal and community level dimension that adds information to individual variability in explaining country differences in elder abuse, highlighting underlying socioeconomic inequalities leading to such behavior. Copyright © 2014 Elsevier Inc. All rights reserved.

Associations between state minimum wage policy and health care access: a multi-level analysis of the 2004 Behavioral Risk Factor survey.

PubMed

McCarrier, Kelly P; Martin, Diane P; Ralston, James D; Zimmerman, Frederick J

2010-05-01

Minimum wage policies have been advanced as mechanisms to improve the economic conditions of the working poor. Both positive and negative effects of such policies on health care access have been hypothesized, but associations have yet to be thoroughly tested. To examine whether the presence of minimum wage policies in excess of the federal standard of $5.15 per hour was associated with health care access indicators among low-skilled adults of working age, a cross-sectional analysis of 2004 Behavioral Risk Factor Surveillance System data was conducted. Self-reported health insurance status and experience with cost-related barriers to needed medical care were adjusted in multi-level logistic regression models to control for potential confounding at the state, county, and individual levels. State-level wage policy was not found to be associated with insurance status or unmet medical need in the models, providing early evidence that increased minimum wage rates may neither strengthen nor weaken access to care as previously predicted.

The role of the clinical departments for understanding patient heterogeneity in one-year mortality after a diagnosis of heart failure: A multilevel analysis of individual heterogeneity for profiling provider outcomes

PubMed Central

Frølich, Anne; Merlo, Juan

2017-01-01

Purpose To evaluate the general contextual effect (GCE) of the hospital department on one-year mortality in Swedish and Danish patients with heart failure (HF) by applying a multilevel analysis of individual heterogeneity. Methods Using the Swedish patient register, we obtained data on 36,943 patients who were 45–80 years old and admitted for HF to the hospital between 2007 and 2009. From the Danish Heart Failure Database (DHFD), we obtained data on 12,001 patients with incident HF who were 18 years or older and treated at hospitals between June 2010 and June2013. For each year, we applied two-step single and multilevel logistic regression models. We evaluated the general effects of the department by quantifying the intra-class correlation coefficient (ICC) and the increment in the area under the receiver operating characteristic curve (AUC) obtained by adding the random effects of the department in a multilevel logistic regression analysis. Results One-year mortality for Danish incident HF patients was low in the three audit years (around 11.1% -13.1%) and departments performed homogeneously (ICC ≈1.5% - 3.5%). The discriminatory accuracy of a model including age and gender was rather high (AUC≈ 0.71–0.73) but the increment in AUC after adding the department random effects into these models was only about 0.011–0.022 units in the three years. One-year mortality in Swedish patients with first hospitalization for heart failure, was relatively higher for 2007–2009 (≈21.3% - 22%) and departments performed homogeneously (ICC ≈ 1.5% - 3%). The discriminatory accuracy of a model including age, gender and patient risk score was rather high (AUC≈ 0.726–0.728) but the increment in AUC after adding the department random effects was only about 0.010–0.017 units in the three years. Conclusion Using the DHFD standard benchmark for one-year mortality, Danish departments had a good, homogeneous performance. In reference to literature, Swedish departments had a homogeneous performance and the mortality rates for patients with first hospitalization for heart failure were similar to those reported since 2000. Considering this, if health authorities decide to further reduce mortality rates, a comprehensive quality strategy should focus on all Swedish hospitals. Yet, a complementary assessment for the period after the study period is required to confirm whether department performance is still homogeneous or not to determine the most appropriate action. PMID:29211785

Multilevel mixed effects parametric survival models using adaptive Gauss-Hermite quadrature with application to recurrent events and individual participant data meta-analysis.

PubMed

Crowther, Michael J; Look, Maxime P; Riley, Richard D

2014-09-28

Multilevel mixed effects survival models are used in the analysis of clustered survival data, such as repeated events, multicenter clinical trials, and individual participant data (IPD) meta-analyses, to investigate heterogeneity in baseline risk and covariate effects. In this paper, we extend parametric frailty models including the exponential, Weibull and Gompertz proportional hazards (PH) models and the log logistic, log normal, and generalized gamma accelerated failure time models to allow any number of normally distributed random effects. Furthermore, we extend the flexible parametric survival model of Royston and Parmar, modeled on the log-cumulative hazard scale using restricted cubic splines, to include random effects while also allowing for non-PH (time-dependent effects). Maximum likelihood is used to estimate the models utilizing adaptive or nonadaptive Gauss-Hermite quadrature. The methods are evaluated through simulation studies representing clinically plausible scenarios of a multicenter trial and IPD meta-analysis, showing good performance of the estimation method. The flexible parametric mixed effects model is illustrated using a dataset of patients with kidney disease and repeated times to infection and an IPD meta-analysis of prognostic factor studies in patients with breast cancer. User-friendly Stata software is provided to implement the methods. Copyright © 2014 John Wiley & Sons, Ltd.

Social Context and Dental Pain in Adults of Colombian Ethnic Minority Groups: A Multilevel Cross-Sectional Study.

PubMed

Ardila, Carlos M; Agudelo-Suárez, Andrés A

2016-01-01

To estimate the effect of social context on dental pain in adults of Colombian ethnic minority groups (CEGs). Information from 34,843 participants was used. A multilevel model was constructed that had ethnic groups (ie, CEGs and non-CEGs) at level 1 and Colombian states at level 2. Contextual variables included gross domestic product (GDP), Human Development Index (HDI), and Unmet Basic Needs Index (UBNI). Dental pain was observed in 12.3% of 6,440 CEGs. In an unadjusted logistic regression model, dental pain was associated with being a CEG (odds ratio [95% confidence interval], 1.34 [1.22-1.46]; P = .0001). This association remained significant after adjusting for possible confounding variables. An unconditional multilevel analysis showed that the variance in dental pain was statistically significant at the ethnic group level (β = 0.047 ± 0.015; P = .0009) and at the state level (β = 0.038 ± 0.019; P = .02) and that the variation between ethnic groups was higher than the variation between states (55% vs 45%, respectively). In a multivariate model, the variance in dental pain was also statistically significant at the ethnic group level (β = 0.029 ± 0.012; P = .007) and the state level (β = 0.042 ± .019; P = .01), but the variation between states was higher (40% vs 60%). The results of multilevel multivariate analyses showed that dental pain was associated with increasing age (β = 0.009 ± 0.001; P = .0001), lower education level (β = 0.302 ± 0.103; P = .0001), female sex (β = 0.031 ± 0.069; P = .003), GDP (β = 5.136 ± 2.009; P = .002) and HDI (β = 6.862 ± 5.550; P = .004); however, UBNI was not associated with dental pain. The variance in dental pain was higher between states than between ethnic groups in the multivariate multilevel model. Dental pain in CEGs was associated with contextual and individual factors. Considering contextual factors, GDP and HDI may play a major role in dental pain prevalence.

[Prevalence of common mental disorders and the relationship to the social context: multilevel analysis of the São Paulo Ageing & Health Study (SPAH)].

PubMed

Coutinho, Letícia Maria Silva; Matijasevich, Alícia; Scazufca, Márcia; Menezes, Paulo Rossi

2014-09-01

Social context can play a important role in the etiology and prevalence of mental disorders. The aim of the present study was to investigate risk factors for common mental disorders (CMD), considering different contextual levels: individual, household, and census tract. The study used a population-based sample of 2,366 respondents from the São Paulo Ageing & Health Study. Presence of CMD was identified by the SRQ-20. Sex, age, education, and occupation were individual characteristics associated with prevalence of CMD. Multilevel logistic regression models showed that part of the variance in prevalence of CMD was associated with the household level, showing associations between crowding, family income, and CMD, even after controlling for individual characteristics. These results suggest that characteristics of the environment where people live can influence their mental health status.

Transgenerational effect of neighborhood poverty on low birth weight among African Americans in Cook County, Illinois.

PubMed

Collins, James W; David, Richard J; Rankin, Kristin M; Desireddi, Jennifer R

2009-03-15

In perinatal epidemiology, transgenerational risk factors are defined as conditions experienced by one generation that affect the pregnancy outcomes of the next generation. The authors investigated the transgenerational effect of neighborhood poverty on infant birth weight among African Americans. Stratified and multilevel logistic regression analyses were performed on an Illinois transgenerational data set with appended US Census income information. Singleton African-American infants (n = 40,648) born in 1989-1991 were considered index births. The mothers of index infants had been born in 1956-1976. The maternal grandmothers of index infants were identified. Rates of infant low birth weight (<2,500 g) rose as maternal grandmother's residential environment during her pregnancy deteriorated, independently of mother's residential environment during her pregnancy. In a multilevel logistic regression model that accounted for clustering by maternal grandmother's residential environment, the adjusted odds ratio (controlling for mother's age, education, prenatal care, cigarette smoking status, and residential environment) for infant low birth weight for maternal grandmother's residence in a poor neighborhood (compared with an affluent neighborhood) equaled 1.3 (95% confidence interval: 1.1, 1.4). This study suggests that maternal grandmother's exposure to neighborhood poverty during her pregnancy is a risk factor for infant low birth weight among African Americans.

Ideal cardiovascular health and inflammation in European adolescents: The HELENA study.

PubMed

González-Gil, E M; Santabárbara, J; Ruiz, J R; Bel-Serrat, S; Huybrechts, I; Pedrero-Chamizo, R; de la O, A; Gottrand, F; Kafatos, A; Widhalm, K; Manios, Y; Molnar, D; De Henauw, S; Plada, M; Ferrari, M; Palacios Le Blé, G; Siani, A; González-Gross, M; Gómez-Martínez, S; Marcos, A; Moreno Aznar, L A

2017-05-01

Inflammation plays a key role in atherosclerosis and this process seems to appear in childhood. The ideal cardiovascular health index (ICHI) has been inversely related to atherosclerotic plaque in adults. However, evidence regarding inflammation and ICHI in adolescents is scarce. The aim is to assess the association between ICHI and inflammation in European adolescents. As many as 543 adolescents (251 boys and 292 girls) from the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) study, a cross-sectional multi-center study including 9 European countries, were measured. C-reactive protein (CRP), complement factors C3 and C4, leptin and white blood cell counts were used to compute an inflammatory score. Multilevel linear models and multilevel logistic regression were used to assess the association between ICHI and inflammation controlling by covariates. Higher ICHI was associated with a lower inflammatory score, as well as with several individual components, both in boys and girls (p < 0.01). In addition, adolescents with at least 4 ideal components of the ICHI had significantly lower inflammatory score and lower levels of the study biomarkers, except CRP. Finally, the multilevel logistic regression showed that for every unit increase in the ICHI, the probability of having an inflammatory profile decreased by 28.1% in girls. Results from this study suggest that a better ICHI is associated with a lower inflammatory profile already in adolescence. Improving these health behaviors, and health factors included in the ICHI, could play an important role in CVD prevention. Copyright © 2016 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

Immigrant maternal depression and social networks. A multilevel Bayesian spatial logistic regression in South Western Sydney, Australia.

PubMed

Eastwood, John G; Jalaludin, Bin B; Kemp, Lynn A; Phung, Hai N; Barnett, Bryanne E W

2013-09-01

The purpose is to explore the multilevel spatial distribution of depressive symptoms among migrant mothers in South Western Sydney and to identify any group level associations that could inform subsequent theory building and local public health interventions. Migrant mothers (n=7256) delivering in 2002 and 2003 were assessed at 2-3 weeks after delivery for risk factors for depressive symptoms. The binary outcome variables were Edinburgh Postnatal Depression Scale scores (EPDS) of >9 and >12. Individual level variables included were: financial income, self-reported maternal health, social support network, emotional support, practical support, baby trouble sleeping, baby demanding and baby not content. The group level variable reported here is aggregated social support networks. We used Bayesian hierarchical multilevel spatial modelling with conditional autoregression. Migrant mothers were at higher risk of having depressive symptoms if they lived in a community with predominantly Australian-born mothers and strong social capital as measured by aggregated social networks. These findings suggest that migrant mothers are socially isolated and current home visiting services should be strengthened for migrant mothers living in communities where they may have poor social networks. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

[Two-level logistic modeling analysis on the factors that influence birth in hospitals in poor rural areas of Sichuan province].

PubMed

Yu, Chuan; Li, Xiao-song

2008-11-01

To identify the determinants of birth in hospitals in the poor rural areas. A questionnaire survey in eight poor counties in Sichuan province was conducted. Multilevel logistic regression analysis was performed to identify the factors that influenced birth in hospitals. Hospitals delivered 61.4% of babies in the selected counties. Education, eligibility to poverty relief, numbers of pre-natal examinations and abnormalities found in pre-natal examinations had a significant impact on birth in hospitals. Education of women and medical relief in the poor rural areas need to be strengthened to increase the proportion of babies delivered in hospitals in the poor rural areas. Systematic management of pregnant women and increased pre-natal examinations could also contribute to hospital delivery of babies.

Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection by Streptococcus pneumoniae Identified in Multi-Level Mathematical Modeling.

PubMed

Santos, Guido; Lai, Xin; Eberhardt, Martin; Vera, Julio

2018-01-01

Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By "multi-level" we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization.

The importance of proximal fusion level selection for outcomes of multi-level lumbar posterolateral fusion.

PubMed

Nam, Woo Dong; Cho, Jae Hwan

2015-03-01

There are few studies about risk factors for poor outcomes from multi-level lumbar posterolateral fusion limited to three or four level lumbar posterolateral fusions. The purpose of this study was to analyze the outcomes of multi-level lumbar posterolateral fusion and to search for possible risk factors for poor surgical outcomes. We retrospectively analyzed 37 consecutive patients who underwent multi-level lumbar or lumbosacral posterolateral fusion with posterior instrumentation. The outcomes were deemed either 'good' or 'bad' based on clinical and radiological results. Many demographic and radiological factors were analyzed to examine potential risk factors for poor outcomes. Student t-test, Fisher exact test, and the chi-square test were used based on the nature of the variables. Multiple logistic regression analysis was used to exclude confounding factors. Twenty cases showed a good outcome (group A, 54.1%) and 17 cases showed a bad outcome (group B, 45.9%). The overall fusion rate was 70.3%. The revision procedures (group A: 1/20, 5.0%; group B: 4/17, 23.5%), proximal fusion to L2 (group A: 5/20, 25.0%; group B: 10/17, 58.8%), and severity of stenosis (group A: 12/19, 63.3%; group B: 3/11, 27.3%) were adopted as possible related factors to the outcome in univariate analysis. Multiple logistic regression analysis revealed that only the proximal fusion level (superior instrumented vertebra, SIV) was a significant risk factor. The cases in which SIV was L2 showed inferior outcomes than those in which SIV was L3. The odds ratio was 6.562 (95% confidence interval, 1.259 to 34.203). The overall outcome of multi-level lumbar or lumbosacral posterolateral fusion was not as high as we had hoped it would be. Whether the SIV was L2 or L3 was the only significant risk factor identified for poor outcomes in multi-level lumbar or lumbosacral posterolateral fusion in the current study. Thus, the authors recommend that proximal fusion levels be carefully determined when multi-level lumbar fusions are considered.

The Importance of Proximal Fusion Level Selection for Outcomes of Multi-Level Lumbar Posterolateral Fusion

PubMed Central

Nam, Woo Dong

2015-01-01

Background There are few studies about risk factors for poor outcomes from multi-level lumbar posterolateral fusion limited to three or four level lumbar posterolateral fusions. The purpose of this study was to analyze the outcomes of multi-level lumbar posterolateral fusion and to search for possible risk factors for poor surgical outcomes. Methods We retrospectively analyzed 37 consecutive patients who underwent multi-level lumbar or lumbosacral posterolateral fusion with posterior instrumentation. The outcomes were deemed either 'good' or 'bad' based on clinical and radiological results. Many demographic and radiological factors were analyzed to examine potential risk factors for poor outcomes. Student t-test, Fisher exact test, and the chi-square test were used based on the nature of the variables. Multiple logistic regression analysis was used to exclude confounding factors. Results Twenty cases showed a good outcome (group A, 54.1%) and 17 cases showed a bad outcome (group B, 45.9%). The overall fusion rate was 70.3%. The revision procedures (group A: 1/20, 5.0%; group B: 4/17, 23.5%), proximal fusion to L2 (group A: 5/20, 25.0%; group B: 10/17, 58.8%), and severity of stenosis (group A: 12/19, 63.3%; group B: 3/11, 27.3%) were adopted as possible related factors to the outcome in univariate analysis. Multiple logistic regression analysis revealed that only the proximal fusion level (superior instrumented vertebra, SIV) was a significant risk factor. The cases in which SIV was L2 showed inferior outcomes than those in which SIV was L3. The odds ratio was 6.562 (95% confidence interval, 1.259 to 34.203). Conclusions The overall outcome of multi-level lumbar or lumbosacral posterolateral fusion was not as high as we had hoped it would be. Whether the SIV was L2 or L3 was the only significant risk factor identified for poor outcomes in multi-level lumbar or lumbosacral posterolateral fusion in the current study. Thus, the authors recommend that proximal fusion levels be carefully determined when multi-level lumbar fusions are considered. PMID:25729522

Social capital and sense of insecurity in the neighbourhood: a population-based multilevel analysis in Malmö, Sweden.

PubMed

Lindström, Martin; Merlo, Juan; Ostergren, Per Olof

2003-03-01

The aim of this study was to investigate the influence of social capital on self-reported sense of insecurity in the neighbourhood. The public health survey in Malmö, Sweden in 1994 was a cross-sectional study. A total of 5600 individuals aged 20-80 years were asked to answer a postal questionnaire. The participation rate was 71%. A multilevel logistic regression model, with individuals at the first level and neighbourhoods at the second, was performed. We analysed the effect (intra-area correlation, cross-level modification and odds ratios) of individual (social participation) and neighbourhood social capital (electoral participation in the 1994 municipal election) on sense of insecurity after adjustment for compositional factors. Neighbourhood factors accounted for 7.2% of the total variance in individual insecurity. This effect was marginally reduced when the individual factors were included in the model. In contrast, it was reduced by 70% by the introduction of the contextual variable. This study suggests that social capital, measured as electoral participation, may partly explain the individual's sense of insecurity in the neighbourhood.

Social capital and neo-materialist contextual determinants of sense of insecurity in the neighbourhood: a multilevel analysis in Southern Sweden.

PubMed

Lindström, Martin; Lindström, Christine; Moghaddassi, Mahnaz; Merlo, Juan

2006-12-01

The aim of this study was to investigate the influence of contextual (social capital and neo-materialist) and individual factors on sense of insecurity in the neighbourhood. The 2000 public health survey in Scania is a cross-sectional study. A total of 13,715 persons answered a postal questionnaire, which is 59% of the random sample. A multilevel logistic regression model, with individuals at the first level and municipalities at the second, was performed. The effect (median odds ratios, intra-class correlation, cross-level modification and odds ratios) of individual and municipality/city quarter (social capital and police district) factors on sense of insecurity was analysed. The crude variance between municipalities/city quarters was not affected by individual factors. The introduction of administrative police district in the model reduced the municipality variance, although some of the significant variance between municipalities remained. The introduction of social capital did not affect the municipality variance. This study suggests that the neo-materialist factor administrative police district may partly explain the individual's sense of insecurity in the neighbourhood.

Using Cluster Bootstrapping to Analyze Nested Data With a Few Clusters.

PubMed

Huang, Francis L

2018-04-01

Cluster randomized trials involving participants nested within intact treatment and control groups are commonly performed in various educational, psychological, and biomedical studies. However, recruiting and retaining intact groups present various practical, financial, and logistical challenges to evaluators and often, cluster randomized trials are performed with a low number of clusters (~20 groups). Although multilevel models are often used to analyze nested data, researchers may be concerned of potentially biased results due to having only a few groups under study. Cluster bootstrapping has been suggested as an alternative procedure when analyzing clustered data though it has seen very little use in educational and psychological studies. Using a Monte Carlo simulation that varied the number of clusters, average cluster size, and intraclass correlations, we compared standard errors using cluster bootstrapping with those derived using ordinary least squares regression and multilevel models. Results indicate that cluster bootstrapping, though more computationally demanding, can be used as an alternative procedure for the analysis of clustered data when treatment effects at the group level are of primary interest. Supplementary material showing how to perform cluster bootstrapped regressions using R is also provided.

Multilevel Model Prediction

ERIC Educational Resources Information Center

Frees, Edward W.; Kim, Jee-Seon

2006-01-01

Multilevel models are proven tools in social research for modeling complex, hierarchical systems. In multilevel modeling, statistical inference is based largely on quantification of random variables. This paper distinguishes among three types of random variables in multilevel modeling--model disturbances, random coefficients, and future response…

Individual self-reported health, social participation and neighbourhood: a multilevel analysis in Malmö, Sweden.

PubMed

Lindström, Martin; Moghaddassi, Mahnaz; Merlo, Juan

2004-07-01

The influence of neighbourhood and individual factors on self-reported health was investigated. The public health survey in Malmö 1994 is a cross-sectional study. A total of 3,602 individuals aged 20-80 living in 75 neighbourhoods answered a postal questionnaire. The participation rate was 71%. A multilevel logistic regression model, with individuals at the first level and neighbourhoods at the second, was performed. We analysed the effect (intra-area correlation, cross-level modification and odds ratios) of neighbourhood on self-reported health after adjustment for individual factors. The neighbourhoods accounted for 2.8% of the crude total variance in self-reported health status. This effect was significantly reduced when individual factors such as country of origin, education and social participation were included in the model. In fact, no significant variance in self-reported health remained after the introduction of the individual factors in the model. In Malmö, the neighbourhood variance in self-reported health is mainly affected by individual factors, especially country of origin, socioeconomic status measured as level of education and individual social participation. Copyright 2004 The Institute for Cancer Prevention and Elsevier Inc.

Geographic and socioeconomic variations in adolescent toothbrushing: A multilevel cross-sectional study of 15 year olds in Scotland

PubMed Central

Levin, KA; Nicholls, N; Macdonald, S; Dundas, R; Douglas, GVA

2015-01-01

Background This study examined urban-rural and socioeconomic differences in adolescent toothbrushing. Methods The data were modelled using logistic multilevel modelling and the Markov Chain Monte Carlo (MCMC) method of estimation. Twice-a-day toothbrushing was regressed upon age, family affluence, family structure, school type, area-level deprivation and rurality, for boys and girls separately. Results Boys’ toothbrushing was associated with area- level deprivation but not rurality. Variance at the school level remained significant in the final model for boys’ toothbrushing. The association between toothbrushing and area-level deprivation was particularly strong for girls, after adjustment for individuals’ family affluence and type of school attended. Rurality too was independently significant with lower odds of brushing teeth in accessible rural areas. Conclusions The findings are at odds with the results of a previous study which showed, lower caries prevalence among children living in rural Scotland. A further study concluded that adolescents have a better diet in rural Scotland. In total, these studies highlight the need for an examination into the relative importance of diet and oral health on caries, as increases are observed in population obesity and consumption of sugars. PMID:24917568

Multi-level analysis in information systems research: the case of enterprise resource planning system usage in China

NASA Astrophysics Data System (ADS)

Sun, Yuan; Bhattacherjee, Anol

2011-11-01

Information technology (IT) usage within organisations is a multi-level phenomenon that is influenced by individual-level and organisational-level variables. Yet, current theories, such as the unified theory of acceptance and use of technology, describe IT usage as solely an individual-level phenomenon. This article postulates a model of organisational IT usage that integrates salient organisational-level variables such as user training, top management support and technical support within an individual-level model to postulate a multi-level model of IT usage. The multi-level model was then empirically validated using multi-level data collected from 128 end users and 26 managers in 26 firms in China regarding their use of enterprise resource planning systems and analysed using the multi-level structural equation modelling (MSEM) technique. We demonstrate the utility of MSEM analysis of multi-level data relative to the more common structural equation modelling analysis of single-level data and show how single-level data can be aggregated to approximate multi-level analysis when multi-level data collection is not possible. We hope that this article will motivate future scholars to employ multi-level data and multi-level analysis for understanding organisational phenomena that are truly multi-level in nature.

Formulation and Application of the Generalized Multilevel Facets Model

ERIC Educational Resources Information Center

Wang, Wen-Chung; Liu, Chih-Yu

2007-01-01

In this study, the authors develop a generalized multilevel facets model, which is not only a multilevel and two-parameter generalization of the facets model, but also a multilevel and facet generalization of the generalized partial credit model. Because the new model is formulated within a framework of nonlinear mixed models, no efforts are…

Does Social Context Matter? Income Inequality, Racialized Identity, and Health Among Canada's Aboriginal Peoples Using a Multilevel Approach.

PubMed

Spence, Nicholas D

2016-03-01

Debates surrounding the importance of social context versus individual level processes have a long history in public health. Aboriginal peoples in Canada are very diverse, and the reserve communities in which they reside are complex mixes of various cultural and socioeconomic circumstances. The social forces of these communities are believed to affect health, in addition to individual level determinants, but no large scale work has ever probed their relative effects. One aspect of social context, relative deprivation, as indicated by income inequality, has greatly influenced the social determinants of health landscape. An investigation of relative deprivation in Canada's Aboriginal population has never been conducted. This paper proposes a new model of Aboriginal health, using a multidisciplinary theoretical approach that is multilevel. This study explored the self-rated health of respondents using two levels of determinants, contextual and individual. Data were from the 2001 Aboriginal Peoples Survey. There were 18,890 Registered First Nations (subgroup of Aboriginal peoples) on reserve nested within 134 communities. The model was assessed using a hierarchical generalized linear model. There was no significant variation at the contextual level. Subsequently, a sequential logistic regression analysis was run. With the sole exception culture, demographics, lifestyle factors, formal health services, and social support were significant in explaining self-rated health. The non-significant effect of social context, and by extension relative deprivation, as indicated by income inequality, is noteworthy, and the primary role of individual level processes, including the material conditions, social support, and lifestyle behaviors, on health outcomes is illustrated. It is proposed that social structure is best conceptualized as a dynamic determinant of health inequality and more multilevel theoretical models of Aboriginal health should be developed and tested.

Political regimes, political ideology, and self-rated health in Europe: a multilevel analysis.

PubMed

Huijts, Tim; Perkins, Jessica M; Subramanian, S V

2010-07-22

Studies on political ideology and health have found associations between individual ideology and health as well as between ecological measures of political ideology and health. Individual ideology and aggregate measures such as political regimes, however, were never examined simultaneously. Using adjusted logistic multilevel models to analyze data on individuals from 29 European countries and Israel, we found that individual ideology and political regime are independently associated with self-rated health. Individuals with rightwing ideologies report better health than leftwing individuals. Respondents from Eastern Europe and former Soviet republics report poorer health than individuals from social democratic, liberal, Christian conservative, and former Mediterranean dictatorship countries. In contrast to individual ideology and political regimes, country level aggregations of individual ideology are not related to reporting poor health. This study shows that although both individual political ideology and contextual political regime are independently associated with individuals' self-rated health, individual political ideology appears to be more strongly associated with self-rated health than political regime.

Political Regimes, Political Ideology, and Self-Rated Health in Europe: A Multilevel Analysis

PubMed Central

Huijts, Tim; Perkins, Jessica M.; Subramanian, S. V.

2010-01-01

Background Studies on political ideology and health have found associations between individual ideology and health as well as between ecological measures of political ideology and health. Individual ideology and aggregate measures such as political regimes, however, were never examined simultaneously. Methodology/Principal Findings Using adjusted logistic multilevel models to analyze data on individuals from 29 European countries and Israel, we found that individual ideology and political regime are independently associated with self-rated health. Individuals with rightwing ideologies report better health than leftwing individuals. Respondents from Eastern Europe and former Soviet republics report poorer health than individuals from social democratic, liberal, Christian conservative, and former Mediterranean dictatorship countries. In contrast to individual ideology and political regimes, country level aggregations of individual ideology are not related to reporting poor health. Conclusions/Significance This study shows that although both individual political ideology and contextual political regime are independently associated with individuals' self-rated health, individual political ideology appears to be more strongly associated with self-rated health than political regime. PMID:20661433

Does workplace social capital buffer the effects of job stress? A cross-sectional, multilevel analysis of cigarette smoking among U.S. manufacturing workers

PubMed Central

Sapp, Amy L.; Kawachi, Ichiro; Sorensen, Glorian; LaMontagne, Anthony D.; Subramanian, S.V.

2010-01-01

Objective To investigate whether workplace social capital buffers the association between job stress and smoking status. Methods As part of the Harvard Cancer Prevention Project’s Healthy Directions-Small Business Study, interviewer-administered questionnaires were completed by 1740 workers and 288 managers in 26 manufacturing firms (84% and 85% response). Social capital was assessed by multiple items measured at the individual-level among workers, and contextual-level among managers. Job stress was operationalized by the demand-control model. Multilevel logistic regression was used to estimate associations between job stressors and smoking, and test for effect modification by social capital measures. Results Workplace social capital (both summary measures) buffered associations between high job demands and smoking. One compositional item—worker trust in managers—buffered associations between job strain and smoking. Conclusion Workplace social capital may modify the effects of psychosocial working conditions on health behaviors. PMID:20595910

Health of the Elderly Migration Population in China: Benefit from Individual and Local Socioeconomic Status?

PubMed Central

Wang, Qing

2017-01-01

The study aims to estimate the relationship between the individual/local socioeconomic status and the health of internal elderly migrants in China. A multilevel logistic model was used to estimate this association. The estimations were undertaken for 11,111 migrants aged over 60 years, using nationally representative data: the 2015 Migrant Dynamics Monitoring Survey (MDMS), which was carried out in China. Odds ratios with 95% confidence intervals were reported. Both the household income per capita and the area-level average wage were positively associated with migrants’ self-reported health; however, public service supply was not significantly related to their health. In addition, given the household income, migrants living in communities with a higher average wage were more likely to report poor health. Migrants’ health benefited from individual socioeconomic status, but not from the local socioeconomic status, which the migrants cannot enjoy. This study highlights the importance of multilevel and non-discriminatory policies between migrants and local residents. PMID:28368314

Health of the Elderly Migration Population in China: Benefit from Individual and Local Socioeconomic Status?

PubMed

Wang, Qing

2017-04-01

The study aims to estimate the relationship between the individual/local socioeconomic status and the health of internal elderly migrants in China. A multilevel logistic model was used to estimate this association. The estimations were undertaken for 11,111 migrants aged over 60 years, using nationally representative data: the 2015 Migrant Dynamics Monitoring Survey (MDMS), which was carried out in China. Odds ratios with 95% confidence intervals were reported. Both the household income per capita and the area-level average wage were positively associated with migrants' self-reported health; however, public service supply was not significantly related to their health. In addition, given the household income, migrants living in communities with a higher average wage were more likely to report poor health. Migrants' health benefited from individual socioeconomic status, but not from the local socioeconomic status, which the migrants cannot enjoy. This study highlights the importance of multilevel and non-discriminatory policies between migrants and local residents.

Social capital and administrative contextual determinants of lack of access to a regular doctor: a multilevel analysis in southern Sweden.

PubMed

Lindström, Martin; Axén, Elin; Lindström, Christine; Beckman, Anders; Moghaddassi, Mahnaz; Merlo, Juan

2006-12-01

The aim of this study was to investigate the influence of contextual (social capital and administrative/neo-materialist) and individual factors on lack of access to a regular doctor. The 2000 public health survey in Scania is a cross-sectional study. A total of 13,715 persons answered a postal questionnaire, which is 59% of the random sample. A multilevel logistic regression model, with individuals at the first level and municipalities at the second, was performed. The effect (intra-class correlations, cross-level modification and odds ratios) of individual and municipality (social capital and health care district) factors on lack of access to a regular doctor was analysed using simulation method. The Deviance Information Criterion (DIC) was used as information criterion for the models. The second level municipality variance in lack of access to a regular doctor is substantial even in the final models with all individual and contextual variables included. The model that results in the largest reduction in DIC is the model including age, sex and individual social participation (which is a network aspect of social capital), but the models which include administrative and social capital second level factors also reduced the DIC values. This study suggests that both administrative health care district and social capital may partly explain the individual's self reported lack of access to a regular doctor.

Availability and quality of coronary heart disease family history in primary care medical records: implications for cardiovascular risk assessment.

PubMed

Dhiman, Paula; Kai, Joe; Horsfall, Laura; Walters, Kate; Qureshi, Nadeem

2014-01-01

The potential to use data on family history of premature disease to assess disease risk is increasingly recognised, particularly in scoring risk for coronary heart disease (CHD). However the quality of family health information in primary care records is unclear. To assess the availability and quality of family history of CHD documented in electronic primary care records. Cross-sectional study. 537 UK family practices contributing to The Health Improvement Network database. Data were obtained from patients aged 20 years or more, registered with their current practice between 1(st) January 1998 and 31(st) December 2008, for at least one year. The availability and quality of recorded CHD family history was assessed using multilevel logistic and ordinal logistic regression respectively. In a cross-section of 1,504,535 patients, 19% had a positive or negative family history of CHD recorded. Multilevel logistic regression showed patients aged 50-59 had higher odds of having their family history recorded compared to those aged 20-29 (OR:1.23 (1.21 to 1.25)), however most deprived patients had lower odds compared to those least deprived (OR: 0.86 (0.85 to 0.88)). Of the 140,058 patients with a positive family history recorded (9% of total cohort), age of onset was available in 45%; with data specifying both age of onset and relative affected available in only 11% of records. Multilevel ordinal logistic regression confirmed no statistical association between the quality of family history recording and age, gender, deprivation and year of registration. Family history of CHD is documented in a small proportion of primary care records; and where positive family history is documented the details are insufficient to assess familial risk or populate cardiovascular risk assessment tools. Data capture needs to be improved particularly for more disadvantaged patients who may be most likely to benefit from CHD risk assessment.

Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data

PubMed Central

Sharafi, Zahra

2017-01-01

Background The purpose of this study was to evaluate the effectiveness of two methods of detecting differential item functioning (DIF) in the presence of multilevel data and polytomously scored items. The assessment of DIF with multilevel data (e.g., patients nested within hospitals, hospitals nested within districts) from large-scale assessment programs has received considerable attention but very few studies evaluated the effect of hierarchical structure of data on DIF detection for polytomously scored items. Methods The ordinal logistic regression (OLR) and hierarchical ordinal logistic regression (HOLR) were utilized to assess DIF in simulated and real multilevel polytomous data. Six factors (DIF magnitude, grouping variable, intraclass correlation coefficient, number of clusters, number of participants per cluster, and item discrimination parameter) with a fully crossed design were considered in the simulation study. Furthermore, data of Pediatric Quality of Life Inventory™ (PedsQL™) 4.0 collected from 576 healthy school children were analyzed. Results Overall, results indicate that both methods performed equivalently in terms of controlling Type I error and detection power rates. Conclusions The current study showed negligible difference between OLR and HOLR in detecting DIF with polytomously scored items in a hierarchical structure. Implications and considerations while analyzing real data were also discussed. PMID:29312463

Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data.

PubMed

Sharafi, Zahra; Mousavi, Amin; Ayatollahi, Seyyed Mohammad Taghi; Jafari, Peyman

2017-01-01

The purpose of this study was to evaluate the effectiveness of two methods of detecting differential item functioning (DIF) in the presence of multilevel data and polytomously scored items. The assessment of DIF with multilevel data (e.g., patients nested within hospitals, hospitals nested within districts) from large-scale assessment programs has received considerable attention but very few studies evaluated the effect of hierarchical structure of data on DIF detection for polytomously scored items. The ordinal logistic regression (OLR) and hierarchical ordinal logistic regression (HOLR) were utilized to assess DIF in simulated and real multilevel polytomous data. Six factors (DIF magnitude, grouping variable, intraclass correlation coefficient, number of clusters, number of participants per cluster, and item discrimination parameter) with a fully crossed design were considered in the simulation study. Furthermore, data of Pediatric Quality of Life Inventory™ (PedsQL™) 4.0 collected from 576 healthy school children were analyzed. Overall, results indicate that both methods performed equivalently in terms of controlling Type I error and detection power rates. The current study showed negligible difference between OLR and HOLR in detecting DIF with polytomously scored items in a hierarchical structure. Implications and considerations while analyzing real data were also discussed.

On the Multilevel Nature of Meta-Analysis: A Tutorial, Comparison of Software Programs, and Discussion of Analytic Choices.

PubMed

Pastor, Dena A; Lazowski, Rory A

2018-01-01

The term "multilevel meta-analysis" is encountered not only in applied research studies, but in multilevel resources comparing traditional meta-analysis to multilevel meta-analysis. In this tutorial, we argue that the term "multilevel meta-analysis" is redundant since all meta-analysis can be formulated as a special kind of multilevel model. To clarify the multilevel nature of meta-analysis the four standard meta-analytic models are presented using multilevel equations and fit to an example data set using four software programs: two specific to meta-analysis (metafor in R and SPSS macros) and two specific to multilevel modeling (PROC MIXED in SAS and HLM). The same parameter estimates are obtained across programs underscoring that all meta-analyses are multilevel in nature. Despite the equivalent results, not all software programs are alike and differences are noted in the output provided and estimators available. This tutorial also recasts distinctions made in the literature between traditional and multilevel meta-analysis as differences between meta-analytic choices, not between meta-analytic models, and provides guidance to inform choices in estimators, significance tests, moderator analyses, and modeling sequence. The extent to which the software programs allow flexibility with respect to these decisions is noted, with metafor emerging as the most favorable program reviewed.

Healthcare access and mammography screening in Michigan: a multilevel cross-sectional study

PubMed Central

2012-01-01

Background Breast cancer screening rates have increased over time in the United States. However actual screening rates appear to be lower among black women compared with white women. Purpose To assess determinants of breast cancer screening among women in Michigan USA, focusing on individual and neighborhood socio-economic status and healthcare access. Methods Data from 1163 women ages 50-74 years who participated in the 2008 Michigan Special Cancer Behavioral Risk Factor Survey were analyzed. County-level SES and healthcare access were obtained from the Area Resource File. Multilevel logistic regression models were fit using SAS Proc Glimmix to account for clustering of individual observations by county. Separate models were fit for each of the two outcomes of interest; mammography screening and clinical breast examination. For each outcome, two sequential models were fit; a model including individual level covariates and a model including county level covariates. Results After adjusting for misclassification bias, overall cancer screening rates were lower than reported by survey respondents; black women had lower mammography screening rates but higher clinical breast examination rates than white women. However, after adjusting for other individual level variables, race was not a significant predictor of screening. Having health insurance or a usual healthcare provider were the most important predictors of cancer screening. Discussion Access to healthcare is important to ensuring appropriate cancer screening among women in Michigan. PMID:22436125

Prediction models for solitary pulmonary nodules based on curvelet textural features and clinical parameters.

PubMed

Wang, Jing-Jing; Wu, Hai-Feng; Sun, Tao; Li, Xia; Wang, Wei; Tao, Li-Xin; Huo, Da; Lv, Ping-Xin; He, Wen; Guo, Xiu-Hua

2013-01-01

Lung cancer, one of the leading causes of cancer-related deaths, usually appears as solitary pulmonary nodules (SPNs) which are hard to diagnose using the naked eye. In this paper, curvelet-based textural features and clinical parameters are used with three prediction models [a multilevel model, a least absolute shrinkage and selection operator (LASSO) regression method, and a support vector machine (SVM)] to improve the diagnosis of benign and malignant SPNs. Dimensionality reduction of the original curvelet-based textural features was achieved using principal component analysis. In addition, non-conditional logistical regression was used to find clinical predictors among demographic parameters and morphological features. The results showed that, combined with 11 clinical predictors, the accuracy rates using 12 principal components were higher than those using the original curvelet-based textural features. To evaluate the models, 10-fold cross validation and back substitution were applied. The results obtained, respectively, were 0.8549 and 0.9221 for the LASSO method, 0.9443 and 0.9831 for SVM, and 0.8722 and 0.9722 for the multilevel model. All in all, it was found that using curvelet-based textural features after dimensionality reduction and using clinical predictors, the highest accuracy rate was achieved with SVM. The method may be used as an auxiliary tool to differentiate between benign and malignant SPNs in CT images.

Social capital and leisure time physical activity: a population based multilevel analysis in Malmö, Sweden

PubMed Central

Lindstrom, M; Moghaddassi, M; Merlo, J

2003-01-01

Objective: To investigate the influence of social capital and individual factors on the level of leisure time physical inactivity in the neighbourhoods. Methods: The public health survey in Malmö 1994 is a cross sectional study. A total of 5600 people aged 20–80 years were invited to answer a postal questionnaire. The participation rate was 71%. A multilevel logistic regression model, with individuals at the first level and neighbourhoods at the second, was performed. The effect (intra-area correlation, cross level modification, and odds ratios) was analysed of individual and neighbourhood (the 1993 migration out of an area as a proxy for social capital) factors on leisure time physical inactivity after adjustment for individual factors. Results: Neighbourhood factors accounted for 5.0% of the crude total variance in physical inactivity. This effect was significantly reduced when the individual factors, especially country of origin, education, and social participation, were included in the model. In contrast, it was not reduced by the introduction of the contextual social capital variable. Conclusion: This study suggests that in the neighbourhoods of Malmö leisure time physical inactivity is mainly affected by individual factors. PMID:12490644

School Collective Efficacy and Bullying Behaviour: A Multilevel Study.

PubMed

Olsson, Gabriella; Låftman, Sara Brolin; Modin, Bitte

2017-12-20

As with other forms of violent behaviour, bullying is the result of multiple influences acting on different societal levels. Yet the majority of studies on bullying focus primarily on the characteristics of individual bullies and bullied. Fewer studies have explored how the characteristics of central contexts in young people's lives are related to bullying behaviour over and above the influence of individual-level characteristics. This study explores how teacher-rated school collective efficacy is related to student-reported bullying behaviour (traditional and cyberbullying victimization and perpetration). A central focus is to explore if school collective efficacy is related similarly to both traditional bullying and cyberbullying. Analyses are based on combined information from two independent data collections conducted in 2016 among 11th grade students ( n = 6067) and teachers ( n = 1251) in 58 upper secondary schools in Stockholm. The statistical method used is multilevel modelling, estimating two-level binary logistic regression models. The results demonstrate statistically significant between-school differences in all outcomes, except traditional bullying perpetration. Strong school collective efficacy is related to less traditional bullying perpetration and less cyberbullying victimization and perpetration, indicating that collective norm regulation and school social cohesion may contribute to reducing the occurrence of bullying.

School Collective Efficacy and Bullying Behaviour: A Multilevel Study

PubMed Central

Olsson, Gabriella; Låftman, Sara Brolin; Modin, Bitte

2017-01-01

As with other forms of violent behaviour, bullying is the result of multiple influences acting on different societal levels. Yet the majority of studies on bullying focus primarily on the characteristics of individual bullies and bullied. Fewer studies have explored how the characteristics of central contexts in young people’s lives are related to bullying behaviour over and above the influence of individual-level characteristics. This study explores how teacher-rated school collective efficacy is related to student-reported bullying behaviour (traditional and cyberbullying victimization and perpetration). A central focus is to explore if school collective efficacy is related similarly to both traditional bullying and cyberbullying. Analyses are based on combined information from two independent data collections conducted in 2016 among 11th grade students (n = 6067) and teachers (n = 1251) in 58 upper secondary schools in Stockholm. The statistical method used is multilevel modelling, estimating two-level binary logistic regression models. The results demonstrate statistically significant between-school differences in all outcomes, except traditional bullying perpetration. Strong school collective efficacy is related to less traditional bullying perpetration and less cyberbullying victimization and perpetration, indicating that collective norm regulation and school social cohesion may contribute to reducing the occurrence of bullying. PMID:29261114

Income inequality and high blood pressure in Colombia: a multilevel analysis.

PubMed

Lucumi, Diego I; Schulz, Amy J; Roux, Ana V Diez; Grogan-Kaylor, Andrew

2017-11-21

The objective of this research was to examine the association between income inequality and high blood pressure in Colombia. Using a nationally representative Colombian sample of adults, and data from departments and municipalities, we fit sex-stratified linear and logistic multilevel models with blood pressure as a continuous and binary variable, respectively. In adjusted models, women living in departments with the highest quintile of income inequality in 1997 had higher systolic blood pressure than their counterparts living in the lowest quintile of income inequality (mean difference 4.42mmHg; 95%CI: 1.46, 7.39). Women living in departments that were at the fourth and fifth quintile of income inequality in 1994 were more likely to have hypertension than those living in departments at the first quintile in the same year (OR: 1.56 and 1.48, respectively). For men, no associations of income inequality with either systolic blood pressure or hypertension were observed. Our findings are consistent with the hypothesis that income inequality is associated with increased risk of high blood pressure for women. Future studies to analyze pathways linking income inequality to high blood pressure in Colombia are needed.

Examining the relationships between life satisfaction and alcohol, tobacco and marijuana use among school-aged children.

PubMed

Lew, D; Xian, H; Qian, Z; Vaughn, M G

2018-05-03

There are many known risk factors associated with youth substance use. Nonetheless, the impact of life satisfaction (LS) on the use of alcohol, tobacco and marijuana by adolescents still remains largely unknown. The present analysis utilized data from the Health Behavior in School-Aged Children 2009-10 US study. Multilevel logistic regression models were used to assess the relationship between LS and individual substance use. Multilevel multinomial regression models examined the relationship with total number of substances used. After controlling for numerous variables associated with substance use, individuals reporting low LS were significantly more likely to ever use tobacco (OR = 1.34, 95% CI = [1.01, 1.78]), alcohol (OR = 1.45, 95% CI = [1.10, 1.92]) and marijuana (OR = 1.98, 95% CI = [1.39, 2.82]). Additionally, students with low LS were significantly more likely to use two substances (OR = 1.90, 95% CI = [1.15, 3.14]) and three substances concurrently (OR = 2.00, 95% CI = [1.27, 3.16]). The present study identified strong associations between LS and individual, as well as concurrent, substance use among adolescents. Interventions aiming to reduce adolescent substance use may benefit from incorporating components to improve LS.

Multilevel SEM Strategies for Evaluating Mediation in Three-Level Data

ERIC Educational Resources Information Center

Preacher, Kristopher J.

2011-01-01

Strategies for modeling mediation effects in multilevel data have proliferated over the past decade, keeping pace with the demands of applied research. Approaches for testing mediation hypotheses with 2-level clustered data were first proposed using multilevel modeling (MLM) and subsequently using multilevel structural equation modeling (MSEM) to…

Social participation, social capital and daily tobacco smoking: a population-based multilevel analysis in Malmö, Sweden.

PubMed

Lindström, Martin; Moghaddassi, Mahnaz; Bolin, Kristian; Lindgren, Björn; Merlo, Juan

2003-01-01

The aim of this study was to investigate the influence of contextual and individual factors on daily tobacco smoking. The public-health survey in Malmö 1994 is a cross-sectional study. A total of 5600 individuals aged 20-80 years were invited to answer a postal questionnaire. The participation rate was 71%. A multilevel logistic regression model, with individuals at the first level and neighbourhoods at the second, was performed. We analysed the effect (intra-area correlation, cross-level modification and odds ratios) of individual and neighbourhood factors on smoking after adjustment for individual factors. Neighbourhood factors accounted for 2.5% of the crude total variance in daily tobacco smoking. This effect was significantly reduced when the individual factors such as education were included in the model. However, individual social capital, measured by social participation, only marginally affected the total neighbourhood variance in daily tobacco smoking. In fact, no significant variance in daily tobacco smoking remained after the introduction of the individual factors other than individual social capital in the model. In Malmö, the neighbourhood variance in daily tobacco smoking is mainly affected by individual factors other than individual social capital, especially socioeconomic status measured as level of education.

Personal, relational and school factors associated with involvement in fights with weapons among school-age youth in Brazil: a multilevel ecological approach.

PubMed

Peres, Maria Fernanda Tourinho; Azeredo, Catarina Machado; de Rezende, Leandro Fórnias Machado; Zucchi, Eliana Miura; Franca-Junior, Ivan; Luiz, Olinda do Carmo; Levy, Renata Bertazzi

2018-06-08

To investigate the association between personal, relational and school factors with involvement in fights with weapon among Brazilian school-age youth. Using data from the Adolescent School-Based Health Survey 2015 (n = 102.072), we conducted multilevel logistic regression models. IFW was associated with female sex (OR = 0.45), and with older age (OR = 1.15), previous involvement in physical violence (OR = 2.05), history of peer verbal (OR = 1.14) and domestic victimization (OR = 2.11), alcohol use (OR = 2.42) and drug use (OR = 3.23). The relational variables (e.g., parent's supervision) were mostly negatively associated with IFW. At the school level, attending public school and attending schools in violent surroundings were both positively associated with IFW. The intraclass correlation coefficient estimated in the empty model showed that 5.77% of the variance of IFW was at school level. When all individual- and school-level variables were included in the model, the proportional changes in variance were 61.7 and 71.55%, respectively. IFW is associated with personal, relational and school factors. Part of the variance in IFW by school is explained by characteristics of the school context.

Geographic and socioeconomic variations in adolescent toothbrushing: a multilevel cross-sectional study of 15 year olds in Scotland.

PubMed

Levin, K A; Nicholls, N; Macdonald, S; Dundas, R; Douglas, G V A

2015-03-01

This study examined urban-rural and socioeconomic differences in adolescent toothbrushing. The data were modelled using logistic multilevel modelling and the Markov Chain Monte Carlo method of estimation. Twice-a-day toothbrushing was regressed upon age, family affluence, family structure, school type, area-level deprivation and rurality, for boys and girls separately. Boys' toothbrushing was associated with area-level deprivation but not rurality. Variance at the school level remained significant in the final model for boys' toothbrushing. The association between toothbrushing and area-level deprivation was particularly strong for girls, after adjustment for individuals' family affluence and type of school attended. Rurality too was independently significant with lower odds of brushing teeth in accessible rural areas. The findings are at odds with the results of a previous study which showed lower caries prevalence among children living in rural Scotland. A further study concluded that adolescents have a better diet in rural Scotland. In total, these studies highlight the need for an examination into the relative importance of diet and oral health on caries, as increases are observed in population obesity and consumption of sugars. © The Author 2014. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Is religiosity positively associated with school connectedness: evidence from high school students in Atlantic Canada?

PubMed

Azagba, Sunday; Asbridge, Mark; Langille, Donald B

2014-12-01

School connectedness (SC) is associated with decreased student risk behavior and better health and social outcomes. While a considerable body of research has examined the factors associated with SC, there is limited evidence about the particular role of religiosity in shaping levels of SC. Employing data reported by junior and senior high school students from Atlantic Canada, this study examines whether religiosity is positively associated with SC and whether such associations differ by gender. We tested the association between SC and religiosity using a random intercept multilevel logistic regression. The between-school variability in SC was first determined by our estimating a null or empty model; three different model specifications that included covariates were estimated: in Model 1 we adjusted for gender, age, academic performance, parental education, and living arrangement; in Model 2 for sensation seeking and subjective social status in addition to Model 1 variables; and in Model 3 we added substance use to the analysis. Our multilevel regression analyses showed that religiosity was protectively associated with lower SC across the three model specifications when both genders were examined together. In gender-stratified analyses we found similar protective associations of religiosity, with lower SC for both males and females in all three models. Given the overwhelming positive impact of SC on a range of health, social and school outcomes, it is important to understand the role of religiosity, among other factors, that may be modified to enhance student's connectedness to school.

The association between neighborhood social capital and self-reported dentate status in elderly Japanese--the Ohsaki Cohort 2006 Study.

PubMed

Aida, J; Kuriyama, S; Ohmori-Matsuda, K; Hozawa, A; Osaka, K; Tsuji, I

2011-06-01

Little is known about the influence of social capital on dental health. The aim of the present cross-sectional study was to determine the association between neighborhood social capital, individual social networks and social support and the number of remaining teeth in elderly Japanese. In December 2006, self-administered questionnaires were sent to 31,237 eligible community-dwelling individuals (response rate: 73.9%). Included in the analysis were 21,736 participants. Five neighborhood social capital variables were calculated from individual civic networks, sports and hobby networks, volunteer networks, friendship networks and social support variables. We used multilevel logistic regression models to estimate the odds ratio (OR) of having 20 or more teeth according to neighborhood social capital variables with adjustment for sex, age, individual social networks and social support, educational attainment, neighborhood educational level, dental health behavior, smoking status, history of diabetes and self-rated health. The average age of the participants was 74.9 (standard deviation; 6.6) years, and 28.5% of them had 20 or more teeth. In the univariate multilevel model, there were statistically significant associations between neighborhood sports and hobby networks, friendship networks and self-reported dentate status. In the multivariable multilevel model, compared with participants living in lowest friendship network neighborhoods, those living in highest friendship network neighborhoods had an OR 1.17 (95% confidence interval, 1.04-1.30) times higher for having 20 or more teeth. There is a significant association between one network aspect of neighborhood social capital and individual dentate status regardless of individual social networks and social support. © 2010 John Wiley & Sons A/S.

[Nursing Workforce Characteristics and Control of Diabetes Mellitus in Primary Care: a Multilevel Analysis].

PubMed

Parro Moreno, Ana; Santiago Pérez, M Isolina; Abraira Santos, Victor; Aréjula Torres, José Luis Aréjula Torres; Díaz Holgado, Antonio; Gandarillas Grande, Ana; Morales Asencio, José Miguel; Serrano Gallardo, Pilar

2016-03-04

Nurse activity is determined by the characteristics of nursing staff. The objective was to determine the impact of Primary Health Care (PHC) nursing workforce characteristics on the control of Diabetes Mellitus (DM) in adults. Cross-sectional analytical study. Administrative and clinical registries and questionnaire PES-Nursing Work Index from PHC nurses. Participants 44.214 diabetic patients in two health zones within the Community of Madrid, North-West Zone (NWZ) with higher socioeconomic situation and South-West Zone (SWZ) with lower socioeconomic situation, and their 507 reference nurses. Analyses were performed to multivariate multilevel logistic regression models. Poor DM control (figures equal or higher than 7% HbA1c). The prevalence of poor DM control was 40.1% [CI95%: 38.2-42.1]. There was a risk of 25% more of poor control if the patient changed centre and of 27% if changed of doctor-nurse pair. In the multilevel multivariate regression models: in SWZ increasing the ratio of patients over 65 years per nurse increased the poor control (OR=1.00008 [CI95%:1.00006-1.001]); and higher proportion of patients whose Hb1Ac was not measured at the centre contributed to poor DM control (OR=5.1 [CI95%:1.6-15.6]). In two models for health zone, the economic immigration condition increased poor control, in SWZ (OR=1.3 [CI95%:1.03-1.7]); and in NWZ (OR=1.29 [CI95%:1.03-1.6]). Higher 65 years old patients ratio per nurse, economic immigration condition and a higher proportion of patients whose Hb1Ac was not measured contribute to worse DM control.

Trimethoprim and ciprofloxacin resistance and prescribing in urinary tract infection associated with Escherichia coli: a multilevel model.

PubMed

Vellinga, Akke; Tansey, Sana; Hanahoe, Belinda; Bennett, Kathleen; Murphy, Andrew W; Cormican, Martin

2012-10-01

Individual and group level factors associated with the probability of antimicrobial resistance of uropathogenic Escherichia coli were analysed in a multilevel model. Adult patients consulting with a suspected urinary tract infection (UTI) in 22 general practices over a 9 month period supplied a urine sample for laboratory analysis. Cases were patients with a UTI associated with a resistant E. coli. Previous antimicrobial exposure and other patient characteristics were recorded from the medical files. Six hundred and thirty-three patients with an E. coli UTI and a full record for all variables were included. Of the E. coli isolates, 36% were resistant to trimethoprim and 12% to ciprofloxacin. A multilevel logistic regression model was fitted. The odds that E. coli was resistant increased with increasing number of prescriptions over the previous year for trimethoprim from 1.4 (0.8-2.2) for one previous prescription to 4.7 (1.9-12.4) for two and 6.4 (2.0-25.4) for three or more. For ciprofloxacin the ORs were 2.7 (1.2-5.6) for one and 6.5 (2.9-14.8) for two or more. The probability that uropathogenic E. coli was resistant showed important variation between practices and a difference of 17% for trimethoprim and 33% for ciprofloxacin was observed for an imaginary patient moving from a practice with low to a practice with high probability. This difference could not be explained by practice prescribing or practice resistance levels. Previous antimicrobial use and the practice visited affect the risk that a patient with a UTI will be diagnosed with an E. coli resistant to this agent, which was particularly important for ciprofloxacin.

Individual relocation decisions after tornadoes: a multi-level analysis.

PubMed

Cong, Zhen; Nejat, Ali; Liang, Daan; Pei, Yaolin; Javid, Roxana J

2018-04-01

This study examines how multi-level factors affected individuals' relocation decisions after EF4 and EF5 (Enhanced Fujita Tornado Intensity Scale) tornadoes struck the United States in 2013. A telephone survey was conducted with 536 respondents, including oversampled older adults, one year after these two disaster events. Respondents' addresses were used to associate individual information with block group-level variables recorded by the American Community Survey. Logistic regression revealed that residential damage and homeownership are important predictors of relocation. There was also significant interaction between these two variables, indicating less difference between homeowners and renters at higher damage levels. Homeownership diminished the likelihood of relocation among younger respondents. Random effects logistic regression found that the percentage of homeownership and of higher income households in the community buffered the effect of damage on relocation; the percentage of older adults reduced the likelihood of this group relocating. The findings are assessed from the standpoint of age difference, policy implications, and social capital and vulnerability. © 2018 The Author(s). Disasters © Overseas Development Institute, 2018.

State variations in women's socioeconomic status and use of modern contraceptives in Nigeria.

PubMed

Lamidi, Esther O

2015-01-01

According to the 2014 World Population Data Sheet, Nigeria has one of the highest fertility and lowest contraceptive prevalence rates around the world. However, research suggests that national contraceptive prevalence rate overshadows enormous spatial variations in reproductive behavior in the country. I examined the variations in women's socioeconomic status and modern contraceptive use across states in Nigeria. Using the 2013 Nigeria Demographic and Health Survey data (n = 18,910), I estimated the odds of modern contraceptive use among sexually active married and cohabiting women in a series of multilevel logistic regression models. The share of sexually active, married and cohabiting women using modern contraceptives widely varied, from less than one percent in Kano, Yobe, and Jigawa states, to 40 percent in Osun state. Most of the states with low contraceptive prevalence rates also ranked low on women's socioeconomic attributes. Results of multilevel logistic regression analyses showed that women residing in states with greater shares of women with secondary or higher education, higher female labor force participation rates, and more women with health care decision-making power, had significantly higher odds of using modern contraceptives. Differences in women's participation in health care decisions across states remained significantly associated with modern contraceptive use, net of individual-level socioeconomic status and other covariates of modern contraceptive use. Understanding of state variations in contraceptive use is crucial to the design and implementation of family planning programs. The findings reinforce the need for state-specific family planning programs in Nigeria.

A spatially filtered multilevel model to account for spatial dependency: application to self-rated health status in South Korea

PubMed Central

2014-01-01

Background This study aims to suggest an approach that integrates multilevel models and eigenvector spatial filtering methods and apply it to a case study of self-rated health status in South Korea. In many previous health-related studies, multilevel models and single-level spatial regression are used separately. However, the two methods should be used in conjunction because the objectives of both approaches are important in health-related analyses. The multilevel model enables the simultaneous analysis of both individual and neighborhood factors influencing health outcomes. However, the results of conventional multilevel models are potentially misleading when spatial dependency across neighborhoods exists. Spatial dependency in health-related data indicates that health outcomes in nearby neighborhoods are more similar to each other than those in distant neighborhoods. Spatial regression models can address this problem by modeling spatial dependency. This study explores the possibility of integrating a multilevel model and eigenvector spatial filtering, an advanced spatial regression for addressing spatial dependency in datasets. Methods In this spatially filtered multilevel model, eigenvectors function as additional explanatory variables accounting for unexplained spatial dependency within the neighborhood-level error. The specification addresses the inability of conventional multilevel models to account for spatial dependency, and thereby, generates more robust outputs. Results The findings show that sex, employment status, monthly household income, and perceived levels of stress are significantly associated with self-rated health status. Residents living in neighborhoods with low deprivation and a high doctor-to-resident ratio tend to report higher health status. The spatially filtered multilevel model provides unbiased estimations and improves the explanatory power of the model compared to conventional multilevel models although there are no changes in the signs of parameters and the significance levels between the two models in this case study. Conclusions The integrated approach proposed in this paper is a useful tool for understanding the geographical distribution of self-rated health status within a multilevel framework. In future research, it would be useful to apply the spatially filtered multilevel model to other datasets in order to clarify the differences between the two models. It is anticipated that this integrated method will also out-perform conventional models when it is used in other contexts. PMID:24571639

Predicting Falls and When to Intervene in Older People: A Multilevel Logistical Regression Model and Cost Analysis

PubMed Central

Smith, Matthew I.; de Lusignan, Simon; Mullett, David; Correa, Ana; Tickner, Jermaine; Jones, Simon

2016-01-01

Introduction Falls are the leading cause of injury in older people. Reducing falls could reduce financial pressures on health services. We carried out this research to develop a falls risk model, using routine primary care and hospital data to identify those at risk of falls, and apply a cost analysis to enable commissioners of health services to identify those in whom savings can be made through referral to a falls prevention service. Methods Multilevel logistical regression was performed on routinely collected general practice and hospital data from 74751 over 65’s, to produce a risk model for falls. Validation measures were carried out. A cost-analysis was performed to identify at which level of risk it would be cost-effective to refer patients to a falls prevention service. 95% confidence intervals were calculated using a Monte Carlo Model (MCM), allowing us to adjust for uncertainty in the estimates of these variables. Results A risk model for falls was produced with an area under the curve of the receiver operating characteristics curve of 0.87. The risk cut-off with the highest combination of sensitivity and specificity was at p = 0.07 (sensitivity of 81% and specificity of 78%). The risk cut-off at which savings outweigh costs was p = 0.27 and the risk cut-off with the maximum savings was p = 0.53, which would result in referral of 1.8% and 0.45% of the over 65’s population respectively. Above a risk cut-off of p = 0.27, costs do not exceed savings. Conclusions This model is the best performing falls predictive tool developed to date; it has been developed on a large UK city population; can be readily run from routine data; and can be implemented in a way that optimises the use of health service resources. Commissioners of health services should use this model to flag and refer patients at risk to their falls service and save resources. PMID:27448280

Determinants of Exclusive Breast Feeding in sub-Saharan Africa: A Multilevel Approach.

PubMed

Yalçin, Siddika Songül; Berde, Anselm S; Yalçin, Suzan

2016-09-01

The study aimed to provide an overall picture of the general pattern of exclusive breast feeding (EBF) in sub-Saharan Africa (SSA) by examining maternal sociodemographic, antenatal and postnatal factors associated with EBF in the region, as well as explore countries variations in EBF rates. We utilised cross-sectional data from the Demographic Health Surveys in 27 SSA countries. Our study sample included 25 084 infants under 6 months of age. The key outcome variable was EBF in the last 24 h. Due to the hierarchical structure of the data, a multilevel logistic regression model was used to explore factors associated with EBF. The overall prevalence of EBF in SSA was 36.0%, the prevalence was highest in Rwanda and lowest in Gabon. In the multilevel regression model, factors that were associated with increased likelihood of EBF included secondary and above maternal education, mothers within the ages of 25-34 years, rural residence, richer household wealth quantile, 4+ antenatal care visit, delivering in a health facility, singleton births, female infants, early initiation of breast feeding (EIBF), and younger infants. However, countries with higher gross national income per capita had lower EBF rates. To achieve a substantial increase in EBF rates in SSA, breast-feeding interventions and policies should target all women but with more emphasis to mothers with younger age, low educational status, urban residence, poor status, multiple births, and male infants. In addition, there is a need to promote antenatal care utilisation, hospital deliveries, and EIBF. © 2016 John Wiley & Sons Ltd.

Neighborhood contextual factors, maternal smoking, and birth outcomes: multilevel analysis of the South Carolina PRAMS survey, 2000-2003.

PubMed

Nkansah-Amankra, Stephen

2010-08-01

Previous studies investigating relationships among neighborhood contexts, maternal smoking behaviors, and birth outcomes (low birth weight [LBW] or preterm births) have produced mixed results. We evaluated independent effects of neighborhood contexts on maternal smoking behaviors and risks of LBW or preterm birth outcomes among mothers participating in the South Carolina Pregnancy Risk Assessment and Monitoring System (PRAMS) survey, 2000-2003. The PRAMS data were geocoded to 2000 U.S. Census data to create a multilevel data structure. We used a multilevel regression analysis (SAS PROC GLIMMIX) to estimate odds ratios (OR) and corresponding 95% confidence intervals (CI). In multivariable logistic regression models, high poverty, predominantly African American neighborhoods, upper quartiles of low education, and second quartile of neighborhood household crowding were significantly associated with LBW. However, only mothers resident in predominantly African American Census tract areas were statistically significantly at an increased risk of delivering preterm (OR 2.2, 95% CI 1.29-3.78). In addition, mothers resident in medium poverty neighborhoods remained modestly associated with smoking after adjustment for maternal-level covariates. The results also indicated that maternal smoking has more consistent effects on LBW than preterm births, particularly for mothers living in deprived neighborhoods. Interventions seeking to improve maternal and child health by reducing smoking during pregnancy need to engage specific community factors that encourage maternal quitting behaviors and reduce smoking relapse rates. Inclusion of maternal-level covariates in neighborhood models without careful consideration of the causal pathway might produce misleading interpretation of the results.

Deepening our Understanding of Quality in Australia (DUQuA): a study protocol for a nationwide, multilevel analysis of relationships between hospital quality management systems and patient factors

PubMed Central

Taylor, Natalie; Clay-Williams, Robyn; Hogden, Emily; Pye, Victoria; Li, Zhicheng; Groene, Oliver; Suñol, Rosa; Braithwaite, Jeffrey

2015-01-01

Introduction Despite the growing body of research on quality and safety in healthcare, there is little evidence of the association between the way hospitals are organised for quality and patient factors, limiting our understanding of how to effect large-scale change. The ‘Deepening our Understanding of Quality in Australia’ (DUQuA) study aims to measure and examine relationships between (1) organisation and department-level quality management systems (QMS), clinician leadership and culture, and (2) clinical treatment processes, clinical outcomes and patient-reported perceptions of care within Australian hospitals. Methods and analysis The DUQuA project is a national, multilevel, cross-sectional study with data collection at organisation (hospital), department, professional and patient levels. Sample size calculations indicate a minimum of 43 hospitals are required to adequately power the study. To allow for rejection and attrition, 70 hospitals across all Australian jurisdictions that meet the inclusion criteria will be invited to participate. Participants will consist of hospital quality management professionals; clinicians; and patients with stroke, acute myocardial infarction and hip fracture. Organisation and department-level QMS, clinician leadership and culture, patient perceptions of safety, clinical treatment processes, and patient outcomes will be assessed using validated, evidence-based or consensus-based measurement tools. Data analysis will consist of simple correlations, linear and logistic regression and multilevel modelling. Multilevel modelling methods will enable identification of the amount of variation in outcomes attributed to the hospital and department levels, and the factors contributing to this variation. Ethics and dissemination Ethical approval has been obtained. Results will be disseminated to individual hospitals in de-identified national and international benchmarking reports with data-driven recommendations. This ground-breaking national study has the potential to influence decision-making on the implementation of quality and safety systems and processes in Australian and international hospitals. PMID:26644128

Multilevel Modeling of Social Segregation

ERIC Educational Resources Information Center

Leckie, George; Pillinger, Rebecca; Jones, Kelvyn; Goldstein, Harvey

2012-01-01

The traditional approach to measuring segregation is based upon descriptive, non-model-based indices. A recently proposed alternative is multilevel modeling. The authors further develop the argument for a multilevel modeling approach by first describing and expanding upon its notable advantages, which include an ability to model segregation at a…

Improvement of the Work Environment and Work-Related Stress: A Cross-Sectional Multilevel Study of a Nationally Representative Sample of Japanese Workers.

PubMed

Watanabe, Kazuhiro; Tabuchi, Takahiro; Kawakami, Norito

2017-03-01

This cross-sectional multilevel study aimed to investigate the relationship between improvement of the work environment and work-related stress in a nationally representative sample in Japan. The study was based on a national survey that randomly sampled 1745 worksites and 17,500 nested employees. The survey asked the worksites whether improvements of the work environment were conducted; and it asked the employees to report the number of work-related stresses they experienced. Multilevel multinominal logistic and linear regression analyses were conducted. Improvement of the work environment was not significantly associated with any level of work-related stress. Among men, it was significantly and negatively associated with the severe level of work-related stress. The association was not significant among women. Improvements to work environments may be associated with reduced work-related stress among men nationwide in Japan.

Social capital and self-rated health among middle-aged and older adults in China: a multilevel analysis.

PubMed

Shen, Yuying; Yeatts, Dale E; Cai, Tianji; Yang, Philip Q; Cready, Cynthia M

2014-07-01

This study examined the association between social capital, at both the individual and the community level, and self-rated health among older adults in China. Using data from the 2008 Pilot Survey of China Health and Retirement Longitudinal Study, a series of multilevel logistic models were estimated in SAS 9.2. The association between social capital and self-rated health was examined among 996 adults aged 45 or older from two provinces in China, while controlling for demographic characteristics and socioeconomic variables. Our results suggest the significant association between certain aspects of social capital, at both the individual and the community level, and self-rated health. The individual-level social capital in the form of perceived help in the future and the social capital of community in the form of the availability of amenities and associations within the community were significantly related to self-rated health. A significant cross-level interaction effect between individual- and community-level social capital was also observed. © The Author(s) 2013.

Tooth-related risk factors for periodontal disease in community-dwelling elderly people.

PubMed

Hirotomi, Toshinobu; Yoshihara, Akihiro; Ogawa, Hiroshi; Miyazaki, Hideo

2010-06-01

While most previous epidemiological studies have focused on subject-level risk factors for periodontal destruction, tooth-related factors have not been fully explored. The purpose of this study was to evaluate both tooth-related and subject-related factors affecting periodontal disease progression using a two-level multilevel model. A longitudinal survey over a period of 10 years was carried out on 286 community-dwelling elderly subjects aged 70 years at baseline. Clinical attachment level (CAL) was measured at six sites per tooth on all teeth present and periodontal disease progression was defined as CAL> or =3 mm. Periodontal disease progression was found in 79% of the subjects and most frequently in maxillary molars. Multilevel logistic regressions revealed that subjects wearing removable dentures were significantly at risk for periodontal disease progression. Abutment teeth for removable/fixed dentures were also significantly more likely to suffer periodontal breakdown. Furthermore, the following tooth-related variables were found to be possible risk factors for periodontal disease progression: maxillary and multirooted teeth. Multirooted teeth and abutments for a fixed denture were possible risk factors for periodontal disease progression.

Material deprivation and unemployment affect coercive sex among young people in the urban slums of Blantyre, Malawi: A multi-level approach.

PubMed

Kamndaya, Mphatso; Kazembe, Lawrence N; Vearey, Jo; Kabiru, Caroline W; Thomas, Liz

2015-05-01

We explore relations among material deprivation (measured by insufficient housing, food insecurity and poor healthcare access), socio-economic status (employment, income and education) and coercive sex. A binary logistic multi-level model is used in the estimation of data from a survey of 1071 young people aged 18-23 years, undertaken between June and July 2013, in the urban slums of Blantyre, Malawi. For young men, unemployment was associated with coercive sex (odds ratio [OR]=1.77, 95% confidence interval [CI]: 1.09-3.21) while material deprivation (OR=1.34, 95% CI: 0.75-2.39) was not. Young women in materially deprived households were more likely to report coercive sex (OR=1.37, 95% CI: 1.07-2.22) than in non-materially deprived households. Analysis of local indicators of deprivation is critical to inform the development of effective strategies to reduce coercive sex in urban slums in Malawi. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Administrative Climate and Novices' Intent to Remain Teaching

ERIC Educational Resources Information Center

Pogodzinski, Ben; Youngs, Peter; Frank, Kenneth A.; Belman, Dale

2012-01-01

Using survey data from novice teachers at the elementary and middle school level across 11 districts, multilevel logistic regressions were estimated to examine the association between novices' perceptions of the administrative climate and their desire to remain teaching within their schools. We find that the probability that a novice teacher…

Foreign-Born Concentration and Acculturation to Volunteering among Immigrant Youth

ERIC Educational Resources Information Center

Tong, Yuying

2010-01-01

Using children of immigrants sample from National Longitudinal Study of Adolescent Health, this study investigates how immigrant youth acculturating to the American social norm of volunteering and how the acculturation is modified by living in immigrant neighborhoods. Multilevel logistic regression produces distinct patterns for children living in…

Application of Hierarchical Linear Models/Linear Mixed-Effects Models in School Effectiveness Research

ERIC Educational Resources Information Center

Ker, H. W.

2014-01-01

Multilevel data are very common in educational research. Hierarchical linear models/linear mixed-effects models (HLMs/LMEs) are often utilized to analyze multilevel data nowadays. This paper discusses the problems of utilizing ordinary regressions for modeling multilevel educational data, compare the data analytic results from three regression…

Testing Group Mean Differences of Latent Variables in Multilevel Data Using Multiple-Group Multilevel CFA and Multilevel MIMIC Modeling.

PubMed

Kim, Eun Sook; Cao, Chunhua

2015-01-01

Considering that group comparisons are common in social science, we examined two latent group mean testing methods when groups of interest were either at the between or within level of multilevel data: multiple-group multilevel confirmatory factor analysis (MG ML CFA) and multilevel multiple-indicators multiple-causes modeling (ML MIMIC). The performance of these methods were investigated through three Monte Carlo studies. In Studies 1 and 2, either factor variances or residual variances were manipulated to be heterogeneous between groups. In Study 3, which focused on within-level multiple-group analysis, six different model specifications were considered depending on how to model the intra-class group correlation (i.e., correlation between random effect factors for groups within cluster). The results of simulations generally supported the adequacy of MG ML CFA and ML MIMIC for multiple-group analysis with multilevel data. The two methods did not show any notable difference in the latent group mean testing across three studies. Finally, a demonstration with real data and guidelines in selecting an appropriate approach to multilevel multiple-group analysis are provided.

Multilevel Modeling: A Review of Methodological Issues and Applications

ERIC Educational Resources Information Center

Dedrick, Robert F.; Ferron, John M.; Hess, Melinda R.; Hogarty, Kristine Y.; Kromrey, Jeffrey D.; Lang, Thomas R.; Niles, John D.; Lee, Reginald S.

2009-01-01

This study analyzed the reporting of multilevel modeling applications of a sample of 99 articles from 13 peer-reviewed journals in education and the social sciences. A checklist, derived from the methodological literature on multilevel modeling and focusing on the issues of model development and specification, data considerations, estimation, and…

Building Path Diagrams for Multilevel Models

ERIC Educational Resources Information Center

Curran, Patrick J.; Bauer, Daniel J.

2007-01-01

Multilevel models have come to play an increasingly important role in many areas of social science research. However, in contrast to other modeling strategies, there is currently no widely used approach for graphically diagramming multilevel models. Ideally, such diagrams would serve two functions: to provide a formal structure for deriving the…

Individual and contextual factors influencing dental health care utilization by preschool children: a multilevel analysis

PubMed

Piovesan, Chaiana; Ardenghi, Thiago Machado; Mendes, Fausto Medeiros; Agostini, Bernardo Antonio; Michel-Crosato, Edgard

2017-03-30

The effect of contextual factors on dental care utilization was evaluated after adjustment for individual characteristics of Brazilian preschool children. This cross-sectional study assessed 639 preschool children aged 1 to 5 years from Santa Maria, a town in Rio Grande do Sul State, located in southern Brazil. Participants were randomly selected from children attending the National Children's Vaccination Day and 15 health centers were selected for this research. Visual examinations followed the ICDAS criteria. Parents answered a questionnaire about demographic and socioeconomic characteristics. Contextual influences on children's dental care utilization were obtained from two community-related variables: presence of dentists and presence of workers' associations in the neighborhood. Unadjusted and adjusted multilevel logistic regression models were used to describe the association between outcome and predictor variables. A prevalence of 21.6% was found for regular use of dental services. The unadjusted assessment of the associations of dental health care utilization with individual and contextual factors included children's ages, family income, parents' schooling, mothers' participation in their children's school activities, dental caries, and presence of workers' associations in the neighborhood as the main outcome covariates. Individual variables remained associated with the outcome after adding contextual variables in the model. In conclusion, individual and contextual variables were associated with dental health care utilization by preschool children.

Detecting Differential Item Discrimination (DID) and the Consequences of Ignoring DID in Multilevel Item Response Models

ERIC Educational Resources Information Center

Lee, Woo-yeol; Cho, Sun-Joo

2017-01-01

Cross-level invariance in a multilevel item response model can be investigated by testing whether the within-level item discriminations are equal to the between-level item discriminations. Testing the cross-level invariance assumption is important to understand constructs in multilevel data. However, in most multilevel item response model…

Alternative Methods for Assessing Mediation in Multilevel Data: The Advantages of Multilevel SEM

ERIC Educational Resources Information Center

Preacher, Kristopher J.; Zhang, Zhen; Zyphur, Michael J.

2011-01-01

Multilevel modeling (MLM) is a popular way of assessing mediation effects with clustered data. Two important limitations of this approach have been identified in prior research and a theoretical rationale has been provided for why multilevel structural equation modeling (MSEM) should be preferred. However, to date, no empirical evidence of MSEM's…

Assessing dose–response effects of national essential medicine policy in China: comparison of two methods for handling data with a stepped wedge-like design and hierarchical structure

PubMed Central

Ren, Yan; Yang, Min; Li, Qian; Pan, Jay; Chen, Fei; Li, Xiaosong; Meng, Qun

2017-01-01

Objectives To introduce multilevel repeated measures (RM) models and compare them with multilevel difference-in-differences (DID) models in assessing the linear relationship between the length of the policy intervention period and healthcare outcomes (dose–response effect) for data from a stepped-wedge design with a hierarchical structure. Design The implementation of national essential medicine policy (NEMP) in China was a stepped-wedge-like design of five time points with a hierarchical structure. Using one key healthcare outcome from the national NEMP surveillance data as an example, we illustrate how a series of multilevel DID models and one multilevel RM model can be fitted to answer some research questions on policy effects. Setting Routinely and annually collected national data on China from 2008 to 2012. Participants 34 506 primary healthcare facilities in 2675 counties of 31 provinces. Outcome measures Agreement and differences in estimates of dose–response effect and variation in such effect between the two methods on the logarithm-transformed total number of outpatient visits per facility per year (LG-OPV). Results The estimated dose–response effect was approximately 0.015 according to four multilevel DID models and precisely 0.012 from one multilevel RM model. Both types of model estimated an increase in LG-OPV by 2.55 times from 2009 to 2012, but 2–4.3 times larger SEs of those estimates were found by the multilevel DID models. Similar estimates of mean effects of covariates and random effects of the average LG-OPV among all levels in the example dataset were obtained by both types of model. Significant variances in the dose–response among provinces, counties and facilities were estimated, and the ‘lowest’ or ‘highest’ units by their dose–response effects were pinpointed only by the multilevel RM model. Conclusions For examining dose–response effect based on data from multiple time points with hierarchical structure and the stepped wedge-like designs, multilevel RM models are more efficient, convenient and informative than the multilevel DID models. PMID:28399510

Changes in health care utilisation following a reform involving choice and privatisation in Swedish primary care: a five-year follow-up of GP-visits

PubMed Central

2013-01-01

Background The organisation of Swedish primary health care has changed following introduction of free choice of provider for the population in combination with freedom of establishment for private primary care providers. Our aim was to investigate changes in individual health care utilisation following choice and privatisation in Swedish primary care from an equity perspective, in subgroups defined by age, gender and family income. Methods The study is based on register data years 2007 – 2011 from the Skåne Regional Council (population 1.2 million) regarding individual health care utilisation in the form of visits to general practitioner (GP). Health utilisation data was matched with data about individual’s age, gender and family income provided by Statistics Sweden. Multilevel, logistic regression models were constructed to analyse changes in health utilisation in different subgroups and the probability of a GP-visit before and after reform. Results Health care utilisation in terms of both number of individuals that had visited a GP and number of GP-visits per capita increased in all defined subgroups, but to a varying degree. Multilevel logistic regression showed that individuals of both genders aged above 64 and belonging to a family with an income above median had more advantage of the reform, OR 1.25-1.29. Conclusions Reforms involving choice and privatisation in Swedish primary health care improved access to GP-visits generally, but more so for individuals belonging to a family with income above the median. PMID:24171894

Revisiting Robinson: The perils of individualistic and ecologic fallacy

PubMed Central

Subramanian, S V; Jones, Kelvyn; Kaddour, Afamia; Krieger, Nancy

2009-01-01

Background W S Robinson made a seminal contribution by demonstrating that correlations for the same two variables can be different at the individual and ecologic level. This study reanalyzes and historically situates Robinson's influential study that laid the foundation for the primacy of analyzing data at only the individual level. Methods We applied a binomial multilevel logistic model to analyse variation in illiteracy as enumerated by the 1930 US. Census (the same data as used by Robinson). The outcome was log odds of being illiterate, while predictors were race/nativity (‘native whites’, ‘foreign-born whites’ and ‘negroes’) at the individual-level, and presence of Jim Crow segregation laws for education at the state-level. We conducted historical research to identify the social and scientific context within which Robinson's study was produced and favourably received. Results Empirically, the substantial state variations in illiteracy could not be accounted by the states' race/nativity composition. Different approaches to modelling state-effects yielded considerably attenuated associations at the individual-level between illiteracy and race/nativity. Furthermore, state variation in illiteracy was different across the race/nativity groups, with state variation being largest for whites and least for foreign-born whites. Strong effects of Jim Crow education laws on illiteracy were observed with the effect being strongest for blacks. Historically, Robinson's study was consonant with the post-World War II ascendancy of methodological individualism. Conclusion Applying a historically informed multilevel perspective to Robinson's profoundly influential study, we demonstrate that meaningful analysis of individual-level relationships requires attention to substantial heterogeneity in state characteristics. The implication is that perils are posed by not only ecological fallacy but also individualistic fallacy. Multilevel thinking, grounded in historical and spatiotemporal context, is thus a necessity, not an option. PMID:19179348

Revisiting Robinson: the perils of individualistic and ecologic fallacy.

PubMed

Subramanian, S V; Jones, Kelvyn; Kaddour, Afamia; Krieger, Nancy

2009-04-01

W S Robinson made a seminal contribution by demonstrating that correlations for the same two variables can be different at the individual and ecologic level. This study reanalyzes and historically situates Robinson's influential study that laid the foundation for the primacy of analyzing data at only the individual level. We applied a binomial multilevel logistic model to analyse variation in illiteracy as enumerated by the 1930 US. Census (the same data as used by Robinson). The outcome was log odds of being illiterate, while predictors were race/nativity ('native whites', 'foreign-born whites' and 'negroes') at the individual-level, and presence of Jim Crow segregation laws for education at the state-level. We conducted historical research to identify the social and scientific context within which Robinson's study was produced and favourably received. Empirically, the substantial state variations in illiteracy could not be accounted by the states' race/nativity composition. Different approaches to modelling state-effects yielded considerably attenuated associations at the individual-level between illiteracy and race/nativity. Furthermore, state variation in illiteracy was different across the race/nativity groups, with state variation being largest for whites and least for foreign-born whites. Strong effects of Jim Crow education laws on illiteracy were observed with the effect being strongest for blacks. Historically, Robinson's study was consonant with the post-World War II ascendancy of methodological individualism. Applying a historically informed multilevel perspective to Robinson's profoundly influential study, we demonstrate that meaningful analysis of individual-level relationships requires attention to substantial heterogeneity in state characteristics. The implication is that perils are posed by not only ecological fallacy but also individualistic fallacy. Multilevel thinking, grounded in historical and spatiotemporal context, is thus a necessity, not an option.

Adolescents' psychological health complaints and the economic recession in late 2007: a multilevel study in 31 countries.

PubMed

Pfoertner, Timo-Kolja; Rathmann, Katharina; Elgar, Frank J; de Looze, Margaretha; Hofmann, Felix; Ottova-Jordan, Veronika; Ravens-Sieberer, Ulrike; Bosakova, Lucia; Currie, Candace; Richter, Matthias

2014-12-01

The recent economic recession, which began in 2007, has had a detrimental effect on the health of the adult population, but no study yet has investigated the impact of this downturn on adolescent health. This article uniquely examines the effect of the crisis on adolescents' psychological health complaints in a cross-national comparison. Data came from the World Health Organization collaborative 'Health Behaviour in School-aged Children' study in 2005-06 and 2009-10. We measured change in psychological health complaints from before to during the recession in the context of changing adult and adolescent unemployment rates. Furthermore, we used logistic multilevel regression to model the impact of absolute unemployment in 2010 and its change rate between 2005-06 and 2009-10 on adolescents' psychological health complaints in 2010. Descriptive results showed that although youth and adult unemployment has increased during the economic crisis, rates of psychological health complaints among adolescents were unaffected in some countries and even decreased in others. Multilevel regression models support this finding and reveal that only youth unemployment in 2010 increased the likelihood of psychological health complaints, whereas its change rate in light of the recession as well as adult unemployment did not relate to levels of psychological health complaints. In contrast to recent findings, our study indicates that the negative shift of the recent recession on the employment market in several countries has not affected adolescents' psychological health complaints. Adolescents' well-being instead seems to be influenced by the current situation on the labour market that shapes their occupational outlook. © The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Family and School Influences on Adolescent Smoking Behaviour

ERIC Educational Resources Information Center

Wiium, Nora; Wold, Bente

2006-01-01

Purpose: This paper aims to examine how influences at home and school interact to predict smoking among adolescents. Design/methodology/approach: Data were collected from 15-year-old pupils from Norway (n=1,404 in 73 Grade 10 school classes). Multilevel logistic regression analysis was used to determine how family and school influences interact to…

Sample size estimation for alternating logistic regressions analysis of multilevel randomized community trials of under-age drinking.

PubMed

Reboussin, Beth A; Preisser, John S; Song, Eun-Young; Wolfson, Mark

2012-07-01

Under-age drinking is an enormous public health issue in the USA. Evidence that community level structures may impact on under-age drinking has led to a proliferation of efforts to change the environment surrounding the use of alcohol. Although the focus of these efforts is to reduce drinking by individual youths, environmental interventions are typically implemented at the community level with entire communities randomized to the same intervention condition. A distinct feature of these trials is the tendency of the behaviours of individuals residing in the same community to be more alike than that of others residing in different communities, which is herein called 'clustering'. Statistical analyses and sample size calculations must account for this clustering to avoid type I errors and to ensure an appropriately powered trial. Clustering itself may also be of scientific interest. We consider the alternating logistic regressions procedure within the population-averaged modelling framework to estimate the effect of a law enforcement intervention on the prevalence of under-age drinking behaviours while modelling the clustering at multiple levels, e.g. within communities and within neighbourhoods nested within communities, by using pairwise odds ratios. We then derive sample size formulae for estimating intervention effects when planning a post-test-only or repeated cross-sectional community-randomized trial using the alternating logistic regressions procedure.

Sample Size Limits for Estimating Upper Level Mediation Models Using Multilevel SEM

ERIC Educational Resources Information Center

Li, Xin; Beretvas, S. Natasha

2013-01-01

This simulation study investigated use of the multilevel structural equation model (MLSEM) for handling measurement error in both mediator and outcome variables ("M" and "Y") in an upper level multilevel mediation model. Mediation and outcome variable indicators were generated with measurement error. Parameter and standard…

Multilevel modelling: Beyond the basic applications.

PubMed

Wright, Daniel B; London, Kamala

2009-05-01

Over the last 30 years statistical algorithms have been developed to analyse datasets that have a hierarchical/multilevel structure. Particularly within developmental and educational psychology these techniques have become common where the sample has an obvious hierarchical structure, like pupils nested within a classroom. We describe two areas beyond the basic applications of multilevel modelling that are important to psychology: modelling the covariance structure in longitudinal designs and using generalized linear multilevel modelling as an alternative to methods from signal detection theory (SDT). Detailed code for all analyses is described using packages for the freeware R.

Using iMCFA to Perform the CFA, Multilevel CFA, and Maximum Model for Analyzing Complex Survey Data.

PubMed

Wu, Jiun-Yu; Lee, Yuan-Hsuan; Lin, John J H

2018-01-01

To construct CFA, MCFA, and maximum MCFA with LISREL v.8 and below, we provide iMCFA (integrated Multilevel Confirmatory Analysis) to examine the potential multilevel factorial structure in the complex survey data. Modeling multilevel structure for complex survey data is complicated because building a multilevel model is not an infallible statistical strategy unless the hypothesized model is close to the real data structure. Methodologists have suggested using different modeling techniques to investigate potential multilevel structure of survey data. Using iMCFA, researchers can visually set the between- and within-level factorial structure to fit MCFA, CFA and/or MAX MCFA models for complex survey data. iMCFA can then yield between- and within-level variance-covariance matrices, calculate intraclass correlations, perform the analyses and generate the outputs for respective models. The summary of the analytical outputs from LISREL is gathered and tabulated for further model comparison and interpretation. iMCFA also provides LISREL syntax of different models for researchers' future use. An empirical and a simulated multilevel dataset with complex and simple structures in the within or between level was used to illustrate the usability and the effectiveness of the iMCFA procedure on analyzing complex survey data. The analytic results of iMCFA using Muthen's limited information estimator were compared with those of Mplus using Full Information Maximum Likelihood regarding the effectiveness of different estimation methods.

Using Visual Analysis to Evaluate and Refine Multilevel Models of Single-Case Studies

ERIC Educational Resources Information Center

Baek, Eun Kyeng; Petit-Bois, Merlande; Van den Noortgate, Wim; Beretvas, S. Natasha; Ferron, John M.

2016-01-01

In special education, multilevel models of single-case research have been used as a method of estimating treatment effects over time and across individuals. Although multilevel models can accurately summarize the effect, it is known that if the model is misspecified, inferences about the effects can be biased. Concern with the potential for model…

Community Influences on Married Women's Safer Sex Negotiation Attitudes in Bangladesh: A Multilevel Analysis.

PubMed

Jesmin, Syeda S; Cready, Cynthia M

2016-02-01

The influence of disadvantaged or deprived community on individuals' health risk-behaviors is increasingly being documented in a growing body of literature. However, little is known about the effects of community characteristics on women's sexual attitudes and behaviors. To examine community effects on married women's safer sex negotiation attitudes, we analyzed cross-sectional data from the 2011 Bangladesh Demographic and Health Surveys on a sample of 15,134 married women in 600 communities. We estimated two multilevel logistic regression models. Model 1, which included only individual-level variables, showed that women's autonomy/empowerment, age, and HIV knowledge had significant associations with their safer sex negotiation attitudes. We did not find any socioeconomic status gradient in safer sex negotiation attitudes at the individual level. Adding community-level variables in Model 2 significantly improved the fit of the model. Strikingly, we found that higher community-level poverty was associated with greater positive safer sex negotiation attitudes. Prevailing gender norms and overall women's empowerment in the community also had significant effects. While research on community influences calls for focusing on disadvantaged communities, our research highlights the importance of not underestimating the challenges that married women in economically privileged communities may face in negotiating safer sex. To have sufficient and equitable impact on married women's sexual and reproductive health, sexual and reproductive health promotion policies and programs need to be directed to women in wealthier communities as well.

Multilevel structural equation models for assessing moderation within and across levels of analysis.

PubMed

Preacher, Kristopher J; Zhang, Zhen; Zyphur, Michael J

2016-06-01

Social scientists are increasingly interested in multilevel hypotheses, data, and statistical models as well as moderation or interactions among predictors. The result is a focus on hypotheses and tests of multilevel moderation within and across levels of analysis. Unfortunately, existing approaches to multilevel moderation have a variety of shortcomings, including conflated effects across levels of analysis and bias due to using observed cluster averages instead of latent variables (i.e., "random intercepts") to represent higher-level constructs. To overcome these problems and elucidate the nature of multilevel moderation effects, we introduce a multilevel structural equation modeling (MSEM) logic that clarifies the nature of the problems with existing practices and remedies them with latent variable interactions. This remedy uses random coefficients and/or latent moderated structural equations (LMS) for unbiased tests of multilevel moderation. We describe our approach and provide an example using the publicly available High School and Beyond data with Mplus syntax in Appendix. Our MSEM method eliminates problems of conflated multilevel effects and reduces bias in parameter estimates while offering a coherent framework for conceptualizing and testing multilevel moderation effects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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.

Multilevel Evaluation Alignment: An Explication of a Four-Step Model

ERIC Educational Resources Information Center

Yang, Huilan; Shen, Jianping; Cao, Honggao; Warfield, Charles

2004-01-01

Using the evaluation work on the W.K. Kellogg Foundation's Unleashing Resources Initiative as an example, in this article we explicate a general four-step model appropriate for multilevel evaluation alignment. We review the relevant literature, argue for the need for evaluation alignment in a multilevel context, explain the four-step model,…

Alternatives to Multilevel Modeling for the Analysis of Clustered Data

ERIC Educational Resources Information Center

Huang, Francis L.

2016-01-01

Multilevel modeling has grown in use over the years as a way to deal with the nonindependent nature of observations found in clustered data. However, other alternatives to multilevel modeling are available that can account for observations nested within clusters, including the use of Taylor series linearization for variance estimation, the design…

The Impact of Misspecifying the Within-Subject Covariance Structure in Multiwave Longitudinal Multilevel Models: A Monte Carlo Study

ERIC Educational Resources Information Center

Kwok, Oi-man; West, Stephen G.; Green, Samuel B.

2007-01-01

This Monte Carlo study examined the impact of misspecifying the [big sum] matrix in longitudinal data analysis under both the multilevel model and mixed model frameworks. Under the multilevel model approach, under-specification and general-misspecification of the [big sum] matrix usually resulted in overestimation of the variances of the random…

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

PubMed

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

2015-11-01

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

Surgical and Functional Outcomes After Multilevel Cervical Fusion for Degenerative Disc Disease Compared With Fusion for Radiculopathy: A Study of Workers' Compensation Population.

PubMed

Faour, Mhamad; Anderson, Joshua T; Haas, Arnold R; Percy, Rick; Woods, Stephen T; Ahn, Uri M; Ahn, Nicholas U

2017-05-01

Retrospective cohort comparative study. To evaluate presurgical and surgical factors that affect return to work (RTW) status after multilevel cervical fusion, and to compare outcomes after multilevel cervical fusion for degenerative disc disease (DDD) versus radiculopathy. Cervical fusion provides more than 90% of symptomatic relief for radiculopathy and myelopathy. However, cervical fusion for DDD without radiculopathy is considered controversial. In addition, multilevel fusion is associated with poorer surgical outcomes with increased levels fused. Data of cervical comorbidities was collected from Ohio Bureau of Workers' Compensation for subjects with work-related injuries. The study population included subjects who underwent multilevel cervical fusion. Patients with radiculopathy or DDD were identified. Multivariate logistic regression was performed to identify factors that affect RTW status. Surgical and functional outcomes were compared between groups. Stable RTW status within 3 years after multilevel cervical fusion was negatively affected by: fusion for DDD, age > 55 years, preoperative opioid use, initial psychological evaluation before surgery, injury-to-surgery > 2 years and instrumentation.DDD group had lower rate of achieving stable RTW status (P= 0.0001) and RTW within 1 year of surgery (P= 0.0003) compared with radiculopathy group. DDD patients were less likely to have a stable RTW status [odds ratio, OR = 0.63 (0.50-0.79)] or RTW within 1 year after surgery [OR = 0.65 (0.52-0.82)].DDD group had higher rate of opioid use (P= 0.001), and higher rate of disability after surgery (P= 0.002). Multiple detriments affect stable RTW status after multilevel cervical fusion including DDD. DDD without radiculopathy was associated with lower RTW rates, less likelihood to return to work, higher disability, and higher opioid use after surgery. Multilevel cervical fusion for DDD may be counterproductive. Future studies should investigate further treatment options of DDD, and optimize patient selection criteria for surgical intervention. 3.

Hierarchical models of very large problems, dilemmas, prospects, and an agenda for the future

NASA Technical Reports Server (NTRS)

Richardson, J. M., Jr.

1975-01-01

Interdisciplinary approaches to the modeling of global problems are discussed in terms of multilevel cooperation. A multilevel regionalized model of the Lake Erie Basin is analyzed along with a multilevel regionalized world modeling project. Other topics discussed include: a stratified model of interacting region in a world system, and the application of the model to the world food crisis in south Asia. Recommended research for future development of integrated models is included.

Assessing dose-response effects of national essential medicine policy in China: comparison of two methods for handling data with a stepped wedge-like design and hierarchical structure.

PubMed

Ren, Yan; Yang, Min; Li, Qian; Pan, Jay; Chen, Fei; Li, Xiaosong; Meng, Qun

2017-02-22

To introduce multilevel repeated measures (RM) models and compare them with multilevel difference-in-differences (DID) models in assessing the linear relationship between the length of the policy intervention period and healthcare outcomes (dose-response effect) for data from a stepped-wedge design with a hierarchical structure. The implementation of national essential medicine policy (NEMP) in China was a stepped-wedge-like design of five time points with a hierarchical structure. Using one key healthcare outcome from the national NEMP surveillance data as an example, we illustrate how a series of multilevel DID models and one multilevel RM model can be fitted to answer some research questions on policy effects. Routinely and annually collected national data on China from 2008 to 2012. 34 506 primary healthcare facilities in 2675 counties of 31 provinces. Agreement and differences in estimates of dose-response effect and variation in such effect between the two methods on the logarithm-transformed total number of outpatient visits per facility per year (LG-OPV). The estimated dose-response effect was approximately 0.015 according to four multilevel DID models and precisely 0.012 from one multilevel RM model. Both types of model estimated an increase in LG-OPV by 2.55 times from 2009 to 2012, but 2-4.3 times larger SEs of those estimates were found by the multilevel DID models. Similar estimates of mean effects of covariates and random effects of the average LG-OPV among all levels in the example dataset were obtained by both types of model. Significant variances in the dose-response among provinces, counties and facilities were estimated, and the 'lowest' or 'highest' units by their dose-response effects were pinpointed only by the multilevel RM model. For examining dose-response effect based on data from multiple time points with hierarchical structure and the stepped wedge-like designs, multilevel RM models are more efficient, convenient and informative than the multilevel DID models. 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/.

Multilevel Modeling and School Psychology: A Review and Practical Example

ERIC Educational Resources Information Center

Graves, Scott L., Jr.; Frohwerk, April

2009-01-01

The purpose of this article is to provide an overview of the state of multilevel modeling in the field of school psychology. The authors provide a systematic assessment of published research of multilevel modeling studies in 5 journals devoted to the research and practice of school psychology. In addition, a practical example from the nationally…

Does the Perceived Neighborhood Reputation Contribute to Neighborhood Differences in Social Trust and Residential Wellbeing?

ERIC Educational Resources Information Center

Kullberg, Agneta; Timpka, Toomas; Svensson, Tommy; Karlsson, Nadine; Lindqvist, Kent

2010-01-01

The authors used a mixed methods approach to examine if the reputation of a housing area has bearing on residential wellbeing and social trust in three pairs of socioeconomically contrasting neighborhoods in a Swedish urban municipality. Multilevel logistic regression analyses were performed to examine associations between area reputation and…

Family Structure and Child Mortality in Sub-Saharan Africa: Cross-National Effects of Polygyny

ERIC Educational Resources Information Center

Omariba, D. Walter Rasugu; Boyle, Michael H.

2007-01-01

This study applies multilevel logistic regression to Demographic and Health Survey data from 22 sub-Saharan African countries to examine whether the relationship between child mortality and family structure, with a specific emphasis on polygyny, varies cross-nationally and over time. Hypotheses were developed on the basis of competing theories on…

Exploring Person Fit with an Approach Based on Multilevel Logistic Regression

ERIC Educational Resources Information Center

Walker, A. Adrienne; Engelhard, George, Jr.

2015-01-01

The idea that test scores may not be valid representations of what students know, can do, and should learn next is well known. Person fit provides an important aspect of validity evidence. Person fit analyses at the individual student level are not typically conducted and person fit information is not communicated to educational stakeholders. In…

School Ethnic Composition and Aspirations of Immigrant Students in Belgium

ERIC Educational Resources Information Center

Van Houtte, Mieke; Stevens, Peter A. J.

2010-01-01

This article examines the association between school ethnic composition and immigrant students' intentions to finish high school and to move on to higher education. We used data from 1324 immigrant and 10,546 native students gathered in the school year 2004-2005 in a sample of 85 Flemish (Belgian) secondary schools. Logistic multilevel analyses…

An integrated and dynamic optimisation model for the multi-level emergency logistics network in anti-bioterrorism system

NASA Astrophysics Data System (ADS)

Liu, Ming; Zhao, Lindu

2012-08-01

Demand for emergency resources is usually uncertain and varies quickly in anti-bioterrorism system. Besides, emergency resources which had been allocated to the epidemic areas in the early rescue cycle will affect the demand later. In this article, an integrated and dynamic optimisation model with time-varying demand based on the epidemic diffusion rule is constructed. The heuristic algorithm coupled with the MATLAB mathematical programming solver is adopted to solve the optimisation model. In what follows, the application of the optimisation model as well as a short sensitivity analysis of the key parameters in the time-varying demand forecast model is presented. The results show that both the model and the solution algorithm are useful in practice, and both objectives of inventory level and emergency rescue cost can be controlled effectively. Thus, it can provide some guidelines for decision makers when coping with emergency rescue problem with uncertain demand, and offers an excellent reference when issues pertain to bioterrorism.

Deepening our Understanding of Quality in Australia (DUQuA): a study protocol for a nationwide, multilevel analysis of relationships between hospital quality management systems and patient factors.

PubMed

Taylor, Natalie; Clay-Williams, Robyn; Hogden, Emily; Pye, Victoria; Li, Zhicheng; Groene, Oliver; Suñol, Rosa; Braithwaite, Jeffrey

2015-12-07

Despite the growing body of research on quality and safety in healthcare, there is little evidence of the association between the way hospitals are organised for quality and patient factors, limiting our understanding of how to effect large-scale change. The 'Deepening our Understanding of Quality in Australia' (DUQuA) study aims to measure and examine relationships between (1) organisation and department-level quality management systems (QMS), clinician leadership and culture, and (2) clinical treatment processes, clinical outcomes and patient-reported perceptions of care within Australian hospitals. The DUQuA project is a national, multilevel, cross-sectional study with data collection at organisation (hospital), department, professional and patient levels. Sample size calculations indicate a minimum of 43 hospitals are required to adequately power the study. To allow for rejection and attrition, 70 hospitals across all Australian jurisdictions that meet the inclusion criteria will be invited to participate. Participants will consist of hospital quality management professionals; clinicians; and patients with stroke, acute myocardial infarction and hip fracture. Organisation and department-level QMS, clinician leadership and culture, patient perceptions of safety, clinical treatment processes, and patient outcomes will be assessed using validated, evidence-based or consensus-based measurement tools. Data analysis will consist of simple correlations, linear and logistic regression and multilevel modelling. Multilevel modelling methods will enable identification of the amount of variation in outcomes attributed to the hospital and department levels, and the factors contributing to this variation. Ethical approval has been obtained. Results will be disseminated to individual hospitals in de-identified national and international benchmarking reports with data-driven recommendations. This ground-breaking national study has the potential to influence decision-making on the implementation of quality and safety systems and processes in Australian and international hospitals. 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/

Do Health Care Providers Use Online Patient Ratings to Improve the Quality of Care? Results From an Online-Based Cross-Sectional Study.

PubMed

Emmert, Martin; Meszmer, Nina; Sander, Uwe

2016-09-19

Physician-rating websites have become a popular tool to create more transparency about the quality of health care providers. So far, it remains unknown whether online-based rating websites have the potential to contribute to a better standard of care. Our goal was to examine which health care providers use online rating websites and for what purposes, and whether health care providers use online patient ratings to improve patient care. We conducted an online-based cross-sectional study by surveying 2360 physicians and other health care providers (September 2015). In addition to descriptive statistics, we performed multilevel logistic regression models to ascertain the effects of providers' demographics as well as report card-related variables on the likelihood that providers implement measures to improve patient care. Overall, more than half of the responding providers surveyed (54.66%, 1290/2360) used online ratings to derive measures to improve patient care (implemented measures: mean 3.06, SD 2.29). Ophthalmologists (68%, 40/59) and gynecologists (65.4%, 123/188) were most likely to implement any measures. The most widely implemented quality measures were related to communication with patients (28.77%, 679/2360), the appointment scheduling process (23.60%, 557/2360), and office workflow (21.23%, 501/2360). Scaled-survey results had a greater impact on deriving measures than narrative comments. Multilevel logistic regression models revealed medical specialty, the frequency of report card use, and the appraisal of the trustworthiness of scaled-survey ratings to be significantly associated predictors for implementing measures to improve patient care because of online ratings. Our results suggest that online ratings displayed on physician-rating websites have an impact on patient care. Despite the limitations of our study and unintended consequences of physician-rating websites, they still may have the potential to improve patient care.

Individual and contextual determinants of self-reported poor psychological health: a population-based multilevel analysis in southern Sweden.

PubMed

Lindström, Martin; Moghaddassi, Mahnaz; Merlo, Juan

2006-01-01

To investigate the influence of contextual and individual factors on self-reported psychological health. The 2000 public health survey in Scania is a cross-sectional postal questionnaire study with a 59% participation rate. A total of 13,715 persons aged 18-80 answered the questionnaire. A multilevel logistic regression model, with individuals at the first level and municipalities/city quarters at the second, was performed. The effect (intra-class correlation, cross-level modification, and odds ratios) of individual and municipality/city quarter factors on self-reported psychological health was analysed. The crude variance between municipalities/city quarters was small but significant. It was particularly affected and lowered by individual civil status, country of origin, economic stress, and social participation. The inclusion of all individual factors age, sex, civil status, country of origin, education, economic stress, and social participation lowered the between municipality variance to not-significant levels, which is the reason why no contextual variables were included in the calculations. The results of this study suggest that poor self-reported psychological health is affected mainly by individual characteristics of the population and not by contextual factors at the municipality/city quarter level.

Travel time to maternity care and its effect on utilization in rural Ghana: a multilevel analysis.

PubMed

Masters, Samuel H; Burstein, Roy; Amofah, George; Abaogye, Patrick; Kumar, Santosh; Hanlon, Michael

2013-09-01

Rates of neonatal and maternal mortality are high in Ghana. In-facility delivery and other maternal services could reduce this burden, yet utilization rates of key maternal services are relatively low, especially in rural areas. We tested a theoretical implication that travel time negatively affects the use of in-facility delivery and other maternal services. Empirically, we used geospatial techniques to estimate travel times between populations and health facilities. To account for uncertainty in Ghana Demographic and Health Survey cluster locations, we adopted a novel approach of treating the location selection as an imputation problem. We estimated a multilevel random-intercept logistic regression model. For rural households, we found that travel time had a significant effect on the likelihood of in-facility delivery and antenatal care visits, holding constant education, wealth, maternal age, facility capacity, female autonomy, and the season of birth. In contrast, a facility's capacity to provide sophisticated maternity care had no detectable effect on utilization. As the Ghanaian health network expands, our results suggest that increasing the availability of basic obstetric services and improving transport infrastructure may be important interventions. Copyright © 2013 Elsevier Ltd. All rights reserved.

The great recession, youth unemployment and inequalities in psychological health complaints in adolescents: a multilevel study in 31 countries.

PubMed

Rathmann, Katharina; Pförtner, Timo-Kolja; Hurrelmann, Klaus; Osorio, Ana M; Bosakova, Lucia; Elgar, Frank J; Richter, Matthias

2016-09-01

Little is known about the impact of recessions on young people's socioeconomic inequalities in health. This study investigates the impact of the economic recession in terms of youth unemployment on socioeconomic inequalities in psychological health complaints among adolescents across Europe and North America. Data from the WHO collaborative 'Health Behaviour in School-aged Children' (HBSC) study were collected in 2005/06 (N = 160,830) and 2009/10 (N = 166,590) in 31 European and North American countries. Logistic multilevel models were used to assess the contribution of youth unemployment in 2009/10 (enduring recession) and the change in youth unemployment (2005-2010) to adolescent psychological health complaints and socioeconomic inequalities in complaints in 2009/10. Youth unemployment during the recession is positively related to psychological health complaints, but not to inequalities in complaints. Changes in youth unemployment (2005-2010) were not associated with adolescents' psychological health complaints, whereas greater inequalities in complaints were found in countries with greater increases in youth unemployment. This study highlights the need to tackle the impact of increasing unemployment on adolescent health and health inequalities during economic recessions.

Multiple imputation by chained equations for systematically and sporadically missing multilevel data.

PubMed

Resche-Rigon, Matthieu; White, Ian R

2018-06-01

In multilevel settings such as individual participant data meta-analysis, a variable is 'systematically missing' if it is wholly missing in some clusters and 'sporadically missing' if it is partly missing in some clusters. Previously proposed methods to impute incomplete multilevel data handle either systematically or sporadically missing data, but frequently both patterns are observed. We describe a new multiple imputation by chained equations (MICE) algorithm for multilevel data with arbitrary patterns of systematically and sporadically missing variables. The algorithm is described for multilevel normal data but can easily be extended for other variable types. We first propose two methods for imputing a single incomplete variable: an extension of an existing method and a new two-stage method which conveniently allows for heteroscedastic data. We then discuss the difficulties of imputing missing values in several variables in multilevel data using MICE, and show that even the simplest joint multilevel model implies conditional models which involve cluster means and heteroscedasticity. However, a simulation study finds that the proposed methods can be successfully combined in a multilevel MICE procedure, even when cluster means are not included in the imputation models.

The Impact of Ignoring the Level of Nesting Structure in Nonparametric Multilevel Latent Class Models

ERIC Educational Resources Information Center

Park, Jungkyu; Yu, Hsiu-Ting

2016-01-01

The multilevel latent class model (MLCM) is a multilevel extension of a latent class model (LCM) that is used to analyze nested structure data structure. The nonparametric version of an MLCM assumes a discrete latent variable at a higher-level nesting structure to account for the dependency among observations nested within a higher-level unit. In…

Multilevel Modeling in Psychosomatic Medicine Research

PubMed Central

Myers, Nicholas D.; Brincks, Ahnalee M.; Ames, Allison J.; Prado, Guillermo J.; Penedo, Frank J.; Benedict, Catherine

2012-01-01

The primary purpose of this manuscript is to provide an overview of multilevel modeling for Psychosomatic Medicine readers and contributors. The manuscript begins with a general introduction to multilevel modeling. Multilevel regression modeling at two-levels is emphasized because of its prevalence in psychosomatic medicine research. Simulated datasets based on some core ideas from the Familias Unidas effectiveness study are used to illustrate key concepts including: communication of model specification, parameter interpretation, sample size and power, and missing data. Input and key output files from Mplus and SAS are provided. A cluster randomized trial with repeated measures (i.e., three-level regression model) is then briefly presented with simulated data based on some core ideas from a cognitive behavioral stress management intervention in prostate cancer. PMID:23107843

Multilevel Higher-Order Item Response Theory Models

ERIC Educational Resources Information Center

Huang, Hung-Yu; Wang, Wen-Chung

2014-01-01

In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…

Conducting Multilevel Analyses in Medical Education

ERIC Educational Resources Information Center

Zyphur, Michael J.; Kaplan, Seth A.; Islam, Gazi; Barsky, Adam P.; Franklin, Michael S.

2008-01-01

A significant body of education literature has begun using multilevel statistical models to examine data that reside at multiple levels of analysis. In order to provide a primer for medical education researchers, the current work gives a brief overview of some issues associated with multilevel statistical modeling. To provide an example of this…

Influence of municipal- and individual-level socioeconomic conditions on mortality in Japan.

PubMed

Honjo, Kaori; Iso, Hiroyasu; Fukuda, Yoshiharu; Nishi, Nobuo; Nakaya, Tomoki; Fujino, Yoshihisa; Tanabe, Naohito; Suzuki, Sadao; Subramanian, S V; Tamakoshi, Akiko

2014-01-01

The health effect of area socioeconomic conditions has been evident especially in Western countries; however, limited research has focused on the effect of municipal-level socioeconomic conditions, especially in Asia. Multilevel research using data from the Japan Collaborative Cohort Study, a large cohort study followed from 1990 to 2006, was conducted to examine individual as well as municipal socioeconomic conditions on risk of death, adjusting for each other. We included 24,460 men and 32,649 women aged 40 to 65 years at baseline in 35 municipalities as our study population. Primary predictors were municipal socioeconomic conditions (proportion of college graduates, per capita income, unemployment rate, and proportion of households receiving public assistance) and individual socioeconomic conditions (education level and occupation). Among men, the multilevel logistic estimate (standard errors) of proportion of college graduates and unemployment rate for mortality from cardiovascular disease were -0.399 (0.094) and -0.343 (0.122), respectively. Among women, the multilevel logistic estimate (standard errors) of proportion of college graduates and per capita annual income for mortality from injuries were -0.386 (0.171) and -1.069 (0.407). Individual education level and occupation were associated with all-cause mortality, in particular, mortality from cardiovascular disease or injuries. Interactions between individual education level and indicators of municipal socioeconomic conditions were observed for mortality from cancer and cardiovascular disease among men and mortality from injuries among women. Municipal and individual socioeconomic conditions were independently and interactively associated with premature death; this suggests that reducing social inequalities in health demands a focus on municipal conditions in addition to those of individuals.

Analyzing Multiple Outcomes in Clinical Research Using Multivariate Multilevel Models

PubMed Central

Baldwin, Scott A.; Imel, Zac E.; Braithwaite, Scott R.; Atkins, David C.

2014-01-01

Objective Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers. Method and Results Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix provides annotated computer code and simulated example data for implementing a multivariate model. Conclusions Multivariate multilevel models are flexible, powerful models that can enhance clinical research. PMID:24491071

Relationships between Religion and Two Forms of Homonegativity in Europe--A Multilevel Analysis of Effects of Believing, Belonging and Religious Practice.

PubMed

Doebler, Stefanie

2015-01-01

This paper examines relationships between religion and two forms of homonegativity across 43 European countries using a bivariate response binary logistic multilevel model. The model analyzes effects of religious believing, belonging and practice on two response variables: a) a moral rejection of homosexuality as a practice and b) intolerance toward homosexuals as a group. The findings indicate that both forms of homonegativity are prevalent in Europe. Traditional doctrinal religious believing (belief in a personal God) is positively related to a moral rejection of homosexuality but to a much lesser extent associated with intolerance toward homosexuals as a group. Members of religious denominations are more likely than non-members to reject homosexuality as morally wrong and to reject homosexuals as neighbors. The analysis found significant differences between denominations that are likely context-dependent. Attendance at religious services is positively related to homonegativity in a majority of countries. The findings vary considerably across countries: Religion is more strongly related to homonegativity in Western than in Eastern Europe. In the post-soviet countries homonegativity appears to be largely a secular phenomenon. National contexts of high religiosity, high perceived government corruption, high income inequality and shortcomings in the implementation of gay rights in the countries' legislations are statistically related to higher levels of both moralistic homonegativity and intolerance toward homosexuals as a group.

Relationships between Religion and Two Forms of Homonegativity in Europe—A Multilevel Analysis of Effects of Believing, Belonging and Religious Practice

PubMed Central

Doebler, Stefanie

2015-01-01

This paper examines relationships between religion and two forms of homonegativity across 43 European countries using a bivariate response binary logistic multilevel model. The model analyzes effects of religious believing, belonging and practice on two response variables: a) a moral rejection of homosexuality as a practice and b) intolerance toward homosexuals as a group. The findings indicate that both forms of homonegativity are prevalent in Europe. Traditional doctrinal religious believing (belief in a personal God) is positively related to a moral rejection of homosexuality but to a much lesser extent associated with intolerance toward homosexuals as a group. Members of religious denominations are more likely than non-members to reject homosexuality as morally wrong and to reject homosexuals as neighbors. The analysis found significant differences between denominations that are likely context-dependent. Attendance at religious services is positively related to homonegativity in a majority of countries. The findings vary considerably across countries: Religion is more strongly related to homonegativity in Western than in Eastern Europe. In the post-soviet countries homonegativity appears to be largely a secular phenomenon. National contexts of high religiosity, high perceived government corruption, high income inequality and shortcomings in the implementation of gay rights in the countries’ legislations are statistically related to higher levels of both moralistic homonegativity and intolerance toward homosexuals as a group. PMID:26247352

Is an index of co-occurring unhealthy lifestyles suitable for understanding migrant health?

PubMed

Feng, Xiaoqi; Astell-Burt, Thomas; Kolt, Gregory S

2014-12-01

This study investigated variation in unhealthy lifestyles within Australia according to where people were born. Multilevel linear regression models were used to explore variation in co-occurring unhealthy lifestyles (from 0 to 8) constructed from responses to tobacco smoking, alcohol consumption, moderate-to-vigorous physical activity and a range of dietary indicators for 217,498 adults born in 22 different countries now living in Australia. Models were adjusted for socio-economic variables. Data was from the 45 and Up Study (2006-2009). Further analyses involved multilevel logistic regression to examine country-of-birth patterning of each individual unhealthy lifestyle. Small differences in the co-occurrence of unhealthy lifestyles were observed by country of birth, ranging from 3.1 (Philippines) to 3.8 (Russia). More substantial variation was observed for each individual unhealthy lifestyle. Smoking and alcohol ranged from 7.3% and 4.2% (both China) to 28.5% (Lebanon) and 30.8% (Ireland) respectively. Non-adherence to physical activity guidelines was joint-highest among participants born in Japan and China (both 74.5%), but lowest among those born in Scandinavian countries (52.5%). Substantial variation in meeting national dietary guidelines was also evident between participants born in different countries. The growing trend for constructing unhealthy lifestyle indices can hide important variation in individual unhealthy lifestyles by country of birth. Copyright © 2014. Published by Elsevier Inc.

Socio-demographic predictors and average annual rates of caesarean section in Bangladesh between 2004 and 2014.

PubMed

Khan, Md Nuruzzaman; Islam, M Mofizul; Shariff, Asma Ahmad; Alam, Md Mahmudul; Rahman, Md Mostafizur

2017-01-01

Globally the rates of caesarean section (CS) have steadily increased in recent decades. This rise is not fully accounted for by increases in clinical factors which indicate the need for CS. We investigated the socio-demographic predictors of CS and the average annual rates of CS in Bangladesh between 2004 and 2014. Data were derived from four waves of nationally representative Bangladesh Demographic and Health Survey (BDHS) conducted between 2004 and 2014. Rate of change analysis was used to calculate the average annual rate of increase in CS from 2004 to 2014, by socio-demographic categories. Multi-level logistic regression was used to identify the socio-demographic predictors of CS in a cross-sectional analysis of the 2014 BDHS data. CS rates increased from 3.5% in 2004 to 23% in 2014. The average annual rate of increase in CS was higher among women of advanced maternal age (≥35 years), urban areas, and relatively high socio-economic status; with higher education, and who regularly accessed antenatal services. The multi-level logistic regression model indicated that lower (≤19) and advanced maternal age (≥35), urban location, relatively high socio-economic status, higher education, birth of few children (≤2), antenatal healthcare visits, overweight or obese were the key factors associated with increased utilization of CS. Underweight was a protective factor for CS. The use of CS has increased considerably in Bangladesh over the survey years. This rising trend and the risk of having CS vary significantly across regions and socio-economic status. Very high use of CS among women of relatively high socio-economic status and substantial urban-rural difference call for public awareness and practice guideline enforcement aimed at optimizing the use of CS.

Socio-demographic predictors and average annual rates of caesarean section in Bangladesh between 2004 and 2014

PubMed Central

Khan, Md. Nuruzzaman; Islam, M. Mofizul; Shariff, Asma Ahmad; Alam, Md. Mahmudul; Rahman, Md. Mostafizur

2017-01-01

Background Globally the rates of caesarean section (CS) have steadily increased in recent decades. This rise is not fully accounted for by increases in clinical factors which indicate the need for CS. We investigated the socio-demographic predictors of CS and the average annual rates of CS in Bangladesh between 2004 and 2014. Methods Data were derived from four waves of nationally representative Bangladesh Demographic and Health Survey (BDHS) conducted between 2004 and 2014. Rate of change analysis was used to calculate the average annual rate of increase in CS from 2004 to 2014, by socio-demographic categories. Multi-level logistic regression was used to identify the socio-demographic predictors of CS in a cross-sectional analysis of the 2014 BDHS data. Result CS rates increased from 3.5% in 2004 to 23% in 2014. The average annual rate of increase in CS was higher among women of advanced maternal age (≥35 years), urban areas, and relatively high socio-economic status; with higher education, and who regularly accessed antenatal services. The multi-level logistic regression model indicated that lower (≤19) and advanced maternal age (≥35), urban location, relatively high socio-economic status, higher education, birth of few children (≤2), antenatal healthcare visits, overweight or obese were the key factors associated with increased utilization of CS. Underweight was a protective factor for CS. Conclusion The use of CS has increased considerably in Bangladesh over the survey years. This rising trend and the risk of having CS vary significantly across regions and socio-economic status. Very high use of CS among women of relatively high socio-economic status and substantial urban-rural difference call for public awareness and practice guideline enforcement aimed at optimizing the use of CS. PMID:28493956

Is physician adherence to prescription guidelines a general trait of health care practices or dependent on drug type?--a multilevel logistic regression analysis in South Sweden.

PubMed

Ohlsson, Henrik; Merlo, Juan

2009-08-01

Therapeutic traditions at health care practices (HCPs) influence physicians' adherence to prescription guidelines for specific drugs, however, it is not known if such traditions affect all kinds of prescriptions or only specific types of drug. Our goal was to determine whether adherence to prescription guidelines is a common trait of HCPs or dependent on drug type. We fitted separate multi-level logistic regression models to all patients in the Skåne region who received a prescription for a statin drug (ATC: C10AA, n = 6232), an agent acting on the renin-angiotensin system (ATC: C09, n = 7222) or a proton pump inhibitor (ATC: A02BC, n = 11 563) at 198 HCPs from July 2006 to December 2006. There was a high clustering of adherence to prescription guidelines at HCPs for the different drug types (MOR(agents acting on the renin-angiotensin system) = 4.72 [95% CI: 3.90-5.92], MOR(Statins) = 2.71 [95% CI: 2.23-3.39] and MOR(Proton pump inhibitors) = 2.16 [95% CI: 1.95-2.45]). Compared with HCPs with low adherence to guidelines in two drug types, those HCPs with the highest level of adherence for these two drug types also showed a higher probability of adherence for the third drug type. Physicians' decisions to follow prescription guidelines seem to be influenced by therapeutic traditions at the HCP. Moreover, these therapeutic traditions seem to affect all kinds of prescriptions. This information can be used as basis for interventions to support rational and cost-effective medication use. Copyright 2009 John Wiley & Sons, Ltd.

Constructing and validating readability models: the method of integrating multilevel linguistic features with machine learning.

PubMed

Sung, Yao-Ting; Chen, Ju-Ling; Cha, Ji-Her; Tseng, Hou-Chiang; Chang, Tao-Hsing; Chang, Kuo-En

2015-06-01

Multilevel linguistic features have been proposed for discourse analysis, but there have been few applications of multilevel linguistic features to readability models and also few validations of such models. Most traditional readability formulae are based on generalized linear models (GLMs; e.g., discriminant analysis and multiple regression), but these models have to comply with certain statistical assumptions about data properties and include all of the data in formulae construction without pruning the outliers in advance. The use of such readability formulae tends to produce a low text classification accuracy, while using a support vector machine (SVM) in machine learning can enhance the classification outcome. The present study constructed readability models by integrating multilevel linguistic features with SVM, which is more appropriate for text classification. Taking the Chinese language as an example, this study developed 31 linguistic features as the predicting variables at the word, semantic, syntax, and cohesion levels, with grade levels of texts as the criterion variable. The study compared four types of readability models by integrating unilevel and multilevel linguistic features with GLMs and an SVM. The results indicate that adopting a multilevel approach in readability analysis provides a better representation of the complexities of both texts and the reading comprehension process.

Mathematical model comparing of the multi-level economics systems

NASA Astrophysics Data System (ADS)

Brykalov, S. M.; Kryanev, A. V.

2017-12-01

The mathematical model (scheme) of a multi-level comparison of the economic system, characterized by the system of indices, is worked out. In the mathematical model of the multi-level comparison of the economic systems, the indicators of peer review and forecasting of the economic system under consideration can be used. The model can take into account the uncertainty in the estimated values of the parameters or expert estimations. The model uses the multi-criteria approach based on the Pareto solutions.

An Exploration of Teacher Attrition and Mobility in High Poverty Racially Segregated Schools

ERIC Educational Resources Information Center

Djonko-Moore, Cara M.

2016-01-01

The purpose of this study was to examine the mobility (movement to a new school) and attrition (quitting teaching) patterns of teachers in high poverty, racially segregated (HPRS) schools in the US. Using 2007-9 survey data from the National Center for Education Statistics, a multi-level multinomial logistic regression was performed to examine the…

Hospitalization of Nursing Home Residents with Cognitive Impairments: The Influence of Organizational Features and State Policies

ERIC Educational Resources Information Center

Gruneir, Andrea; Miller, Susan C.; Intrator, Orna; Mor, Vincent

2007-01-01

Purpose: The purpose of this study was to quantify the effect of specific nursing home features and state Medicaid policies on the risk of hospitalization among cognitively impaired nursing home residents. Design and Methods: We used multilevel logistic regression to estimate the odds of hospitalization among long-stay (greater than 90 days)…

Multilevel corporate environmental responsibility.

PubMed

Karassin, Orr; Bar-Haim, Aviad

2016-12-01

The multilevel empirical study of the antecedents of corporate social responsibility (CSR) has been identified as "the first knowledge gap" in CSR research. Based on an extensive literature review, the present study outlines a conceptual multilevel model of CSR, then designs and empirically validates an operational multilevel model of the principal driving factors affecting corporate environmental responsibility (CER), as a measure of CSR. Both conceptual and operational models incorporate three levels of analysis: institutional, organizational, and individual. The multilevel nature of the design allows for the assessment of the relative importance of the levels and of their components in the achievement of CER. Unweighted least squares (ULS) regression analysis reveals that the institutional-level variables have medium relationships with CER, some variables having a negative effect. The organizational level is revealed as having strong and positive significant relationships with CER, with organizational culture and managers' attitudes and behaviors as significant driving forces. The study demonstrates the importance of multilevel analysis in improving the understanding of CSR drivers, relative to single level models, even if the significance of specific drivers and levels may vary by context. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cross-national differences in the gender gap in subjective health in Europe: does country-level gender equality matter?

PubMed

Dahlin, Johanna; Härkönen, Juho

2013-12-01

Multiple studies have found that women report being in worse health despite living longer. Gender gaps vary cross-nationally, but relatively little is known about the causes of comparative differences. Existing literature is inconclusive as to whether gender gaps in health are smaller in more gender equal societies. We analyze gender gaps in self-rated health (SRH) and limiting longstanding illness (LLI) with five waves of European Social Survey data for 191,104 respondents from 28 countries. We use means, odds ratios, logistic regressions, and multilevel random slopes logistic regressions. Gender gaps in subjective health vary visibly across Europe. In many countries (especially in Eastern and Southern Europe), women report distinctly worse health, while in others (such as Estonia, Finland, and Great Britain) there are small or no differences. Logistic regressions ran separately for each country revealed that individual-level socioeconomic and demographic variables explain a majority of these gaps in some countries, but contribute little to their understanding in most countries. In yet other countries, men had worse health when these variables were controlled for. Cross-national variation in the gender gaps exists after accounting for individual-level factors. Against expectations, the remaining gaps are not systematically related to societal-level gender inequality in the multilevel analyses. Our findings stress persistent cross-national variability in gender gaps in health and call for further analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Exploring alternate specifications to explain agency-level effects in placement decisions regarding aboriginal children: further analysis of the Canadian Incidence Study of Reported Child Abuse and Neglect Part B.

PubMed

Chabot, Martin; Fallon, Barbara; Tonmyr, Lil; MacLaurin, Bruce; Fluke, John; Blackstock, Cindy

2013-01-01

This paper builds upon the analyses presented in two companion papers (Fluke et al., 2010; Fallon et al., 2013) using data from the 1998 and 2003 cycles of the Canadian Incidence Study of Reported Child Abuse and Neglect (CIS-1998 and CIS-2003) to examine the influence of clinical and organizational characteristics on the decision to place a child in out-of-home care at the conclusion of a child maltreatment investigation. This paper explores various model specifications to explain the effect of an agency-level factor, proportion of Aboriginal reports, which emerged as a stable and significant factor through the two data collection cycles. It addresses the issue of data comparability between the two cycles and explores various re-specifications and descriptive analyses of reported models to evaluate their solidity with regards to the sampling schemes and the precise contribution of a multi-level specification. The decision to place a child in out-of-home care was examined using data from the CIS-2003. This child welfare dataset collected information about the results of nearly 12,000 child maltreatment investigations as well as a description of the characteristics of the workers and organization responsible for conducting those investigations. Multi-level statistical models were developed using MPlus software, which can accommodate dichotomous outcome variables and are more reflective of decision-making in child welfare. The models are thus multi-level binary logistic regressions. Final models revealed that two agency-level variables, 'Education degree of majority of workers' and 'Degree of centralization in the agency' clarify the nature of the effect of 'Proportion of Aboriginal reports', a stable, key second level predictor of the placement decision. The comparability of the effect of this agency-level variable across the 1998 and 2003 cycles becomes further evident through this analysis. By using a unified database including both cycles and various specifications of models, the comparability was found to be robust, in addition to clarifying the precise contribution of a multi-level specification. This third paper in a series establishes the 'Proportion of Aboriginal reports' received by the child welfare agency as an important agency level predictor associated with a child's likelihood of being placed in the Canadian child protection system. While the more complex models give support to the notion that unequal resources subtend those results, more analyses are needed to confirm this hypothesis. Unequal resources for agencies with larger Aboriginal caseloads may explain the persistence of the results. These findings suggest that specific resource constraints related to worker education may be explanatory. Copyright © 2012 Elsevier Ltd. All rights reserved.

Macro-level gender equality and alcohol consumption: a multi-level analysis across U.S. States.

PubMed

Roberts, Sarah C M

2012-07-01

Higher levels of women's alcohol consumption have long been attributed to increases in gender equality. However, only limited research examines the relationship between gender equality and alcohol consumption. This study examined associations between five measures of state-level gender equality and five alcohol consumption measures in the United States. Survey data regarding men's and women's alcohol consumption from the 2005 Behavioral Risk Factor Surveillance System were linked to state-level indicators of gender equality. Gender equality indicators included state-level women's socioeconomic status, gender equality in socioeconomic status, reproductive rights, policies relating to violence against women, and women's political participation. Alcohol consumption measures included past 30-day drinker status, drinking frequency, binge drinking, volume, and risky drinking. Other than drinker status, consumption is measured for drinkers only. Multi-level linear and logistic regression models adjusted for individual demographics as well as state-level income inequality, median income, and % Evangelical Protestant/Mormon. All gender equality indicators were positively associated with both women's and men's drinker status in models adjusting only for individual-level covariates; associations were not significant in models adjusting for other state-level characteristics. All other associations between gender equality and alcohol consumption were either negative or non-significant for both women and men in models adjusting for other state-level factors. Findings do not support the hypothesis that higher levels of gender equality are associated with higher levels of alcohol consumption by women or by men. In fact, most significant findings suggest that higher levels of equality are associated with less alcohol consumption overall. Copyright © 2012 Elsevier Ltd. All rights reserved.

Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection by Streptococcus pneumoniae Identified in Multi-Level Mathematical Modeling

PubMed Central

Santos, Guido; Lai, Xin; Eberhardt, Martin; Vera, Julio

2018-01-01

Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By “multi-level” we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization. PMID:29868515

Comparisons of Multilevel Modeling and Structural Equation Modeling Approaches to Actor-Partner Interdependence Model.

PubMed

Hong, Sehee; Kim, Soyoung

2018-01-01

There are basically two modeling approaches applicable to analyzing an actor-partner interdependence model: the multilevel modeling (hierarchical linear model) and the structural equation modeling. This article explains how to use these two models in analyzing an actor-partner interdependence model and how these two approaches work differently. As an empirical example, marital conflict data were used to analyze an actor-partner interdependence model. The multilevel modeling and the structural equation modeling produced virtually identical estimates for a basic model. However, the structural equation modeling approach allowed more realistic assumptions on measurement errors and factor loadings, rendering better model fit indices.

Self-rated health in Canadian immigrants: analysis of the Longitudinal Survey of Immigrants to Canada.

PubMed

Setia, Maninder Singh; Lynch, John; Abrahamowicz, Michal; Tousignant, Pierre; Quesnel-Vallee, Amelie

2011-03-01

Using a multi-level random effects logistic model, we examine the contribution of source country, individual characteristics and post-migration experiences to the self-rated health (SRH) of 2468 male and 2614 female immigrants from the Longitudinal Survey of Immigrants to Canada (2001-2005). Sex/gender differences were found for all categories of health determinants. Source country characteristics explained away some ethnic differentials in health and had independent negative effects, particularly among women. Thus, women from countries lower on the development index appear at greater risk of poor SRH, and should be at the forefront of public health programmes aimed at new immigrants in Canada. Copyright © 2011 Elsevier Ltd. All rights reserved.

Sources of Interactional Problems in a Survey of Racial/Ethnic Discrimination

PubMed Central

Johnson, Timothy P.; Shariff-Marco, Salma; Willis, Gordon; Cho, Young Ik; Breen, Nancy; Gee, Gilbert C.; Krieger, Nancy; Grant, David; Alegria, Margarita; Mays, Vickie M.; Williams, David R.; Landrine, Hope; Liu, Benmei; Reeve, Bryce B.; Takeuchi, David; Ponce, Ninez A.

2014-01-01

Cross-cultural variability in respondent processing of survey questions may bias results from multiethnic samples. We analyzed behavior codes, which identify difficulties in the interactions of respondents and interviewers, from a discrimination module contained within a field test of the 2007 California Health Interview Survey. In all, 553 (English) telephone interviews yielded 13,999 interactions involving 22 items. Multilevel logistic regression modeling revealed that respondent age and several item characteristics (response format, customized questions, length, and first item with new response format), but not race/ethnicity, were associated with interactional problems. These findings suggest that item function within a multi-cultural, albeit English language, survey may be largely influenced by question features, as opposed to respondent characteristics such as race/ethnicity. PMID:26166949

Influence of health providers on pediatrics' immunization rate.

PubMed

Al-lela, Omer Q B; Baidi Bahari, Mohd; Al-abbassi, Mustafa G; Salih, Muhannad R M; Basher, Amena Y

2012-12-01

To identify the immunization providers' characteristics associated with immunization rate in children younger than 2 years. A cohort and a cluster sampling design were implemented; 528 children between 18 and 70 months of age were sampled in five public health clinics in Mosul-Iraq. Providers' characterizations were obtained. Immunization rate for the children was assessed. Risk factors for partial immunization were explored using both bivariate analyses and multi-level logistic regression models. Less than half of the children had one or more than one missed dose, considered as partial immunization cases. The study found significant association of immunization rate with provider's type. Two factors were found that strongly impacted on immunization rate in the presence of other factors: birthplace and immunization providers' type.

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

A Multilevel AR(1) Model: Allowing for Inter-Individual Differences in Trait-Scores, Inertia, and Innovation Variance.

PubMed

Jongerling, Joran; Laurenceau, Jean-Philippe; Hamaker, Ellen L

2015-01-01

In this article we consider a multilevel first-order autoregressive [AR(1)] model with random intercepts, random autoregression, and random innovation variance (i.e., the level 1 residual variance). Including random innovation variance is an important extension of the multilevel AR(1) model for two reasons. First, between-person differences in innovation variance are important from a substantive point of view, in that they capture differences in sensitivity and/or exposure to unmeasured internal and external factors that influence the process. Second, using simulation methods we show that modeling the innovation variance as fixed across individuals, when it should be modeled as a random effect, leads to biased parameter estimates. Additionally, we use simulation methods to compare maximum likelihood estimation to Bayesian estimation of the multilevel AR(1) model and investigate the trade-off between the number of individuals and the number of time points. We provide an empirical illustration by applying the extended multilevel AR(1) model to daily positive affect ratings from 89 married women over the course of 42 consecutive days.

Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic.

PubMed

Neumayr, Bernd; Schuetz, Christoph G; Jeusfeld, Manfred A; Schrefl, Michael

2018-01-01

An enterprise database contains a global, integrated, and consistent representation of a company's data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data requirements of diverse applications. Multi-level models transcend the traditional separation of class and object with clabjects as the central modeling primitive, which allows for a more flexible and natural representation of many real-world use cases. In deep instantiation, the number of instantiation levels of a clabject or property is indicated by a single potency. Dual deep modeling (DDM) differentiates between source potency and target potency of a property or association and supports the flexible instantiation and refinement of the property by statements connecting clabjects at different modeling levels. DDM comes with multiple generalization of clabjects, subsetting/specialization of properties, and multi-level cardinality constraints. Examples are presented using a UML-style notation for DDM together with UML class and object diagrams for the representation of two-level user views derived from the multi-level model. Syntax and semantics of DDM are formalized and implemented in F-Logic, supporting the modeler with integrity checks and rich query facilities.

A multilevel analysis of lifestyle variations in symptoms of acute respiratory infection among young children under five in Nigeria.

PubMed

Adesanya, Oluwafunmilade A; Chiao, Chi

2016-08-25

Nigeria has the second highest estimated number of deaths due to acute respiratory infection (ARI) among children under five in the world. A common hypothesis is that the inequitable distribution of socioeconomic resources shapes individual lifestyles and health behaviors, which leads to poorer health, including symptoms of ARI. This study examined whether lifestyle factors are associated with ARI risk among Nigerian children aged less than 5 years, taking individual-level and contextual-level risk factors into consideration. Data were obtained from the nationally representative 2013 Nigeria Demographic and Health Survey. A total of 28,596 surviving children aged 5 years or younger living in 896 communities were analyzed. We employed two-level multilevel logistic regressions to model the relationship between lifestyle factors and ARI symptoms. The multivariate results from multilevel regressions indicated that the odds of having ARI symptoms were increased by a number of lifestyle factors such as in-house biomass cooking (OR = 2.30; p < 0.01) and no hand-washing (OR = 1.66; p < 0.001). An increased risk of ARI symptoms was also significantly associated with living in the North West region and the community with a high proportion of orphaned/vulnerable children (OR = 1.74; p < 0.001). Our findings underscore the importance of Nigerian children's lifestyle within the neighborhoods where they reside above their individual characteristics. Program-based strategies that are aimed at reducing ARI symptoms should consider policies that embrace making available basic housing standards, providing improved cooking stoves and enhancing healthy behaviors.

The relationship between session frequency and psychotherapy outcome in a naturalistic setting.

PubMed

Erekson, David M; Lambert, Michael J; Eggett, Dennis L

2015-12-01

The dose-response relationship in psychotherapy has been examined extensively, but few studies have included session frequency as a component of psychotherapy "dose." Studies that have examined session frequency have indicated that it may affect both the speed and the amount of recovery. No studies were found examining the clinical significance of this construct in a naturalistic setting, which is the aim of the current study. Using an archival database of session-by-session Outcome Questionnaire 45 (OQ-45) measures over 17 years, change trajectories of 21,488 university counseling center clients (54.9% female, 85.0% White, mean age = 22.5) were examined using multilevel modeling, including session frequency at the occasion level. Of these clients, subgroups that attended therapy approximately weekly or fortnightly were compared to each other for differences in speed of recovery (using multilevel Cox regression) and clinically significant change (using multilevel logistic regression). Results indicated that more frequent therapy was associated with steeper recovery curves (Cohen's f2 = 0.07; an effect size between small and medium). When comparing weekly and fortnightly groups, clinically significant gains were achieved faster for those attending weekly sessions; however, few significant differences were found between groups in total amount of change in therapy. Findings replicated previous session frequency literature and supported a clinically significant effect, where higher session frequency resulted in faster recovery. Session frequency appears to be an impactful component in delivering more efficient psychotherapy, and it is important to consider in individual treatment planning, institutional policy, and future research. (c) 2015 APA, all rights reserved).

Estimating trajectories of energy intake through childhood and adolescence using linear-spline multilevel models.

PubMed

Anderson, Emma L; Tilling, Kate; Fraser, Abigail; Macdonald-Wallis, Corrie; Emmett, Pauline; Cribb, Victoria; Northstone, Kate; Lawlor, Debbie A; Howe, Laura D

2013-07-01

Methods for the assessment of changes in dietary intake across the life course are underdeveloped. We demonstrate the use of linear-spline multilevel models to summarize energy-intake trajectories through childhood and adolescence and their application as exposures, outcomes, or mediators. The Avon Longitudinal Study of Parents and Children assessed children's dietary intake several times between ages 3 and 13 years, using both food frequency questionnaires (FFQs) and 3-day food diaries. We estimated energy-intake trajectories for 12,032 children using linear-spline multilevel models. We then assessed the associations of these trajectories with maternal body mass index (BMI), and later offspring BMI, and also their role in mediating the relation between maternal and offspring BMIs. Models estimated average and individual energy intake at 3 years, and linear changes in energy intake from age 3 to 7 years and from age 7 to 13 years. By including the exposure (in this example, maternal BMI) in the multilevel model, we were able to estimate the average energy-intake trajectories across levels of the exposure. When energy-intake trajectories are the exposure for a later outcome (in this case offspring BMI) or a mediator (between maternal and offspring BMI), results were similar, whether using a two-step process (exporting individual-level intercepts and slopes from multilevel models and using these in linear regression/path analysis), or a single-step process (multivariate multilevel models). Trajectories were similar when FFQs and food diaries were assessed either separately, or when combined into one model. Linear-spline multilevel models provide useful summaries of trajectories of dietary intake that can be used as an exposure, outcome, or mediator.

A 2 x 2 Taxonomy of Multilevel Latent Contextual Models: Accuracy-Bias Trade-Offs in Full and Partial Error Correction Models

ERIC Educational Resources Information Center

Ludtke, Oliver; Marsh, Herbert W.; Robitzsch, Alexander; Trautwein, Ulrich

2011-01-01

In multilevel modeling, group-level variables (L2) for assessing contextual effects are frequently generated by aggregating variables from a lower level (L1). A major problem of contextual analyses in the social sciences is that there is no error-free measurement of constructs. In the present article, 2 types of error occurring in multilevel data…

Translating multilevel theory into multilevel research: Challenges and opportunities for understanding the social determinants of psychiatric disorders

PubMed Central

Dunn, Erin C.; Masyn, Katherine E.; Yudron, Monica; Jones, Stephanie M.; Subramanian, S.V.

2014-01-01

The observation that features of the social environment, including family, school, and neighborhood characteristics, are associated with individual-level outcomes has spurred the development of dozens of multilevel or ecological theoretical frameworks in epidemiology, public health, psychology, and sociology, among other disciplines. Despite the widespread use of such theories in etiological, intervention, and policy studies, challenges remain in bridging multilevel theory and empirical research. This paper set out to synthesize these challenges and provide specific examples of methodological and analytical strategies researchers are using to gain a more nuanced understanding of the social determinants of psychiatric disorders, with a focus on children’s mental health. To accomplish this goal, we begin by describing multilevel theories, defining their core elements, and discussing what these theories suggest is needed in empirical work. In the second part, we outline the main challenges researchers face in translating multilevel theory into research. These challenges are presented for each stage of the research process. In the third section, we describe two methods being used as alternatives to traditional multilevel modeling techniques to better bridge multilevel theory and multilevel research. These are: (1) multilevel factor analysis and multilevel structural equation modeling; and (2) dynamic systems approaches. Through its review of multilevel theory, assessment of existing strategies, and examination of emerging methodologies, this paper offers a framework to evaluate and guide empirical studies on the social determinants of child psychiatric disorders as well as health across the lifecourse. PMID:24469555

Generalized Multilevel Structural Equation Modeling

ERIC Educational Resources Information Center

Rabe-Hesketh, Sophia; Skrondal, Anders; Pickles, Andrew

2004-01-01

A unifying framework for generalized multilevel structural equation modeling is introduced. The models in the framework, called generalized linear latent and mixed models (GLLAMM), combine features of generalized linear mixed models (GLMM) and structural equation models (SEM) and consist of a response model and a structural model for the latent…

An Integrative, Multilevel, and Transdisciplinary Research Approach to Challenges of Work, Family, and Health

PubMed Central

Bray, Jeremy W.; Kelly, Erin L.; Hammer, Leslie B.; Almeida, David M.; Dearing, James W.; King, Rosalind B.; Buxton, Orfeu M.

2013-01-01

Recognizing a need for rigorous, experimental research to support the efforts of workplaces and policymakers in improving the health and wellbeing of employees and their families, the National Institutes of Health and the Centers for Disease Control and Prevention formed the Work, Family & Health Network (WFHN). The WFHN is implementing an innovative multisite study with a rigorous experimental design (adaptive randomization, control groups), comprehensive multilevel measures, a novel and theoretically based intervention targeting the psychosocial work environment, and translational activities. This paper describes challenges and benefits of designing a multilevel and transdisciplinary research network that includes an effectiveness study to assess intervention effects on employees, families, and managers; a daily diary study to examine effects on family functioning and daily stress; a process study to understand intervention implementation; and translational research to understand and inform diffusion of innovation. Challenges were both conceptual and logistical, spanning all aspects of study design and implementation. In dealing with these challenges, however, the WFHN developed innovative, transdisciplinary, multi-method approaches to conducting workplace research that will benefit both the research and business communities. PMID:24618878

Dental Care Utilization for Examination and Regional Deprivation

PubMed Central

Kim, Cheol-Sin; Han, Sun-Young; Lee, Seung Eun; Kang, Jeong-Hee; Kim, Chul-Woung

2015-01-01

Objectives: Receiving proper dental care plays a significant role in maintaining good oral health. We investigated the relationship between regional deprivation and dental care utilization. Methods: Multilevel logistic regression was used to identify the relationship between the regional deprivation level and dental care utilization purpose, adjusting for individual-level variables, in adults aged 19+ in the 2008 Korean Community Health Survey (n=220 258). Results: Among Korean adults, 12.8% used dental care to undergo examination and 21.0% visited a dentist for other reasons. In the final model, regional deprivation level was associated with significant variations in dental care utilization for examination (p<0.001). However, this relationship was not shown with dental care utilization for other reasons in the final model. Conclusions: This study’s findings suggest that policy interventions should be considered to reduce regional variations in rates of dental care utilization for examination. PMID:26265665

A Methodological Review of Statistical Methods for Handling Multilevel Non-Nested Longitudinal Data in Educational Research

ERIC Educational Resources Information Center

Sun, Shuyan; Pan, Wei

2014-01-01

As applications of multilevel modelling in educational research increase, researchers realize that multilevel data collected in many educational settings are often not purely nested. The most common multilevel non-nested data structure is one that involves student mobility in longitudinal studies. This article provides a methodological review of…

Using multilevel models to quantify heterogeneity in resource selection

USGS Publications Warehouse

Wagner, Tyler; Diefenbach, Duane R.; Christensen, Sonja; Norton, Andrew S.

2011-01-01

Models of resource selection are being used increasingly to predict or model the effects of management actions rather than simply quantifying habitat selection. Multilevel, or hierarchical, models are an increasingly popular method to analyze animal resource selection because they impose a relatively weak stochastic constraint to model heterogeneity in habitat use and also account for unequal sample sizes among individuals. However, few studies have used multilevel models to model coefficients as a function of predictors that may influence habitat use at different scales or quantify differences in resource selection among groups. We used an example with white-tailed deer (Odocoileus virginianus) to illustrate how to model resource use as a function of distance to road that varies among deer by road density at the home range scale. We found that deer avoidance of roads decreased as road density increased. Also, we used multilevel models with sika deer (Cervus nippon) and white-tailed deer to examine whether resource selection differed between species. We failed to detect differences in resource use between these two species and showed how information-theoretic and graphical measures can be used to assess how resource use may have differed. Multilevel models can improve our understanding of how resource selection varies among individuals and provides an objective, quantifiable approach to assess differences or changes in resource selection.

Multilevel Modeling and Policy Development: Guidelines and Applications to Medical Travel.

PubMed

Garcia-Garzon, Eduardo; Zhukovsky, Peter; Haller, Elisa; Plakolm, Sara; Fink, David; Petrova, Dafina; Mahalingam, Vaishali; Menezes, Igor G; Ruggeri, Kai

2016-01-01

Medical travel has expanded rapidly in recent years, resulting in new markets and increased access to medical care. Whereas several studies investigated the motives of individuals seeking healthcare abroad, the conventional analytical approach is limited by substantial caveats. Classical techniques as found in the literature cannot provide sufficient insight due to the nested nature of data generated. The application of adequate analytical techniques, specifically multilevel modeling, is scarce to non-existent in the context of medical travel. This study introduces the guidelines for application of multilevel techniques in public health research by presenting an application of multilevel modeling in analyzing the decision-making patterns of potential medical travelers. Benefits and potential limitations are discussed.

Multilevel Modeling and Policy Development: Guidelines and Applications to Medical Travel

PubMed Central

Garcia-Garzon, Eduardo; Zhukovsky, Peter; Haller, Elisa; Plakolm, Sara; Fink, David; Petrova, Dafina; Mahalingam, Vaishali; Menezes, Igor G.; Ruggeri, Kai

2016-01-01

Medical travel has expanded rapidly in recent years, resulting in new markets and increased access to medical care. Whereas several studies investigated the motives of individuals seeking healthcare abroad, the conventional analytical approach is limited by substantial caveats. Classical techniques as found in the literature cannot provide sufficient insight due to the nested nature of data generated. The application of adequate analytical techniques, specifically multilevel modeling, is scarce to non-existent in the context of medical travel. This study introduces the guidelines for application of multilevel techniques in public health research by presenting an application of multilevel modeling in analyzing the decision-making patterns of potential medical travelers. Benefits and potential limitations are discussed. PMID:27252672

Exposure to air pollution and tobacco smoking and their combined effects on depression in six low- and middle-income countries.

PubMed

Lin, Hualiang; Guo, Yanfei; Kowal, Paul; Airhihenbuwa, Collins O; Di, Qian; Zheng, Yang; Zhao, Xing; Vaughn, Michael G; Howard, Steven; Schootman, Mario; Salinas-Rodriguez, Aaron; Yawson, Alfred E; Arokiasamy, Perianayagam; Manrique-Espinoza, Betty Soledad; Biritwum, Richard B; Rule, Stephen P; Minicuci, Nadia; Naidoo, Nirmala; Chatterji, Somnath; Qian, Zhengmin Min; Ma, Wenjun; Wu, Fan

2017-09-01

Background Little is known about the joint mental health effects of air pollution and tobacco smoking in low- and middle-income countries. Aims To investigate the effects of exposure to ambient fine particulate matter pollution (PM 2.5 ) and smoking and their combined (interactive) effects on depression. Method Multilevel logistic regression analysis of baseline data of a prospective cohort study ( n = 41 785). The 3-year average concentrations of PM 2.5 were estimated using US National Aeronautics and Space Administration satellite data, and depression was diagnosed using a standardised questionnaire. Three-level logistic regression models were applied to examine the associations with depression. Results The odds ratio (OR) for depression was 1.09 (95% C11.01-1.17) per 10 μg/m 3 increase in ambient PM 2.5 , and the association remained after adjusting for potential confounding factors (adjusted OR = 1.10, 95% CI 1.02-1.19). Tobacco smoking (smoking status, frequency, duration and amount) was also significantly associated with depression. There appeared to be a synergistic interaction between ambient PM 2.5 and smoking on depression in the additive model, but the interaction was not statistically significant in the multiplicative model. Conclusions Our study suggests that exposure to ambient PM 2.5 may increase the risk of depression, and smoking may enhance this effect. © The Royal College of Psychiatrists 2017.

A multivariate multilevel Gaussian model with a mixed effects structure in the mean and covariance part.

PubMed

Li, Baoyue; Bruyneel, Luk; Lesaffre, Emmanuel

2014-05-20

A traditional Gaussian hierarchical model assumes a nested multilevel structure for the mean and a constant variance at each level. We propose a Bayesian multivariate multilevel factor model that assumes a multilevel structure for both the mean and the covariance matrix. That is, in addition to a multilevel structure for the mean we also assume that the covariance matrix depends on covariates and random effects. This allows to explore whether the covariance structure depends on the values of the higher levels and as such models heterogeneity in the variances and correlation structure of the multivariate outcome across the higher level values. The approach is applied to the three-dimensional vector of burnout measurements collected on nurses in a large European study to answer the research question whether the covariance matrix of the outcomes depends on recorded system-level features in the organization of nursing care, but also on not-recorded factors that vary with countries, hospitals, and nursing units. Simulations illustrate the performance of our modeling approach. Copyright © 2013 John Wiley & Sons, Ltd.

A Multilevel Multiset Time-Series Model for Describing Complex Developmental Processes

PubMed Central

Ma, Xin; Shen, Jianping

2017-01-01

The authors sought to develop an analytical platform where multiple sets of time series can be examined simultaneously. This multivariate platform capable of testing interaction effects among multiple sets of time series can be very useful in empirical research. The authors demonstrated that the multilevel framework can readily accommodate this analytical capacity. Given their intention to use the multilevel multiset time-series model to pursue complicated research purposes, their resulting model is relatively simple to specify, to run, and to interpret. These advantages make the adoption of their model relatively effortless as long as researchers have the basic knowledge and skills in working with multilevel growth modeling. With multiple potential extensions of their model, the establishment of this analytical platform for analysis of multiple sets of time series can inspire researchers to pursue far more advanced research designs to address complex developmental processes in reality. PMID:29881094

Does gender inequity increase men's mortality risk in the United States? A multilevel analysis of data from the National Longitudinal Mortality Study.

PubMed

Kavanagh, Shane A; Shelley, Julia M; Stevenson, Christopher

2017-12-01

A number of theoretical approaches suggest that gender inequity may give rise to health risks for men. This study undertook a multilevel analysis to ascertain if state-level measures of gender inequity are predictors of men's mortality in the United States. Data for the analysis were taken primarily from the National Longitudinal Mortality Study, which is based on a random sample of the non-institutionalised population. The full data set included 174,703 individuals nested within 50 states and had a six-year follow-up for mortality. Gender inequity was measured by nine variables: higher education, reproductive rights, abortion provider access, elected office, management, business ownership, labour force participation, earnings and relative poverty. Covariates at the individual level were age, income, education, race/ethnicity, marital status and employment status. Covariates at the state level were income inequality and per capita gross domestic product. The results of logistic multilevel modelling showed a number of measures of state-level gender inequity were significantly associated with men's mortality. In all of these cases greater gender inequity was associated with an increased mortality risk. In fully adjusted models for all-age adult men the elected office (OR 1.05 95% CI 1.01-1.09), business ownership (OR 1.04 95% CI 1.01-1.08), earnings (OR 1.04 95% CI 1.01-1.08) and relative poverty (OR 1.07 95% CI 1.03-1.10) measures all showed statistically significant effects for each 1 standard deviation increase in the gender inequity z -score. Similar effects were seen for working-age men. In older men (65+ years) only the earnings and relative poverty measures were statistically significant. This study provides evidence that gender inequity may increase men's health risks. The effect sizes while small are large enough across the range of gender inequity identified to have important population health implications.

On the move: Exploring the impact of residential mobility on cannabis use.

PubMed

Morris, Tim; Manley, David; Northstone, Kate; Sabel, Clive E

2016-11-01

A large literature exists suggesting that residential mobility leads to increased participation in risky health behaviours such as cannabis use amongst youth. However, much of this work fails to account for the impact that underlying differences between mobile and non-mobile youth have on this relationship. In this study we utilise multilevel models with longitudinal data to simultaneously estimate between-child and within-child effects in the relationship between residential mobility and cannabis use, allowing us to determine the extent to which cannabis use in adolescence is driven by residential mobility and unobserved confounding. Data come from a UK cohort, The Avon Longitudinal Study of Parents and Children. Consistent with previous research we find a positive association between cumulative residential mobility and cannabis use when using multilevel extensions of conventional logistic regression models (log odds: 0.94, standard error: 0.42), indicating that children who move houses are more likely to use cannabis than those who remain residentially stable. However, decomposing this relationship into within- and between-child components reveals that the conventional model is underspecified and misleading; we find that differences in cannabis use between mobile and non-mobile children are due to underlying differences between these groups (between-child log odds: 3.56, standard error: 1.22), not by a change in status of residential mobility (within-child log odds: 1.33, standard error: 1.02). Our findings suggest that residential mobility in the teenage years does not place children at an increased risk of cannabis use throughout these years. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Goal Programming Model for the Siting of Multilevel EMS Systems.

DTIC Science & Technology

1980-03-01

Management," unpublished Ph.D. thesis, University of Texas, Austin, Texas, 1971. -23- (11) Daskin , M. and E. Stern, " A Multiobjective Set Covering...GOAL PROGRAM4MING MODEL FOR THE SITING OF MULTILEVEL EMS SYSTE-ETC(U) UNM1AR 80 A CHARNES, J E STORBECK N000iA-75-C-569 WICLASSIFIED CCS-366 N...366 A GOAL PROGRAMMING MODEL FOR THE SITING OF MULTILEVEL EMS SYSTEMS by A . Charnes J. Storbeck March 1980 This project was partially supported by

Predicting Homework Effort: Support for a Domain-Specific, Multilevel Homework Model

ERIC Educational Resources Information Center

Trautwein, Ulrich; Ludtke, Oliver; Schnyder, Inge; Niggli, Alois

2006-01-01

According to the domain-specific, multilevel homework model proposed in the present study, students' homework effort is influenced by expectancy and value beliefs, homework characteristics, parental homework behavior, and conscientiousness. The authors used structural equation modeling and hierarchical linear modeling analyses to test the model in…

School Leadership and Cyberbullying—A Multilevel Analysis

PubMed Central

Låftman, Sara B.; Östberg, Viveca; Modin, Bitte

2017-01-01

Cyberbullying is a relatively new form of bullying, with both similarities and differences to traditional bullying. While earlier research has examined associations between school-contextual characteristics and traditional bullying, fewer studies have focused on the links to students’ involvement in cyberbullying behavior. The aim of the present study is to assess whether school-contextual conditions in terms of teachers’ ratings of the school leadership are associated with the occurrence of cyberbullying victimization and perpetration among students. The data are derived from two separate data collections performed in 2016: The Stockholm School Survey conducted among students in the second grade of upper secondary school (ages 17–18 years) in Stockholm municipality, and the Stockholm Teacher Survey which was carried out among teachers in the same schools. The data include information from 6067 students distributed across 58 schools, linked with school-contextual information based on reports from 1251 teachers. Cyberbullying victimization and perpetration are measured by students’ self-reports. Teachers’ ratings of the school leadership are captured by an index based on 10 items; the mean value of this index was aggregated to the school level. Results from binary logistic multilevel regression models show that high teacher ratings of the school leadership are associated with less cyberbullying victimization and perpetration. We conclude that a strong school leadership potentially prevents cyberbullying behavior among students. PMID:29036933

School Leadership and Cyberbullying-A Multilevel Analysis.

PubMed

Låftman, Sara B; Östberg, Viveca; Modin, Bitte

2017-10-15

Cyberbullying is a relatively new form of bullying, with both similarities and differences to traditional bullying. While earlier research has examined associations between school-contextual characteristics and traditional bullying, fewer studies have focused on the links to students' involvement in cyberbullying behavior. The aim of the present study is to assess whether school-contextual conditions in terms of teachers' ratings of the school leadership are associated with the occurrence of cyberbullying victimization and perpetration among students. The data are derived from two separate data collections performed in 2016: The Stockholm School Survey conducted among students in the second grade of upper secondary school (ages 17-18 years) in Stockholm municipality, and the Stockholm Teacher Survey which was carried out among teachers in the same schools. The data include information from 6067 students distributed across 58 schools, linked with school-contextual information based on reports from 1251 teachers. Cyberbullying victimization and perpetration are measured by students' self-reports. Teachers' ratings of the school leadership are captured by an index based on 10 items; the mean value of this index was aggregated to the school level. Results from binary logistic multilevel regression models show that high teacher ratings of the school leadership are associated with less cyberbullying victimization and perpetration. We conclude that a strong school leadership potentially prevents cyberbullying behavior among students.

Does income inequality get under the skin? A multilevel analysis of depression, anxiety and mental disorders in Sao Paulo, Brazil.

PubMed

Chiavegatto Filho, Alexandre Dias Porto; Kawachi, Ichiro; Wang, Yuan Pang; Viana, Maria Carmen; Andrade, Laura Helena Silveira Guerra

2013-11-01

Test the original income inequality theory, by analysing its association with depression, anxiety and any mental disorders. We analysed a sample of 3542 individuals aged 18 years and older selected through a stratified, multistage area probability sample of households from the São Paulo Metropolitan Area. Mental disorder symptoms were assessed using the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria. Bayesian multilevel logistic models were performed. Living in areas with medium and high-income inequality was statistically associated with increased risk of depression, relative to low-inequality areas (OR 1.76; 95% CI 1.21 to 2.55, and 1.53; 95% CI 1.07 to 2.19, respectively). The same was not true for anxiety (OR 1.25; 95% CI 0.90 to 1.73, and OR 1.07; 95% CI 0.79 to 1.46). In the case of any mental disorder, results were mixed. In general, our findings were consistent with the income inequality theory, that is, people living in places with higher income inequality had an overall higher odd of mental disorders, albeit not always statistically significant. The fact that depression, but not anxiety, was statistically significant could indicate a pathway by which inequality influences health.

Effects of individual characteristics and school environment on cigarette smoking among students ages 13-15: A multilevel analysis of the 2007 Global Youth Tobacco Survey (GYTS) data from Vietnam.

PubMed

Van Minh, Hoang; Hai, Phan Thi; Giang, Kim Bao; Nga, Pham Quynh; Khanh, Pham Huyen; Lam, Nguyen Tuan; Kinh, Ly Ngoc

2011-01-01

This paper aims to estimate the prevalence of cigarette smoking among students in Vietnam ages 13-15 and examines its relationship with compositional and contextual factors. The data used in this paper were obtained from the 2007 Global Youth Tobacco Survey conducted in nine provinces in Vietnam. A multilevel logistic regression model was applied to analyse the association between the current incidence of cigarette smoking and factors on both the individual and school level. The prevalence of cigarette smoking among students was 3.3% overall. The prevalence of smoking among male students (5.9%) was higher than that among females (1.2%). Parental smoking was a significant risk factor for smoking among the students. Having a friend who smoked was the strongest predictor of smoking status among the study subjects. We have demonstrated that school-level factors appeared to impact the prevalence of cigarette smoking among students ages 13-15. This paper highlights the importance of utilising an extensive range of actions to prevent students from using tobacco in Vietnam. These actions should include providing specific curricula for students that address both individual characteristics and the school environment. Further, prevention programmes should also target both parental- and peer-smoking issues.

Neighborhood Racial Diversity and Metabolic Syndrome: 2003-2008 National Health and Nutrition Examination Survey.

PubMed

Li, Kelin; Wen, Ming; Fan, Jessie X

2018-03-30

This study investigated the independent association between neighborhood racial/ethnic diversity and metabolic syndrome among US adults, and focused on how this association differed across individual and neighborhood characteristics (i.e., race/ethnicity, sex, age, urbanity, neighborhood poverty). Objectively-measured biomarker data from 2003 to 2008 National Health and Nutrition Examination Survey were linked to census-tract profiles from 2000 decennial census (N = 10,122). Multilevel random intercept logistic regression models were estimated to examine the contextual effects of tract-level racial/ethnic diversity on individual risks of metabolic syndrome. Overall, more than 20% of the study population were identified as having metabolic syndrome, although the prevalence also varied across demographic subgroups and specific biomarkers. Multilevel analyses showed that increased racial/ethnic diversity within a census tract was associated with decreased likelihood of having metabolic syndrome (OR 0.71, 95% CI 0.52-0.96), particularly among female (OR 0.64; 95% CI 0.43-0.96), young adults (OR 0.60; 95% CI 0.39-0.93), and residents living in urban (OR 0.67; 95% CI 0.48-0.93) or poverty neighborhoods (OR 0.54; 95% CI 0.31-0.95). The findings point to the potential benefits of neighborhood racial/ethnic diversity on individual health risks.

Quality of antenatal care predicts retention in skilled birth attendance: a multilevel analysis of 28 African countries.

PubMed

Chukwuma, Adanna; Wosu, Adaeze C; Mbachu, Chinyere; Weze, Kelechi

2017-05-25

An effective continuum of maternal care ensures that mothers receive essential health packages from pre-pregnancy to delivery, and postnatally, reducing the risk of maternal death. However, across Africa, coverage of skilled birth attendance is lower than coverage for antenatal care, indicating mothers are not retained in the continuum between antenatal care and delivery. This paper explores predictors of retention of antenatal care clients in skilled birth attendance across Africa, including sociodemographic factors and quality of antenatal care received. We pooled nationally representative data from Demographic and Health Surveys conducted in 28 African countries between 2006 and 2015. For the 115,374 births in our sample, we estimated logistic multilevel models of retention in skilled birth attendance (SBA) among clients that received skilled antenatal care (ANC). Among ANC clients in the study sample, 66% received SBA. Adjusting for all demographic covariates and country indicators, the odds of retention in SBA were higher among ANC clients that had their blood pressure checked, received information about pregnancy complications, had blood tests conducted, received at least one tetanus injection, and had urine tests conducted. Higher quality of ANC predicts retention in SBA in Africa. Improving quality of skilled care received prenatally may increase client retention during delivery, reducing maternal mortality.

Physician Satisfaction in Treating Medically Unexplained Symptoms.

PubMed

Brauer, Simon G; Yoon, John D; Curlin, Farr A

2017-05-01

To determine whether treating conditions having medically unexplained symptoms is associated with lower physician satisfaction and higher ascribed patient responsibility, and to determine whether higher ascribed patient responsibility is associated with lower physician satisfaction in treating a given condition. We surveyed a nationally representative sample of 1504 US primary care physicians. Respondents were asked how responsible patients are for two conditions with more-developed medical explanations (depression and anxiety) and two conditions with less-developed medical explanations (chronic back pain and fibromyalgia), and how much satisfaction they experienced in treating each condition. We used Wald tests to compare mean satisfaction and ascribed patient responsibility between medically explained conditions and medically unexplained conditions. We conducted single-level and multilevel ordinal logistic models to test the relation between ascribed patient responsibility and physician satisfaction. Treating medically unexplained conditions elicited less satisfaction than treating medically explained conditions (Wald P < 0.001). Physicians attribute significantly more patient responsibility to the former (Wald P < 0.005), although the magnitude of the difference is small. Across all four conditions, physicians reported experiencing less satisfaction when treating symptoms that result from choices for which patients are responsible (multilevel odds ratio 0.57, P = 0.000). Physicians experience less satisfaction in treating conditions characterized by medically unexplained conditions and in treating conditions for which they believe the patient is responsible.

Can economic deprivation protect health? Paradoxical multilevel effects of poverty on Hispanic children's wheezing.

PubMed

Collins, Timothy W; Kim, Young-an; Grineski, Sara E; Clark-Reyna, Stephanie

2014-08-06

Prior research suggests that economic deprivation has a generally negative influence on residents' health. We employ hierarchical logistic regression modeling to test if economic deprivation presents respiratory health risks or benefits to Hispanic children living in the City of El Paso (Texas, USA) at neighborhood- and individual-levels, and whether individual-level health effects of economic deprivation vary based on neighborhood-level economic deprivation. Data come from the US Census Bureau and a population-based survey of El Paso schoolchildren. The dependent variable is children's current wheezing, an established respiratory morbidity measure, which is appropriate for use with economically-deprived children with an increased likelihood of not receiving a doctor's asthma diagnosis. Results reveal that economic deprivation (measured based on poverty status) at both neighborhood- and individual-levels is associated with reduced odds of wheezing for Hispanic children. A sensitivity analysis revealed similar significant effects of individual- and neighborhood-level poverty on the odds of doctor-diagnosed asthma. Neighborhood-level poverty did not significantly modify the observed association between individual-level poverty and Hispanic children's wheezing; however, greater neighborhood poverty tends to be more protective for poor (as opposed to non-poor) Hispanic children. These findings support a novel, multilevel understanding of seemingly paradoxical effects of economic deprivation on Hispanic health.

Authoritative School Climate and High School Student Risk Behavior: A Cross-sectional Multi-level Analysis of Student Self-Reports.

PubMed

Cornell, Dewey; Huang, Francis

2016-11-01

Many adolescents engage in risk behaviors such as substance use and aggression that jeopardize their healthy development. This study tested the hypothesis that an authoritative school climate characterized by strict but fair discipline and supportive teacher-student relationships is conducive to lower risk behavior for high school students. Multilevel logistic regression models were used to analyze cross-sectional, student-report survey data from a statewide sample of 47,888 students (50.6 % female) in 319 high schools. The students included ninth (26.6 %), tenth (25.5 %), eleventh (24.1 %) and twelfth (23.8 %) grade with a racial/ethnic breakdown of 52.2 % White, 18.0 % Black, 13.1 % Hispanic, 5.9 % Asian, and 10.8 % reporting another or two or more race/ethnicities. Schools with an authoritative school climate had lower levels of student-reported alcohol and marijuana use; bullying, fighting, and weapon carrying at school; interest in gang membership; and suicidal thoughts and behavior. These results controlled for demographic variables of student gender, race, grade, and parent education level as well as school size, percentage of minority students, and percentage of low income students. Overall, these findings add new evidence that an authoritative school climate is associated with positive student outcomes.

Can Economic Deprivation Protect Health? Paradoxical Multilevel Effects of Poverty on Hispanic Children’s Wheezing

PubMed Central

Collins, Timothy W.; Kim, Young-an; Grineski, Sara E.; Clark-Reyna, Stephanie

2014-01-01

Prior research suggests that economic deprivation has a generally negative influence on residents’ health. We employ hierarchical logistic regression modeling to test if economic deprivation presents respiratory health risks or benefits to Hispanic children living in the City of El Paso (Texas, USA) at neighborhood- and individual-levels, and whether individual-level health effects of economic deprivation vary based on neighborhood-level economic deprivation. Data come from the US Census Bureau and a population-based survey of El Paso schoolchildren. The dependent variable is children’s current wheezing, an established respiratory morbidity measure, which is appropriate for use with economically-deprived children with an increased likelihood of not receiving a doctor’s asthma diagnosis. Results reveal that economic deprivation (measured based on poverty status) at both neighborhood- and individual-levels is associated with reduced odds of wheezing for Hispanic children. A sensitivity analysis revealed similar significant effects of individual- and neighborhood-level poverty on the odds of doctor-diagnosed asthma. Neighborhood-level poverty did not significantly modify the observed association between individual-level poverty and Hispanic children’s wheezing; however, greater neighborhood poverty tends to be more protective for poor (as opposed to non-poor) Hispanic children. These findings support a novel, multilevel understanding of seemingly paradoxical effects of economic deprivation on Hispanic health. PMID:25101769

From the battlefield to the bedroom: a multilevel analysis of the links between political conflict and intimate partner violence in Liberia.

PubMed

Kelly, Jocelyn T D; Colantuoni, Elizabeth; Robinson, Courtland; Decker, Michele R

2018-01-01

Assess the link between levels of armed conflict and postconflict intimate partner violence (IPV) experienced by women in Liberia. Armed Conflict Location and Event Data Project data were used to measure conflict-related fatalities in districts in Liberia during the country's civil war from 1999 to 2003. These data were linked to individual-level data from the 2007 Demographic and Health Survey, including past-year IPV. Multilevel logistic models accounting for the clustering of women within districts evaluated the relationship of conflict fatalities with postconflict past-year IPV. Additional conflict measures, including conflict events and cumulative years of conflict, were assessed. After adjusting for individual-level characteristics correlated with IPV, residence in a conflict fatality-affected district was associated with a 50% increase in risk of IPV (adjusted OR (aOR): 1.55, 95% CI 1.26 to 1.92). Women living in a district that experienced 4-5 cumulative years of conflict were also more likely to experience IPV (aOR 1.88, 95% CI 1.29 to 2.75). Residing in a conflict-affected district even 5 years after conflict was associated with postconflict IPV. Recognising and preventing postconflict IPV violence is important to support long-term recovery in postconflict settings.

Neighbourhood environments and obesity among adults: A multilevel analysis of an urban Brazilian context.

PubMed

Matozinhos, Fernanda Penido; Gomes, Crizian Saar; Andrade, Amanda Cristina de Souza; Mendes, Larissa Loures; Pessoa, Milene Cristine; Friche, Amélia Augusta de Lima; Velasquez-Melendez, Gustavo

2015-01-01

Objective. This study identified environmental variables associated with obesity in the adult population of a city in Brazil. Methods. It was conducted using the Surveillance System for Risk and Protective Factors for Chronic Diseases by Telephone Survey from 2008 to 2010. The body mass index (BMI) was calculated from the participants' self-reported weight and height. Obesity was defined as a BMI ≥ 30 kg/m2. The food establishments, georeferenced areas conducive to physical activity, total income of the neighbourhood, homicide rate and population density were used to characterise the environment. In addition, individual variables were considered. A multilevel logistic regression was performed. Results. A total of 5273 individuals were evaluated. The odds of obesity was found to be significantly decreased with increases in the number of establishments that sell healthy food, number of restaurants, number of places for physical activity and total income - in different models. In addition, these associations remained significant after adjustment for age, gender, education and consumption of meat with visible fat. Conclusions. This study contributes to a better understanding of the complex interaction between environmental and individual determinants of obesity and may aid in the development of effective interventions, such as the expansion of obesity control programmes.

The role of community, family, peer, and school factors in group bullying: implications for school-based intervention.

PubMed

Mann, Michael J; Kristjansson, Alfgeir L; Sigfusdottir, Inga Dora; Smith, Megan L

2015-07-01

Although an ecological perspective suggests the importance of multiple levels of intervention, most bullying research has emphasized individual- and school-focused strategies. This study investigated community and family factors that influence school efforts to reduce odds of group bullying behavior and victimization. We used multilevel logistic regression to analyze data from the 2009 Youth in Iceland population school survey (N = 7084, response rate: 83.5%, 50.8% girls). Parental support and time spent with parents were protective against group bullying behavior while worsening relationships with teachers and disliking school increased the likelihood of such behavior. Knowing kids in the area increased the likelihood of group bullying while intergenerational closure was a protective factor. Normlessness was consistently positively related to group bullying. We found no indication of higher-level relationships across the bullying models. Parental support was protective against victimization. Disliking school, intergenerational closure, and anomie/normlessness were strongly and negatively related to victimization. We found some indication of multilevel relationships for victimization. Findings support efforts to increase family and community connection, closure, and support as a part of school-based intervention. These factors become more important as young people participate in or experience greater odds of group bullying behavior and victimization. © 2015, American School Health Association.

Neck/upper back and low back pain in parents and their adult offspring: Family linkage data from the Norwegian HUNT Study.

PubMed

Lier, R; Nilsen, T I L; Vasseljen, O; Mork, P J

2015-07-01

Chronic pain in the neck and low back is highly prevalent. Although heritable components have been identified, knowledge about generational transmission of spinal pain between parents and their adult offspring is sparse. This study examined the intergenerational association of spinal pain using data from 11,081 parent-offspring trios participating in the population-based HUNT Study in Norway. Logistic regression was used to calculate adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for offspring spinal pain associated with parental spinal pain. In total, 3654 (33%) offspring reported spinal pain at participation. Maternal and paternal spinal pain was consistently associated with higher ORs for offspring spinal pain. The results suggest a slightly stronger association for parental multilevel spinal pain (i.e., both neck/upper back pain and low back pain) than for pain localized to the neck/upper back or low back. Multilevel spinal pain in both parents was associated with ORs of 2.6 (95% CI, 2.1-3.3), 2.4 (95% CI, 1.9-3.1) and 3.1 (95% CI, 2.2-4.4) for offspring neck/upper back, low back and multilevel spinal pain, respectively. Parental chronic spinal pain was consistently associated with increased occurrence of chronic spinal pain in their adult offspring, and this association was particularly strong for multilevel spinal pain. © 2014 European Pain Federation - EFIC®

Multilevel modeling and panel data analysis in educational research (Case study: National examination data senior high school in West Java)

NASA Astrophysics Data System (ADS)

Zulvia, Pepi; Kurnia, Anang; Soleh, Agus M.

2017-03-01

Individual and environment are a hierarchical structure consist of units grouped at different levels. Hierarchical data structures are analyzed based on several levels, with the lowest level nested in the highest level. This modeling is commonly call multilevel modeling. Multilevel modeling is widely used in education research, for example, the average score of National Examination (UN). While in Indonesia UN for high school student is divided into natural science and social science. The purpose of this research is to develop multilevel and panel data modeling using linear mixed model on educational data. The first step is data exploration and identification relationships between independent and dependent variable by checking correlation coefficient and variance inflation factor (VIF). Furthermore, we use a simple model approach with highest level of the hierarchy (level-2) is regency/city while school is the lowest of hierarchy (level-1). The best model was determined by comparing goodness-of-fit and checking assumption from residual plots and predictions for each model. Our finding that for natural science and social science, the regression with random effects of regency/city and fixed effects of the time i.e multilevel model has better performance than the linear mixed model in explaining the variability of the dependent variable, which is the average scores of UN.

Associations between Responsible Beverage Service Laws and Binge Drinking and Alcohol-Impaired Driving

PubMed Central

Linde, Ann C.; Toomey, Traci L.; Wolfson, Julian; Lenk, Kathleen M.; Jones-Webb, Rhonda; Erickson, Darin J.

2017-01-01

We explored potential associations between the strength of state Responsible Beverage Service (RBS) laws and self-reported binge drinking and alcohol-impaired driving in the U.S. A multilevel logistic mixed-effects model was used, adjusting for potential confounders. Analyses were conducted on the overall BRFSS sample and drinkers only. Seven percent of BRFSS respondents lived in states with the strongest RBS laws, 15% reported binge drinking and 2% reported driving after having too much to drink at least once in the past 30 days. There was no evidence of a significant association between RBS law strength and self-reported binge drinking or alcohol-impaired driving. Future studies should include additional information about RBS laws and use a prospective research design. PMID:29225382

Suppressor Variables and Multilevel Mixture Modelling

ERIC Educational Resources Information Center

Darmawan, I Gusti Ngurah; Keeves, John P.

2006-01-01

A major issue in educational research involves taking into consideration the multilevel nature of the data. Since the late 1980s, attempts have been made to model social science data that conform to a nested structure. Among other models, two-level structural equation modelling or two-level path modelling and hierarchical linear modelling are two…

Understanding organisational development, sustainability, and diffusion of innovations within hospitals participating in a multilevel quality collaborative.

PubMed

Dückers, Michel La; Wagner, Cordula; Vos, Leti; Groenewegen, Peter P

2011-03-09

Between 2004 and 2008, 24 Dutch hospitals participated in a two-year multilevel quality collaborative (MQC) comprised of (a) a leadership programme for hospital executives, (b) six quality-improvement collaboratives (QICs) for healthcare professionals and other staff, and (c) an internal programme organisation to help senior management monitor and coordinate team progress. The MQC aimed to stimulate the development of quality-management systems and the spread of methods to improve patient safety and logistics. The objective of this study is to describe how the first group of eight MQC hospitals sustained and disseminated improvements made and the quality methods used. The approach followed by the hospitals was described using interview and questionnaire data gathered from eight programme coordinators. MQC hospitals followed a systematic strategy of diffusion and sustainability. Hospital quality-management systems are further developed according to a model linking plan-do-study-act cycles at the unit and hospital level. The model involves quality norms based on realised successes, performance agreements with unit heads, organisational support, monitoring, and quarterly accountability reports. It is concluded from this study that the MQC contributed to organisational development and dissemination within participating hospitals. Organisational learning effects were demonstrated. System changes affect the context factors in the theory of organisational readiness: organisational culture, policies and procedures, past experience, organisational resources, and organisational structure. Programme coordinator responses indicate that these factors are utilised to manage spread and sustainability. Further research is needed to assess long-term effects.

Proinflammatory Dietary Intake is Associated with Increased Risk of Colorectal Cancer: Results of a Case-Control Study in Argentina Using a Multilevel Modeling Approach.

PubMed

Niclis, Camila; Pou, Sonia A; Shivappa, Nitin; Hébert, James R; Steck, Susan E; Díaz, María Del Pilar

2018-01-01

Little evidence regarding the inflammatory potential of diet and its effect on colorectal cancer exists in Latin American countries. The aim of the present study was to evaluate the association between the Dietary Inflammatory Index (DII®) and colorectal cancer (CRC) risk in Córdoba, Argentina. A frequency-matched case-control study (N = 446, including 144 (32.3%) CRC cases and 302 (67.7%) controls was conducted in Córdoba (Argentina) from 2008 through 2015. DII® scores were computed based on dietary intake assessed by a validated food frequency questionnaire (FFQ). Multilevel logistic regression models were fit to evaluate the association between DII scores and CRC, following adjustment for age, body mass index, sex, energy intake, smoking habits, socio-economic status, physical activity, and use of nonsteroidal anti-inflammatory drugs as first-level covariates and level of urbanization as the contextual variable. Odds of colorectal cancer increased linearly with increasing DII scores (OR continuous 1.34; 95%CI 1.07 to 1.69 and OR tertile3 vs. tertile1 1.21; 95%CI 1.01 to 1.44). The association was stronger among men than women (OR continuous 1.29; 95%CI 1.21 to 1.37 vs. OR continuous 1.05; 95%CI 0.83 to 1.33, respectively). A proinflammatory diet, reflected by higher DII scores, was positively associated with colorectal cancer occurrence, mainly in men.

Macro-level gender equality and alcohol consumption: A multi-level analysis across U.S. States

PubMed Central

Roberts, Sarah C.M.

2014-01-01

Higher levels of women’s alcohol consumption have long been attributed to increases in gender equality. However, only limited research examines the relationship between gender equality and alcohol consumption. This study examined associations between five measures of state-level gender equality and five alcohol consumption measures in the United States. Survey data regarding men’s and women’s alcohol consumption from the 2005 Behavioral Risk Factor Surveillance System were linked to state-level indicators of gender equality. Gender equality indicators included state-level women’s socioeconomic status, gender equality in socioeconomic status, reproductive rights, policies relating to violence against women, and women’s political participation. Alcohol consumption measures included past 30-day drinker status, drinking frequency, binge drinking, volume, and risky drinking. Other than drinker status, consumption is measured for drinkers only. Multi-level linear and logistic regression models adjusted for individual demographics as well as state-level income inequality, median income, and % Evangelical Protestant/Mormon. All gender equality indicators were positively associated with both women’s and men’s drinker status in models adjusting only for individual-level covariates; associations were not significant in models adjusting for other state-level characteristics. All other associations between gender equality and alcohol consumption were either negative or non-significant for both women and men in models adjusting for other state-level factors. Findings do not support the hypothesis that higher levels of gender equality are associated with higher levels of alcohol consumption by women or by men. In fact, most significant findings suggest that higher levels of equality are associated with less alcohol consumption overall. PMID:22521679

Area-level socioeconomic inequalities in the use of mammography screening: A multilevel analysis of the Health of Houston Survey

PubMed Central

Calo, William A.; Vernon, Sally W.; Lairson, David R.; Linder, Stephen H.

2015-01-01

Background An emerging literature reports that women who reside in socioeconomically deprived communities are less likely to adhere to mammography screening. This study explored associations between area-level socioeconomic measures and mammography screening among a racially and ethnically diverse sample of women in Texas. Methods We conducted a cross-sectional multilevel study linking individual-level data from the 2010 Health of Houston Survey and contextual data from the U.S. Census. Women ages 40–74 years (N=1,541) were included in the analyses. We examined tract-level poverty, unemployment, education, Hispanic and Black composition, female-headed householder families, and crowding as contextual measures. Using multilevel logistic regression modeling, we compared most disadvantaged tracts (quartiles 2–4) to the most advantaged tract (quartile 1). Results Overall, 64% of the sample was adherent to mammography screening. Screening rates were lower (P<.05) among Hispanics, those foreign born, women aged 40–49 years, and those with low educational attainment, unemployed, and without health insurance coverage. Women living in areas with high levels of poverty (quartile 2 vs. quartile 1: OR=0.50; 95% CI: 0.30–0.85), Hispanic composition (quartile 3 vs. quartile 1: OR=0.54; 95% CI: 0.32–0.90), and crowding (quartile 4 vs. quartile 1: OR=0.53; 95% CI: 0.29–0.96) were less likely to have up-to-date mammography screening, net of individual-level factors. Conclusion Our findings highlight the importance of examining area-level socioeconomic inequalities in mammography screening. The study represents an advance on previous research because we examined multiple area measures, controlled for key individual-level covariates, used data aggregated at the tract level, and accounted for the nested structure of the data. PMID:26809487

High Maternal Body Mass Index Is Associated with an Early-Onset of Overweight/Obesity in Pre-School-Aged Children in Malawi. A Multilevel Analysis of the 2015-16 Malawi Demographic and Health Survey.

PubMed

Ntenda, Peter Austin Morton; Mhone, Thomas Gabriel; Nkoka, Owen

2018-05-25

Overweight/obesity in young children is one of the most serious public health issues globally. We examined whether individual- and community-level maternal nutritional status is associated with an early onset of overweight/obesity in pre-school-aged children in Malawi. Data were obtained from the 2015-16 Malawi Demographic and Health Survey (MDHS). The maternal nutritional status as body mass index and childhood overweight/obesity status was assessed by using the World Health Organization (WHO) recommendations. To examine whether the maternal nutritional status is associated with overweight/obesity in pre-school-aged children, two-level multilevel logistic regression models were constructed on 4023 children of age less than five years dwelling in 850 different communities. The multilevel regression analysis showed that children born to overweight/obese mothers had increased odds of being overweight/obese [adjusted odds ratio (aOR) = 3.11; 95% confidence interval (CI): 1.13-8.54]. At the community level, children born to mothers from the middle (aOR: 1.68; 95% CI: 1.02-2.78) and high (aOR: 1.69; 95% CI: 1.00-2.90) percentage of overweight/obese women had increased odds of being overweight/obese. In addition, there were significant variations in the odds of childhood overweight/obesity in the communities. Strategies aimed at reducing childhood overweight/obesity in Malawi should address not only women and their children but also their communities. Appropriate choices of nutrition, diet and physical activity patterns should be emphasized upon in overweight/obese women of childbearing age throughout pregnancy and beyond.

Analyzing average and conditional effects with multigroup multilevel structural equation models

PubMed Central

Mayer, Axel; Nagengast, Benjamin; Fletcher, John; Steyer, Rolf

2014-01-01

Conventionally, multilevel analysis of covariance (ML-ANCOVA) has been the recommended approach for analyzing treatment effects in quasi-experimental multilevel designs with treatment application at the cluster-level. In this paper, we introduce the generalized ML-ANCOVA with linear effect functions that identifies average and conditional treatment effects in the presence of treatment-covariate interactions. We show how the generalized ML-ANCOVA model can be estimated with multigroup multilevel structural equation models that offer considerable advantages compared to traditional ML-ANCOVA. The proposed model takes into account measurement error in the covariates, sampling error in contextual covariates, treatment-covariate interactions, and stochastic predictors. We illustrate the implementation of ML-ANCOVA with an example from educational effectiveness research where we estimate average and conditional effects of early transition to secondary schooling on reading comprehension. PMID:24795668

A multilevel analysis to explain self-reported adverse health effects and adaptation to urban heat: a cross-sectional survey in the deprived areas of 9 Canadian cities.

PubMed

Bélanger, Diane; Abdous, Belkacem; Valois, Pierre; Gosselin, Pierre; Sidi, Elhadji A Laouan

2016-02-12

This study identifies the characteristics and perceptions related to the individual, the dwelling and the neighbourhood of residence associated with the prevalence of self-reported adverse health impacts and an adaptation index when it is very hot and humid in summer in the most disadvantaged sectors of the nine most populous cities of Québec, Canada, in 2011. The study uses a cross-sectional design and a stratified representative sample; 3485 people (individual-level) were interviewed in their residence. They lived in 1647 buildings (building-level) in 87 most materially and socially disadvantaged census dissemination areas (DA-level). Multilevel analysis was used to perform 3-level models nested one in the other to examine individual impacts as well as the adaptation index. For the prevalence of impacts, which is 46 %, the logistic model includes 13 individual-level indicators (including air conditioning and the adaptation index) and 1 building-level indicator. For the adaptation index, with values ranging from -3 to +3, the linear model has 10 individual-level indicators, 1 building-level indicator and 2 DA-level indicators. Of all these indicators, 9 were associated to the prevalence of impacts only and 8 to the adaptation index only. This 3-level analysis shows the differential importance of the characteristics of residents, buildings and their surroundings on self-reported adverse health impacts and on adaptation (other than air conditioning) under hot and humid summer conditions. It also identifies indicators specific to impacts or adaptation. People with negative health impacts from heat rely more on adaptation strategies while low physical activity and good dwelling/building insulation lead to lower adaptation. Better neighbourhood walkability favors adaptations other than air conditioning. Thus, adaptation to heat in these neighbourhoods seems reactive rather than preventive. These first multi-level insights pave the way for the development of a theoretical framework of the process from heat exposure to impacts and adaptation for research, surveillance and public health interventions at all relevant levels.

Construction of Covariance Functions with Variable Length Fields

NASA Technical Reports Server (NTRS)

Gaspari, Gregory; Cohn, Stephen E.; Guo, Jing; Pawson, Steven

2005-01-01

This article focuses on construction, directly in physical space, of three-dimensional covariance functions parametrized by a tunable length field, and on an application of this theory to reproduce the Quasi-Biennial Oscillation (QBO) in the Goddard Earth Observing System, Version 4 (GEOS-4) data assimilation system. These Covariance models are referred to as multi-level or nonseparable, to associate them with the application where a multi-level covariance with a large troposphere to stratosphere length field gradient is used to reproduce the QBO from sparse radiosonde observations in the tropical lower stratosphere. The multi-level covariance functions extend well-known single level covariance functions depending only on a length scale. Generalizations of the first- and third-order autoregressive covariances in three dimensions are given, providing multi-level covariances with zero and three derivatives at zero separation, respectively. Multi-level piecewise rational covariances with two continuous derivatives at zero separation are also provided. Multi-level powerlaw covariances are constructed with continuous derivatives of all orders. Additional multi-level covariance functions are constructed using the Schur product of single and multi-level covariance functions. A multi-level powerlaw covariance used to reproduce the QBO in GEOS-4 is described along with details of the assimilation experiments. The new covariance model is shown to represent the vertical wind shear associated with the QBO much more effectively than in the baseline GEOS-4 system.

General method to find the attractors of discrete dynamic models of biological systems.

PubMed

Gan, Xiao; Albert, Réka

2018-04-01

Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.

General method to find the attractors of discrete dynamic models of biological systems

NASA Astrophysics Data System (ADS)

Gan, Xiao; Albert, Réka

2018-04-01

Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.

Multilevel Modeling with Correlated Effects

ERIC Educational Resources Information Center

Kim, Jee-Seon; Frees, Edward W.

2007-01-01

When there exist omitted effects, measurement error, and/or simultaneity in multilevel models, explanatory variables may be correlated with random components, and standard estimation methods do not provide consistent estimates of model parameters. This paper introduces estimators that are consistent under such conditions. By employing generalized…

Comparative assessment of analytical approaches to quantify the risk for introduction of rare animal diseases: the example of avian influenza in Spain.

PubMed

Sánchez-Vizcaíno, Fernando; Perez, Andrés; Martínez-López, Beatriz; Sánchez-Vizcaíno, José Manuel

2012-08-01

Trade of animals and animal products imposes an uncertain and variable risk for exotic animal diseases introduction into importing countries. Risk analysis provides importing countries with an objective, transparent, and internationally accepted method for assessing that risk. Over the last decades, European Union countries have conducted probabilistic risk assessments quite frequently to quantify the risk for rare animal diseases introduction into their territories. Most probabilistic animal health risk assessments have been typically classified into one-level and multilevel binomial models. One-level models are more simple than multilevel models because they assume that animals or products originate from one single population. However, it is unknown whether such simplification may result in substantially different results compared to those obtained through the use of multilevel models. Here, data used on a probabilistic multilevel binomial model formulated to assess the risk for highly pathogenic avian influenza introduction into Spain were reanalyzed using a one-level binomial model and their outcomes were compared. An alternative ordinal model is also proposed here, which makes use of simpler assumptions and less information compared to those required by traditional one-level and multilevel approaches. Results suggest that, at least under certain circumstances, results of the one-level and ordinal approaches are similar to those obtained using multilevel models. Consequently, we argue that, when data are insufficient to run traditional probabilistic models, the ordinal approach presented here may be a suitable alternative to rank exporting countries in terms of the risk that they impose for the spread of rare animal diseases into disease-free countries. © 2012 Society for Risk Analysis.

Level-Specific Evaluation of Model Fit in Multilevel Structural Equation Modeling

ERIC Educational Resources Information Center

Ryu, Ehri; West, Stephen G.

2009-01-01

In multilevel structural equation modeling, the "standard" approach to evaluating the goodness of model fit has a potential limitation in detecting the lack of fit at the higher level. Level-specific model fit evaluation can address this limitation and is more informative in locating the source of lack of model fit. We proposed level-specific test…

Integrating Space with Place in Health Research: A Multilevel Spatial Investigation Using Child Mortality in 1880 Newark, New Jersey

PubMed Central

Xu, Hongwei; Logan, John R.; Short, Susan E.

2014-01-01

Research on neighborhoods and health increasingly acknowledges the need to conceptualize, measure, and model spatial features of social and physical environments. In ignoring underlying spatial dynamics, we run the risk of biased statistical inference and misleading results. In this paper, we propose an integrated multilevel-spatial approach for Poisson models of discrete responses. In an empirical example of child mortality in 1880 Newark, New Jersey, we compare this multilevel-spatial approach with the more typical aspatial multilevel approach. Results indicate that spatially-defined egocentric neighborhoods, or distance-based measures, outperform administrative areal units, such as census units. In addition, although results did not vary by specific definitions of egocentric neighborhoods, they were sensitive to geographic scale and modeling strategy. Overall, our findings confirm that adopting a spatial-multilevel approach enhances our ability to disentangle the effect of space from that of place, and point to the need for more careful spatial thinking in population research on neighborhoods and health. PMID:24763980

Multilevel model to estimate county-level untreated dental caries among US children aged 6-9years using the National Health and Nutrition Examination Survey.

PubMed

Lin, Mei; Zhang, Xingyou; Holt, James B; Robison, Valerie; Li, Chien-Hsun; Griffin, Susan O

2018-06-01

Because conducting population-based oral health screening is resource intensive, oral health data at small-area levels (e.g., county-level) are not commonly available. We applied the multilevel logistic regression and poststratification method to estimate county-level prevalence of untreated dental caries among children aged 6-9years in the United States using data from the National Health and Nutrition Examination Survey (NHANES) 2005-2010 linked with various area-level data at census tract, county and state levels. We validated model-based national estimates against direct estimates from NHANES. We also compared model-based estimates with direct estimates from select State Oral Health Surveys (SOHS) at state and county levels. The model with individual-level covariates only and the model with individual-, census tract- and county-level covariates explained 7.2% and 96.3% respectively of overall county-level variation in untreated caries. Model-based county-level prevalence estimates ranged from 4.9% to 65.2% with median of 22.1%. The model-based national estimate (19.9%) matched the NHANES direct estimate (19.8%). We found significantly positive correlations between model-based estimates for 8-year-olds and direct estimates from the third-grade State Oral Health Surveys (SOHS) at state level for 34 states (Pearson coefficient: 0.54, P=0.001) and SOHS estimates at county level for 53 New York counties (Pearson coefficient: 0.38, P=0.006). This methodology could be a useful tool to characterize county-level disparities in untreated dental caries among children aged 6-9years and complement oral health surveillance to inform public health programs especially when local-level data are not available although the lack of external validation due to data unavailability should be acknowledged. Published by Elsevier Inc.

Interviewer effects on non-response propensity in longitudinal surveys: a multilevel modelling approach

PubMed Central

Vassallo, Rebecca; Durrant, Gabriele B; Smith, Peter W F; Goldstein, Harvey

2015-01-01

The paper investigates two different multilevel approaches, the multilevel cross-classified and the multiple-membership models, for the analysis of interviewer effects on wave non-response in longitudinal surveys. The models proposed incorporate both interviewer and area effects to account for the non-hierarchical structure, the influence of potentially more than one interviewer across waves and possible confounding of area and interviewer effects arising from the non-random allocation of interviewers across areas. The methods are compared by using a data set: the UK Family and Children Survey. PMID:25598587

How to compare cross-lagged associations in a multilevel autoregressive model.

PubMed

Schuurman, Noémi K; Ferrer, Emilio; de Boer-Sonnenschein, Mieke; Hamaker, Ellen L

2016-06-01

By modeling variables over time it is possible to investigate the Granger-causal cross-lagged associations between variables. By comparing the standardized cross-lagged coefficients, the relative strength of these associations can be evaluated in order to determine important driving forces in the dynamic system. The aim of this study was twofold: first, to illustrate the added value of a multilevel multivariate autoregressive modeling approach for investigating these associations over more traditional techniques; and second, to discuss how the coefficients of the multilevel autoregressive model should be standardized for comparing the strength of the cross-lagged associations. The hierarchical structure of multilevel multivariate autoregressive models complicates standardization, because subject-based statistics or group-based statistics can be used to standardize the coefficients, and each method may result in different conclusions. We argue that in order to make a meaningful comparison of the strength of the cross-lagged associations, the coefficients should be standardized within persons. We further illustrate the bivariate multilevel autoregressive model and the standardization of the coefficients, and we show that disregarding individual differences in dynamics can prove misleading, by means of an empirical example on experienced competence and exhaustion in persons diagnosed with burnout. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Post test review of a single car test of multi-level passenger equipment

DOT National Transportation Integrated Search

2008-04-22

The single car test of multi-level equipment described in : this paper was designed to help evaluate the crashworthiness of : a multi-level car in a controlled collision. The data collected : from this test will be used to refine engineering models. ...

On the application of multilevel modeling in environmental and ecological studies

USGS Publications Warehouse

Qian, Song S.; Cuffney, Thomas F.; Alameddine, Ibrahim; McMahon, Gerard; Reckhow, Kenneth H.

2010-01-01

This paper illustrates the advantages of a multilevel/hierarchical approach for predictive modeling, including flexibility of model formulation, explicitly accounting for hierarchical structure in the data, and the ability to predict the outcome of new cases. As a generalization of the classical approach, the multilevel modeling approach explicitly models the hierarchical structure in the data by considering both the within- and between-group variances leading to a partial pooling of data across all levels in the hierarchy. The modeling framework provides means for incorporating variables at different spatiotemporal scales. The examples used in this paper illustrate the iterative process of model fitting and evaluation, a process that can lead to improved understanding of the system being studied.

Evidencing Learning Outcomes: A Multi-Level, Multi-Dimensional Course Alignment Model

ERIC Educational Resources Information Center

Sridharan, Bhavani; Leitch, Shona; Watty, Kim

2015-01-01

This conceptual framework proposes a multi-level, multi-dimensional course alignment model to implement a contextualised constructive alignment of rubric design that authentically evidences and assesses learning outcomes. By embedding quality control mechanisms at each level for each dimension, this model facilitates the development of an aligned…

Examining Elementary Social Studies Marginalization: A Multilevel Model

ERIC Educational Resources Information Center

Fitchett, Paul G.; Heafner, Tina L.; Lambert, Richard G.

2014-01-01

Utilizing data from the National Center for Education Statistics Schools and Staffing Survey (SASS), a multilevel model (Hierarchical Linear Model) was developed to examine the association of teacher/classroom and state level indicators on reported elementary social studies instructional time. Findings indicated that state testing policy was a…

Handling Correlations between Covariates and Random Slopes in Multilevel Models

ERIC Educational Resources Information Center

Bates, Michael David; Castellano, Katherine E.; Rabe-Hesketh, Sophia; Skrondal, Anders

2014-01-01

This article discusses estimation of multilevel/hierarchical linear models that include cluster-level random intercepts and random slopes. Viewing the models as structural, the random intercepts and slopes represent the effects of omitted cluster-level covariates that may be correlated with included covariates. The resulting correlations between…

Modeling Learning in Doubly Multilevel Binary Longitudinal Data Using Generalized Linear Mixed Models: An Application to Measuring and Explaining Word Learning.

PubMed

Cho, Sun-Joo; Goodwin, Amanda P

2016-04-01

When word learning is supported by instruction in experimental studies for adolescents, word knowledge outcomes tend to be collected from complex data structure, such as multiple aspects of word knowledge, multilevel reader data, multilevel item data, longitudinal design, and multiple groups. This study illustrates how generalized linear mixed models can be used to measure and explain word learning for data having such complexity. Results from this application provide deeper understanding of word knowledge than could be attained from simpler models and show that word knowledge is multidimensional and depends on word characteristics and instructional contexts.

Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information

PubMed Central

Wang, Xiaohong; Wang, Lizhi

2017-01-01

Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system. PMID:28926930

Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information.

PubMed

Wang, Jingbin; Wang, Xiaohong; Wang, Lizhi

2017-09-15

Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system.

Multilevel Modeling of Two Cyclical Processes: Extending Differential Structural Equation Modeling to Nonlinear Coupled Systems

ERIC Educational Resources Information Center

Butner, Jonathan; Amazeen, Polemnia G.; Mulvey, Genna M.

2005-01-01

The authors present a dynamical multilevel model that captures changes over time in the bidirectional, potentially asymmetric influence of 2 cyclical processes. S. M. Boker and J. Graham's (1998) differential structural equation modeling approach was expanded to the case of a nonlinear coupled oscillator that is common in bimanual coordination…

Coupling Longitudinal Data and Multilevel Modeling to Examine the Antecedents and Consequences of Jealousy Experiences in Romantic Relationships: A Test of the Relational Turbulence Model

ERIC Educational Resources Information Center

Theiss, Jennifer A.; Solomon, Denise Haunani

2006-01-01

We used longitudinal data and multilevel modeling to examine how intimacy, relational uncertainty, and failed attempts at interdependence influence emotional, cognitive, and communicative responses to romantic jealousy, and how those experiences shape subsequent relationship characteristics. The relational turbulence model (Solomon & Knobloch,…

Determinants of unmet need for family planning in rural Burkina Faso: a multilevel logistic regression analysis.

PubMed

Wulifan, Joseph K; Jahn, Albrecht; Hien, Hervé; Ilboudo, Patrick Christian; Meda, Nicolas; Robyn, Paul Jacob; Saidou Hamadou, T; Haidara, Ousmane; De Allegri, Manuela

2017-12-19

Unmet need for family planning has implications for women and their families, such as unsafe abortion, physical abuse, and poor maternal health. Contraceptive knowledge has increased across low-income settings, yet unmet need remains high with little information on the factors explaining it. This study assessed factors associated with unmet need among pregnant women in rural Burkina Faso. We collected data on pregnant women through a population-based survey conducted in 24 rural districts between October 2013 and March 2014. Multivariate multilevel logistic regression was used to assess the association between unmet need for family planning and a selection of relevant demand- and supply-side factors. Of the 1309 pregnant women covered in the survey, 239 (18.26%) reported experiencing unmet need for family planning. Pregnant women with more than three living children [OR = 1.80; 95% CI (1.11-2.91)], those with a child younger than 1 year [OR = 1.75; 95% CI (1.04-2.97)], pregnant women whose partners disapproves contraceptive use [OR = 1.51; 95% CI (1.03-2.21)] and women who desired fewer children compared to their partners preferred number of children [OR = 1.907; 95% CI (1.361-2.672)] were significantly more likely to experience unmet need for family planning, while health staff training in family planning logistics management (OR = 0.46; 95% CI (0.24-0.73)] was associated with a lower probability of experiencing unmet need for family planning. Findings suggest the need to strengthen family planning interventions in Burkina Faso to ensure greater uptake of contraceptive use and thus reduce unmet need for family planning.

Social support, volunteering and health around the world: cross-national evidence from 139 countries.

PubMed

Kumar, Santosh; Calvo, Rocio; Avendano, Mauricio; Sivaramakrishnan, Kavita; Berkman, Lisa F

2012-03-01

High levels of social capital and social integration are associated with self-rated health in many developed countries. However, it is not known whether this association extends to non-western and less economically advanced countries. We examine associations between social support, volunteering, and self-rated health in 139 low-, middle- and high-income countries. Data come from the Gallup World Poll, an internationally comparable survey conducted yearly from 2005 to 2009 for those 15 and over. Volunteering was measured by self-reports of volunteering to an organization in the past month. Social support was based on self-reports of access to support from relatives and friends. We started by estimating random coefficient (multi-level) models and then used multivariate logistic regression to model health as a function of social support and volunteering, controlling for age, gender, education, marital status, and religiosity. We found statistically significant evidence of cross-national variation in the association between social capital variables and self-rated health. In the multivariate logistic model, self-rated health were significantly associated with having social support from friends and relatives and volunteering. Results from stratified analyses indicate that these associations are strikingly consistent across countries. Our results indicate that the link between social capital and health is not restricted to high-income countries but extends across many geographical regions regardless of their national-income level. Copyright © 2012 Elsevier Ltd. All rights reserved.

Variability in the prescription of biological drugs in rheumatoid arthritis in Spain: a multilevel analysis.

PubMed

López-Longo, Francisco Javier; Seoane-Mato, Daniel; Martín-Martínez, María A; Sánchez-Alonso, Fernando

2018-04-01

To describe variability in the prescription of biologics (B-DMARDs) for patients with rheumatoid arthritis (RA) in hospitals in Spain, and to explore which characteristics of the patient, the doctor and the hospital are associated with this variability. Cross-sectional multicentric study in 46 rheumatology services of the National Health System. Medical records of 1188 randomly selected patients were reviewed. The association of each variable with B-DMARD prescription was analyzed using simple logistic regressions. Multilevel logistic regression models were created to analyze variability among centers. 36.8% of patients had received B-DMARD. The proportion of patients being treated with B-DMARDs varied between 3.6 and 71.4% depending on the center. Association of prescription of B-DMARD with patient age (OR = 0.958, 95% CI = 0.947-0.968, p < 0.001), longer disease duration (OR = 1.05, 95% CI = 1.032-1.069, p < 0.001), higher CRP levels (OR = 1.022, 95% CI = 1.003-1.042, p = 0.023), and higher number of hospitalizations (OR = 1.286, 95% CI = 1.145-1.446, p < 0.001) was observed. With regard to the center characteristics, the existence of telephone consultations (OR = 1.438, 95% CI = 1.037-1.994, p = 0.03) and the number of beds (OR = 1.045, 95% CI = 1.001-1.091, p = 0.044) were positively associated with prescription of B-DMARDs. Patient variables explained 34.04% of the variability among centers. By adjusting for patient and hospital characteristics, it went up to 83.71%. There is variability in the prescription of B-DMARDs for patients with RA among hospitals which is associated, to a greater extent, with the center characteristics. B-DMARDs prescription could be partly explained by other factors not covered by the current study including the provider's attitudes towards biologics and other hospital characteristics.

Downward economic mobility and preterm birth: an exploratory study of Chicago-born upper class White mothers.

PubMed

Collins, James W; Rankin, Kristin M; David, Richard J

2015-07-01

A paucity of published data exists on the factors underlying the relatively poor birth outcome of non-Hispanic White women in the United States. To determine whether downward economic mobility is a risk factor for preterm birth (<37 weeks, PTB) among upper class-born White women. Stratified and multilevel logistic regression analyses were performed on an Illinois transgenerational dataset of non-Hispanic White infants (1989-1991) and their women (1956-1976) with appended US census income information. The study sample was restricted to singleton births of Chicago-born upper-class (defined by early-life residence in affluent neighborhoods) non-Hispanic White women. Upper class-born White women (n = 4,891) who did not experience downward economic mobility by the time of delivery had a PTB rate of 5.4 %. Those women who experienced slight (n = 5,112), moderate (n = 2,158), or extreme (n = 339) downward economic mobility had PTB rates of 6.5, 8.5, and 10.1 %, respectively; RR (95 % CI) = 1.2 (1.0-4.0), 1.6 (1.3-1.9), and 1.9 (1.3-2.6), respectively. Maternal downward economic mobility was also associated with an increased prevalence of biologic, medical, and behavioral risk factors. Interestingly, the relationship between moderate to extreme downward mobility and preterm birth was stronger among former low birth weight (<2500 g, LBW) than non-LBW women: 2.8 (1.4-5.8) versus 1.6 (1.3-1.9), respectively. In multilevel logistic regression models, the adjusted odds ratio of preterm birth for former LBW and non-LBW women who experienced any downward mobility (compared to those women with lifelong upper class status) equaled 2.4 (1.1-5.3) and 1.1 (1.0-1.1), respectively. Downward economic mobility is associated with an increased risk of preterm birth among upper class-born White urban women; this phenomenon is strongest among former low birth weight women.

Municipality and Neighborhood Influences on Volunteering in Later Life.

PubMed

Dury, Sarah; Willems, Jurgen; De Witte, Nico; De Donder, Liesbeth; Buffel, Tine; Verté, Dominique

2016-06-01

This article explores the relationships between municipality features and volunteering by older adults. In the literature, strong evidence exists of the influence of place on older people's health. However, the question how neighborhoods and municipalities promote or hinder volunteer participation remains under-explored. Data for the research are derived from the Belgian Aging Studies. We estimate logistic multilevel models for older individuals' engagement in volunteering across 141 municipalities in Belgium (N = 67,144). Analysis shows that neighborhood connectedness, neighborhood satisfaction, home ownership, and presence of services predict voluntary engagement at older ages. The findings support that perceptions and quality of social resources that relate to neighborhoods may be important factors to explain volunteering among older adults. Moreover, the findings suggest that volunteering in later life must be considered within a broader framework. © The Author(s) 2014.

(En)gendering Racial Disparities in Health Trajectories: A Life Course and Intersectional Analysis.

PubMed

Richardson, Liana J; Brown, Tyson H

2016-12-01

Historically, intersectionality has been an underutilized framework in sociological research on racial/ethnic and gender inequalities in health. To demonstrate its utility and importance, we conduct an intersectional analysis of the social stratification of health using the exemplar of hypertension-a health condition in which racial/ethnic and gender differences have been well-documented. Previous research has tended to examine these differences separately and ignore how the interaction of social status dimensions may influence health over time. Using seven waves of data from the Health and Retirement Study and multilevel logistic regression models, we found a multiplicative effect of race/ethnicity and gender on hypertension risk trajectories, consistent with both an intersectionality perspective and persistent inequality hypothesis. Group differences in past and contemporaneous socioeconomic and behavioral factors did not explain this effect.

A General Multilevel SEM Framework for Assessing Multilevel Mediation

ERIC Educational Resources Information Center

Preacher, Kristopher J.; Zyphur, Michael J.; Zhang, Zhen

2010-01-01

Several methods for testing mediation hypotheses with 2-level nested data have been proposed by researchers using a multilevel modeling (MLM) paradigm. However, these MLM approaches do not accommodate mediation pathways with Level-2 outcomes and may produce conflated estimates of between- and within-level components of indirect effects. Moreover,…

The Consequences of Ignoring Individuals' Mobility in Multilevel Growth Models: A Monte Carlo Study

ERIC Educational Resources Information Center

Luo, Wen; Kwok, Oi-man

2012-01-01

In longitudinal multilevel studies, especially in educational settings, it is fairly common that participants change their group memberships over time (e.g., students switch to different schools). Participant's mobility changes the multilevel data structure from a purely hierarchical structure with repeated measures nested within individuals and…

The Effects of Autonomy and Empowerment on Employee Turnover: Test of a Multilevel Model in Teams

ERIC Educational Resources Information Center

Liu, Dong; Zhang, Shu; Wang, Lei; Lee, Thomas W.

2011-01-01

Extending research on voluntary turnover in the team setting, this study adopts a multilevel self-determination theoretical approach to examine the unique roles of individual and social-contextual motivational precursors, autonomy orientation and autonomy support, in reducing team member voluntary turnover. Analysis of multilevel time-lagged data…

A multilevel model of the impact of farm-level best management practices on phosphorus runoff

USDA-ARS?s Scientific Manuscript database

Multilevel or hierarchical models have been applied for a number of years in the social sciences but only relatively recently in the environmental sciences. These models can be developed in either a frequentist or Bayesian context and have similarities to other methods such as empirical Bayes analys...

Using Multilevel Factor Analysis with Clustered Data: Investigating the Factor Structure of the Positive Values Scale

ERIC Educational Resources Information Center

Huang, Francis L.; Cornell, Dewey G.

2016-01-01

Advances in multilevel modeling techniques now make it possible to investigate the psychometric properties of instruments using clustered data. Factor models that overlook the clustering effect can lead to underestimated standard errors, incorrect parameter estimates, and model fit indices. In addition, factor structures may differ depending on…

Cross-Classified Random Effects Models in Institutional Research

ERIC Educational Resources Information Center

Meyers, Laura E.

2012-01-01

Multilevel modeling offers researchers a rich array of tools that can be used for a variety of purposes, such as analyzing specific institutional issues, looking for macro-level trends, and helping to shape and inform educational policy. One of the more complex multilevel modeling tools available to institutional researchers is cross-classified…

Outward Bound Outcome Model Validation and Multilevel Modeling

ERIC Educational Resources Information Center

Luo, Yuan-Chun

2011-01-01

This study was intended to measure construct validity for the Outward Bound Outcomes Instrument (OBOI) and to predict outcome achievement from individual characteristics and course attributes using multilevel modeling. A sample of 2,340 participants was collected by Outward Bound USA between May and September 2009 using the OBOI. Two phases of…

Introduction to Multilevel Item Response Theory Analysis: Descriptive and Explanatory Models

ERIC Educational Resources Information Center

Sulis, Isabella; Toland, Michael D.

2017-01-01

Item response theory (IRT) models are the main psychometric approach for the development, evaluation, and refinement of multi-item instruments and scaling of latent traits, whereas multilevel models are the primary statistical method when considering the dependence between person responses when primary units (e.g., students) are nested within…

Teaching Quality Management Model for the Training of Innovation Ability and the Multilevel Decomposition Indicators

ERIC Educational Resources Information Center

Lu, Xingjiang; Yao, Chen; Zheng, Jianmin

2013-01-01

This paper focuses on the training of undergraduate students' innovation ability. On top of the theoretical framework of the Quality Function Deployment (QFD), we propose a teaching quality management model. Based on this model, we establish a multilevel decomposition indicator system, which integrates innovation ability characterized by four…

Distinguishing Continuous and Discrete Approaches to Multilevel Mixture IRT Models: A Model Comparison Perspective

ERIC Educational Resources Information Center

Zhu, Xiaoshu

2013-01-01

The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…

A Multilevel Analysis of Phase II of the Louisiana School Effectiveness Study.

ERIC Educational Resources Information Center

Kennedy, Eugene; And Others

This paper presents findings of a study that used conventional modeling strategies (student- and school-level) and a new multilevel modeling strategy, Hierarchical Linear Modeling, to investigate school effects on student-achievement outcomes for data collected as part of Phase 2 of the Louisiana School Effectiveness Study. The purpose was to…

Multilevel Modeling and Ordinary Least Squares Regression: How Comparable Are They?

ERIC Educational Resources Information Center

Huang, Francis L.

2018-01-01

Studies analyzing clustered data sets using both multilevel models (MLMs) and ordinary least squares (OLS) regression have generally concluded that resulting point estimates, but not the standard errors, are comparable with each other. However, the accuracy of the estimates of OLS models is important to consider, as several alternative techniques…

Developing an Adequately Specified Model of State Level Student Achievement with Multilevel Data.

ERIC Educational Resources Information Center

Bernstein, Lawrence

Limitations of using linear, unilevel regression procedures in modeling student achievement are discussed. This study is a part of a broader study that is developing an empirically-based predictive model of variables associated with academic achievement from a multilevel perspective and examining the differences by which parameters are estimated…

A Bayesian Multi-Level Factor Analytic Model of Consumer Price Sensitivities across Categories

ERIC Educational Resources Information Center

Duvvuri, Sri Devi; Gruca, Thomas S.

2010-01-01

Identifying price sensitive consumers is an important problem in marketing. We develop a Bayesian multi-level factor analytic model of the covariation among household-level price sensitivities across product categories that are substitutes. Based on a multivariate probit model of category incidence, this framework also allows the researcher to…

Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research

ERIC Educational Resources Information Center

de Jong, Martijn G.; Steenkamp, Jan-Benedict E. M.

2010-01-01

We present a class of finite mixture multilevel multidimensional ordinal IRT models for large scale cross-cultural research. Our model is proposed for confirmatory research settings. Our prior for item parameters is a mixture distribution to accommodate situations where different groups of countries have different measurement operations, while…

Modeling Latent Growth Curves With Incomplete Data Using Different Types of Structural Equation Modeling and Multilevel Software

ERIC Educational Resources Information Center

Ferrer, Emilio; Hamagami, Fumiaki; McArdle, John J.

2004-01-01

This article offers different examples of how to fit latent growth curve (LGC) models to longitudinal data using a variety of different software programs (i.e., LISREL, Mx, Mplus, AMOS, SAS). The article shows how the same model can be fitted using both structural equation modeling and multilevel software, with nearly identical results, even in…

Factors determining anti-poliovirus type 3 antibodies among orally immunised Indian infants.

PubMed

Kaliappan, Saravanakumar Puthupalayam; Venugopal, Srinivasan; Giri, Sidhartha; Praharaj, Ira; Karthikeyan, Arun S; Babji, Sudhir; John, Jacob; Muliyil, Jayaprakash; Grassly, Nicholas; Kang, Gagandeep

2016-09-22

Among the three poliovirus serotypes, the lowest responses after vaccination with trivalent oral polio vaccine (tOPV) are to serotype 3. Although improvements in routine immunisation and supplementary immunisation activities have greatly increased vaccine coverage, there are limited data on antibody prevalence in Indian infants. Children aged 5-11months with a history of not having received inactivated polio vaccine were screened for serum antibodies to poliovirus serotype 3 (PV3) by a micro-neutralisation assay according to a modified World Health Organization (WHO) protocol. Limited demographic information was collected to assess risk-factors for a lack of protective antibodies. Student's t-test, logistic regression and multilevel logistic regression (MLR) model were used to estimate model parameters. Of 8454 children screened at a mean age of 8.3 (standard deviation [SD]-1.8) months, 88.1% (95% confidence interval (CI): 87.4-88.8) had protective antibodies to PV3. The number of tOPV doses received was the main determinant of seroprevalence; the maximum likelihood estimate yields a 37.7% (95% CI: 36.2-38.3) increase in seroprevalence per dose of tOPV. In multivariable logistic regression analysis increasing age, male sex, and urban residence were also independently associated with seropositivity (Odds Ratios (OR): 1.17 (95% CI: 1.12-1.23) per month of age, 1.27 (1.11-1.46) and 1.24 (1.05-1.45) respectively). Seroprevalence of antibodies to PV3 is associated with age, gender and place of residence, in addition to the number of tOPV doses received. Ensuring high coverage and monitoring of response are essential as long as oral vaccines are used in polio eradication. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

The Effect of Small Sample Size on Two-Level Model Estimates: A Review and Illustration

ERIC Educational Resources Information Center

McNeish, Daniel M.; Stapleton, Laura M.

2016-01-01

Multilevel models are an increasingly popular method to analyze data that originate from a clustered or hierarchical structure. To effectively utilize multilevel models, one must have an adequately large number of clusters; otherwise, some model parameters will be estimated with bias. The goals for this paper are to (1) raise awareness of the…

Does a wife's education influence spousal agreement on approval of family planning?: Random-effects Modeling using data from two West African Countries.

PubMed

Hossain, Mian; Ahmed, Saifuddin; Rogers, Laurencia

2014-05-01

Spousal approval of family planning is critical for contraceptive use. Both contraceptive use rates and women's education are low in many West-African countries and this study examines the role of wives' education in spousal agreement on approval of family planning in two sub-Saharan West African countries. We used couples' data from Demographic Health Surveys in Senegal and in Niger, conducted in 2005 and 2006, respectively. Multiple logistic regression results using multilevel modeling show that the odds of spousal agreement on approval of family planning were slightly over three times [OR: 3.16; 95% CI: 1.32 to 7.57] in Senegal and were about three times [OR: 3.07; 95% CI: 1.64 to 5.76] in Niger higher for women with more than primary education. Findings suggest that improvement in women's education could lead to spousal agreement on approval of family planning, which may lead to use of family planning in sub-Saharan African countries.

Women's health in a rural community in Kerala, India: do caste and socioeconomic position matter?

PubMed Central

Mohindra, K S; Haddad, Slim; Narayana, D

2006-01-01

Objectives To examine the social patterning of women's self‐reported health status in India and the validity of the two hypotheses: (1) low caste and lower socioeconomic position is associated with worse reported health status, and (2) associations between socioeconomic position and reported health status vary across castes. Design Cross‐sectional household survey, age‐adjusted percentages and odds ratios, and multilevel multinomial logistic regression models were used for analysis. Setting A panchayat (territorial decentralised unit) in Kerala, India, in 2003. Participants 4196 non‐elderly women. Outcome measures Self‐perceived health status and reported limitations in activities in daily living. Results Women from lower castes (scheduled castes/scheduled tribes (SC/ST) and other backward castes (OBC) reported a higher prevalence of poor health than women from forward castes. Socioeconomic inequalities were observed in health regardless of the indicators, education, women's employment status or household landholdings. The multilevel multinomial models indicate that the associations between socioeconomic indicators and health vary across caste. Among SC/ST and OBC women, the influence of socioeconomic variables led to a “magnifying” effect, whereas among forward caste women, a “buffering” effect was found. Among lower caste women, the associations between socioeconomic factors and self‐assessed health are graded; the associations are strongest when comparing the lowest and highest ratings of health. Conclusions Even in a relatively egalitarian state in India, there are caste and socioeconomic inequalities in women's health. Implementing interventions that concomitantly deal with caste and socioeconomic disparities will likely produce more equitable results than targeting either type of inequality in isolation. PMID:17108296

Urban-rural differences in adolescent eating behaviour: a multilevel cross-sectional study of 15-year-olds in Scotland.

PubMed

Levin, Kate A

2014-08-01

Improving the diet of the Scottish population has been a government focus in recent years. Population health is known to vary between geographies; therefore alongside trends and socio-economic inequalities in eating behaviour, geographic differences should also be monitored. Eating behaviour data from the 2010 Scotland Health Behaviour in School-aged Children survey were modelled using multilevel linear and logistic modelling. Data were collected in schools across urban and rural Scotland. Schoolchildren aged 15 years. Adolescents living in remote rural Scotland had the highest consumption frequency of vegetables (on average consumed on 6·68 d/week) and the lowest consumption frequency of sweets and crisps (on 4·27 and 3·02 d/week, respectively). However, it was not in the major four cities of Scotland (Glasgow, Edinburgh, Dundee and Aberdeen) but in the geography described by the classification 'other urban' areas (large towns of between 10 000 and 125 000 residents) that adolescents had the poorest diet. Deprivation and rurality were independently associated with food consumption for all but fruit consumption. Sharing a family meal, dieting behaviour, food poverty and breakfast consumption did not differ by rurality. Variance at the school level was significant for fruit and vegetable consumption frequencies and for irregular breakfast consumption, regardless of rurality. Young people from rural areas have a healthier diet than those living in urban areas. The eating behaviours examined did not explain these differences. Future research should investigate why urban-rural differences exist for consumption frequencies of 'healthy' and 'unhealthy' foods.

Multilevel analysis of the role of human factors in regional disparities in crash outcomes.

PubMed

Adanu, Emmanuel Kofi; Smith, Randy; Powell, Lars; Jones, Steven

2017-12-01

A growing body of research has examined the disparities in road traffic safety among population groups and geographic regions. These studies reveal disparities in crash outcomes between people and regions with different socioeconomic characteristics. A critical aspect of the road traffic crash epidemic that has received limited attention is the influence of local characteristics on human elements that increase the risk of getting into a crash. This paper applies multilevel logistic regression modeling techniques to investigate the influence of driver residential factors on driver behaviors in an attempt to explain the area-based differences in the severity of road crashes across the State of Alabama. Specifically, the paper reports the effects of characteristics attributable to drivers and the geographic regions they reside on the likelihood of a crash resulting in serious injuries. Model estimation revealed that driver residence (postal code or region) accounted for about 7.3% of the variability in the probability of a driver getting into a serious injury crash, regardless of driver characteristics. The results also reveal disparities in serious injury crash rate as well as significant proportions of serious injury crashes involving no seatbelt usage, driving under influence (DUI), unemployed drivers, young drivers, distracted driving, and African American drivers among some regions. The average credit scores, average commute times, and populations of driver postal codes are shown to be significant predictors for risk of severe injury crashes. This approach to traffic crash analysis presented can serve as the foundation for evidence-based policies and also guide the implementation of targeted countermeasures. Copyright © 2017 Elsevier Ltd. All rights reserved.

Understanding organisational development, sustainability, and diffusion of innovations within hospitals participating in a multilevel quality collaborative

PubMed Central

2011-01-01

Background Between 2004 and 2008, 24 Dutch hospitals participated in a two-year multilevel quality collaborative (MQC) comprised of (a) a leadership programme for hospital executives, (b) six quality-improvement collaboratives (QICs) for healthcare professionals and other staff, and (c) an internal programme organisation to help senior management monitor and coordinate team progress. The MQC aimed to stimulate the development of quality-management systems and the spread of methods to improve patient safety and logistics. The objective of this study is to describe how the first group of eight MQC hospitals sustained and disseminated improvements made and the quality methods used. Methods The approach followed by the hospitals was described using interview and questionnaire data gathered from eight programme coordinators. Results MQC hospitals followed a systematic strategy of diffusion and sustainability. Hospital quality-management systems are further developed according to a model linking plan-do-study-act cycles at the unit and hospital level. The model involves quality norms based on realised successes, performance agreements with unit heads, organisational support, monitoring, and quarterly accountability reports. Conclusions It is concluded from this study that the MQC contributed to organisational development and dissemination within participating hospitals. Organisational learning effects were demonstrated. System changes affect the context factors in the theory of organisational readiness: organisational culture, policies and procedures, past experience, organisational resources, and organisational structure. Programme coordinator responses indicate that these factors are utilised to manage spread and sustainability. Further research is needed to assess long-term effects. PMID:21385467

The nonmedical use of prescription medicines among high school students: a cross-sectional study in Southern China.

PubMed

Wang, Hui; Deng, Jianxiong; Zhou, Xiaolan; Lu, Ciyong; Huang, Jinghui; Huang, Guoliang; Gao, Xue; He, Yuan

2014-08-01

The objective of this study was to examine the prevalence of the nonmedical use of prescription medicines (NMUPM) and the association between NMUPM and demographic, family and school factors. A cross-sectional study was conducted from 2007 to 2009. A total of 21,672 middle and high school students were surveyed in seven cities of Guangdong Province. Self-reported NMUPM and information regarding family and school factors were collected. Multilevel logistic regression analyses were used to explore potentially influential factors. Of the total sample, the mean age was 16 (±1.9) years. Approximately 6.0% of respondents reported lifetime NMUPM. The most common nonmedically used prescription drug among NMUPM users was scattered analgesics, at approximately 3.9%, followed by cough medicine with codeine (2.1%). Multilevel logistic regression analysis indicated that living arrangements, available money, social friends, and smoking were significantly correlated with NMUPM among boys and girls. Academic achievement and family relationships were only significantly correlated with NMUPM among girls, and communication with parents was only associated with NMUPM among boys. These results indicate that NMUPM represented a considerable problem for particular subgroups of adolescents. A well-established surveillance system and target intervention programs are needed given the potential long-term negative outcomes of NMUPM. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A multilevel analysis on the relationship between neighbourhood poverty and public hospital utilization: is the high Indigenous morbidity avoidable?

PubMed Central

2011-01-01

Background The estimated life expectancy at birth for Indigenous Australians is 10-11 years less than the general Australian population. The mean family income for Indigenous people is also significantly lower than for non-Indigenous people. In this paper we examine poverty or socioeconomic disadvantage as an explanation for the Indigenous health gap in hospital morbidity in Australia. Methods We utilised a cross-sectional and ecological design using the Northern Territory public hospitalisation data from 1 July 2004 to 30 June 2008 and socio-economic indexes for areas (SEIFA) from the 2006 census. Multilevel logistic regression models were used to estimate odds ratios and confidence intervals. Both total and potentially avoidable hospitalisations were investigated. Results This study indicated that lifting SEIFA scores for family income and education/occupation by two quintile categories for low socio-economic Indigenous groups was sufficient to overcome the excess hospital utilisation among the Indigenous population compared with the non-Indigenous population. The results support a reframing of the Indigenous health gap as being a consequence of poverty and not simplistically of ethnicity. Conclusions Socio-economic disadvantage is a likely explanation for a substantial proportion of the hospital morbidity gap between Indigenous and non-Indigenous populations. Efforts to improve Indigenous health outcomes should recognise poverty as an underlying determinant of the health gap. PMID:21951514

A multilevel analysis of individual and community effect on chronic childhood malnutrition in rural Nigeria.

PubMed

Uthman, Olalekan A

2009-04-01

Protein energy malnutrition is the second most important cause of childhood morbidity and mortality in Nigeria after infections. The purpose of this article was to develop and test a model of childhood malnutrition that includes individual-level characteristics along with contextual characteristics defined at the community level. Multilevel logistic regression analysis. A total of 4007 children resident in 96 rural villages in Nigeria. Stunting: height-for-age that is less than the international reference value by >2 standard deviations (SDs). Independent of other factors, children born to underweight mothers were 1.32-times more likely to be stunted [adjusted odds ratio (aOR) 1.32; 95% confidence interval (CI) 1.07-1.64]. For each additional month of breastfeeding the odds of being stunted increased by 4% (aOR 1.04; 95% CI 1.03-1.06). Each SD increase in the household wealth index and maternal health-seeking behaviour index decreased the odds of being stunted by 16% (aOR 0.84; 95% CI 0.76-0.94) and 29% (aOR 0.71; 95% CI 0.60 -0.82), respectively. The study has provided evidence that both individual and community characteristics are important predictors of childhood malnutrition in rural Nigeria; and that scholars trying to understand variation in childhood malnutrition should pay attention to the characteristics of both children and place of residence.

Relationship between a Centers for Disease Control and Prevention expanded HIV testing initiative and past-year testing by race/ethnicity: a multilevel analysis of the Behavioral Risk Factor Surveillance System.

PubMed

Gaines, Tommi L; Caldwell, Julia T; Ford, Chandra L; Mulatu, Mesfin S; Godette, Dionne C

2016-01-01

The Centers for Disease Control and Prevention's (CDC) expanded testing initiative (ETI) aims to bolster HIV testing among populations disproportionately affected by the HIV epidemic by providing additional funding to health departments serving these communities. ETI prioritizes testing in clinical settings; therefore, we examined the relationship between state-level ETI participation and past-year HIV testing among a racially/ethnically diverse sample of adult respondents to the 2012 Behavioral Risk Factor Surveillance System who accessed health services within the 12 months prior to being interviewed. Controlling for individual- and state-level characteristics in a multilevel logistic regression model, ETI participation was independently and positively associated with past-year testing, but this association varied by race/ethnicity. Hispanics had higher odds (adjusted odds ratio [AOR]: 1.49; 95% CI: 1.11-2.02) and American Indian/Alaska Natives had lower odds (AOR: 0.66; 95% CI: 0.43-0.99) of testing if they resided in states with (vs. without) ETI participation. State-level ETI participation did not significantly alter past-year testing among other racial/ethnic groups. Prioritizing public health resources in states most affected by HIV can improve testing patterns, but other mechanisms likely influence which racial/ethnic groups undergo testing.

Neighbourhood safety and leisure-time physical activity among Dutch adults: a multilevel perspective.

PubMed

Kramer, Daniëlle; Maas, Jolanda; Wingen, Marleen; Kunst, Anton E

2013-01-28

Several neighbourhood elements have been found to be related to leisure-time walking and cycling. However, the association with neighbourhood safety remains unclear. This study aimed to assess the association of neighbourhood-level safety with leisure-time walking and cycling among Dutch adults. Data were derived from the national health survey (POLS) 2006-2009, with valid data on 20046 respondents residing in 2127 neighbourhoods. Multilevel logistic regression models were used to examine the association between neighbourhood-level safety (general safety and specific safety components: physical disorder, social disorder, crime-related fear, traffic safety) and residents' engagement in outdoor leisure-time walking and cycling for at least 30 minutes per week. An increase in neighbourhood safety (both general safety and each of the safety components) was significantly associated with an increase in leisure-time cycling participation. Associations were strongest for general safety and among older women. In the general population, neighbourhood safety was not significantly associated with leisure-time walking. However, among younger and older adult men and lower educated individuals, an increase in general safety was associated with a decrease in leisure-time walking participation. In the Netherlands, neighbourhood safety appears to be related to leisure-time cycling but not to walking. Leisure-time cycling may best be encouraged by improving different safety components at once, rather than focusing on one safety aspect such as traffic safety. Special attention is needed for older women.

Coopetition in health care: A multi-level analysis of its individual and organizational determinants.

PubMed

Westra, Daan; Angeli, Federica; Carree, Martin; Ruwaard, Dirk

2017-08-01

Cooperative inter-organizational relations are salient to healthcare delivery. However, they do not match with the pro-competitive healthcare reforms implemented in several countries. Healthcare organizations thus need to balance competition and cooperation in a situation of 'coopetition'. In this paper we study the individual and organizational determinants of coopetition versus those of cooperation in the price-competitive specialized care sector of the Netherlands. We use shared medical specialists as a proxy of collaboration between healthcare organizations. Based on a sample of 15,431 medical specialists and 371 specialized care organizations from March 2016, one logistic multi-level model is used to predict medical specialists' likelihood to be shared and another to predict their likelihood to be shared to a competitor. We find that different organizations share different specialists to competitors and non-competitors. Cooperation and coopetition are hence distinct organizational strategies in health care. Cooperation manifests through spin-off formation. Coopetition occurs most among organizations in the price-competitive market segment but in alternative geographical markets. Hence, coopetition in health care does not appear to be particularly anti-competitive. However, healthcare organizations seem reluctant to share their most specialized human resources, limiting the knowledge-sharing effects of this type of relation. Therefore, it remains unclear whether coopetition in health care is beneficial to patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

Determinants of Academic Entrepreneurship Behavior: A Multilevel Model

ERIC Educational Resources Information Center

Llano, Joseph Anthony

2010-01-01

It is well established that universities encourage the acquisition and dissemination of new knowledge among university community members and beyond. However, what is less well understood is how universities encourage entrepreneurial (opportunity discovery, evaluation, and exploiting) behavior. This research investigated a multilevel model of the…

Attachment, Autonomy, and Emotional Reliance: A Multilevel Model

ERIC Educational Resources Information Center

Lynch, Martin F.

2013-01-01

This article reports a test of a multilevel model investigating how attachment security and autonomy contribute to emotional reliance, or the willingness to seek interpersonal support. Participants ("N" = 247) completed online measures of attachment, autonomy, emotional reliance, and vitality with respect to several everyday…

Evaluating Technical Efficiency of Nursing Care Using Data Envelopment Analysis and Multilevel Modeling.

PubMed

Min, Ari; Park, Chang Gi; Scott, Linda D

2016-05-23

Data envelopment analysis (DEA) is an advantageous non-parametric technique for evaluating relative efficiency of performance. This article describes use of DEA to estimate technical efficiency of nursing care and demonstrates the benefits of using multilevel modeling to identify characteristics of efficient facilities in the second stage of analysis. Data were drawn from LTCFocUS.org, a secondary database including nursing home data from the Online Survey Certification and Reporting System and Minimum Data Set. In this example, 2,267 non-hospital-based nursing homes were evaluated. Use of DEA with nurse staffing levels as inputs and quality of care as outputs allowed estimation of the relative technical efficiency of nursing care in these facilities. In the second stage, multilevel modeling was applied to identify organizational factors contributing to technical efficiency. Use of multilevel modeling avoided biased estimation of findings for nested data and provided comprehensive information on differences in technical efficiency among counties and states. © The Author(s) 2016.

Translating the Socio-Ecological Perspective into Multilevel Interventions: Gaps between Theory and Practice

ERIC Educational Resources Information Center

Schölmerich, Vera L. N.; Kawachi, Ichiro

2016-01-01

Multilevel interventions are inspired by socio-ecological models, and seek to create change on various levels--for example by increasing the health literacy of individuals as well as modifying the social norms within a community. Despite becoming a buzzword in public health, actual multilevel interventions remain scarce. In this commentary, we…

Area-level poverty and preterm birth risk: A population-based multilevel analysis

PubMed Central

DeFranco, Emily A; Lian, Min; Muglia, Louis A; Schootman, Mario

2008-01-01

Background Preterm birth is a complex disease with etiologic influences from a variety of social, environmental, hormonal, genetic, and other factors. The purpose of this study was to utilize a large population-based birth registry to estimate the independent effect of county-level poverty on preterm birth risk. To accomplish this, we used a multilevel logistic regression approach to account for multiple co-existent individual-level variables and county-level poverty rate. Methods Population-based study utilizing Missouri's birth certificate database (1989–1997). We conducted a multilevel logistic regression analysis to estimate the effect of county-level poverty on PTB risk. Of 634,994 births nested within 115 counties in Missouri, two levels were considered. Individual-level variables included demographics factors, prenatal care, health-related behavioral risk factors, and medical risk factors. The area-level variable included the percentage of the population within each county living below the poverty line (US census data, 1990). Counties were divided into quartiles of poverty; the first quartile (lowest rate of poverty) was the reference group. Results PTB < 35 weeks occurred in 24,490 pregnancies (3.9%). The rate of PTB < 35 weeks was 2.8% in counties within the lowest quartile of poverty and increased through the 4th quartile (4.9%), p < 0.0001. High county-level poverty was significantly associated with PTB risk. PTB risk (< 35 weeks) was increased for women who resided in counties within the highest quartile of poverty, adjusted odds ratio (adjOR) 1.18 (95% CI 1.03, 1.35), with a similar effect at earlier gestational ages (< 32 weeks), adjOR 1.27 (95% CI 1.06, 1.52). Conclusion Women residing in socioeconomically deprived areas are at increased risk of preterm birth, above other underlying risk factors. Although the risk increase is modest, it affects a large number of pregnancies. PMID:18793437

Area-level poverty and preterm birth risk: a population-based multilevel analysis.

PubMed

DeFranco, Emily A; Lian, Min; Muglia, Louis A; Schootman, Mario

2008-09-15

Preterm birth is a complex disease with etiologic influences from a variety of social, environmental, hormonal, genetic, and other factors. The purpose of this study was to utilize a large population-based birth registry to estimate the independent effect of county-level poverty on preterm birth risk. To accomplish this, we used a multilevel logistic regression approach to account for multiple co-existent individual-level variables and county-level poverty rate. Population-based study utilizing Missouri's birth certificate database (1989-1997). We conducted a multilevel logistic regression analysis to estimate the effect of county-level poverty on PTB risk. Of 634,994 births nested within 115 counties in Missouri, two levels were considered. Individual-level variables included demographics factors, prenatal care, health-related behavioral risk factors, and medical risk factors. The area-level variable included the percentage of the population within each county living below the poverty line (US census data, 1990). Counties were divided into quartiles of poverty; the first quartile (lowest rate of poverty) was the reference group. PTB < 35 weeks occurred in 24,490 pregnancies (3.9%). The rate of PTB < 35 weeks was 2.8% in counties within the lowest quartile of poverty and increased through the 4th quartile (4.9%), p < 0.0001. High county-level poverty was significantly associated with PTB risk. PTB risk (< 35 weeks) was increased for women who resided in counties within the highest quartile of poverty, adjusted odds ratio (adj OR) 1.18 (95% CI 1.03, 1.35), with a similar effect at earlier gestational ages (< 32 weeks), adj OR 1.27 (95% CI 1.06, 1.52). Women residing in socioeconomically deprived areas are at increased risk of preterm birth, above other underlying risk factors. Although the risk increase is modest, it affects a large number of pregnancies.

Using SEM to Analyze Complex Survey Data: A Comparison between Design-Based Single-Level and Model-Based Multilevel Approaches

ERIC Educational Resources Information Center

Wu, Jiun-Yu; Kwok, Oi-man

2012-01-01

Both ad-hoc robust sandwich standard error estimators (design-based approach) and multilevel analysis (model-based approach) are commonly used for analyzing complex survey data with nonindependent observations. Although these 2 approaches perform equally well on analyzing complex survey data with equal between- and within-level model structures…

Using Design-Based Latent Growth Curve Modeling with Cluster-Level Predictor to Address Dependency

ERIC Educational Resources Information Center

Wu, Jiun-Yu; Kwok, Oi-Man; Willson, Victor L.

2014-01-01

The authors compared the effects of using the true Multilevel Latent Growth Curve Model (MLGCM) with single-level regular and design-based Latent Growth Curve Models (LGCM) with or without the higher-level predictor on various criterion variables for multilevel longitudinal data. They found that random effect estimates were biased when the…

Illustration of a Multilevel Model for Meta-Analysis

ERIC Educational Resources Information Center

de la Torre, Jimmy; Camilli, Gregory; Vargas, Sadako; Vernon, R. Fox

2007-01-01

In this article, the authors present a multilevel (or hierarchical linear) model that illustrates issues in the application of the model to data from meta-analytic studies. In doing so, several issues are discussed that typically arise in the course of a meta-analysis. These include the presence of non-zero between-study variability, how multiple…

The Development of a Multi-Level Model for Crisis Preparedness and Intervention in the Greek Educational System

ERIC Educational Resources Information Center

Hatzichristiou, Chryse; Issari, Philia; Lykitsakou, Konstantina; Lampropoulou, Aikaterini; Dimitropoulou, Panayiota

2011-01-01

This article proposes a multi-level model for crisis preparedness and intervention in the Greek educational system. It presents: a) a brief overview of leading models of school crisis preparedness and intervention as well as cultural considerations for contextually relevant crisis response; b) a description of existing crisis intervention…

Explaining Technology Integration in K-12 Classrooms: A Multilevel Path Analysis Model

ERIC Educational Resources Information Center

Liu, Feng; Ritzhaupt, Albert D.; Dawson, Kara; Barron, Ann E.

2017-01-01

The purpose of this research was to design and test a model of classroom technology integration in the context of K-12 schools. The proposed multilevel path analysis model includes teacher, contextual, and school related variables on a teacher's use of technology and confidence and comfort using technology as mediators of classroom technology…

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

ERIC Educational Resources Information Center

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

2006-01-01

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

Standardized Mean Differences in Two-Level Cross-Classified Random Effects Models

ERIC Educational Resources Information Center

Lai, Mark H. C.; Kwok, Oi-Man

2014-01-01

Multilevel modeling techniques are becoming more popular in handling data with multilevel structure in educational and behavioral research. Recently, researchers have paid more attention to cross-classified data structure that naturally arises in educational settings. However, unlike traditional single-level research, methodological studies about…

Requirements for multi-level systems pharmacology models to reach end-usage: the case of type 2 diabetes.

PubMed

Nyman, Elin; Rozendaal, Yvonne J W; Helmlinger, Gabriel; Hamrén, Bengt; Kjellsson, Maria C; Strålfors, Peter; van Riel, Natal A W; Gennemark, Peter; Cedersund, Gunnar

2016-04-06

We are currently in the middle of a major shift in biomedical research: unprecedented and rapidly growing amounts of data may be obtained today, from in vitro, in vivo and clinical studies, at molecular, physiological and clinical levels. To make use of these large-scale, multi-level datasets, corresponding multi-level mathematical models are needed, i.e. models that simultaneously capture multiple layers of the biological, physiological and disease-level organization (also referred to as quantitative systems pharmacology-QSP-models). However, today's multi-level models are not yet embedded in end-usage applications, neither in drug research and development nor in the clinic. Given the expectations and claims made historically, this seemingly slow adoption may seem surprising. Therefore, we herein consider a specific example-type 2 diabetes-and critically review the current status and identify key remaining steps for these models to become mainstream in the future. This overview reveals how, today, we may use models to ask scientific questions concerning, e.g., the cellular origin of insulin resistance, and how this translates to the whole-body level and short-term meal responses. However, before these multi-level models can become truly useful, they need to be linked with the capabilities of other important existing models, in order to make them 'personalized' (e.g. specific to certain patient phenotypes) and capable of describing long-term disease progression. To be useful in drug development, it is also critical that the developed models and their underlying data and assumptions are easily accessible. For clinical end-usage, in addition, model links to decision-support systems combined with the engagement of other disciplines are needed to create user-friendly and cost-efficient software packages.

The relationship between multilevel models and non-parametric multilevel mixture models: Discrete approximation of intraclass correlation, random coefficient distributions, and residual heteroscedasticity.

PubMed

Rights, Jason D; Sterba, Sonya K

2016-11-01

Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non-parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non-parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non-standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed. © 2016 The British Psychological Society.

Get Over It! A Multilevel Threshold Autoregressive Model for State-Dependent Affect Regulation.

PubMed

De Haan-Rietdijk, Silvia; Gottman, John M; Bergeman, Cindy S; Hamaker, Ellen L

2016-03-01

Intensive longitudinal data provide rich information, which is best captured when specialized models are used in the analysis. One of these models is the multilevel autoregressive model, which psychologists have applied successfully to study affect regulation as well as alcohol use. A limitation of this model is that the autoregressive parameter is treated as a fixed, trait-like property of a person. We argue that the autoregressive parameter may be state-dependent, for example, if the strength of affect regulation depends on the intensity of affect experienced. To allow such intra-individual variation, we propose a multilevel threshold autoregressive model. Using simulations, we show that this model can be used to detect state-dependent regulation with adequate power and Type I error. The potential of the new modeling approach is illustrated with two empirical applications that extend the basic model to address additional substantive research questions.

The Effects of Including Observed Means or Latent Means as Covariates in Multilevel Models for Cluster Randomized Trials

ERIC Educational Resources Information Center

Aydin, Burak; Leite, Walter L.; Algina, James

2016-01-01

We investigated methods of including covariates in two-level models for cluster randomized trials to increase power to detect the treatment effect. We compared multilevel models that included either an observed cluster mean or a latent cluster mean as a covariate, as well as the effect of including Level 1 deviation scores in the model. A Monte…

Adherence to oral anticoagulants in patients with atrial fibrillation-a population-based retrospective cohort study linking health information systems in the Valencia region, Spain: a study protocol.

PubMed

Sanfélix-Gimeno, G; Rodríguez-Bernal, C L; Hurtado, I; Baixáuli-Pérez, C; Librero, J; Peiró, S

2015-10-19

Adherence to oral anticoagulation (OAC) treatment, vitamin K antagonists or new oral anticoagulants, is an essential element for effectiveness. Information on adherence to OAC in atrial fibrillation (AF) and the impact of adherence on clinical outcomes using real-world data barely exists. We aim to describe the patterns of adherence to OAC over time in patients with AF, estimate the associated factors and their impact on clinical events, and assess the same issues with conventional measures of primary and secondary adherence-proportion of days covered (PDC) and persistence-in routine clinical practice. This is a population-based retrospective cohort study including all patients with AF treated with OAC from 2010 to date in Valencia, Spain; data will be obtained from diverse electronic records of the Valencia Health Agency. adherence trajectories. (1) primary non-adherence; (2) secondary adherence: (a) PDC, (b) persistence. Clinical outcomes: hospitalisation for haemorrhagic or thromboembolic events and death during follow-up. (1) description of baseline characteristics, adherence patterns (trajectory models or latent class growth analysis models) and conventional adherence measures; (2) logistic or Cox multivariate regression models, to assess the associations between adherence measures and the covariates, and logistic multinomial regression models, to identify characteristics associated with each trajectory; (3) Cox proportional hazard models, to assess the relationship between adherence and clinical outcomes, with propensity score adjustment applied to further control for potential confounders; (4) to estimate the importance of different healthcare levels in the variations of adherence, logistic or Cox multilevel regression models. This study has been approved by the corresponding Clinical Research Ethics Committee. We plan to disseminate the project's findings through peer-reviewed publications and presentations at relevant health conferences. Policy reports will also be prepared in order to promote the translation of our findings into policy and clinical practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Modeling of the multilevel conduction characteristics and fatigue profile of Ag/La1/3Ca2/3MnO3/Pt structures using a compact memristive approach

NASA Astrophysics Data System (ADS)

Miranda, E.; Román Acevedo, W.; Rubi, D.; Lüders, U.; Granell, P.; Suñé, J.; Levy, P.

2017-05-01

The hysteretic conduction characteristics and fatigue profile of La1/3Ca2/3MnO3 (LCMO)-based memristive devices were investigated. The oxide films were grown by pulsed laser deposition (PLD) and sandwiched between Ag and Pt electrodes. The devices exhibit bipolar resistive switching (RS) effect with well-defined intermediate conduction states that arise from partial SET and RESET events. The current-voltage curves are modeled and simulated using a compact memristive approach. Two equations are considered: one for the electron transport based on the double-diode equation and the other for the memory state of the device driven by the play operator with logistic ridge functions. An expression that accounts for the remnant resistance of the device is obtained after simplifying the model equations in the low-voltage limit. The role played by the power dissipation in the LCMO reset dynamics as well as the asymmetrical reduction of the resistance window caused by long trains of switching pulses are discussed.

An Original Stepwise Multilevel Logistic Regression Analysis of Discriminatory Accuracy: The Case of Neighbourhoods and Health

PubMed Central

Wagner, Philippe; Ghith, Nermin; Leckie, George

2016-01-01

Background and Aim Many multilevel logistic regression analyses of “neighbourhood and health” focus on interpreting measures of associations (e.g., odds ratio, OR). In contrast, multilevel analysis of variance is rarely considered. We propose an original stepwise analytical approach that distinguishes between “specific” (measures of association) and “general” (measures of variance) contextual effects. Performing two empirical examples we illustrate the methodology, interpret the results and discuss the implications of this kind of analysis in public health. Methods We analyse 43,291 individuals residing in 218 neighbourhoods in the city of Malmö, Sweden in 2006. We study two individual outcomes (psychotropic drug use and choice of private vs. public general practitioner, GP) for which the relative importance of neighbourhood as a source of individual variation differs substantially. In Step 1 of the analysis, we evaluate the OR and the area under the receiver operating characteristic (AUC) curve for individual-level covariates (i.e., age, sex and individual low income). In Step 2, we assess general contextual effects using the AUC. Finally, in Step 3 the OR for a specific neighbourhood characteristic (i.e., neighbourhood income) is interpreted jointly with the proportional change in variance (i.e., PCV) and the proportion of ORs in the opposite direction (POOR) statistics. Results For both outcomes, information on individual characteristics (Step 1) provide a low discriminatory accuracy (AUC = 0.616 for psychotropic drugs; = 0.600 for choosing a private GP). Accounting for neighbourhood of residence (Step 2) only improved the AUC for choosing a private GP (+0.295 units). High neighbourhood income (Step 3) was strongly associated to choosing a private GP (OR = 3.50) but the PCV was only 11% and the POOR 33%. Conclusion Applying an innovative stepwise multilevel analysis, we observed that, in Malmö, the neighbourhood context per se had a negligible influence on individual use of psychotropic drugs, but appears to strongly condition individual choice of a private GP. However, the latter was only modestly explained by the socioeconomic circumstances of the neighbourhoods. Our analyses are based on real data and provide useful information for understanding neighbourhood level influences in general and on individual use of psychotropic drugs and choice of GP in particular. However, our primary aim is to illustrate how to perform and interpret a multilevel analysis of individual heterogeneity in social epidemiology and public health. Our study shows that neighbourhood “effects” are not properly quantified by reporting differences between neighbourhood averages but rather by measuring the share of the individual heterogeneity that exists at the neighbourhood level. PMID:27120054

Significant variations in the cervical cancer screening rate in China by individual-level and geographical measures of socioeconomic status: a multilevel model analysis of a nationally representative survey dataset.

PubMed

Bao, Heling; Zhang, Lei; Wang, Limin; Zhang, Mei; Zhao, Zhenping; Fang, Liwen; Cong, Shu; Zhou, Maigeng; Wang, Linhong

2018-05-01

Variations in cervical cancer screening rates in China have rarely been studied in depth. This study aimed to investigate cervical cancer screening rates in relation to both individual-level and geographical measures of socioeconomic status (SES). Data were obtained from women aged 21 years or older by face-to-face interviews between August 2013 and July 2014 as part of the Chinese Chronic Diseases and Risk Factors Surveillance. The geographical variables were obtained from the 2010 Chinese population census. The cervical cancer screening rates and 95% confidence interval (CI) were estimated and mapped. Multilevel logistic regression models were fitted. Overall, only 21.4% (95% CI: 19.6-23.1%) of 91,816 women aged ≥21 years reported having ever been screened for cervical cancer and significant geographical variations at both province and county levels were identified (P < 0.01). The cervical cancer screening rates were the lowest among the poor [13.9% (95% CI: 12.1-15.7%)], uninsured [14.4% (95% CI: 10.3-18.4%)], less-educated [16.0% (95% CI: 14.3-17.6%)], and agricultural employment [18.1% (95% CI: 15.8-20.4%)] women along with those residing in areas of low economic status [15.0% (95% CI: 11.8-18.2%)], of low urbanization [15.6% (95% CI: 13.4-17.7%)], and of low education status [16.0% (95% CI: 14.0-18.1%)]. The multilevel analysis also indicated that women with lower individual-level measures of SES residing in areas with low geographical measures of SES were significantly less likely to receive cervical cancer screening (P < 0.0001). Despite the launch of an organized cancer screening program in China, cervical cancer screening rates remain alarmingly low and significant variations based on geographical regions and measures of SES still exist. It is therefore essential to adopt strategies to better direct limited available public resources to priority groups. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Transportation and socioeconomic impacts of bypasses on communities : an integrated synthesis of panel data, multilevel, and spatial econometric models with case studies.

DOT National Transportation Integrated Search

2011-09-21

Title: Transportation and Socioeconomic Impacts of Bypasses on Communities: An Integrated Synthesis of Panel Data, Multilevel, and Spatial Econometric Models with Case Studies. The title used at the start of this project was Transportation and Soc...

Multilevel Evaluation Systems Project. Final Report.

ERIC Educational Resources Information Center

Herman, Joan L.

Several studies were conducted in 1987 by the Multilevel Evaluation Systems Project, which focuses on developing a model for a multi-purpose, multi-user evaluation system to facilitate educational decision making and evaluation. The project model emphasizes on-going integrated assessment of individuals, classes, and programs using a variety of…

Income Inequality and Risk of Suicide in New York City Neighborhoods: A Multilevel Case-Control Study

ERIC Educational Resources Information Center

Miller, Jeffrey R.; Piper, Tinka Markham; Ahern, Jennifer; Tracy, Melissa; Tardiff, Kenneth J.; Vlahov, David; Galea, Sandro

2005-01-01

Evidence on the relationship between income inequality and suicide is inconsistent. Data from the New York City Office of the Chief Medical Examiner for all fatal injuries was collected to conduct a multilevel case-control study. In multilevel models, suicide decedents (n = 374) were more likely than accident controls (n = 453) to reside in…

National Profiles of Classroom Quality and Family Involvement: A Multilevel Examination of Proximal Influences on Head Start Children's School Readiness

ERIC Educational Resources Information Center

Bulotsky-Shearer, Rebecca J.; Wen, Xiaoli; Faria, Ann-Marie; Hahs-Vaughn, Debbie L.; Korfmacher, Jon

2012-01-01

Guided by a developmental and ecological model, the study employed latent profile analysis to identify a multilevel typology of family involvement and Head Start classroom quality. Using the nationally representative Head Start Family and Child Experiences Survey (FACES 1997; N = 1870), six multilevel latent profiles were estimated, characterized…

Multilevel regression analyses to investigate the relationship between two variables over time: examining the longitudinal association between intrusion and avoidance.

PubMed

Suvak, Michael K; Walling, Sherry M; Iverson, Katherine M; Taft, Casey T; Resick, Patricia A

2009-12-01

Multilevel modeling is a powerful and flexible framework for analyzing nested data structures (e.g., repeated measures or longitudinal designs). The authors illustrate a series of multilevel regression procedures that can be used to elucidate the nature of the relationship between two variables across time. The goal is to help trauma researchers become more aware of the utility of multilevel modeling as a tool for increasing the field's understanding of posttraumatic adaptation. These procedures are demonstrated by examining the relationship between two posttraumatic symptoms, intrusion and avoidance, across five assessment points in a sample of rape and robbery survivors (n = 286). Results revealed that changes in intrusion were highly correlated with changes in avoidance over the 18-month posttrauma period.

A multilevel control system for the large space telescope. [numerical analysis/optimal control

NASA Technical Reports Server (NTRS)

Siljak, D. D.; Sundareshan, S. K.; Vukcevic, M. B.

1975-01-01

A multilevel scheme was proposed for control of Large Space Telescope (LST) modeled by a three-axis-six-order nonlinear equation. Local controllers were used on the subsystem level to stabilize motions corresponding to the three axes. Global controllers were applied to reduce (and sometimes nullify) the interactions among the subsystems. A multilevel optimization method was developed whereby local quadratic optimizations were performed on the subsystem level, and global control was again used to reduce (nullify) the effect of interactions. The multilevel stabilization and optimization methods are presented as general tools for design and then used in the design of the LST Control System. The methods are entirely computerized, so that they can accommodate higher order LST models with both conceptual and numerical advantages over standard straightforward design techniques.

Metamodeling and the Critic-based approach to multi-level optimization.

PubMed

Werbos, Ludmilla; Kozma, Robert; Silva-Lugo, Rodrigo; Pazienza, Giovanni E; Werbos, Paul J

2012-08-01

Large-scale networks with hundreds of thousands of variables and constraints are becoming more and more common in logistics, communications, and distribution domains. Traditionally, the utility functions defined on such networks are optimized using some variation of Linear Programming, such as Mixed Integer Programming (MIP). Despite enormous progress both in hardware (multiprocessor systems and specialized processors) and software (Gurobi) we are reaching the limits of what these tools can handle in real time. Modern logistic problems, for example, call for expanding the problem both vertically (from one day up to several days) and horizontally (combining separate solution stages into an integrated model). The complexity of such integrated models calls for alternative methods of solution, such as Approximate Dynamic Programming (ADP), which provide a further increase in the performance necessary for the daily operation. In this paper, we present the theoretical basis and related experiments for solving the multistage decision problems based on the results obtained for shorter periods, as building blocks for the models and the solution, via Critic-Model-Action cycles, where various types of neural networks are combined with traditional MIP models in a unified optimization system. In this system architecture, fast and simple feed-forward networks are trained to reasonably initialize more complicated recurrent networks, which serve as approximators of the value function (Critic). The combination of interrelated neural networks and optimization modules allows for multiple queries for the same system, providing flexibility and optimizing performance for large-scale real-life problems. A MATLAB implementation of our solution procedure for a realistic set of data and constraints shows promising results, compared to the iterative MIP approach. Copyright © 2012 Elsevier Ltd. All rights reserved.

At the Frontiers of Modeling Intensive Longitudinal Data: Dynamic Structural Equation Models for the Affective Measurements from the COGITO Study.

PubMed

Hamaker, E L; Asparouhov, T; Brose, A; Schmiedek, F; Muthén, B

2018-04-06

With the growing popularity of intensive longitudinal research, the modeling techniques and software options for such data are also expanding rapidly. Here we use dynamic multilevel modeling, as it is incorporated in the new dynamic structural equation modeling (DSEM) toolbox in Mplus, to analyze the affective data from the COGITO study. These data consist of two samples of over 100 individuals each who were measured for about 100 days. We use composite scores of positive and negative affect and apply a multilevel vector autoregressive model to allow for individual differences in means, autoregressions, and cross-lagged effects. Then we extend the model to include random residual variances and covariance, and finally we investigate whether prior depression affects later depression scores through the random effects of the daily diary measures. We end with discussing several urgent-but mostly unresolved-issues in the area of dynamic multilevel modeling.

[How to fit and interpret multilevel models using SPSS].

PubMed

Pardo, Antonio; Ruiz, Miguel A; San Martín, Rafael

2007-05-01

Hierarchic or multilevel models are used to analyse data when cases belong to known groups and sample units are selected both from the individual level and from the group level. In this work, the multilevel models most commonly discussed in the statistic literature are described, explaining how to fit these models using the SPSS program (any version as of the 11 th ) and how to interpret the outcomes of the analysis. Five particular models are described, fitted, and interpreted: (1) one-way analysis of variance with random effects, (2) regression analysis with means-as-outcomes, (3) one-way analysis of covariance with random effects, (4) regression analysis with random coefficients, and (5) regression analysis with means- and slopes-as-outcomes. All models are explained, trying to make them understandable to researchers in health and behaviour sciences.

Multi-level optimization of a beam-like space truss utilizing a continuum model

NASA Technical Reports Server (NTRS)

Yates, K.; Gurdal, Z.; Thangjitham, S.

1992-01-01

A continuous beam model is developed for approximate analysis of a large, slender, beam-like truss. The model is incorporated in a multi-level optimization scheme for the weight minimization of such trusses. This scheme is tested against traditional optimization procedures for savings in computational cost. Results from both optimization methods are presented for comparison.

Investigating Associations between School Climate and Bullying in Secondary Schools: Multilevel Contextual Effects Modeling

ERIC Educational Resources Information Center

Konishi, Chiaki; Miyazaki, Yasuo; Hymel, Shelley; Waterhouse, Terry

2017-01-01

This study examined how student reports of bullying were related to different dimensions of school climate, at both the school and the student levels, using a contextual effects model in a two-level multilevel modeling framework. Participants included 48,874 secondary students (grades 8 to 12; 24,244 girls) from 76 schools in Western Canada.…

Estimating Multi-Level Discrete-Time Hazard Models Using Cross-Sectional Data: Neighborhood Effects on the Onset of Adolescent Cigarette Use.

ERIC Educational Resources Information Center

Reardon, Sean F.; Brennan, Robert T.; Buka, Stephen L.

2002-01-01

Developed procedures for constructing a retrospective person-period data set from cross-sectional data and discusses modeling strategies for estimating multilevel discrete-time event history models. Applied the methods to the analysis of cigarette use by 1,979 urban adolescents. Results show the influence of the racial composition of the…

The Application of a Multiphase Triangulation Approach to Mixed Methods: The Research of an Aspiring School Principal Development Program

ERIC Educational Resources Information Center

Youngs, Howard; Piggot-Irvine, Eileen

2012-01-01

Mixed methods research has emerged as a credible alternative to unitary research approaches. The authors show how a combination of a triangulation convergence model with a triangulation multilevel model was used to research an aspiring school principal development pilot program. The multilevel model is used to show the national and regional levels…

Effects of Individual Nurse and Hospital Characteristics on Patient Adverse Events and Quality of Care: A Multilevel Analysis.

PubMed

Lee, Seung Eun; Vincent, Catherine; Dahinten, V Susan; Scott, Linda D; Park, Chang Gi; Dunn Lopez, Karen

2018-06-14

This study aimed to investigate effects of individual nurse and hospital characteristics on patient adverse events and quality of care using a multilevel approach. This is a secondary analysis of a combination of nurse survey data (N = 1,053 nurses) and facility data (N = 63 hospitals) in Canada. Multilevel ordinal logistic regression was employed to examine effects of individual nurse and hospital characteristics on patient adverse events. Multilevel linear regressions were used to investigate effects of individual nurse and hospital characteristics on quality of care. Organizational safety culture was associated with patient adverse events and quality of care. Controlling for effects of nurse and hospital characteristics, nurses in hospitals with a stronger safety culture were 64% less likely to report administration of wrong medication, time, or dose; 58% less likely to report patient falls with injury; and 60% less likely to report urinary tract infections; and were more likely to report higher levels of quality of care. Additionally, the effects of individual-level baccalaureate education and years of experience on quality of care differed across hospitals, and hospital-level nurse education interacted with individual-level baccalaureate education. This study makes significant contributions to existing knowledge regarding the positive effect of organizational safety culture on patient adverse events and quality of care. Healthcare organizations should strive to improve their safety culture by creating environments where healthcare providers trust each other, work collaboratively, and share accountability for patient safety and care quality. © 2018 Sigma Theta Tau International.

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

PubMed

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

2017-05-01

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

A multi-level model of emerging technology: An empirical study of the evolution of biotechnology from 1976 to 2003

PubMed Central

van Witteloostuijn, Arjen

2018-01-01

In this paper, we develop an ecological, multi-level model that can be used to study the evolution of emerging technology. More specifically, by defining technology as a system composed of a set of interacting components, we can build upon the argument of multi-level density dependence from organizational ecology to develop a distribution-independent model of technological evolution. This allows us to distinguish between different stages of component development, which provides more insight into the emergence of stable component configurations, or dominant designs. We validate our hypotheses in the biotechnology industry by using patent data from the USPTO from 1976 to 2003. PMID:29795575

Racial Residential Segregation and STI Diagnosis Among Non-Hispanic Blacks, 2006-2010.

PubMed

Lutfi, Khaleeq; Trepka, Mary Jo; Fennie, Kristopher P; Ibañez, Gladys; Gladwin, Hugh

2018-06-01

Sexually transmitted infections (STI) disproportionately impact non-Hispanic blacks. Racial residential segregation has been associated with negative socioeconomic outcomes. We sought to examine the association between segregation and STI diagnosis among blacks. The National Survey of Family Growth and US Census served as data sources. Five distinct dimensions represent segregation. The association between STI diagnosis and each segregation dimension was assessed with multilevel logistic regression modeling. 305 (7.4%) blacks reported STI diagnosis during the past 12 months. Depending on the dimension, segregation was a risk factor [dissimilarity aOR 2.41 (95% CI 2.38-2.43)] and a protective factor [isolation aOR 0.90 (95% CI 0.89-0.91)] for STI diagnosis. Findings suggest that STI diagnosis among blacks is associated with segregation. Additional research is needed to identify mechanisms for how segregation affects STI diagnosis and to aid in the development of interventions to decrease STIs.

THE EFFECT OF A MALE SURPLUS ON INTIMATE PARTNER VIOLENCE IN INDIA.

PubMed

Bose, Sunita; Trent, Katherine; South, Scott J

2013-08-31

Theories of the social consequences of imbalanced sex ratios posit that men will exercise extraordinarily strict control over women's behaviour when women's relationship options are plentiful and men's own options are limited. We use data from the third wave of the Indian National Family and Health Survey, conducted in 2005-06, to explore this issue, investigating the effect of the community sex ratio on women's experience of intimate partner violence in India. Multilevel logistic regression models show that a relative surplus of men in a community increases the likelihood of physical abuse by husbands even after adjusting for various other individual, household, and geographic characteristics. Further evidence of control over women when there is a sex ratio imbalance is provided by the increased odds of husbands distrusting wives with money when there is a male surplus in the local community.

THE EFFECT OF A MALE SURPLUS ON INTIMATE PARTNER VIOLENCE IN INDIA

PubMed Central

Bose, Sunita; Trent, Katherine; South, Scott J.

2013-01-01

Theories of the social consequences of imbalanced sex ratios posit that men will exercise extraordinarily strict control over women’s behaviour when women’s relationship options are plentiful and men’s own options are limited. We use data from the third wave of the Indian National Family and Health Survey, conducted in 2005–06, to explore this issue, investigating the effect of the community sex ratio on women’s experience of intimate partner violence in India. Multilevel logistic regression models show that a relative surplus of men in a community increases the likelihood of physical abuse by husbands even after adjusting for various other individual, household, and geographic characteristics. Further evidence of control over women when there is a sex ratio imbalance is provided by the increased odds of husbands distrusting wives with money when there is a male surplus in the local community. PMID:24511150

Obesity and Regional Immigrant Density.

PubMed

Emerson, Scott D; Carbert, Nicole S

2017-11-24

Canada has an increasingly large immigrant population. Areas of higher immigrant density, may relate to immigrants' health through reduced acculturation to Western foods, greater access to cultural foods, and/or promotion of salubrious values/practices. It is unclear, however, whether an association exists between Canada-wide regional immigrant density and obesity among immigrants. Thus, we examined whether regional immigrant density was related to obesity, among immigrants. Adult immigrant respondents (n = 15,595) to a national population-level health survey were merged with region-level immigrant density data. Multi-level logistic regression was used to model the odds of obesity associated with increased immigrant density. The prevalence of obesity among the analytic sample was 16%. Increasing regional immigrant density was associated with lower odds of obesity among minority immigrants and long-term white immigrants. Immigrant density at the region-level in Canada may be an important contextual factor to consider when examining obesity among immigrants.

Highly-Efficient and Modular Medium-Voltage Converters

DTIC Science & Technology

2015-09-28

HVDC modular multilevel converter in decoupled double synchronous reference frame for voltage oscillation reduction," IEEE Trans. Ind...Electron., vol. 29, pp. 77-88, Jan 2014. [10] M. Guan and Z. Xu, "Modeling and control of a modular multilevel converter -based HVDC system under...34 Modular multilevel converter design for VSC HVDC applications," IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 3, pp.

Mathematics Low Achievement in Greece: A Multilevel Analysis of the Programme for International Student Assessment (PISA) 2012 Data

ERIC Educational Resources Information Center

Karakolidis, Anastasios; Pitsia, Vasiliki; Emvalotis, Anastassios

2016-01-01

The main aim of the present study was to carry out an in-depth examination of mathematics underperformance in Greece. By applying a binary multilevel model to the PISA 2012 data, this study investigated the factors which were linked to low achievement in mathematics. The multilevel analysis revealed that students' gender, immigration status,…

Multilevel Factor Analyses of Family Data from the Hawai'i Family Study of Cognition

ERIC Educational Resources Information Center

McArdle, John J.; Hamagami, Fumiaki; Bautista, Randy; Onoye, Jane; Hishinuma, Earl S.; Prescott, Carol A.; Takeshita, Junji; Zonderman, Alan B.; Johnson, Ronald C.

2014-01-01

In this study, we reanalyzed the classic Hawai'i Family Study of Cognition (HFSC) data using contemporary multilevel modeling techniques. We used the HFSC baseline data ("N" = 6,579) and reexamined the factorial structure of 16 cognitive variables using confirmatory (restricted) measurement models in an explicit sequence. These models…

Using Multilevel Modeling in Counseling Research

ERIC Educational Resources Information Center

Lynch, Martin F.

2012-01-01

This conceptual and practical overview of multilevel modeling (MLM) for researchers in counseling and development provides guidelines on setting up SPSS to perform MLM and an example of how to present the findings. It also provides a discussion on how counseling and developmental researchers can use MLM to address their own research questions.…

Multilevel Modeling: Overview and Applications to Research in Counseling Psychology

ERIC Educational Resources Information Center

Kahn, Jeffrey H.

2011-01-01

Multilevel modeling (MLM) is rapidly becoming the standard method of analyzing nested data, for example, data from students within multiple schools, data on multiple clients seen by a smaller number of therapists, and even longitudinal data. Although MLM analyses are likely to increase in frequency in counseling psychology research, many readers…

Multilevel and Single-Level Models for Measured and Latent Variables When Data Are Clustered

ERIC Educational Resources Information Center

Stapleton, Laura M.; McNeish, Daniel M.; Yang, Ji Seung

2016-01-01

Multilevel models are often used to evaluate hypotheses about relations among constructs when data are nested within clusters (Raudenbush & Bryk, 2002), although alternative approaches are available when analyzing nested data (Binder & Roberts, 2003; Sterba, 2009). The overarching goal of this article is to suggest when it is appropriate…

Multilevel Cognitive Diagnosis Models for Assessing Changes in Latent Attributes

ERIC Educational Resources Information Center

Huang, Hung-Yu

2017-01-01

Cognitive diagnosis models (CDMs) have been developed to evaluate the mastery status of individuals with respect to a set of defined attributes or skills that are measured through testing. When individuals are repeatedly administered a cognitive diagnosis test, a new class of multilevel CDMs is required to assess the changes in their attributes…

Multilevel Structural Equation Models for the Analysis of Comparative Data on Educational Performance

ERIC Educational Resources Information Center

Goldstein, Harvey; Bonnet, Gerard; Rocher, Thierry

2007-01-01

The Programme for International Student Assessment comparative study of reading performance among 15-year-olds is reanalyzed using statistical procedures that allow the full complexity of the data structures to be explored. The article extends existing multilevel factor analysis and structural equation models and shows how this can extract richer…

Multilevel Factor Analysis by Model Segregation: New Applications for Robust Test Statistics

ERIC Educational Resources Information Center

Schweig, Jonathan

2014-01-01

Measures of classroom environments have become central to policy efforts that assess school and teacher quality. This has sparked a wide interest in using multilevel factor analysis to test measurement hypotheses about classroom-level variables. One approach partitions the total covariance matrix and tests models separately on the…

Covariate Selection for Multilevel Models with Missing Data

PubMed Central

Marino, Miguel; Buxton, Orfeu M.; Li, Yi

2017-01-01

Missing covariate data hampers variable selection in multilevel regression settings. Current variable selection techniques for multiply-imputed data commonly address missingness in the predictors through list-wise deletion and stepwise-selection methods which are problematic. Moreover, most variable selection methods are developed for independent linear regression models and do not accommodate multilevel mixed effects regression models with incomplete covariate data. We develop a novel methodology that is able to perform covariate selection across multiply-imputed data for multilevel random effects models when missing data is present. Specifically, we propose to stack the multiply-imputed data sets from a multiple imputation procedure and to apply a group variable selection procedure through group lasso regularization to assess the overall impact of each predictor on the outcome across the imputed data sets. Simulations confirm the advantageous performance of the proposed method compared with the competing methods. We applied the method to reanalyze the Healthy Directions-Small Business cancer prevention study, which evaluated a behavioral intervention program targeting multiple risk-related behaviors in a working-class, multi-ethnic population. PMID:28239457

Multilevel poisson regression modelling for determining factors of dengue fever cases in bandung

NASA Astrophysics Data System (ADS)

Arundina, Davila Rubianti; Tantular, Bertho; Pontoh, Resa Septiani

2017-03-01

Scralatina or Dengue Fever is a kind of fever caused by serotype virus which Flavivirus genus and be known as Dengue Virus. Dengue Fever caused by Aedes Aegipty Mosquito bites who infected by a dengue virus. The study was conducted in 151 villages in Bandung. Health Analysts believes that there are two factors that affect the dengue cases, Internal factor (individual) and external factor (environment). The data who used in this research is hierarchical data. The method is used for hierarchical data modelling is multilevel method. Which is, the level 1 is village and level 2 is sub-district. According exploration data analysis, the suitable Multilevel Method is Random Intercept Model. Penalized Quasi Likelihood (PQL) approach on multilevel Poisson is a proper analysis to determine factors that affecting dengue cases in the city of Bandung. Clean and Healthy Behavior factor from the village level have an effect on the number of cases of dengue fever in the city of Bandung. Factor from the sub-district level has no effect.

Experimental studies of a prototype model of the multilevel 6KW-power inverter at supply by 12 accumulators

NASA Astrophysics Data System (ADS)

Taissariyeva, K.; Issembergenov, N.; Dzhobalaeva, G.; Usembaeva, S.

2016-09-01

The given paper considers the multilevel 6 kW-power transistor inverter at supply by 12 accumulators for transformation of solar battery energy to the electric power. At the output of the multilevel transistor inverter, it is possible to receive voltage close to a sinusoidal form. The main objective of this inverter is transformation of solar energy to the electric power of industrial frequency. The analysis of the received output curves of voltage on harmonicity has been carried out. In this paper it is set forth the developed scheme of the multilevel transistor inverter (DC-to-ac converter) which allows receiving at the output the voltage close to sinusoidal form, as well as to regulation of the output voltage level. In the paper, the results of computer modeling and experimental studies are presented.

Linear spline multilevel models for summarising childhood growth trajectories: A guide to their application using examples from five birth cohorts.

PubMed

Howe, Laura D; Tilling, Kate; Matijasevich, Alicia; Petherick, Emily S; Santos, Ana Cristina; Fairley, Lesley; Wright, John; Santos, Iná S; Barros, Aluísio Jd; Martin, Richard M; Kramer, Michael S; Bogdanovich, Natalia; Matush, Lidia; Barros, Henrique; Lawlor, Debbie A

2016-10-01

Childhood growth is of interest in medical research concerned with determinants and consequences of variation from healthy growth and development. Linear spline multilevel modelling is a useful approach for deriving individual summary measures of growth, which overcomes several data issues (co-linearity of repeat measures, the requirement for all individuals to be measured at the same ages and bias due to missing data). Here, we outline the application of this methodology to model individual trajectories of length/height and weight, drawing on examples from five cohorts from different generations and different geographical regions with varying levels of economic development. We describe the unique features of the data within each cohort that have implications for the application of linear spline multilevel models, for example, differences in the density and inter-individual variation in measurement occasions, and multiple sources of measurement with varying measurement error. After providing example Stata syntax and a suggested workflow for the implementation of linear spline multilevel models, we conclude with a discussion of the advantages and disadvantages of the linear spline approach compared with other growth modelling methods such as fractional polynomials, more complex spline functions and other non-linear models. © The Author(s) 2013.

Analyzing chromatographic data using multilevel modeling.

PubMed

Wiczling, Paweł

2018-06-01

It is relatively easy to collect chromatographic measurements for a large number of analytes, especially with gradient chromatographic methods coupled with mass spectrometry detection. Such data often have a hierarchical or clustered structure. For example, analytes with similar hydrophobicity and dissociation constant tend to be more alike in their retention than a randomly chosen set of analytes. Multilevel models recognize the existence of such data structures by assigning a model for each parameter, with its parameters also estimated from data. In this work, a multilevel model is proposed to describe retention time data obtained from a series of wide linear organic modifier gradients of different gradient duration and different mobile phase pH for a large set of acids and bases. The multilevel model consists of (1) the same deterministic equation describing the relationship between retention time and analyte-specific and instrument-specific parameters, (2) covariance relationships relating various physicochemical properties of the analyte to chromatographically specific parameters through quantitative structure-retention relationship based equations, and (3) stochastic components of intra-analyte and interanalyte variability. The model was implemented in Stan, which provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods. Graphical abstract Relationships between log k and MeOH content for acidic, basic, and neutral compounds with different log P. CI credible interval, PSA polar surface area.

Linear spline multilevel models for summarising childhood growth trajectories: A guide to their application using examples from five birth cohorts

PubMed Central

Tilling, Kate; Matijasevich, Alicia; Petherick, Emily S; Santos, Ana Cristina; Fairley, Lesley; Wright, John; Santos, Iná S.; Barros, Aluísio JD; Martin, Richard M; Kramer, Michael S; Bogdanovich, Natalia; Matush, Lidia; Barros, Henrique; Lawlor, Debbie A

2013-01-01

Childhood growth is of interest in medical research concerned with determinants and consequences of variation from healthy growth and development. Linear spline multilevel modelling is a useful approach for deriving individual summary measures of growth, which overcomes several data issues (co-linearity of repeat measures, the requirement for all individuals to be measured at the same ages and bias due to missing data). Here, we outline the application of this methodology to model individual trajectories of length/height and weight, drawing on examples from five cohorts from different generations and different geographical regions with varying levels of economic development. We describe the unique features of the data within each cohort that have implications for the application of linear spline multilevel models, for example, differences in the density and inter-individual variation in measurement occasions, and multiple sources of measurement with varying measurement error. After providing example Stata syntax and a suggested workflow for the implementation of linear spline multilevel models, we conclude with a discussion of the advantages and disadvantages of the linear spline approach compared with other growth modelling methods such as fractional polynomials, more complex spline functions and other non-linear models. PMID:24108269

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes.

PubMed

Li, Baoyue; Lingsma, Hester F; Steyerberg, Ewout W; Lesaffre, Emmanuel

2011-05-23

Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC.Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain.

Individual tree diameter increment model for managed even-aged stands of ponderosa pine throughout the western United States using a multilevel linear mixed effects model

Treesearch

Fabian C.C. Uzoh; William W. Oliver

2008-01-01

A diameter increment model is developed and evaluated for individual trees of ponderosa pine throughout the species range in the United States using a multilevel linear mixed model. Stochastic variability is broken down among period, locale, plot, tree and within-tree components. Covariates acting at tree and stand level, as breast height diameter, density, site index...

Individual schooling and women's community-level media exposure: a multilevel analysis of normative influences associated with women's justification of wife beating in Bangladesh.

PubMed

Krause, Kathleen H; Haardörfer, Regine; Yount, Kathryn M

2017-02-01

Our objective was to examine the multilevel correlates of women's justification of wife beating in Bangladesh, a form of intimate partner violence (IPV). We focus on individual-level schooling, community-level media exposure among women and their interaction. A cross-sectional study using data from the 2011 Bangladesh Demographic and Health Survey. Our sample included 17 749 ever-married women 15-49 years in 600 communities. We fit 6 multilevel logistic regression models to examine factors associated with justifying IPV; focusing on a woman's completed grades of schooling; frequent (at least once weekly) community-level media exposure among women via newspaper/magazine, television and radio; and their cross-level interaction. At the individual level, completing more grades of schooling than the community average was negatively associated with justifying IPV (0.95, 95% CI 0.94 to 0.97). The main effects of women's community-level media exposure were not significant, but suggested that frequent exposure to newspaper/magazine or television was negatively associated with justifying IPV, while exposure to radio was positively associated. In cross-level interactions, a woman's completed grades of schooling above the community average was protective against justifying IPV, even in communities where women's exposure to radio would otherwise increase the odds of justifying IPV. Different forms of media likely send different messages about gender and IPV. Girls' schooling should remain a priority, given its protective effect against justifying wife beating. Targeting girls and women who do not receive any schooling for intervention may yield the most benefit in terms of normative change regarding IPV against women. 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/.

Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway.

PubMed

Shi, Qi; Abdel-Aty, Mohamed; Yu, Rongjie

2016-03-01

In traffic safety studies, crash frequency modeling of total crashes is the cornerstone before proceeding to more detailed safety evaluation. The relationship between crash occurrence and factors such as traffic flow and roadway geometric characteristics has been extensively explored for a better understanding of crash mechanisms. In this study, a multi-level Bayesian framework has been developed in an effort to identify the crash contributing factors on an urban expressway in the Central Florida area. Two types of traffic data from the Automatic Vehicle Identification system, which are the processed data capped at speed limit and the unprocessed data retaining the original speed were incorporated in the analysis along with road geometric information. The model framework was proposed to account for the hierarchical data structure and the heterogeneity among the traffic and roadway geometric data. Multi-level and random parameters models were constructed and compared with the Negative Binomial model under the Bayesian inference framework. Results showed that the unprocessed traffic data was superior. Both multi-level models and random parameters models outperformed the Negative Binomial model and the models with random parameters achieved the best model fitting. The contributing factors identified imply that on the urban expressway lower speed and higher speed variation could significantly increase the crash likelihood. Other geometric factors were significant including auxiliary lanes and horizontal curvature. Copyright © 2015 Elsevier Ltd. All rights reserved.

Review of family relational stress and pediatric asthma: the value of biopsychosocial systemic models.

PubMed

Wood, Beatrice L; Miller, Bruce D; Lehman, Heather K

2015-06-01

Asthma is the most common chronic disease in children. Despite dramatic advances in pharmacological treatments, asthma remains a leading public health problem, especially in socially disadvantaged minority populations. Some experts believe that this health gap is due to the failure to address the impact of stress on the disease. Asthma is a complex disease that is influenced by multilevel factors, but the nature of these factors and their interrelations are not well understood. This paper aims to integrate social, psychological, and biological literatures on relations between family/parental stress and pediatric asthma, and to illustrate the utility of multilevel systemic models for guiding treatment and stimulating future research. We used electronic database searches and conducted an integrated analysis of selected epidemiological, longitudinal, and empirical studies. Evidence is substantial for the effects of family/parental stress on asthma mediated by both disease management and psychobiological stress pathways. However, integrative models containing specific pathways are scarce. We present two multilevel models, with supporting data, as potential prototypes for other such models. We conclude that these multilevel systems models may be of substantial heuristic value in organizing investigations of, and clinical approaches to, the complex social-biological aspects of family stress in pediatric asthma. However, additional systemic models are needed, and the models presented herein could serve as prototypes for model development. © 2015 Family Process Institute.

Squeezed light from conventionally pumped multi-level lasers

NASA Technical Reports Server (NTRS)

Ralph, T. C.; Savage, C. M.

1992-01-01

We have calculated the amplitude squeezing in the output of several conventionally pumped multi-level lasers. We present results which show that standard laser models can produce significantly squeezed outputs in certain parameter ranges.

Generation and transmission of multilevel quadrature amplitude modulation formats using only one optical modulator: MATLAB Simulink simulation models

NASA Astrophysics Data System (ADS)

Binh, Le Nguyen

2009-04-01

A geometrical and phasor representation technique is presented to illustrate the modulation of the lightwave carrier to generate quadrature amplitude modulated (QAM) signals. The modulation of the amplitude and phase of the lightwave carrier is implemented using only one dual-drive Mach-Zehnder interferometric modulator (MZIM) with the assistance of phasor techniques. Any multilevel modulation scheme can be generated, but we illustrate specifically, the multilevel amplitude and differential phase shift keying (MADPSK) signals. The driving voltage levels are estimated for driving the traveling wave electrodes of the modulator. Phasor diagrams are extensively used to demonstrate the effectiveness of modulation schemes. MATLAB Simulink models are formed to generate the multilevel modulation formats, transmission, and detection in optically amplified fiber communication systems. Transmission performance is obtained for the multilevel optical signals and proven to be equivalent or better than those of binary level with equivalent bit rate. Further, the resilience to nonlinear effects is much higher for MADPSK of 50% and 33% pulse width as compared to non-return-to-zero (NRZ) pulse shaping.

Theoretical aspects of diagnostics of car as mechatronic system

NASA Astrophysics Data System (ADS)

Goncharov, A. E.; Bondarenko, E. V.; Krasnoshtanov, S. Yu

2018-03-01

The article describes transformation of mechanical systems of automobiles into mechatronic ones due to application of electronic control systems. To assess the relationship of mechanical and electronic components of the mechatronic systems with regard to their technical states, the method of equivalent elements was employed. A mathematical model of changes in the technical state of equivalent elements was developed. It allowed us to present changes in operation capacity in a graphic form. The analytical model is used to ensure operating capacity potential stability for the mechatronic system. For this purpose, new resources were identified with regard to the information ‘field’. Therefore, a new approach to the systematization of knowledge about mechatronic transport systems (D-C-R-E system) is required. The D-C-R-E system is examined as a separate unit. The article describes Information unit formation based on the physical component of the D-C-R-E system and external information which is collected and processed in the Information Diagnostic Center (IDC). Using probability theory and Boolean algebra methods, the authors obtained a logistic model describing information relations between elements of the upgraded D-C-R-E system and contribution of each component to the road safety protection. The logistic model helped formulate main IDC tasks. Implementation of those tasks was transformed into the logical sequence of data collection and analysis in the IDC. That approach predetermined development of the multi-level diagnosing system which made it possible to put in order existing and improved image identification methods and algorithms and to create a diagnosing method for mechatronic systems of cars which reduces labor content and increases accuracy. That approach can help assess the technical state of vehicles with characteristics of mechatronic systems and their transport and environmental safety.

Modeling the Factors Associated with Children's Mental Health Difficulties in Primary School: A Multilevel Study

ERIC Educational Resources Information Center

Humphrey, Neil; Wigelsworth, Michael

2012-01-01

The current study explores some of the factors associated with children's mental health difficulties in primary school. Multilevel modeling with data from 628 children from 36 schools was used to determine how much variation in mental health difficulties exists between and within schools, and to identify characteristics at the school and…

Pretest-Posttest-Posttest Multilevel IRT Modeling of Competence Growth of Students in Higher Education in Germany

ERIC Educational Resources Information Center

Schmidt, Susanne; Zlatkin-Troitschanskaia, Olga; Fox, Jean-Paul

2016-01-01

Longitudinal research in higher education faces several challenges. Appropriate methods of analyzing competence growth of students are needed to deal with those challenges and thereby obtain valid results. In this article, a pretest-posttest-posttest multivariate multilevel IRT model for repeated measures is introduced which is designed to address…

A Multilevel Model of Minority Opinion Expression and Team Decision-Making Effectiveness

ERIC Educational Resources Information Center

Park, Guihyun; DeShon, Richard P.

2010-01-01

The consideration of minority opinions when making team decisions is an important factor that contributes to team effectiveness. A multilevel model of minority opinion influence in decision-making teams is developed to address the conditions that relate to adequate consideration of minority opinions. Using a sample of 57 teams working on a…

The Dubious Benefits of Multi-Level Modeling

ERIC Educational Resources Information Center

Gorard, Stephen

2007-01-01

This paper presents an argument against the wider adoption of complex forms of data analysis, using multi-level modeling (MLM) as an extended case study. MLM was devised to overcome some deficiencies in existing datasets, such as the bias caused by clustering. The paper suggests that MLM has an unclear theoretical and empirical basis, has not led…

Asymptotic Effect of Misspecification in the Random Part of the Multilevel Model

ERIC Educational Resources Information Center

Berkhof, Johannes; Kampen, Jarl Kennard

2004-01-01

The authors examine the asymptotic effect of omitting a random coefficient in the multilevel model and derive expressions for the change in (a) the variance components estimator and (b) the estimated variance of the fixed effects estimator. They apply the method of moments, which yields a closed form expression for the omission effect. In…

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

ERIC Educational Resources Information Center

Richter, Tobias

2006-01-01

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

Three-Level Models for Indirect Effects in School- and Class-Randomized Experiments in Education

ERIC Educational Resources Information Center

Pituch, Keenan A.; Murphy, Daniel L.; Tate, Richard L.

2009-01-01

Due to the clustered nature of field data, multi-level modeling has become commonly used to analyze data arising from educational field experiments. While recent methodological literature has focused on multi-level mediation analysis, relatively little attention has been devoted to mediation analysis when three levels (e.g., student, class,…

Student-Teacher Racial Match and Its Association with Black Student Achievement: An Exploration Using Multilevel Structural Equation Modeling

ERIC Educational Resources Information Center

Yarnell, Lisa M.; Bohrnstedt, George W.

2018-01-01

This study examines student-teacher "racial match" for its association with Black student achievement. Multilevel structural equation modeling was used to analyze 2013 National Assessment for Educational Progress (NAEP) Grade 4 Reading Assessment data to examine interactions of teacher race and student race in their associations with…

Multilevel Modeling in the Presence of Outliers: A Comparison of Robust Estimation Methods

ERIC Educational Resources Information Center

Finch, Holmes

2017-01-01

Multilevel models (MLMs) have proven themselves to be very useful in social science research, as data from a variety of sources is sampled such that individuals at level-1 are nested within clusters such as schools, hospitals, counseling centers, and business entities at level-2. MLMs using restricted maximum likelihood estimation (REML) provide…

Homework Works If Homework Quality Is High: Using Multilevel Modeling to Predict the Development of Achievement in Mathematics

ERIC Educational Resources Information Center

Dettmers, Swantje; Trautwein, Ulrich; Ludtke, Oliver; Kunter, Mareike; Baumert, Jurgen

2010-01-01

The present study examined the associations of 2 indicators of homework quality (homework selection and homework challenge) with homework motivation, homework behavior, and mathematics achievement. Multilevel modeling was used to analyze longitudinal data from a representative national sample of 3,483 students in Grades 9 and 10; homework effects…

A Multilevel Model of Team Cultural Diversity and Creativity: The Role of Climate for Inclusion

ERIC Educational Resources Information Center

Li, Ci-Rong; Lin, Chen-Ju; Tien, Yun-Hsiang; Chen, Chien-Ming

2017-01-01

We developed a multi-level model to test how team cultural diversity may relate to team- and individual-level creativity, integrating team diversity research and information-exchange perspective. We proposed that the team climate for inclusion would moderate both the relationship between cultural diversity and team information sharing and between…

Chronic pain in families: a cross-sectional study of shared social, behavioural, and environmental influences

PubMed Central

Campbell, Paul; Jordan, Kelvin P.; Smith, Blair H.; Scotland, Generation; Dunn, Kate M.

2017-01-01

Abstract Chronic pain is common and creates a significant burden to the individual and society. Emerging research has shown the influence of the family environment on pain outcomes. However, it is not clear what shared factors between family members associate with chronic pain. This study aimed to investigate the family-level contribution to an individual's chronic pain status. This was a cross-sectional study using the Generation Scotland: Scottish Family Health Study data set. This study focused on a nested cohort of dyads (only 2 relatives per family, n = 2714). Multi-level modelling was first performed to estimate the extent of variance in chronic pain at the family level. Then each member of the dyad was randomly assigned as either the exposure or outcome family member, and logistic regression was used to identify shared factors associated with the outcome of chronic pain status. Multi-level modelling showed just under 10% of variation in chronic pain status was at a family level. There was an increase in odds of chronic pain if exposure family member had chronic pain (odds ratio [OR]: 1.30, 95% confidence interval [CI]: 1.02-1.65), if both were women (OR: 1.39, 95% CI: 0.99-1.94), if both were older in age (OR: 1.80, 95% CI: 1.31-2.48), and if both had low household income (OR: 3.27, 95% CI: 1.72-6.21). These findings show that most explanation for chronic pain is still at the individual level. However, some significant shared effects between family members associate with chronic pain, and this highlights the influence of the family context. PMID:28937576

Contextual and individual factors associated with dental services utilisation by Brazilian adults: A multilevel analysis

PubMed Central

2018-01-01

Background Inequalities in the utilisation of dental services in Brazil are remarkable. The aim of this study was to evaluate the association of contextual and individual factors with the utilisation of dental services by Brazilian adults using the Andersen’s behavioural model. Methods Individual-level data from 27,017 adults residents in the State capitals who were interviewed in the 2013 Brazilian National Health Survey were pooled with contextual city-level data. The outcomes were non-utilisation of dental services and last dental visit over 12 months ago. Individual predisposing variables were age, sex, race/skin colour, schooling and social network. Individual enabling variables included income, health insurance and registration in primary health care. Individual need variables were self-perceived dental health and self-reported missing teeth. Multilevel logistic regression models were performed to estimate odds ratio (OR) and 95% confidence intervals (95% CIs) of the association of contextual and individual predisposing, enabling and need-related variables with dental services outcomes. Results Predisposing (OR = 0.89; 95% CI 0.81–0.97) and enabling (OR = 0.90; 95% CI 0.85–0.96) contextual factors were associated with non-utilisation of dental services. Individual predisposing (sex, race/skin colour, schooling), enabling (income, health insurance) and need (self-perceived oral health, missing teeth) were associated with non-utilisation of dental services and last dental visit over 12 months ago. The latter was also associated with other individual predisposing (age, social network) and need (eating difficulties due to oral problems) characteristics. Conclusions Individual and contextual determinants influenced dental services utilisation in Brazilian adults. These factors should be on the policy agenda and considered in the organisation of health services aiming to reduce oral health inequalities related to access and utilisation of dental services. PMID:29420660

Contextual and individual factors associated with dental services utilisation by Brazilian adults: A multilevel analysis.

PubMed

Herkrath, Fernando José; Vettore, Mario Vianna; Werneck, Guilherme Loureiro

2018-01-01

Inequalities in the utilisation of dental services in Brazil are remarkable. The aim of this study was to evaluate the association of contextual and individual factors with the utilisation of dental services by Brazilian adults using the Andersen's behavioural model. Individual-level data from 27,017 adults residents in the State capitals who were interviewed in the 2013 Brazilian National Health Survey were pooled with contextual city-level data. The outcomes were non-utilisation of dental services and last dental visit over 12 months ago. Individual predisposing variables were age, sex, race/skin colour, schooling and social network. Individual enabling variables included income, health insurance and registration in primary health care. Individual need variables were self-perceived dental health and self-reported missing teeth. Multilevel logistic regression models were performed to estimate odds ratio (OR) and 95% confidence intervals (95% CIs) of the association of contextual and individual predisposing, enabling and need-related variables with dental services outcomes. Predisposing (OR = 0.89; 95% CI 0.81-0.97) and enabling (OR = 0.90; 95% CI 0.85-0.96) contextual factors were associated with non-utilisation of dental services. Individual predisposing (sex, race/skin colour, schooling), enabling (income, health insurance) and need (self-perceived oral health, missing teeth) were associated with non-utilisation of dental services and last dental visit over 12 months ago. The latter was also associated with other individual predisposing (age, social network) and need (eating difficulties due to oral problems) characteristics. Individual and contextual determinants influenced dental services utilisation in Brazilian adults. These factors should be on the policy agenda and considered in the organisation of health services aiming to reduce oral health inequalities related to access and utilisation of dental services.

Effect of a smoking ban and school-based prevention and control policies on adolescent smoking in Spain: a multilevel analysis.

PubMed

Galán, Iñaki; Díez-Gañán, Lucía; Gandarillas, Ana; Mata, Nelva; Cantero, Jose Luis; Durbán, María

2012-12-01

We evaluated the impact of a smoking ban in schools and of school-based smoking prevention and control policies on adolescent smoking. Annual surveys carried out between 2001 and 2005 that were representative of students in the 4th year of secondary education in the Madrid region, with 203 schools and 9127 students participating. The student questionnaire gathered information about personal and family variables. The contextual factors were: the periods before (years 2001-2002) and after the law; and through a survey of school management boards: compliance with the law, policy reflected in the school regulations, existence of complaints against smoking, and undertaking of educational activities regarding smoking. Multilevel logistic regression models were constructed with two dependent variables: current smoking and the proportion giving up smoking. Smoking declined in 2003, the first year after the law came into force (Odds ratio: 0.80; CI 95%: 0.66-0.96), and this decline was maintained in 2005. By contrast, smoking increased in those schools that did not undertake educational programmes regarding smoking (Odds ratio: 1.34; CI 95%: 1.13-1.59), and in those that received complaints about smoking (Odds ratio: 1.12; CI 95%: 0.96-1.29). This association is partly due to the effect of the increase in giving up smoking. The inclusion of contextual variables into the model with the individual factors reduces the variability of smoking between schools by 32.6%. In summary, the coming into force of a law banning smoking in schools, and the implementing of educational policies for the prevention and control of smoking are related to a lower risk of adolescent smoking.

Adjusting for geographic variation in observational comparative effectiveness studies: a case study of antipsychotics using state Medicaid data.

PubMed

Root, Elisabeth Dowling; Thomas, Deborah S K; Campagna, Elizabeth J; Morrato, Elaine H

2014-08-27

Area-level variation in treatment and outcomes may be a potential source of confounding bias in observational comparative effectiveness studies. This paper demonstrates how to use exploratory spatial data analysis (ESDA) and spatial statistical methods to investigate and control for these potential biases. The case presented compares the effectiveness of two antipsychotic treatment strategies: oral second-generation antipsychotics (SGAs) vs. long-acting paliperiodone palmitate (PP). A new-start cohort study was conducted analyzing patient-level administrative claims data (8/1/2008-4/30/2011) from Missouri Medicaid. ESDA techniques were used to examine spatial patterns of antipsychotic prescriptions and outcomes (hospitalization and emergency department (ED) visits). Likelihood of mental health-related outcomes were compared between patients starting PP (N = 295) and oral SGAs (N = 8,626) using multilevel logistic regression models adjusting for patient composition (demographic and clinical factors) and geographic region. ESDA indicated significant spatial variation in antipsychotic prescription patterns and moderate variation in hospitalization and ED visits thereby indicating possible confounding by geography. In the multilevel models for this antipsychotic case example, patient composition represented a stronger source of confounding than geographic context. Because geographic variation in health care delivery is ubiquitous, it could be a comparative effectiveness research (CER) best practice to test for possible geographic confounding in observational data. Though the magnitude of the area-level geography effects were small in this case, they were still statistically significant and should therefore be examined as part of this observational CER study. More research is needed to better estimate the range of confounding due to geography across different types of observational comparative effectiveness studies and healthcare utilization outcomes.

Should policy-makers and managers trust PSI? An empirical validation study of five patient safety indicators in a national health service

PubMed Central

2012-01-01

Background Patient Safety Indicators (PSI) are being modestly used in Spain, somewhat due to concerns on their empirical properties. This paper provides evidence by answering three questions: a) Are PSI differences across hospitals systematic -rather than random?; b) Do PSI measure differences among hospital-providers -as opposed to differences among patients?; and, c) Are measurements able to detect hospitals with a higher than "expected" number of cases? Methods An empirical validation study on administrative data was carried out. All 2005 and 2006 publicly-funded hospital discharges were used to retrieve eligible cases of five PSI: Death in low-mortality DRGs (MLM); decubitus ulcer (DU); postoperative pulmonary embolism or deep-vein thrombosis (PE-DVT); catheter-related infections (CRI), and postoperative sepsis (PS). Empirical Bayes statistic (EB) was used to estimate whether the variation was systematic; logistic-multilevel modelling determined what proportion of the variation was explained by the hospital; and, shrunken residuals, as provided by multilevel modelling, were plotted to flag hospitals performing worse than expected. Results Variation across hospitals was observed to be systematic in all indicators, with EB values ranging from 0.19 (CI95%:0.12 to 0.28) in PE-DVT to 0.34 (CI95%:0.25 to 0.45) in DU. A significant proportion of the variance was explained by the hospital, once patient case-mix was adjusted: from a 6% in MLM (CI95%:3% to 11%) to a 24% (CI95%:20% to 30%) in CRI. All PSI were able to flag hospitals with rates over the expected, although this capacity decreased when the largest hospitals were analysed. Conclusion Five PSI showed reasonable empirical properties to screen healthcare performance in Spanish hospitals, particularly in the largest ones. PMID:22369291

Does area-based social capital matter for the health of Australians? A multilevel analysis of self-rated health in Tasmania.

PubMed

Kavanagh, Anne M; Turrell, Gavin; Subramanian, S V

2006-06-01

Material circumstances and collective psychosocial processes have been invoked as potential explanations for socioeconomic inequalities in health; and, linking social capital has been proposed as a way of reconciling these apparently opposing explanations. We conducted multilevel logistic regression of self-rated health (fair or poor vs excellent, very good, or good) on 14 495 individuals living within 41 statistical local areas who were respondents to the 1998 Tasmanian Healthy Communities Study. We modelled the effects of area-level socioeconomic disadvantage and social capital (neighbourhood integration, neighbourhood alienation, neighbourhood safety, social trust, trust in public/private institutions, and political participation), and adjusted for the effects of individual characteristics. Area-level socioeconomic disadvantage was associated with poor self-rated health (beta = 0.0937, P < 0.001) an effect that was attenuated, but remained significant, after adjusting for individual characteristics (beta = 0.0419, P < 0.001). Social trust was associated with a reduction in poor self-rated health (beta = -0.0501, p = 0.008) and remained significant when individual characteristics (beta = -0.0398, P = 0.005) were included. Political participation was non-significant in the unadjusted model but became significant when adjusted for individual characteristics (beta = -0.2557, P = 0.045). The effects of social trust and political participation were attenuated and became non-significant when area-level socioeconomic disadvantage was included. Area-based socioeconomic disadvantage is a determinant of self-rated health in Tasmania, but we did not find an independent effect of area-level social capital. These findings suggest that in Tasmania investments in improving the material circumstances in which people live are likely to lead to greater improvements in population health than attempts to increase area-level social capital.

Population-based cohort study of variation in the use of emergency cholecystectomy for benign gallbladder diseases.

PubMed

2016-11-01

The aims of this prospective population-based cohort study were to identify the patient and hospital characteristics associated with emergency cholecystectomy, and the influences of these in determining variations between hospitals. Data were collected for consecutive patients undergoing cholecystectomy in acute UK and Irish hospitals between 1 March and 1 May 2014. Potential explanatory variables influencing the performance of emergency cholecystectomy were analysed by means of multilevel, multivariable logistic regression modelling using a two-level hierarchical structure with patients (level 1) nested within hospitals (level 2). Data were collected on 4744 cholecystectomies from 165 hospitals. Increasing age, lower ASA fitness grade, biliary colic, the need for further imaging (magnetic retrograde cholangiopancreatography), endoscopic interventions (endoscopic retrograde cholangiopancreatography) and admission to a non-biliary centre significantly reduced the likelihood of an emergency cholecystectomy being performed. The multilevel model was used to calculate the probability of receiving an emergency cholecystectomy for a woman aged 40 years or over with an ASA grade of I or II and a BMI of at least 25·0 kg/m 2 , who presented with acute cholecystitis with an ultrasound scan showing a thick-walled gallbladder and a normal common bile duct. The mean predicted probability of receiving an emergency cholecystectomy was 0·52 (95 per cent c.i. 0·45 to 0·57). The predicted probabilities ranged from 0·02 to 0·95 across the 165 hospitals, demonstrating significant variation between hospitals. Patients with similar characteristics presenting to different hospitals with acute gallbladder pathology do not receive comparable care. © 2016 BJS Society Ltd Published by John Wiley & Sons Ltd.

The Impact of Intraclass Correlation on the Effectiveness of Level-Specific Fit Indices in Multilevel Structural Equation Modeling: A Monte Carlo Study

ERIC Educational Resources Information Center

Hsu, Hsien-Yuan; Lin, Jr-Hung; Kwok, Oi-Man; Acosta, Sandra; Willson, Victor

2017-01-01

Several researchers have recommended that level-specific fit indices should be applied to detect the lack of model fit at any level in multilevel structural equation models. Although we concur with their view, we note that these studies did not sufficiently consider the impact of intraclass correlation (ICC) on the performance of level-specific…

Multilevel analysis of self-perception in oral health and associated factors in Southern Brazilian adults: a cross-sectional study.

PubMed

Gabardo, Marilisa Carneiro Leão; Moysés, Samuel Jorge; Moysés, Simone Tetu; Olandoski, Marcia; Olinto, Maria Teresa Anselmo; Pattussi, Marcos Pascoal

2015-01-01

The aim of this study was to evaluate the association between individual and contextual variables related to self-perception in oral health among residents in the municipality of São Leopoldo, Rio Grande do Sul State, Brazil. The cross-sectional design involved 1,100 adults in 38 census tracts. The self-perception was evaluated using the Oral Health Impact Profile (OHIP-14) tool. A logistic multilevel analysis was performed. The multivariate analysis revealed that those who are of the female gender, older, with lower scores of quality of life and less social support, with poor healthy eating habits, smokers and those living in low-income census tracts presented higher odds of reporting worse oral health self-perception (OHIP-1). We concluded that individual and contextual variables are associated with oral health self-perception. This is essential information for planning health services wishing to meet the health needs of the population.

The use of simple reparameterizations to improve the efficiency of Markov chain Monte Carlo estimation for multilevel models with applications to discrete time survival models.

PubMed

Browne, William J; Steele, Fiona; Golalizadeh, Mousa; Green, Martin J

2009-06-01

We consider the application of Markov chain Monte Carlo (MCMC) estimation methods to random-effects models and in particular the family of discrete time survival models. Survival models can be used in many situations in the medical and social sciences and we illustrate their use through two examples that differ in terms of both substantive area and data structure. A multilevel discrete time survival analysis involves expanding the data set so that the model can be cast as a standard multilevel binary response model. For such models it has been shown that MCMC methods have advantages in terms of reducing estimate bias. However, the data expansion results in very large data sets for which MCMC estimation is often slow and can produce chains that exhibit poor mixing. Any way of improving the mixing will result in both speeding up the methods and more confidence in the estimates that are produced. The MCMC methodological literature is full of alternative algorithms designed to improve mixing of chains and we describe three reparameterization techniques that are easy to implement in available software. We consider two examples of multilevel survival analysis: incidence of mastitis in dairy cattle and contraceptive use dynamics in Indonesia. For each application we show where the reparameterization techniques can be used and assess their performance.

Theoretical and software considerations for nonlinear dynamic analysis

NASA Technical Reports Server (NTRS)

Schmidt, R. J.; Dodds, R. H., Jr.

1983-01-01

In the finite element method for structural analysis, it is generally necessary to discretize the structural model into a very large number of elements to accurately evaluate displacements, strains, and stresses. As the complexity of the model increases, the number of degrees of freedom can easily exceed the capacity of present-day software system. Improvements of structural analysis software including more efficient use of existing hardware and improved structural modeling techniques are discussed. One modeling technique that is used successfully in static linear and nonlinear analysis is multilevel substructuring. This research extends the use of multilevel substructure modeling to include dynamic analysis and defines the requirements for a general purpose software system capable of efficient nonlinear dynamic analysis. The multilevel substructuring technique is presented, the analytical formulations and computational procedures for dynamic analysis and nonlinear mechanics are reviewed, and an approach to the design and implementation of a general purpose structural software system is presented.

Coherent population transfer in multi-level Allen-Eberly models

NASA Astrophysics Data System (ADS)

Li, Wei; Cen, Li-Xiang

2018-04-01

We investigate the solvability of multi-level extensions of the Allen-Eberly model and the population transfer yielded by the corresponding dynamical evolution. We demonstrate that, under a matching condition of the frequency, the driven two-level system and its multi-level extensions possess a stationary-state solution in a canonical representation associated with a unitary transformation. As a consequence, we show that the resulting protocol is able to realize complete population transfer in a nonadiabatic manner. Moreover, we explore the imperfect pulsing process with truncation and display that the nonadiabatic effect in the evolution can lead to suppression to the cutoff error of the protocol.

Multilevel radiative thermal memory realized by the hysteretic metal-insulator transition of vanadium dioxide

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

Ito, Kota, E-mail: kotaito@mosk.tytlabs.co.jp; Nishikawa, Kazutaka; Iizuka, Hideo

Thermal information processing is attracting much interest as an analog of electronic computing. We experimentally demonstrated a radiative thermal memory utilizing a phase change material. The hysteretic metal-insulator transition of vanadium dioxide (VO{sub 2}) allows us to obtain a multilevel memory. We developed a Preisach model to explain the hysteretic radiative heat transfer between a VO{sub 2} film and a fused quartz substrate. The transient response of our memory predicted by the Preisach model agrees well with the measured response. Our multilevel thermal memory paves the way for thermal information processing as well as contactless thermal management.

Relationships between community social capital and injury in Canadian adolescents: a multilevel analysis

PubMed Central

Vafaei, Afshin; Pickett, William; Alvarado, Beatriz E

2015-01-01

Background Characteristics of social environments are potential risk factors for adolescent injury. Impacts of social capital on the occurrence of such injuries have rarely been explored. Methods General health questionnaires were completed by 8910 youth aged 14 years and older as part of the 2010 Canadian Health Behaviour in School-Aged Children study. These were supplemented with community-level data from the 2006 Canada Census of Population. Multilevel logistic regression models with random intercepts were fit to examine associations of interest. The reliability and validity of variables used in this analysis had been established in past studies, or in new analyses that employed factor analysis. Results Between school differences explained 2% of the variance in the occurrence of injuries. After adjustment for all confounders, community social capital did not have any impact on the occurrence of injuries in boys: OR: 1.01, 95% CI 0.80 to 1.29. However, living in areas with low social capital was associated with lower occurrence of injuries in girls (OR 0.78, 95% CI 0.63 to 0.96). Other factors that were significantly related to injuries in both genders were younger age, engagement in more risky behaviours, and negative behavioural influences from peers. Conclusions After simultaneously taking into account the influence of community-level and individual-level factors, community levels of social capital remained a relatively strong predictor of injury among girls but not boys. Such gender effects provide important clues into the social aetiology of youth injury. PMID:26294708

Associations Between Peer Network Gender Norms and the Perpetration of Intimate Partner Violence Among Urban Tanzanian Men: a Multilevel Analysis.

PubMed

Mulawa, Marta I; Reyes, H Luz McNaughton; Foshee, Vangie A; Halpern, Carolyn T; Martin, Sandra L; Kajula, Lusajo J; Maman, Suzanne

2018-05-01

Male perpetration of intimate partner violence (IPV) against women in sub-Saharan Africa is widespread. Theory and empirical evidence suggest peer networks may play an important role in shaping IPV perpetration, though research on this topic in the region is limited. We assessed the degree to which peer network gender norms are associated with Tanzanian men's perpetration of IPV and examined whether the social cohesion of peer networks moderates this relationship. Using baseline data from sexually active men (n = 1103) nested within 59 peer networks enrolled in an on-going cluster-randomized HIV and IPV prevention trial, we fit multilevel logistic regression models to examine peer network-level factors associated with past-year physical IPV perpetration. Peer network gender norms were significantly associated with men's risk of perpetrating IPV, even after adjusting for their own attitudes toward gender roles (OR = 1.53 , p =  . 04). Peer network social cohesion moderated this relationship (OR = 1.50 , p =  . 04); the positive relationship between increasingly inequitable (i.e., traditional) peer network gender norms and men's risk of perpetrating IPV became stronger, as peer network social cohesion increased. Characteristics of the peer network context are associated with men's IPV perpetration and should be targeted in future interventions. While many IPV prevention interventions focus on changing individual attitudes, our findings support a unique approach, focused on transforming the peer context.

Individual and neighbourhood determinants of social participation and social capital: a multilevel analysis of the city of Malmö, Sweden.

PubMed

Lindström, Martin; Merlo, Juan; Ostergren, Per-Olof

2002-06-01

The aim of this study was to analyse the impact of neighbourhood on individual social capital (measured as social participation). The study population consisted of 14,390 individuals aged 45-73 that participated in the Malmö diet and cancer study in 1992-1994, residing in 90 neighbourhoods of Malmö, Sweden (population 250,000). A multilevel logistic regression model, with individuals at the first level and neighbourhoods at the second level, was performed. The study analysed the effect (intra-area correlation and cross-level modification) of the neighbourhood on individual social capital after adjustment for compositional factors (e.g. age, sex, educational level, occupational status, disability pension, living alone, sick leave, unemployment) and, finally, one contextual migration factor. The prevalence of low social participation varied from 23.0% to 39.7% in the first and third neighbourhood quartiles, respectively. Neighbourhood factors accounted for 6.3% of the total variance in social participation, and this effect was reduced but not eliminated when adjusting for all studied variables (-73%), especially the occupational composition of the neighbourhoods (-58%). The contextual migration variable further reduced the variance in social participation at the neighbourhood level to some extent. Our study supports Putnam's notion that social capital, which is suggested to be an important factor for population health and possibly for health equity, is an aspect that is partly contextual in its nature.

Managing fever in children: a national survey of parents' knowledge and practices in France.

PubMed

Bertille, Nathalie; Fournier-Charrière, Elisabeth; Pons, Gérard; Chalumeau, Martin

2013-01-01

Identifying targets to improve parental practices for managing fever in children is the first step to reducing the overloaded healthcare system related to this common symptom. We aimed to study parents' knowledge and practices and their determinants in managing fever symptoms in children in France as compared with current recommendations. We conducted an observational national study between 2007 and 2008 of French general practitioners, primary care pediatricians and pharmacists. These healthcare professionals (HPs) were asked to include 5 consecutive patients from 1 month to 12 years old with fever for up to 48 hr who were accompanied by a family member. Parents completed a questionnaire about their knowledge of fever in children and their attitudes about the current fever episode. We used a multilevel logistic regression model to assess the joint effects of patient- and HP-level variables. In all, 1,534 HPs (participation rate 13%) included 6,596 children. Parental concordance with current recommendations for temperature measurement methods, the threshold for defining fever, and physical (oral hydration, undressing, room temperature) and drug treatment was 89%, 61%, 15%, and 23%, respectively. Multivariate multi-level analyses revealed a significant HP effect. In general, high concordance with recommendations was associated with high educational level of parents and the HP consulted being a pediatrician. In France, parents' knowledge and practices related to managing fever symptoms in children frequently differ from recommendations. Targeted health education interventions are needed to effectively manage fever symptoms in children.

Managing Fever in Children: A National Survey of Parents' Knowledge and Practices in France

PubMed Central

Bertille, Nathalie; Fournier-Charrière, Elisabeth; Pons, Gérard; Chalumeau, Martin

2013-01-01

Introduction Identifying targets to improve parental practices for managing fever in children is the first step to reducing the overloaded healthcare system related to this common symptom. We aimed to study parents' knowledge and practices and their determinants in managing fever symptoms in children in France as compared with current recommendations. Methods We conducted an observational national study between 2007 and 2008 of French general practitioners, primary care pediatricians and pharmacists. These healthcare professionals (HPs) were asked to include 5 consecutive patients from 1 month to 12 years old with fever for up to 48 hr who were accompanied by a family member. Parents completed a questionnaire about their knowledge of fever in children and their attitudes about the current fever episode. We used a multilevel logistic regression model to assess the joint effects of patient- and HP-level variables. Results In all, 1,534 HPs (participation rate 13%) included 6,596 children. Parental concordance with current recommendations for temperature measurement methods, the threshold for defining fever, and physical (oral hydration, undressing, room temperature) and drug treatment was 89%, 61%, 15%, and 23%, respectively. Multivariate multi-level analyses revealed a significant HP effect. In general, high concordance with recommendations was associated with high educational level of parents and the HP consulted being a pediatrician. Conclusions In France, parents' knowledge and practices related to managing fever symptoms in children frequently differ from recommendations. Targeted health education interventions are needed to effectively manage fever symptoms in children. PMID:24391772

The role of healthcare system in dental check-ups in 27 European countries: multilevel analysis.

PubMed

Kino, Shiho; Bernabé, Eduardo; Sabbah, Wael

2017-06-01

To examine whether public expenditure on health and Euro Health Consumer Index (EHCI) are associated with dental check-ups in European countries. Individual data were from Eurobarometer 72.3, 2009 a cross-national survey of 27 European countries. Eligible participants were those aged 18 years and older in 27 European countries. Dental check-ups reflected dental visits for oral examination and getting advice on oral health in the last 12 months. Individual factors included age, gender, marital status, urbanisation, education, subjective social status, and difficulty in paying bills. Public expenditure on health as a percentage of gross domestic product (GDP) and EHCI were used as contextual factors. A set of multilevel logistic regression models was used to examine the relationship between dental check-ups and each of healthcare expenditure and EHCI adjusting for demographic factors, GDP per capita and socioeconomic indicators. Total number included in the analysis was 23,842. Participants in countries with greater healthcare expenditure and higher score of EHCI were significantly 1.17 (95% CI: 1.03, 1.32) and 1.30 times (95% CI: 1.04, 1.64) more likely to report dental check-ups within the past 12 months after accounting for demographic characteristics, GDP per capita, and all socioeconomic indicators. The findings suggest that greater governmental support for the healthcare and better characteristics of healthcare system are positively associated with routine dental attendance. © 2017 American Association of Public Health Dentistry.

Does social policy moderate the impact of unemployment on health? A multilevel analysis of 23 welfare states.

PubMed

Vahid Shahidi, Faraz; Siddiqi, Arjumand; Muntaner, Carles

2016-12-01

The magnitude of observable health inequalities between the unemployed and their employed counterparts differs considerably across countries. Few attempts have been made to test theoretical explanations for this cross-national variation. Moreover, existing studies suffer from important theoretical and methodological limitations. This study addresses these limitations and investigates whether differences in the generosity of social protection policies and in public attitudes towards those policies explain why unemployment-related health inequalities are steeper in some societies than in others. Multilevel logistic modelling was used to link contextual-level variables on social protection policies and public attitudes in 23 European countries to individual-level data on self-rated health from the 2012 wave of the European Social Survey. The magnitude of inequalities in self-rated health between the unemployed and their employed counterparts varies significantly across countries as a function of cross-national differences in the level of social protection awarded to the unemployed and the level of public support for the welfare state. The results provide empirical support for the claim that governments can play a more active role in mitigating unemployment-related health inequalities by expanding the generosity and scope of social protection policies. Whether such an expansion of social protection will take place in the current climate of fiscal austerity is a political question whose implications merit the attention of population health scholars. © The Author 2016. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Household Expenditure for Dental Care in Low and Middle Income Countries

PubMed Central

Masood, Mohd; Sheiham, Aubrey; Bernabé, Eduardo

2015-01-01

This study assessed the extent of household catastrophic expenditure in dental health care and its possible determinants in 41 low and middle income countries. Data from 182,007 respondents aged 18 years and over (69,315 in 18 low income countries, 59,645 in 15 lower middle income countries and 53,047 in 8 upper middle income countries) who participated in the WHO World Health Survey (WHS) were analyzed. Expenditure in dental health care was defined as catastrophic if it was equal to or higher than 40% of the household capacity to pay. A number of individual and country-level factors were assessed as potential determinants of catastrophic dental health expenditure (CDHE) in multilevel logistic regression with individuals nested within countries. Up to 7% of households in low and middle income countries faced CDHE in the last 4 weeks. This proportion rose up to 35% among households that incurred some dental health expenditure within the same period. The multilevel model showed that wealthier, urban and larger households and more economically developed countries had higher odds of facing CDHE. The results of this study show that payments for dental health care can be a considerable burden on households, to the extent of preventing expenditure on basic necessities. They also help characterize households more likely to incur catastrophic expenditure on dental health care. Alternative health care financing strategies and policies targeted to improve fairness in financial contribution are urgently required in low and middle income countries. PMID:25923691

Neighbourhood safety and leisure-time physical activity among Dutch adults: a multilevel perspective

PubMed Central

2013-01-01

Background Several neighbourhood elements have been found to be related to leisure-time walking and cycling. However, the association with neighbourhood safety remains unclear. This study aimed to assess the association of neighbourhood-level safety with leisure-time walking and cycling among Dutch adults. Methods Data were derived from the national health survey (POLS) 2006–2009, with valid data on 20046 respondents residing in 2127 neighbourhoods. Multilevel logistic regression models were used to examine the association between neighbourhood-level safety (general safety and specific safety components: physical disorder, social disorder, crime-related fear, traffic safety) and residents’ engagement in outdoor leisure-time walking and cycling for at least 30 minutes per week. Results An increase in neighbourhood safety (both general safety and each of the safety components) was significantly associated with an increase in leisure-time cycling participation. Associations were strongest for general safety and among older women. In the general population, neighbourhood safety was not significantly associated with leisure-time walking. However, among younger and older adult men and lower educated individuals, an increase in general safety was associated with a decrease in leisure-time walking participation. Conclusions In the Netherlands, neighbourhood safety appears to be related to leisure-time cycling but not to walking. Leisure-time cycling may best be encouraged by improving different safety components at once, rather than focusing on one safety aspect such as traffic safety. Special attention is needed for older women. PMID:23356476

The importance of intersectoral factors in promoting equity-oriented universal health coverage: a multilevel analysis of social determinants affecting neonatal infant and under-five mortality in Bangladesh.

PubMed

Huda, Tanvir M; Tahsina, Tazeen; El Arifeen, Shams; Dibley, Michael J

2016-01-01

Health is multidimensional and affected by a wide range of factors, many of which are outside the health sector. To improve population health and reduce health inequality, it is important that we take into account the complex interactions among social, environmental, behavioural, and biological factors and design our health interventions accordingly. This study examines mortality differentials in children of different age groups by key social determinants of health (SDH) including parental education and employment, mother's level of autonomy, age, asset index, living arrangements (utilities), and other geographical contextual factors (area of residence, road conditions). We used data from the two rounds of Bangladesh Health and Demographic Survey, a nationally representative sample survey of the population residing in Bangladesh. Multilevel logistic models were used to study the impact of SDH on child mortality. The study found that the mother's age, the education of both parents, the mother's autonomy to take decisions about matters linked to the health of her child, the household socio-economic conditions, the geographical region of residence, and the condition of the roads were significantly associated with higher risks of neonatal, infant, and under-five mortality in Bangladesh. The study findings suggest there are complex relationships among different SDH. Thus larger intersectoral actions will be needed to reduce disparities in child health and mortality and achieve meaningful progress towards equity-oriented universal health coverage.

Minimum Wage and Overweight and Obesity in Adult Women: A Multilevel Analysis of Low and Middle Income Countries.

PubMed

Conklin, Annalijn I; Ponce, Ninez A; Frank, John; Nandi, Arijit; Heymann, Jody

2016-01-01

To describe the relationship between minimum wage and overweight and obesity across countries at different levels of development. A cross-sectional analysis of 27 countries with data on the legislated minimum wage level linked to socio-demographic and anthropometry data of non-pregnant 190,892 adult women (24-49 y) from the Demographic and Health Survey. We used multilevel logistic regression models to condition on country- and individual-level potential confounders, and post-estimation of average marginal effects to calculate the adjusted prevalence difference. We found the association between minimum wage and overweight/obesity was independent of individual-level SES and confounders, and showed a reversed pattern by country development stage. The adjusted overweight/obesity prevalence difference in low-income countries was an average increase of about 0.1 percentage points (PD 0.075 [0.065, 0.084]), and an average decrease of 0.01 percentage points in middle-income countries (PD -0.014 [-0.019, -0.009]). The adjusted obesity prevalence difference in low-income countries was an average increase of 0.03 percentage points (PD 0.032 [0.021, 0.042]) and an average decrease of 0.03 percentage points in middle-income countries (PD -0.032 [-0.036, -0.027]). This is among the first studies to examine the potential impact of improved wages on an important precursor of non-communicable diseases globally. Among countries with a modest level of economic development, higher minimum wage was associated with lower levels of obesity.

The Performance of Multilevel Growth Curve Models under an Autoregressive Moving Average Process

ERIC Educational Resources Information Center

Murphy, Daniel L.; Pituch, Keenan A.

2009-01-01

The authors examined the robustness of multilevel linear growth curve modeling to misspecification of an autoregressive moving average process. As previous research has shown (J. Ferron, R. Dailey, & Q. Yi, 2002; O. Kwok, S. G. West, & S. B. Green, 2007; S. Sivo, X. Fan, & L. Witta, 2005), estimates of the fixed effects were unbiased, and Type I…

Estimation of Contextual Effects through Nonlinear Multilevel Latent Variable Modeling with a Metropolis-Hastings Robbins-Monro Algorithm

ERIC Educational Resources Information Center

Yang, Ji Seung; Cai, Li

2014-01-01

The main purpose of this study is to improve estimation efficiency in obtaining maximum marginal likelihood estimates of contextual effects in the framework of nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM). Results indicate that the MH-RM algorithm can produce estimates and standard…

Explaining Variance and Identifying Predictors of Children's Communication via a Multilevel Model of Single-Case Design Research: Brief Report

ERIC Educational Resources Information Center

Ottley, Jennifer Riggie; Ferron, John M.; Hanline, Mary Frances

2016-01-01

The purpose of this study was to explain the variability in data collected from a single-case design study and to identify predictors of communicative outcomes for children with developmental delays or disabilities (n = 4). Using SAS® University Edition, we fit multilevel models with time nested within children. Children's level of baseline…

Exploring the Association between Transformational Leadership and Teacher's Self-Efficacy in Greek Education System: A Multilevel SEM Model

ERIC Educational Resources Information Center

Gkolia, Aikaterini; Koustelios, Athanasios; Belias, Dimitrios

2018-01-01

The main aim of this study is to examine the effect of principals' transformational leadership on teachers' self-efficacy across 77 different Greek elementary and secondary schools based on a centralized education system. For the investigation of the above effect multilevel Structural Equation Modelling analysis was conducted, recognizing the…

Taiwanese Students' Science Learning Self-Efficacy and Teacher and Student Science Hardiness: A Multilevel Model Approach

ERIC Educational Resources Information Center

Wang, Ya-Ling; Tsai, Chin-Chung

2016-01-01

This study aimed to investigate the factors accounting for science learning self-efficacy (the specific beliefs that people have in their ability to complete tasks in science learning) from both the teacher and the student levels. We thus propose a multilevel model to delineate its relationships with teacher and student science hardiness (i.e.,…

Modeling of Academic Achievement of Primary School Students in Ethiopia Using Bayesian Multilevel Approach

ERIC Educational Resources Information Center

Sebro, Negusse Yohannes; Goshu, Ayele Taye

2017-01-01

This study aims to explore Bayesian multilevel modeling to investigate variations of average academic achievement of grade eight school students. A sample of 636 students is randomly selected from 26 private and government schools by a two-stage stratified sampling design. Bayesian method is used to estimate the fixed and random effects. Input and…

Preschool Classroom Behavioral Context and School Readiness Outcomes for Low-Income Children: A Multilevel Examination of Child- and Classroom-Level Influences

ERIC Educational Resources Information Center

Bulotsky-Shearer, Rebecca J.; Dominguez, Ximena; Bell, Elizabeth R.

2012-01-01

Guided by an ecological theoretical model, the authors used a series of multilevel models to examine associations among children's individual problem behavior, the classroom behavioral context, and school readiness outcomes for a cohort of low-income children (N = 3,861) enrolled in 229 urban Head Start classrooms. Associations were examined…

A method of Modelling and Simulating the Back-to-Back Modular Multilevel Converter HVDC Transmission System

NASA Astrophysics Data System (ADS)

Wang, Lei; Fan, Youping; Zhang, Dai; Ge, Mengxin; Zou, Xianbin; Li, Jingjiao

2017-09-01

This paper proposes a method to simulate a back-to-back modular multilevel converter (MMC) HVDC transmission system. In this paper we utilize an equivalent networks to simulate the dynamic power system. Moreover, to account for the performance of converter station, core components of model of the converter station gives a basic model of simulation. The proposed method is applied to an equivalent real power system.

Multilevel selection analysis of a microbial social trait

PubMed Central

de Vargas Roditi, Laura; Boyle, Kerry E; Xavier, Joao B

2013-01-01

The study of microbial communities often leads to arguments for the evolution of cooperation due to group benefits. However, multilevel selection models caution against the uncritical assumption that group benefits will lead to the evolution of cooperation. We analyze a microbial social trait to precisely define the conditions favoring cooperation. We combine the multilevel partition of the Price equation with a laboratory model system: swarming in Pseudomonas aeruginosa. We parameterize a population dynamics model using competition experiments where we manipulate expression, and therefore the cost-to-benefit ratio of swarming cooperation. Our analysis shows that multilevel selection can favor costly swarming cooperation because it causes population expansion. However, due to high costs and diminishing returns constitutive cooperation can only be favored by natural selection when relatedness is high. Regulated expression of cooperative genes is a more robust strategy because it provides the benefits of swarming expansion without the high cost or the diminishing returns. Our analysis supports the key prediction that strong group selection does not necessarily mean that microbial cooperation will always emerge. PMID:23959025

Spatial Random Effects Survival Models to Assess Geographical Inequalities in Dengue Fever Using Bayesian Approach: a Case Study

NASA Astrophysics Data System (ADS)

Astuti Thamrin, Sri; Taufik, Irfan

2018-03-01

Dengue haemorrhagic fever (DHF) is an infectious disease caused by dengue virus. The increasing number of people with DHF disease correlates with the neighbourhood, for example sub-districts, and the characteristics of the sub-districts are formed from individuals who are domiciled in the sub-districts. Data containing individuals and sub-districts is a hierarchical data structure, called multilevel analysis. Frequently encountered response variable of the data is the time until an event occurs. Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in DHF survival. Using a case study approach, we report on the implications of using multilevel with spatial survival models to study geographical inequalities in all cause survival.

Regional variations in mortality rates in England and Wales: an analysis using multi-level modelling.

PubMed

Langford, I H; Bentham, G

1996-03-01

Mortality rates in England and Wales display a persistent regional pattern indicating generally poorer health in the North and West. Some of this is simply a reflection of regional differences in the extent of social deprivation which is known to exert a profound influence on health. Part of the pattern may also be the result of regional differences in urbanization which also affect mortality rates. However, there may be important regional differences over and above these compositional effects. This study attempts to establish the magnitude of such independent regional differences in mortality rates by using the techniques of multi-level modelling. Standardized mortality rates (SMRs) for males and females under 65 for 1989-91 in local authority districts are grouped into categories using the ACORN classification scheme. The Townsend Index is included as a measure of social deprivation. Using a cross-classified multi-level model, it is shown that region accounts for approximately four times more variation in SMRs than is explained by the ACORN classification. Analysis of diagnostic residuals show a clear North-South divide in excess mortality when both regional and socio-economic classification of districts are modelled simultaneously, a possibility allowed for by the use of a multi-level model.

Multilevel Hierarchical Modeling of Benthic Macroinvertebrate Responses to Urbanization in Nine Metropolitan Regions across the Conterminous United States

USGS Publications Warehouse

Kashuba, Roxolana; Cha, YoonKyung; Alameddine, Ibrahim; Lee, Boknam; Cuffney, Thomas F.

2010-01-01

Multilevel hierarchical modeling methodology has been developed for use in ecological data analysis. The effect of urbanization on stream macroinvertebrate communities was measured across a gradient of basins in each of nine metropolitan regions across the conterminous United States. The hierarchical nature of this dataset was harnessed in a multi-tiered model structure, predicting both invertebrate response at the basin scale and differences in invertebrate response at the region scale. Ordination site scores, total taxa richness, Ephemeroptera, Plecoptera, Trichoptera (EPT) taxa richness, and richness-weighted mean tolerance of organisms at a site were used to describe invertebrate responses. Percentage of urban land cover was used as a basin-level predictor variable. Regional mean precipitation, air temperature, and antecedent agriculture were used as region-level predictor variables. Multilevel hierarchical models were fit to both levels of data simultaneously, borrowing statistical strength from the complete dataset to reduce uncertainty in regional coefficient estimates. Additionally, whereas non-hierarchical regressions were only able to show differing relations between invertebrate responses and urban intensity separately for each region, the multilevel hierarchical regressions were able to explain and quantify those differences within a single model. In this way, this modeling approach directly establishes the importance of antecedent agricultural conditions in masking the response of invertebrates to urbanization in metropolitan regions such as Milwaukee-Green Bay, Wisconsin; Denver, Colorado; and Dallas-Fort Worth, Texas. Also, these models show that regions with high precipitation, such as Atlanta, Georgia; Birmingham, Alabama; and Portland, Oregon, start out with better regional background conditions of invertebrates prior to urbanization but experience faster negative rates of change with urbanization. Ultimately, this urbanization-invertebrate response example is used to detail the multilevel hierarchical construction methodology, showing how the result is a set of models that are both statistically more rigorous and ecologically more interpretable than simple linear regression models.

Cell-phone vs microphone recordings: Judging emotion in the voice.

PubMed

Green, Joshua J; Eigsti, Inge-Marie

2017-09-01

Emotional states can be conveyed by vocal cues such as pitch and intensity. Despite the ubiquity of cellular telephones, there is limited information on how vocal emotional states are perceived during cell-phone transmissions. Emotional utterances (neutral, happy, angry) were elicited from two female talkers and simultaneously recorded via microphone and cell-phone. Ten-step continua (neutral to happy, neutral to angry) were generated using the straight algorithm. Analyses compared reaction time (RT) and emotion judgment as a function of recording type (microphone vs cell-phone). Logistic regression revealed no judgment differences between recording types, though there were interactions with emotion type. Multi-level model analyses indicated that RT data were best fit by a quadratic model, with slower RT at the middle of each continuum, suggesting greater ambiguity, and slower RT for cell-phone stimuli across blocks. While preliminary, results suggest that critical acoustic cues to emotion are largely retained in cell-phone transmissions, though with effects of recording source on RT, and support the methodological utility of collecting speech samples by phone.

Comparing Classic and Interval Analytical Hierarchy Process Methodologies for Measuring Area-Level Deprivation to Analyze Health Inequalities.

PubMed

Cabrera-Barona, Pablo; Ghorbanzadeh, Omid

2018-01-16

Deprivation indices are useful measures to study health inequalities. Different techniques are commonly applied to construct deprivation indices, including multi-criteria decision methods such as the analytical hierarchy process (AHP). The multi-criteria deprivation index for the city of Quito is an index in which indicators are weighted by applying the AHP. In this research, a variation of this index is introduced that is calculated using interval AHP methodology. Both indices are compared by applying logistic generalized linear models and multilevel models, considering self-reported health as the dependent variable and deprivation and self-reported quality of life as the independent variables. The obtained results show that the multi-criteria deprivation index for the city of Quito is a meaningful measure to assess neighborhood effects on self-reported health and that the alternative deprivation index using the interval AHP methodology more thoroughly represents the local knowledge of experts and stakeholders. These differences could support decision makers in improving health planning and in tackling health inequalities in more deprived areas.

Comparing Classic and Interval Analytical Hierarchy Process Methodologies for Measuring Area-Level Deprivation to Analyze Health Inequalities

PubMed Central

Cabrera-Barona, Pablo

2018-01-01

Deprivation indices are useful measures to study health inequalities. Different techniques are commonly applied to construct deprivation indices, including multi-criteria decision methods such as the analytical hierarchy process (AHP). The multi-criteria deprivation index for the city of Quito is an index in which indicators are weighted by applying the AHP. In this research, a variation of this index is introduced that is calculated using interval AHP methodology. Both indices are compared by applying logistic generalized linear models and multilevel models, considering self-reported health as the dependent variable and deprivation and self-reported quality of life as the independent variables. The obtained results show that the multi-criteria deprivation index for the city of Quito is a meaningful measure to assess neighborhood effects on self-reported health and that the alternative deprivation index using the interval AHP methodology more thoroughly represents the local knowledge of experts and stakeholders. These differences could support decision makers in improving health planning and in tackling health inequalities in more deprived areas. PMID:29337915

Barriers to Gender Transition-Related Healthcare: Identifying Underserved Transgender Adults in Massachusetts

PubMed Central

White Hughto, Jaclyn M.; Rose, Adam J.; Pachankis, John E.; Reisner, Sari L.

2017-01-01

Abstract Purpose: The present study sought to examine whether individual (e.g., age, gender), interpersonal (e.g., healthcare provider discrimination), and structural (e.g., lack of insurance coverage) factors are associated with access to transition-related care in a statewide sample of transgender adults. Method: In 2013, 364 transgender residents of Massachusetts completed an electronic web-based survey online (87.1%) or in person (12.9%). A multivariable logistic regression model tested whether individual, interpersonal, and structural factors were associated with access to transition-related care. Results: Overall, 23.6% reported being unable to access transition-related care in the past 12 months. In a multivariable model, younger age, low income, low educational attainment, private insurance coverage, and healthcare discrimination were significantly associated with being unable to access transition-related care (all p<0.05). Discussion: Despite state nondiscrimination policies and universal access to healthcare, many of the Massachusetts transgender residents sampled were unable to access transition-related care. Multilevel interventions are needed, including supportive policies and policy enforcement, to ensure that underserved transgender adults can access medically necessary transition-related care. PMID:29082331

Aggressive crime, alcohol and drug use, and concentrated poverty in 24 U.S. urban areas.

PubMed

Valdez, Avelardo; Kaplan, Charles D; Curtis, Russell L

2007-01-01

The nexus between substance use and aggressive crime involves a complex interrelationship among mediating individual and community-level variables. Using multilevel logistic regression models, we investigate how community-level concentration of poverty variables mediate the predictive relationships among individual level social attachment variables and substance use on aggressive crime in a large national sample of male arrestees (N = 20,602) drawn from 24 U.S. urban areas. The findings support our hypothesis that individual social attachments to marriage and the labor force (education and employment) are the principal individual-level pathway mediating the substance abuse/aggression nexus. In the random intercept model, 3.17% of the variation not explained by the individual-level predictor variables is attributable to community-level variation in urban area female-headed households and households receiving welfare. This confirms our hypothesis that social structural conditions of an urban environment differentially expose persons to conditions that predict being arrested for an aggressive crime. Our findings tend to counter the cultural theorists who argue for an indigenous culture of violence in inner-city ghettos and barrios.

Development of an algorithm for controlling a multilevel three-phase converter

NASA Astrophysics Data System (ADS)

Taissariyeva, Kyrmyzy; Ilipbaeva, Lyazzat

2017-08-01

This work is devoted to the development of an algorithm for controlling transistors in a three-phase multilevel conversion system. The developed algorithm allows to organize a correct operation and describes the state of transistors at each moment of time when constructing a computer model of a three-phase multilevel converter. The developed algorithm of operation of transistors provides in-phase of a three-phase converter and obtaining a sinusoidal voltage curve at the converter output.

Using multilevel modeling to assess case-mix adjusters in consumer experience surveys in health care.

PubMed

Damman, Olga C; Stubbe, Janine H; Hendriks, Michelle; Arah, Onyebuchi A; Spreeuwenberg, Peter; Delnoij, Diana M J; Groenewegen, Peter P

2009-04-01

Ratings on the quality of healthcare from the consumer's perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for analyzing healthcare performance data, it has rarely been used to assess case-mix adjustment of such data. The purpose of this article is to investigate whether multilevel regression analysis is a useful tool to detect case-mix adjusters in consumer assessment of healthcare. We used data on 11,539 consumers from 27 Dutch health plans, which were collected using the Dutch Consumer Quality Index health plan instrument. We conducted multilevel regression analyses of consumers' responses nested within health plans to assess the effects of consumer characteristics on consumer experience. We compared our findings to the results of another methodology: the impact factor approach, which combines the predictive effect of each case-mix variable with its heterogeneity across health plans. Both multilevel regression and impact factor analyses showed that age and education were the most important case-mix adjusters for consumer experience and ratings of health plans. With the exception of age, case-mix adjustment had little impact on the ranking of health plans. On both theoretical and practical grounds, multilevel modeling is useful for adequate case-mix adjustment and analysis of performance ratings.

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study

PubMed Central

Vickers, T. Winston; Ernest, Holly B.; Boyce, Walter M.

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species. PMID:28609466

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study.

PubMed

Zeller, Katherine A; Vickers, T Winston; Ernest, Holly B; Boyce, Walter M

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species.

Identifying Synergies in Multilevel Interventions.

PubMed

Lewis, Megan A; Fitzgerald, Tania M; Zulkiewicz, Brittany; Peinado, Susana; Williams, Pamela A

2017-04-01

Social ecological models of health often describe multiple levels of influence that interact to influence health. However, it is still common for interventions to target only one or two of these levels, perhaps owing in part to a lack of guidance on how to design multilevel interventions to achieve optimal impact. The convergence strategy emphasizes that interventions at different levels mutually reinforce each other by changing patterns of interaction among two or more intervention audiences; this strategy is one approach for combining interventions at different levels to produce synergistic effects. We used semistructured interviews with 65 representatives in a cross-site national initiative that enhanced health and outcomes for patients with diabetes to examine whether the convergence strategy was a useful conceptual model for multilevel interventions. Using a framework analysis approach to analyze qualitative interview data, we found three synergistic themes that match the convergence strategy and support how multilevel interventions can be successful. These three themes were (1) enhancing engagement between patient and provider and access to quality care; (2) supporting communication, information sharing, and coordination among providers, community stakeholders, and systems; and (3) building relationships and fostering alignment among providers, community stakeholders, and systems. These results support the convergence strategy as a testable conceptual model and provide examples of successful intervention strategies for combining multilevel interventions to produce synergies across levels and promote diabetes self-management and that may extend to management of other chronic illnesses as well.

A Multilevel Modelling Approach to Investigating Factors Impacting Science Achievement for Secondary School Students: PISA Hong Kong Sample

ERIC Educational Resources Information Center

Sun, Letao; Bradley, Kelly D.; Akers, Kathryn

2012-01-01

This study utilized data from the 2006 Programme for International Student Assessment Hong Kong sample to investigate the factors that impact the science achievement of 15-year-old students. A multilevel model was used to examine the factors from both student and school perspectives. At the student level, the results indicated that male students,…

Longitudinal Assessment of Intellectual Abilities of Children with Williams Syndrome: Multilevel Modeling of Performance on the Kaufman Brief Intelligence Test--Second Edition

ERIC Educational Resources Information Center

Mervis, Carolyn B.; Kistler, Doris J.; John, Angela E.; Morris, Colleen A.

2012-01-01

Multilevel modeling was used to address the longitudinal stability of standard scores (SSs) measuring intellectual ability for children with Williams syndrome (WS). Participants were 40 children with genetically confirmed WS who completed the Kaufman Brief Intelligence Test--Second Edition (KBIT-2; A. S. Kaufman & N. L. Kaufman, 2004) 4-7…

The Use of Multilevel Modeling to Estimate Which Measures Are Most Influential in Determining an Institution's Placement in Carnegie's New Doctoral/Research University Classification Schema

ERIC Educational Resources Information Center

Micceri, Theodore

2007-01-01

This research sought to determine whether any measure(s) used in the Carnegie Foundation's classification of Doctoral/Research Universities contribute to a greater degree than other measures to final rank placement. Multilevel Modeling (MLM) was applied to all eight of the Carnegie Foundation's predictor measures using final rank…

A Primer for Analyzing Nested Data: Multilevel Modeling in SPSS Using an Example from a REL Study. REL 2015-046

ERIC Educational Resources Information Center

O'Dwyer, Laura M.; Parker, Caroline E.

2014-01-01

Analyzing data that possess some form of nesting is often challenging for applied researchers or district staff who are involved in or in charge of conducting data analyses. This report provides a description of the challenges for analyzing nested data and provides a primer of how multilevel regression modeling may be used to resolve these…

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses

ERIC Educational Resources Information Center

Cho, Sun-Joo; Preacher, Kristopher J.; Bottge, Brian A.

2015-01-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test--post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test…

Conceptualizing and Testing Random Indirect Effects and Moderated Mediation in Multilevel Models: New Procedures and Recommendations

ERIC Educational Resources Information Center

Bauer, Daniel J.; Preacher, Kristopher J.; Gil, Karen M.

2006-01-01

The authors propose new procedures for evaluating direct, indirect, and total effects in multilevel models when all relevant variables are measured at Level 1 and all effects are random. Formulas are provided for the mean and variance of the indirect and total effects and for the sampling variances of the average indirect and total effects.…

A closed-loop multi-level model of glucose homeostasis

PubMed Central

Uluseker, Cansu; Simoni, Giulia; Dauriz, Marco; Matone, Alice

2018-01-01

Background The pathophysiologic processes underlying the regulation of glucose homeostasis are considerably complex at both cellular and systemic level. A comprehensive and structured specification for the several layers of abstraction of glucose metabolism is often elusive, an issue currently solvable with the hierarchical description provided by multi-level models. In this study we propose a multi-level closed-loop model of whole-body glucose homeostasis, coupled with the molecular specifications of the insulin signaling cascade in adipocytes, under the experimental conditions of normal glucose regulation and type 2 diabetes. Methodology/Principal findings The ordinary differential equations of the model, describing the dynamics of glucose and key regulatory hormones and their reciprocal interactions among gut, liver, muscle and adipose tissue, were designed for being embedded in a modular, hierarchical structure. The closed-loop model structure allowed self-sustained simulations to represent an ideal in silico subject that adjusts its own metabolism to the fasting and feeding states, depending on the hormonal context and invariant to circadian fluctuations. The cellular level of the model provided a seamless dynamic description of the molecular mechanisms downstream the insulin receptor in the adipocytes by accounting for variations in the surrounding metabolic context. Conclusions/Significance The combination of a multi-level and closed-loop modeling approach provided a fair dynamic description of the core determinants of glucose homeostasis at both cellular and systemic scales. This model architecture is intrinsically open to incorporate supplementary layers of specifications describing further individual components influencing glucose metabolism. PMID:29420588

A collision dynamics model of a multi-level train

DOT National Transportation Integrated Search

2006-11-05

In train collisions, multi-level rail passenger vehicles can deform in modes that are different from the behavior of single level cars. The deformation in single level cars usually occurs at the front end during a collision. In one particular inciden...

Placement decisions and disparities among aboriginal groups: an application of the decision making ecology through multi-level analysis.

PubMed

Fluke, John D; Chabot, Martin; Fallon, Barbara; MacLaurin, Bruce; Blackstock, Cindy

2010-01-01

This paper examined the relative influence of clinical and organizational characteristics on the decision to place a child in out-of-home care at the conclusion of a child maltreatment investigation. It tested the hypothesis that extraneous factors, specifically, organizational characteristics, impact the decision to place a child in out-of-home care. A secondary aim was to identify possible decision making influences related to disparities in placement decisions tied to Aboriginal children. Research suggests that the Aboriginal status of the child and structural risk factors affecting the family, such as poverty and poor housing, substantially account for this overrepresentation. The decision to place a child in out-of-home care was examined using data from the Canadian Incidence Study of Reported Child Abuse and Neglect. This child welfare dataset collected information about the results of nearly 5,000 child maltreatment investigations as well as a description of the characteristics of the workers and organization responsible for conducting those investigations. Multi-level statistical models were developed using MPlus software, which can accommodate dichotomous outcome variables, which are more reflective of decision making in child welfare. MPlus allows the specific case of the logistic link function for binary outcome variables under maximum likelihood estimation. Final models revealed the importance of the number of Aboriginal reports to an organization as a key second level predictor of the placement decision. It is the only second level factor that remains in the final model. This finding was very stable when tested over several different levels of proportionate caseload representation ranging from greater than 50% to 20% of the caseload. Disparities among Aboriginal children in child welfare decision making were identified at the agency level. The study provides additional evidence supporting the possibility that one source of overrepresentation of Aboriginal children in the Canadian foster care system is a lack of appropriate resources at the agency or community level. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

A Multilevel Analysis of Neighbourhood Built and Social Environments and Adult Self-Reported Physical Activity and Body Mass Index in Ottawa, Canada

PubMed Central

Prince, Stephanie A.; Kristjansson, Elizabeth A.; Russell, Katherine; Billette, Jean-Michel; Sawada, Michael; Ali, Amira; Tremblay, Mark S.; Prud’homme, Denis

2011-01-01

Canadian research examining the combined effects of social and built environments on physical activity (PA) and obesity is limited. The purpose of this study was to determine the relationships among built and social environments and PA and overweight/obesity in 85 Ottawa neighbourhoods. Self-reported PA, height and weight were collected from 3,883 adults using the International PA Questionnaire from the 2003–2007 samples of the Rapid Risk Factor Surveillance System. Data on neighbourhood characteristics were obtained from the Ottawa Neighbourhood Study; a large study of neighbourhoods and health in Ottawa. Two-level binomial logistic regression models stratified by sex were used to examine the relationships of environmental and individual variables with PA and overweight/obesity while using survey weights. Results identified that approximately half of the adults were insufficiently active or overweight/obese. Multilevel models identified that for every additional convenience store, men were two times more likely to be physically active (OR = 2.08, 95% CI: 1.72, 2.43) and with every additional specialty food store women were almost two times more likely to be overweight or obese (OR = 1.77, 95% CI: 1.33, 2.20). Higher green space was associated with a reduced likelihood of PA (OR = 0.93, 95% CI: 0.86, 0.99) and increased odds of overweight and obesity in men (OR = 1.10, 95% CI: 1.01, 1.19), and decreased odds of overweight/obesity in women (OR = 0.66, 95% CI: 0.44, 0.89). In men, neighbourhood socioeconomic scores, voting rates and sense of community belonging were all significantly associated with overweight/obesity. Intraclass coefficients were low, but identified that the majority of neighbourhood variation in outcomes was explained by the models. Findings identified that green space, food landscapes and social cohesiveness may play different roles on PA and overweight/obesity in men and women and future prospective studies are needed. PMID:22073022

Psychometric evaluation of a short measure of social capital at work.

PubMed

Kouvonen, Anne; Kivimäki, Mika; Vahtera, Jussi; Oksanen, Tuula; Elovainio, Marko; Cox, Tom; Virtanen, Marianna; Pentti, Jaana; Cox, Sara J; Wilkinson, Richard G

2006-10-13

Prior studies on social capital and health have assessed social capital in residential neighbourhoods and communities, but the question whether the concept should also be applicable in workplaces has been raised. The present study reports on the psychometric properties of an 8-item measure of social capital at work. Data were derived from the Finnish Public Sector Study (N = 48,592) collected in 2000-2002. Based on face validity, an expert unfamiliar with the data selected 8 questionnaire items from the available items for a scale of social capital. Reliability analysis included tests of internal consistency, item-total correlations, and within-unit (interrater) agreement by rwg index. The associations with theoretically related and unrelated constructs were examined to assess convergent and divergent validity (construct validity). Criterion-related validity was explored with respect to self-rated health using multilevel logistic regression models. The effects of individual level and work unit level social capital were modelled on self-rated health. The internal consistency of the scale was good (Cronbach's alpha = 0.88). The rwg index was 0.88, which indicates a significant within-unit agreement. The scale was associated with, but not redundant to, conceptually close constructs such as procedural justice, job control, and effort-reward imbalance. Its associations with conceptually more distant concepts, such as trait anxiety and magnitude of change in work, were weaker. In multilevel models, significantly elevated age adjusted odds ratios (ORs) of poor self-rated health (OR = 2.42, 95% confidence interval (CI): 2.24-2.61 for the women and OR = 2.99, 95% CI: 2.56-3.50 for the men) were observed for the employees in the lowest vs. highest quartile of individual level social capital. In addition, low social capital at the work unit level was associated with a higher likelihood of poor self-rated health. Psychometric techniques show our 8-item measure of social capital to be a valid tool reflecting the construct and displaying the postulated links with other variables.

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China

PubMed Central

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-01-01

Background: In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. Methods: As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6–12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. Results: The prevalence of anemia was 12.60% with a range of 3.47%–40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. Conclusions: The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities. PMID:27174328

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China.

PubMed

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-05-20

In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6-12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. The prevalence of anemia was 12.60% with a range of 3.47%-40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities.

From organized internal traffic to collective navigation of bacterial swarms

NASA Astrophysics Data System (ADS)

Ariel, Gil; Shklarsh, Adi; Kalisman, Oren; Ingham, Colin; Ben-Jacob, Eshel

2013-12-01

Bacterial swarming resulting in collective navigation over surfaces provides a valuable example of cooperative colonization of new territories. The social bacterium Paenibacillus vortex exhibits successful and diverse swarming strategies. When grown on hard agar surfaces with peptone, P. vortex develops complex colonies of vortices (rotating bacterial aggregates). In contrast, during growth on Mueller-Hinton broth gelled into a soft agar surface, a new strategy of multi-level organization is revealed: the colonies are organized into a special network of swarms (or ‘snakes’ of a fraction of millimeter in width) with intricate internal traffic. More specifically, cell movement is organized in two or three lanes of bacteria traveling between the back and the front of the swarm. This special form of cellular logistics suggests new methods in which bacteria can share resources and risk while searching for food or migrating into new territories. While the vortices-based organization on hard agar surfaces has been modeled before, here, we introduce a new multi-agent bacterial swarming model devised to capture the swarms-based organization on soft surfaces. We test two putative generic mechanisms that may underlie the observed swarming logistics: (i) chemo-activated taxis in response to chemical cues and (ii) special align-and-push interactions between the bacteria and the boundary of the layer of lubricant collectively generated by the swarming bacteria. Using realistic parameters, the model captures the observed phenomena with semi-quantitative agreement in terms of the velocity as well as the dynamics of the swarm and its envelope. This agreement implies that the bacteria interactions with the swarm boundary play a crucial role in mediating the interplay between the collective movement of the swarm and the internal traffic dynamics.

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes

PubMed Central

2011-01-01

Background Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. Methods We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC. Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. Results The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. Conclusions On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain. PMID:21605357

Dispositional and Environmental Predictors of the Development of Internalizing Problems in Childhood: Testing a Multilevel Model.

PubMed

Hastings, Paul D; Helm, Jonathan; Mills, Rosemary S L; Serbin, Lisa A; Stack, Dale M; Schwartzman, Alex E

2015-07-01

This investigation evaluated a multilevel model of dispositional and environmental factors contributing to the development of internalizing problems from preschool-age to school-age. In a sample of 375 families (185 daughters, 190 sons) drawn from three independent samples, preschoolers' behavioral inhibition, cortisol and gender were examined as moderators of the links between mothers' negative parenting behavior, negative emotional characteristics, and socioeconomic status when children were 3.95 years, and their internalizing problems when they were 8.34 years. Children's dispositional characteristics moderated all associations between these environmental factors and mother-reported internalizing problems in patterns that were consistent with either diathesis-stress or differential-susceptibility models of individual-environment interaction, and with gender models of developmental psychopathology. Greater inhibition and lower socioeconomic status were directly predictive of more teacher reported internalizing problems. These findings highlight the importance of using multilevel models within a bioecological framework to understand the complex pathways through which internalizing difficulties develop.

[Relationship between perceptions of safety climate at workplace and depressive disorders in manufacturing workers].

PubMed

Liu, Xu-hua; Xiao, Ya-ni; Huang, Zhi-xiong; Huang, Shao-bin; Cao, Xiao-ou; Guan, Dong-bo; Chen, Wei-qing

2013-04-01

To investigate the risk factors for depressive disorders in manufacturing workers and to provide a basis for developing health promotion measures at workplace. A questionnaire survey was performed in 8085 front-line production workers from 33 manufacturing enterprises in Nanhai District of Foshan, Guangdong Province, China. The questionnaire contained a survey of demographic characteristics, the Safety Climate Scale, the Center for Epidemiological Studies Depression Scale, etc. The multilevel logistic regression analysis was applied to investigate the risk factors for depressive disorders in workers. A total of 6260 workers completed the survey; their mean age was 31.1 ± 8.6 years, and 53.2% of them were males. The multilevel logistic regression analysis showed that after adjustment for sociodemographic factors such as age, sex, and martial status, more depressive disorders were reported in the enterprises with higher score of "production safety training" than in those with lower score (OR = 1.46, 95%CI = 1.07 ∼ 1.97); fewer depressive disorders were reported in the enterprises with higher score of "colleagues concerned about production safety" than in those with lower score (OR = 0.08, 95%CI = 0.03 ∼ 0.26); the relationships of "safety warnings and precautions" and "managers concerned about production safety" with workers' depressive disorders were not statistically significant (OR = 0.78, 95%CI = 0.48 ∼ 1.28; OR = 1.08, 95%CI = 0.68 ∼ 1.72). Depressive disorders in manufacturing workers are related to the safety climate at workplace, which indicates that a good safety climate at workplace should be created to prevent and control depressive disorders in workers.

Longitudinal Multilevel Models of the Big Fish Little Pond Effect on Academic Self-Concept: Counterbalancing Contrast and Reflected Glory Effects in Hong Kong Schools.

ERIC Educational Resources Information Center

Marsh, Herbert W.; Kong, Chit-Kwong; Hau, Kit-Tai

Longitudinal multilevel path models (7,997 students, 44 high schools, 4 years) evaluated the effects of school-average achievement and perceived school status on academic self-concept in Hong Kong, a collectivist culture with a highly achievement-segregated high school system. Consistent with a priori predictions based on the big-fish-little-pond…

Disentangling the Relative Influence of Schools and Neighborhoods on Adolescents’ Risk for Depressive Symptoms

PubMed Central

Milliren, Carly E.; Evans, Clare R.; Subramanian, S. V.; Richmond, Tracy K.

2015-01-01

Objectives. Although schools and neighborhoods influence health, little is known about their relative importance, or the influence of one context after the influence of the other has been taken into account. We simultaneously examined the influence of each setting on depression among adolescents. Methods. Analyzing data from wave 1 (1994–1995) of the National Longitudinal Study of Adolescent Health, we used cross-classified multilevel modeling to examine between-level variation and individual-, school-, and neighborhood-level predictors of adolescent depressive symptoms. Also, we compared the results of our cross-classified multilevel models (CCMMs) with those of a multilevel model wherein either school or neighborhood was excluded. Results. In CCMMs, the school-level random effect was significant and more than 3 times the neighborhood-level random effect, even after individual-level characteristics had been taken into account. Individual-level indicators (e.g., race/ethnicity, socioeconomic status) were associated with depressive symptoms, but there was no association with either school- or neighborhood-level fixed effects. The between-level variance in depressive symptoms was driven largely by schools as opposed to neighborhoods. Conclusions. Schools appear to be more salient than neighborhoods in explaining variation in depressive symptoms. Future work incorporating cross-classified multilevel modeling is needed to understand the relative effects of schools and neighborhoods. PMID:25713969

A longitudinal multilevel CFA-MTMM model for interchangeable and structurally different methods

PubMed Central

Koch, Tobias; Schultze, Martin; Eid, Michael; Geiser, Christian

2014-01-01

One of the key interests in the social sciences is the investigation of change and stability of a given attribute. Although numerous models have been proposed in the past for analyzing longitudinal data including multilevel and/or latent variable modeling approaches, only few modeling approaches have been developed for studying the construct validity in longitudinal multitrait-multimethod (MTMM) measurement designs. The aim of the present study was to extend the spectrum of current longitudinal modeling approaches for MTMM analysis. Specifically, a new longitudinal multilevel CFA-MTMM model for measurement designs with structurally different and interchangeable methods (called Latent-State-Combination-Of-Methods model, LS-COM) is presented. Interchangeable methods are methods that are randomly sampled from a set of equivalent methods (e.g., multiple student ratings for teaching quality), whereas structurally different methods are methods that cannot be easily replaced by one another (e.g., teacher, self-ratings, principle ratings). Results of a simulation study indicate that the parameters and standard errors in the LS-COM model are well recovered even in conditions with only five observations per estimated model parameter. The advantages and limitations of the LS-COM model relative to other longitudinal MTMM modeling approaches are discussed. PMID:24860515

Multilevel processes and cultural adaptation: Examples from past and present small-scale societies.

PubMed

Reyes-García, V; Balbo, A L; Gomez-Baggethun, E; Gueze, M; Mesoudi, A; Richerson, P; Rubio-Campillo, X; Ruiz-Mallén, I; Shennan, S

2016-12-01

Cultural adaptation has become central in the context of accelerated global change with authors increasingly acknowledging the importance of understanding multilevel processes that operate as adaptation takes place. We explore the importance of multilevel processes in explaining cultural adaptation by describing how processes leading to cultural (mis)adaptation are linked through a complex nested hierarchy, where the lower levels combine into new units with new organizations, functions, and emergent properties or collective behaviours. After a brief review of the concept of "cultural adaptation" from the perspective of cultural evolutionary theory and resilience theory, the core of the paper is constructed around the exploration of multilevel processes occurring at the temporal, spatial, social and political scales. We do so by examining small-scale societies' case studies. In each section, we discuss the importance of the selected scale for understanding cultural adaptation and then present an example that illustrates how multilevel processes in the selected scale help explain observed patterns in the cultural adaptive process. We end the paper discussing the potential of modelling and computer simulation for studying multilevel processes in cultural adaptation.

Multilevel processes and cultural adaptation: Examples from past and present small-scale societies

PubMed Central

Reyes-García, V.; Balbo, A. L.; Gomez-Baggethun, E.; Gueze, M.; Mesoudi, A.; Richerson, P.; Rubio-Campillo, X.; Ruiz-Mallén, I.; Shennan, S.

2016-01-01

Cultural adaptation has become central in the context of accelerated global change with authors increasingly acknowledging the importance of understanding multilevel processes that operate as adaptation takes place. We explore the importance of multilevel processes in explaining cultural adaptation by describing how processes leading to cultural (mis)adaptation are linked through a complex nested hierarchy, where the lower levels combine into new units with new organizations, functions, and emergent properties or collective behaviours. After a brief review of the concept of “cultural adaptation” from the perspective of cultural evolutionary theory and resilience theory, the core of the paper is constructed around the exploration of multilevel processes occurring at the temporal, spatial, social and political scales. We do so by examining small-scale societies’ case studies. In each section, we discuss the importance of the selected scale for understanding cultural adaptation and then present an example that illustrates how multilevel processes in the selected scale help explain observed patterns in the cultural adaptive process. We end the paper discussing the potential of modelling and computer simulation for studying multilevel processes in cultural adaptation. PMID:27774109

Using Multilevel Modeling in Language Assessment Research: A Conceptual Introduction

ERIC Educational Resources Information Center

Barkaoui, Khaled

2013-01-01

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

[Biodiversity and depressive symptoms in Mexican adults: Exploration of beneficial environmental effects].

PubMed

Duarte-Tagles, Héctor; Salinas-Rodríguez, Aarón; Idrovo, Álvaro J; Búrquez, Alberto; Corral-Verdugo, Víctor

2015-08-01

Depression is a highly prevalent illness among adults, and it is the second most frequently reported mental disorder in urban settings in México. Exposure to natural environments and its components may improve the mental health of the population. To evaluate the association between biodiversity indicators and the prevalence of depressive symptoms among the adult population (20 to 65 years of age) in México. Information from the Encuesta Nacional de Salud y Nutrición 2006 (ENSANUT 2006) and the Compendio de Estadísticas Ambientales 2008 was analyzed. A biodiversity index was constructed based on the species richness and ecoregions in each state. A multilevel logistic regression model was built with random intercepts and a multiple logistic regression was generated with clustering by state. The factors associated with depressive symptoms were being female, self-perceived as indigenous, lower education level, not living with a partner, lack of steady paid work, having a chronic illness and drinking alcohol. The biodiversity index was found to be inversely associated with the prevalence of depressive symptoms when defined as a continuous variable, and the results from the regression were grouped by state (OR=0.71; 95% CI = 0.59-0.87). Although the design was cross-sectional, this study adds to the evidence of the potential benefits to mental health from contact with nature and its components.

School-level economic disadvantage and obesity in middle school children in central Texas, USA: a cross-sectional study

PubMed Central

2015-01-01

Background Although children of lower socio-economic status (SES) in the United States have generally been found to be at greater risk for obesity, the SES-obesity association varies when stratified by racial/ethnic groups-with no consistent association found for African American and Hispanic children. Research on contextual and setting-related factors may provide further insights into ethnic and SES disparities in obesity. We examined whether obesity levels among central Texas 8th grade students (n=2682) vary by school-level economic disadvantage across individual-level family SES and racial/ethnicity groups. As a secondary aim, we compared the association of school-level economic disadvantage and obesity by language spoken with parents (English or Spanish) among Hispanic students. Methods Multilevel regression models stratified by family SES and ethnicity were run using cross-sectional baseline data from five school districts participating in the Central Texas CATCH Middle School project. For family SES, independent multi-level logistic regression models were run for total sample and by gender for each family SES stratum (poor/near poor/just getting by, living comfortably, and very well off), adjusting for age, ethnicity, and gender. Similarly, multi-level regression models were run by race/ethnic group (African American, Hispanic, and White), adjusting for age, family SES, and gender. Results Students attending highly economically disadvantaged (ED) schools were between 1.7 (95% CI: 1.1-2.6) and 2.4 (95% CI: 1.2-4.8) times more likely to be obese as students attending low ED schools across family SES groups (p<.05). African American (ORAdj =3.4, 95% CI: 1.1-11.4), Hispanic (ORAdj=1.8, 95% CI 1.1-3.0) and White (ORAdj=3.8, 95% CI: 1.6-8.9) students attending high ED schools were more likely to be obese as counterparts at low ED schools (p<.05). Gender-stratified findings were similar to findings for total sample, although fewer results reached significance. While no obesity differences across school ED categories were found for Hispanic Spanish-speaking students, Hispanic English-speaking students (HES) attending high ED schools were 2.4 times more likely to be obese as HES students at low ED schools (p=.003). Conclusion Findings support the need to prioritize economically disadvantaged schools for obesity prevention efforts and support further exploration of school SES context in shaping children’s physical activity and dietary behaviors. PMID:26222099

Geographic Variation in Household and Catastrophic Health Spending in India: Assessing the Relative Importance of Villages, Districts, and States, 2011-2012.

PubMed

Mohanty, Sanjay K; Kim, Rockli; Khan, Pijush Kanti; Subramanian, S V

2018-03-01

Policy Points: Per-capita household health spending was higher in economically developed states and was associated with ability to pay, but catastrophic health spending (CHS) was equally high in both poorer and more developed states in India. Based on multilevel modeling, we found that the largest geographic variation in health spending and CHS was at the state and village levels, reflecting wide inequality in the accessibility to and cost of health care at these levels. Contextual factors at macro and micro political units are important to reduce health spending and CHS in India. In India, health care is a local good, and households are the major source of financing it. Earlier studies have examined diverse determinants of health care spending, but no attempt has been made to understand the geographical variation in household and catastrophic health spending. We used multilevel modeling to assess the relative importance of villages, districts, and states to health spending in India. We used data on the health expenditures of 101,576 households collected in the consumption expenditure schedule (68th round) carried out by the National Sample Survey in 2011-2012. We examined 4 dependent variables: per-capita health spending (PHS), per-capita institutional health spending (PIHS), per-capita noninstitutional health spending (PNHS), and catastrophic health spending (CHS). CHS was defined as household health spending exceeding 40% of its capacity to pay. We used multilevel linear regression and logistic models to decompose the variation in each outcome by state, region, district, village, and household levels. The average PHS was 1,331 Indian rupees (INR), which varied by state-level economic development. About one-fourth of Indian households incurred CHS, which was equally high in both the economically developed and poorer states. After controlling for household level factors, 77.1% of the total variation in PHS was attributable to households, 10.1% to states, 9.5% to villages, 2.6% to districts, and 0.7% to regions. The pattern in variance partitioning was similar for PNHS. The largest interstate variation was found for CHS (15.9%), while the opposite was true for PIHS (3.2%). We observed substantial variations in household health spending at the state and village levels compared with India's districts and regions. The large variation in CHS attributable to states indicates interstate inequality in the accessibility to and cost of health care. Our findings suggest that contextual factors at the macro and micro political units are important to reduce India's household health spending and CHS. © 2018 Milbank Memorial Fund.

Contemporary New Zealand coefficients for the Trauma Injury Severity Score: TRISS(NZ).

PubMed

Schluter, Philip J; Cameron, Cate M; Davey, Tamzyn M; Civil, Ian; Orchard, Jodie; Dansey, Rangi; Hamill, James; Naylor, Helen; James, Carolyn; Dorrian, Jenny; Christey, Grant; Pollard, Cliff; McClure, Rod J

2009-09-11

To develop local contemporary coefficients for the Trauma Injury Severity Score in New Zealand, TRISS(NZ), and to evaluate their performance at predicting survival against the original TRISS coefficients. Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until presentation at Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Coefficients were estimated using ordinary and multilevel mixed-effects logistic regression models. 1735 eligible patients were identified, 1672 (96%) injured from a blunt mechanism and 63 (4%) from a penetrating mechanism. For blunt mechanism trauma, 1250 (75%) were male and average age was 38 years (range: 15-94 years). TRISS information was available for 1565 patients of whom 204 (13%) died. Area under the Receiver Operating Characteristic (ROC) curves was 0.901 (95%CI: 0.879-0.923) for the TRISS(NZ) model and 0.890 (95% CI: 0.866-0.913) for TRISS (P<0.001). Insufficient data were available to determine coefficients for penetrating mechanism TRISS(NZ) models. Both TRISS models accurately predicted survival for blunt mechanism trauma. However, TRISS(NZ) coefficients were statistically superior to TRISS coefficients. A strong case exists for replacing TRISS coefficients in the New Zealand benchmarking software with these updated TRISS(NZ) estimates.

Childbearing in crisis: war, migration and fertility in Angola.

PubMed

Avogo, Winfred; Agadjanian, Victor

2008-09-01

This study examines the short- and long-term effects of war-induced and war-unrelated migration on fertility outcomes using data from two peri-urban municipalities of Greater Luanda in Angola. In the short term, results from multi-level discrete-time logistic regression models indicate that net of other factors, war-unrelated migration is associated with a lower probability of birth than war-induced migration in a given year. Similar results are obtained when the effects of migration are lagged by a year. At the same time, the effects of war-triggered migration do not differ significantly from those of not migrating in a given year but are statistically significant when the effects of migration are lagged by a year. In the long term, the effects of migration experience on cumulative fertility are negligible and not statistically significant net of demographic and socioeconomic variables. Interpretations of the results are offered in the context of Angola and their broader implications are reflected on.

Nutritional status of under-five children in Bangladesh: a multilevel analysis.

PubMed

Alom, Jahangir; Quddus, Md Abdul; Islam, Mohammad Amirul

2012-09-01

The nutritional status of under-five children is a sensitive sign of a country's health status as well as economic condition. This study investigated the differential impact of some demographic, socioeconomic, environmental and health-related factors on the nutritional status among under-five children in Bangladesh using Bangladesh Demographic and Health Survey 2007 data. Two-level random intercept binary logistic regression models were used to identify the determinants of under-five malnutrition. The analyses revealed that 16% of the children were severely stunted and 25% were moderately stunted. Among the children under five years of age 3% were severely wasted and 14% were moderately wasted. Furthermore, 11% of the children were severely underweight and 28% were moderately underweight. The main contributing factors for under-five malnutrition were found to be child's age, mother's education, father's education, father's occupation, family wealth index, currently breast-feeding, place of delivery and division. Significant community-level variations were found in the analyses.

Does time of day influence cancer detection and recall rates in mammography?

NASA Astrophysics Data System (ADS)

Stinton, Chris; Jenkinson, David; Adekanmbi, Victor; Clarke, Aileen; Taylor-Phillips, Sian

2017-03-01

Background: The interpretation of screening mammograms is influenced by factors such as reader experience and their annual interpretative volume. There is some evidence that time of day can also have an effect, with better diagnostic accuracy for readings conducted early in the day. This is not a consistent finding, however. The aim of our study is to provide further evidence on whether there is an effect of time of day on recall- and breast cancer detection rates. Method: We analysed breast screening data from 222,577 women from the Midlands of England. Data were split into three eight hour periods: 0900-1700, 1700-0100, 0100-0900. Differences in recall- and cancer detection rates were analysed using multilevel logistic regression models. Results: Recall rates were lowest for mammograms read between the 1700-0100 time period. Cancer detection rates were lowest during the 0100-0900 time period. Conclusions: Our findings suggest that there are fluctuations in recall- and cancer detection rates over the course of the day.

Tourism Experiences and Self-Rated Health Among Older Adults in China.

PubMed

Gu, Danan; Zhu, Haiyan; Brown, Tyson; Hoenig, Helen; Zeng, Yi

2016-06-01

To investigate factors associated with tourism experiences, and the association between tourism experiences and subsequent self-rated health. Multilevel logistic regression models and four waves of panel data from a large nationally representative survey of older adults in China were employed. Those who had a tourism experience tended to be younger, men, urban residents, have a higher socioeconomic status (SES), and frequently participate in leisure activities and exercise. However, controlling for SES, women were more likely than men to have a tourism experience. Notably, tourism was negatively associated with poor self-rated health and the association was robust to adjustments for a wide range of confounders. The net beneficial impact of tourism on self-rated health may operate through several mechanisms such as improvements in tourists' cognitive functioning, healthy lifestyles, self-esteen, family and social relations, and psychological and spirtual well-being. Tourism participation is an effective way to promote healthy aging. © The Author(s) 2015.

E-cigarette use among students and e-cigarette specialty retailer presence near schools.

PubMed

Bostean, Georgiana; Crespi, Catherine M; Vorapharuek, Patsornkarn; McCarthy, William J

2016-11-01

This study examined the association between presence of e-cigarette specialty retailers near schools and e-cigarette use among middle and high school students in Orange County (OC), CA. The OC subsample of the 2013-2014 California Healthy Kids Survey (N=67,701) was combined with geocoded e-cigarette retailers to determine whether a retailer was present within one-quarter mile of each public school in OC. Multilevel logistic regression models evaluated individual-level and school-level e-cigarette use correlates among middle and high school students. Among middle school students, the presence of an e-cigarette retailer within one-quarter mile of their school predicted lifetime e-cigarette use (OR=1.70, 95% CI=1.02, 2.83), controlling for confounders but no effect for current use. No significant effect was found for high school students. E-cigarette specialty retailers clustered around schools may be an environmental influence on student e-cigarette experimentation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Risk factors for ceftiofur resistance in Escherichia coli from Belgian broilers.

PubMed

Persoons, D; Haesebrouck, F; Smet, A; Herman, L; Heyndrickx, M; Martel, A; Catry, B; Berge, A C; Butaye, P; Dewulf, J

2011-05-01

A cross-sectional study on 32 different Belgian broiler farms was performed in 2007 and 2008 to identify risk factors for ceftiofur resistance in Escherichia coli. On each farm, one E. coli colony was isolated from 30 random birds. Following susceptibility testing of 14 antimicrobials, an on-farm questionnaire was used to obtain information on risk factors. Using a multilevel logistic regression model two factors were identified at the animal level: resistance to amoxicillin and to trimethoprim-sulfonamide. On the farm level, besides antimicrobial use, seven management factors were found to be associated with the occurrence of ceftiofur resistance in E. coli from broilers: poor hygienic condition of the medicinal treatment reservoir, no acidification of drinking water, more than three feed changes during the production cycle, hatchery of origin, breed, litter material used, and treatment with amoxicillin. This study confirms that not only on-farm antimicrobial therapy, but also management- and hatchery-related factors influence the occurrence of antimicrobial resistance.

Tourism Experiences and Self-Rated Health Among Older Adults in China

PubMed Central

Gu, Danan; Zhu, Haiyan; Brown, Tyson; Hoenig, Helen; Zeng, Yi

2017-01-01

Objective To investigate factors associated with tourism experiences, and the association between tourism experiences and subsequent self-rated health. Method Multilevel logistic regression models and four waves of panel data from a large nationally representative survey of older adults in China were employed. Results Those who had a tourism experience tended to be younger, men, urban residents, have a higher socioeconomic status (SES), and frequently participate in leisure activities and exercise. However, controlling for SES, women were more likely than men to have a tourism experience. Notably, tourism was negatively associated with poor self-rated health and the association was robust to adjustments for a wide range of confounders. Discussion The net beneficial impact of tourism on self-rated health may operate through several mechanisms such as improvements in tourists’ cognitive functioning, healthy lifestyles, self-esteen, family and social relations, and psychological and spirtual well-being. Tourism participation is an effective way to promote healthy aging. PMID:26486781

Race, Ethnicity, and Adolescent Violent Victimization.

PubMed

Tillyer, Marie Skubak; Tillyer, Rob

2016-07-01

The risk of adolescent violent victimization in the United States varies considerably across racial and ethnic populations; it is unknown whether the sources of risk also vary by race and ethnicity. This study examined the correlates of violent victimization for White, Black, and Hispanic youth. Data collected from 11,070 adolescents (51 % female, mean age = 15.04 years) during the first two waves of the National Longitudinal Study of Adolescent to Adult Health were used to estimate group-specific multilevel logistic regression models. The results indicate that male, violent offending, peer deviance, gang membership, and low self-control were significantly associated with increased odds of violent victimization for all groups. Some activities-including getting drunk, sneaking out, and unstructured socializing with peers-were risk factors for Black adolescents only; skipping school was a risk factor only for Hispanic adolescents. Although there are many similarities across groups, the findings suggest that minority adolescents are particularly vulnerable to violent victimization when they engage in some activities and minor forms of delinquency.

THE CONSEQUENCES OF INDIA’S MALE SURPLUS FOR WOMEN’S PARTNERING AND SEXUAL EXPERIENCES*

PubMed Central

Trent, Katherine; South, Scott J.; Bose, Sunita

2013-01-01

Data from the third wave of India’s 2005–2006 National Family and Health Survey are used to examine the influence of the community-level sex ratio on several dimensions of women’s partnering behavior and sexual experiences. Multi-level logistic regression models that control for individual demographic attributes and community-level characteristics reveal that the local male-to-female sex ratio is positively and significantly associated with the likelihood that women marry prior to age 16 and have experienced forced sex. These associations are modest in magnitude. However, no significant associations are observed between the sex ratio and whether women have had two or more lifetime sexual partners or women’s risk of contracting a sexually-transmitted disease. Birth cohort, education, religion, caste, region, urban residence, and several community-level measures of women’s status also emerge as significant predictors of Indian women’s partnering and sexual experiences. The implications of our results for India’s growing surplus of adult men are discussed. PMID:26085706

THE CONSEQUENCES OF INDIA'S MALE SURPLUS FOR WOMEN'S PARTNERING AND SEXUAL EXPERIENCES.

PubMed

Trent, Katherine; South, Scott J; Bose, Sunita

2015-06-01

Data from the third wave of India's 2005-2006 National Family and Health Survey are used to examine the influence of the community-level sex ratio on several dimensions of women's partnering behavior and sexual experiences. Multi-level logistic regression models that control for individual demographic attributes and community-level characteristics reveal that the local male-to-female sex ratio is positively and significantly associated with the likelihood that women marry prior to age 16 and have experienced forced sex. These associations are modest in magnitude. However, no significant associations are observed between the sex ratio and whether women have had two or more lifetime sexual partners or women's risk of contracting a sexually-transmitted disease. Birth cohort, education, religion, caste, region, urban residence, and several community-level measures of women's status also emerge as significant predictors of Indian women's partnering and sexual experiences. The implications of our results for India's growing surplus of adult men are discussed.

E-cigarette use among students and e-cigarette specialty retailer presence near schools

PubMed Central

Crespi, Catherine M.; Vorapharuek, Patsornkarn; McCarthy, William J.

2016-01-01

Objective This study examined the association between presence of e-cigarette specialty retailers near schools and e-cigarette use among middle and high school students in Orange County (OC), CA. Methods The OC subsample of the 2013–2014 California Healthy Kids Survey (N=67,701) was combined with geocoded e-cigarette retailers to determine whether a retailer was present within one-quarter mile of each public school in OC. Multilevel logistic regression models evaluated individual-level and school-level e-cigarette use correlates among middle and high school students. Results Among middle school students, the presence of an e-cigarette retailer within one-quarter mile of their school predicted lifetime e-cigarette use (OR = 1.70, 95% CI=1.02, 2.83), controlling for confounders but no effect for current use. No significant effect was found for high school students. Conclusions E-cigarette specialty retailers clustered around schools may be an environmental influence on student e-cigarette experimentation. PMID:27770669

Access to a Car and the Self-Reported Health and Mental Health of People Aged 65 and Older in Northern Ireland.

PubMed

Doebler, Stefanie

2016-05-01

This article examines relationships between access to a car and the self-reported health and mental health of older people. The analysis is based on a sample of N = 65,601 individuals aged 65 years and older from the Northern Ireland Longitudinal Study linked to 2001 and 2011 census returns. The findings from hierarchical linear and binary logistic multilevel path models indicate that having no access to a car is related to a considerable health and mental health disadvantage particularly for older people who live alone. Rural-urban health and mental health differences are mediated by access to a car. The findings support approaches that emphasize the importance of autonomy and independence for the well-being of older people and indicate that not having access to a car can be a problem for older people not only in rural but also in intermediate and urban areas, if no sufficient alternative forms of mobility are provided. © The Author(s) 2015.

Geographic proximity to treatment for early stage breast cancer and likelihood of mastectomy.

PubMed

Boscoe, Francis P; Johnson, Christopher J; Henry, Kevin A; Goldberg, Daniel W; Shahabi, Kaveh; Elkin, Elena B; Ballas, Leslie K; Cockburn, Myles

2011-08-01

Women with early stage breast cancer who live far from a radiation therapy facility may be more likely to opt for mastectomy over breast conserving surgery (BCS). The geographic dimensions of this relationship deserve further scrutiny. For over 100,000 breast cancer patients in 10 states who received either mastectomy or BCS, a newly-developed software tool was used to calculate the shortest travel distance to the location of surgery and to the nearest radiation treatment center. The likelihood of receipt of mastectomy was modeled as a function of these distance measures and other demographic variables using multilevel logistic regression. Women traveling over 75 km for treatment are about 1.4 times more likely to receive a mastectomy than those traveling under 15 km. Geographic barriers to optimal breast cancer treatment remain a valid concern, though most women traveling long distances to receive mastectomies are doing so after bypassing local options. Copyright © 2011 Elsevier Ltd. All rights reserved.

Association between sporting event attendance and self-rated health: an analysis of multiyear cross-sectional national data in Japan.

PubMed

Inoue, Yuhei; Sato, Mikihiro; Nakazawa, Makoto

2018-01-01

This study examined the extent to which sporting event attendance is associated with self-rated health. Drawing from an economic model of health production and psychological research on the health benefits of psychosocial resources, sporting event attendance was hypothesized to have a positive relationship with self-rated health. A two-level multilevel ordered logistic regression was used to analyze multiyear cross-sectional data collected from national surveys in Japan. The results demonstrate that, controlling for the effects of personal and environmental characteristics, sporting event attendance positively correlates with self-rated health over a 12-year period. Specifically, when compared to individuals who did not attend any sporting event during the past year, those who attended a sporting event were 33% more likely to indicate a higher level of self-rated health. These findings provide evidence for a positive association between sport spectatorship and the perception of general health and contribute to the literature examining the relationship between sport spectatorship and health outcomes.

Longitudinal cognitive biomarkers predicting symptom onset in presymptomatic frontotemporal dementia.

PubMed

Jiskoot, Lize C; Panman, Jessica L; van Asseldonk, Lauren; Franzen, Sanne; Meeter, Lieke H H; Donker Kaat, Laura; van der Ende, Emma L; Dopper, Elise G P; Timman, Reinier; van Minkelen, Rick; van Swieten, John C; van den Berg, Esther; Papma, Janne M

2018-06-01

We performed 4-year follow-up neuropsychological assessment to investigate cognitive decline and the prognostic abilities from presymptomatic to symptomatic familial frontotemporal dementia (FTD). Presymptomatic MAPT (n = 15) and GRN mutation carriers (n = 31), and healthy controls (n = 39) underwent neuropsychological assessment every 2 years. Eight mutation carriers (5 MAPT, 3 GRN) became symptomatic. We investigated cognitive decline with multilevel regression modeling; the prognostic performance was assessed with ROC analyses and stepwise logistic regression. MAPT converters declined on language, attention, executive function, social cognition, and memory, and GRN converters declined on attention and executive function (p < 0.05). Cognitive decline in ScreeLing phonology (p = 0.046) and letter fluency (p = 0.046) were predictive for conversion to non-fluent variant PPA, and decline on categorical fluency (p = 0.025) for an underlying MAPT mutation. Using longitudinal neuropsychological assessment, we detected a mutation-specific pattern of cognitive decline, potentially suggesting prognostic value of neuropsychological trajectories in conversion to symptomatic FTD.

Depression, neighborhood deprivation and risk of type 2 diabetes

PubMed Central

Mezuk, Briana; Chaikiat, Åsa; Li, Xinjun; Sundquist, Jan; Kendler, Kenneth S.; Sundquist, Kristina

2013-01-01

Neighborhood characteristics have been associated with both depression and diabetes, but to date little attention has been paid to whether the association between depression and diabetes varies across different types of neighborhoods. This prospective study examined the relationship between depression, neighborhood deprivation, and risk of type 2 diabetes among 336,340 adults from a national-representative sample of primary care centers in Sweden (2001–2007). Multi-level logistic regression models were used to assess associations between depression and risk of type 2 diabetes across affluent and deprived neighborhoods. After accounting for demographic, individual-level socioeconomic, and health characteristics, depression was significantly associated with risk of diabetes (odds ratio (OR): 1.10, 95% confidence interval (CI): 1.06–1.14), as was neighborhood deprivation (OR for high vs. low deprivation: 1.66, 95% CI: 1.22–1.34). The interaction term between depression and neighborhood deprivation was non-significant, indicating that the relationship between depression and diabetes risk is similar across levels of neighborhood socioeconomic deprivation. PMID:23771166

Community opioid treatment perspectives on contingency management: Perceived feasibility, effectiveness, and transportability of social and financial incentives

PubMed Central

Hartzler, Bryan; Rabun, Carl

2013-01-01

Treatment community reluctance toward contingency management (CM) may be better understood by eliciting views of its feasibility, effectiveness, and transportability when social vs. financial incentives are utilized. This mixed method study involved individual staff interviews representing three personnel tiers (an executive, clinical supervisor, and two front-line clinicians) at 16 opiate treatment programs. Interviews included Likert ratings of feasibility, effectiveness, and transportability of each incentive type, and content analysis of corresponding interviewee narrative. Multi-level modeling analyses indicated that social incentives were perceived more feasible, more effective, and more transportable than financial incentives, with results pervading personnel tier. Content analysis suggested the more positive perception of social incentives was most often due to expected logistical advantages, positive impacts on patient quality-of-life, and philosophical congruence among staff. Weaker perception of financial incentives was most often influenced by concerns about costs, patient dissatisfaction, and staff philosophical incongruence. Implications for CM dissemination are discussed. PMID:23506780

Undermet needs for assistance in personal activities of daily living among community-dwelling oldest old in China from 2005 to 2008.

PubMed

Peng, Rong; Wu, Bei; Ling, Li

2015-02-01

Based on the 2005 and 2008 Chinese Longitudinal Healthy Longevity Survey, this study examined the prevalence of undermet needs for assistance in personal activities of daily living (ADL) and its associated risk factors among the oldest old aged 80+. Multilevel multinomial logistic modeling was used to analyze the risk factors and changes of undermet needs over time. The results show that the prevalence of slightly undermet needs decreased in urban China from 2005 to 2008. However, the prevalence of undermet needs remained high; 50% or more for both rural and urban residents. Compared to 2005, the likelihood of having slightly undermet needs in 2008 significantly decreased by 28% among rural residents and 22% among urban residents. The common risk factors of undermet needs among rural and urban residents included financial dependence, living alone, having unwilling caregivers, more ADL disabilities, and having poor self-rated health. © The Author(s) 2014.

Children who have received no routine polio vaccines in Nigeria: Who are they and where do they live?

PubMed

Uthman, Olalekan A; Adedokun, Sulaimon T; Olukade, Tawa; Watson, Samuel; Adetokunboh, Olatunji; Adeniran, Adeyinka; Oyetoyan, Solomon A; Gidado, Saheed; Lawoko, Stephen; Wiysonge, Charles S

2017-09-02

Nigeria has made remarkable progress against polio, but 2 wild polio virus cases were reported in August 2016; putting an end to 2 y without reported cases. We examined the extent of geographical disparities in childhren not vaccinated against polio and examined individual- and community-level predictors of non-vaccination in Nigeria. We applied multilevel logistic regression models to the recent Nigeria Demographic and Health Survey. The percentage of children not routinely vaccinated against polio in Nigeria varied greatly and clustered geographically, mainly in north-eastern states, with a great risk of spread of transmission within these states and potential exportation to neighboring states and countries. Only about one-third had received all recommended 4 routine oral polio vaccine doses. Non-vaccinated children tended to have a mother who had no formal education and who was currently not working, live in poorer households and were from neighborhoods with higher maternal illiteracy rates.

Manager support for work/family issues and its impact on employee-reported pain in the extended care setting

PubMed Central

O’Donnell, Emily M.; Berkman, Lisa F.; Subramanian, Sv

2012-01-01

Objective Supervisor-level policies and the presence of a manager engaged in an employee’s need to achieve work/family balance, or “supervisory support,” may benefit employee health, including self-reported pain. Methods We conducted a census of employees at four selected extended-care facilities in the Boston metropolitan region (n= 368). Supervisory support was assessed through interviews with managers and pain was employee-reported. Results Our multilevel logistic models indicate that employees with managers who report the lowest levels of support for work/family balance experience twice as much overall pain as employees with managers who report high levels of support. Conclusions Low supervisory support for work/family balance is associated with an increased prevalence of employee-reported pain in extended-care facilities. We recommend that manager-level policies and practices receive additional attention as a potential risk factor for poor health in this setting. PMID:22892547

Neighbourhood food environments and obesity in southeast Louisiana.

PubMed

Hutchinson, Paul L; Nicholas Bodor, J; Swalm, Chris M; Rice, Janet C; Rose, Donald

2012-07-01

Supermarkets might influence food choices, and more distal outcomes like obesity, by increasing the availability of healthy foods. However, recent evidence about their effects is ambiguous, perhaps because supermarkets also increase the availability of unhealthy options. We develop an alternative measure of food environment quality that characterizes urban neighborhoods by the relative amounts of healthy (e.g. fruits and vegetables) to unhealthy foods (e.g. energy-dense snacks). Using data from 307 food stores and 1243 telephone interviews with residents in urban southeastern Louisiana, we estimate a multilevel multinomial logistic model for overweight status. We find that higher quality food environments - but not food store types - decrease the risk of obesity (RR 0.474, 95% CI 0.269-0.835) and overweight (RR 0.532, 95% CI 0.312-0.907). The findings suggest a need to move beyond a sole consideration of food store types to a more nuanced view of the food environment when planning for change. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multilevel Analysis Methods for Partially Nested Cluster Randomized Trials

ERIC Educational Resources Information Center

Sanders, Elizabeth A.

2011-01-01

This paper explores multilevel modeling approaches for 2-group randomized experiments in which a treatment condition involving clusters of individuals is compared to a control condition involving only ungrouped individuals, otherwise known as partially nested cluster randomized designs (PNCRTs). Strategies for comparing groups from a PNCRT in the…

Daily Stressors in School-Age Children: A Multilevel Approach

ERIC Educational Resources Information Center

Escobar, Milagros; Alarcón, Rafael; Blanca, María J.; Fernández-Baena, F. Javier; Rosel, Jesús F.; Trianes, María Victoria

2013-01-01

This study uses hierarchical or multilevel modeling to identify variables that contribute to daily stressors in a population of schoolchildren. Four hierarchical levels with several predictive variables were considered: student (age, sex, social adaptation of the student, number of life events and chronic stressors experienced, and educational…

Commitment to the Study of International Business and Cultural Intelligence: A Multilevel Model

ERIC Educational Resources Information Center

Ramsey, Jase R.; Barakat, Livia L.; Aad, Amine Abi

2014-01-01

Adopting a multilevel theoretical framework, we examined how metacognitive and motivational cultural intelligence influence an individual's commitment to the study of international business (IB). Data from 292 undergraduate and graduate business students nested in 12 U.S. business school classes demonstrated that individuals' metacognitive and…

Minimum Wage and Overweight and Obesity in Adult Women: A Multilevel Analysis of Low and Middle Income Countries

PubMed Central

Conklin, Annalijn I.; Ponce, Ninez A.; Frank, John; Nandi, Arijit; Heymann, Jody

2016-01-01

Objectives To describe the relationship between minimum wage and overweight and obesity across countries at different levels of development. Methods A cross-sectional analysis of 27 countries with data on the legislated minimum wage level linked to socio-demographic and anthropometry data of non-pregnant 190,892 adult women (24–49 y) from the Demographic and Health Survey. We used multilevel logistic regression models to condition on country- and individual-level potential confounders, and post-estimation of average marginal effects to calculate the adjusted prevalence difference. Results We found the association between minimum wage and overweight/obesity was independent of individual-level SES and confounders, and showed a reversed pattern by country development stage. The adjusted overweight/obesity prevalence difference in low-income countries was an average increase of about 0.1 percentage points (PD 0.075 [0.065, 0.084]), and an average decrease of 0.01 percentage points in middle-income countries (PD -0.014 [-0.019, -0.009]). The adjusted obesity prevalence difference in low-income countries was an average increase of 0.03 percentage points (PD 0.032 [0.021, 0.042]) and an average decrease of 0.03 percentage points in middle-income countries (PD -0.032 [-0.036, -0.027]). Conclusion This is among the first studies to examine the potential impact of improved wages on an important precursor of non-communicable diseases globally. Among countries with a modest level of economic development, higher minimum wage was associated with lower levels of obesity. PMID:26963247

The use of dental care facilities and oral health: a multilevel approach of schoolchildren in the Brazilian context.

PubMed

Antunes, José Leopoldo; Peres, Marco Aurélio; Jahn, Graciela Medeiros Jabôr; Levy, Bárbara Bianca da Silva

2006-01-01

To appraise the association between dental care utilisation and gingival status in the Brazilian context, controlling for covariates on socio-demographic characteristics and dentofacial anomalies (12-year-old children). A survey of oral health comprising 5780 schoolchildren in 35 towns of the state of São Paulo, Brazil, provided primary information regarding the assessment of the community periodontal index. The survey also provided information on socio-demographic characteristics and the dental aesthetic index of participants. The utilization of dental services was measured at the town-level, in terms of the dental care index (F/DMFT ratio). Multilevel models of logistic regression fitted the adjustment of covariates for gingival bleeding on probing and calculus. Almost 32% of the children examined presented unhealthy gingival conditions, with a significantly poorer profile for boys, black children and those enrolled in public schools than for their counterparts. Several dentofacial anomalies associated with unhealthy gingival status: crowding of the incisal segments, maxillary and mandibular irregularity, antero posterior molar relation, maxillary overjet and vertical anterior openbite. Towns with a higher dental care index presented a lower proportion of children with gingival bleeding and calculus. This study confirmed previous observations of boys, blacks and children enrolled in public schools as presenting poorer oral health status than their counterparts in the Brazilian context. The utilization of dental services was significantly associated with improved profile of gingival status of participating towns, and this association is unlikely to be due to insufficient control of confounding on socio-demographic characteristics and dentofacial anomalies.

Passive Suicide Ideation Among Older Adults in Europe: A Multilevel Regression Analysis of Individual and Societal Determinants in 12 Countries (SHARE).

PubMed

Stolz, Erwin; Fux, Beat; Mayerl, Hannes; Rásky, Éva; Freidl, Wolfgang

2016-09-01

Passive suicide ideation (PSI) is common among older adults, but prevalences have been reported to vary considerably across European countries. The goal of this study was to assess the role of individual-level risk factors and societal contextual factors associated with PSI in old age. We analyzed longitudinal data from the Survey of Health, Ageing, and Retirement in Europe (SHARE) on 6,791 community-dwelling respondents (75+) from 12 countries. Bayesian logistic multilevel regression models were used to assess variance components, individual-level and country-level risk factors. About 4% of the total variance of PSI was located at the country level, a third of which was attributable to compositional effects of individual-level predictors. Predictors for the development of PSI at the individual level were female gender, depression, older age, poor health, smaller social network size, loneliness, nonreligiosity, and low perceived control (R (2) = 25.8%). At the country level, cultural acceptance of suicide, religiosity, and intergenerational cohabitation were associated with the rates of PSI. Cross-national variation in old-age PSI is mostly attributable to individual-level determinants and compositional differences, but there is also evidence for contextual effects of country-level characteristics. Suicide prevention programs should be intensified in high-risk countries and attitudes toward suicide should be addressed in information campaigns. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Self-reported illness and household strategies for coping with health-care payments in Bangladesh

PubMed Central

Gilmour, Stuart; Saito, Eiko; Sultana, Papia; Shibuya, Kenji

2013-01-01

Abstract Objective To investigate self-reported illness and household strategies for coping with payments for health care in a city in Bangladesh. Methods A cluster-sampled probability survey of 1593 households in the city of Rajshahi, Bangladesh, was conducted in 2011. Multilevel logistic regression – with adjustment for any clustering within households – was used to examine the risk of self-reported illness in the previous 30 days. A multilevel Poisson regression model, with adjustment for clustering within households and individuals, was used to explore factors potentially associated with the risk of health-care-related “distress” financing (e.g. paying for health care by borrowing, selling, reducing food expenditure, removing children from school or performing additional paid work). Findings According to the interviewees, about 45% of the surveyed individuals had suffered at least one episode of illness in the previous 30 days. The most frequently reported illnesses among children younger than 5 years and adults were common tropical infections and noncommunicable diseases, respectively. The risks of self-reported illness in the previous 30 days were relatively high for adults older than 44 years, women and members of households in the poorest quintile. Distress financing, which had been implemented to cover health-care payments associated with 13% of the reported episodes, was significantly associated with heart and liver disease, asthma, typhoid, inpatient care, the use of public outpatient facilities, and poverty at the household level. Conclusion Despite the subsidization of public health services in Bangladesh, high prevalences of distress financing – and illness – were detected in the surveyed, urban households. PMID:24052682

Associations of neighborhood-level workplace violence with workers' mental distress problems: a multilevel analysis of Taiwanese employees.

PubMed

Pien, Li-Chung; Chen, Duan-Rung; Chen, Chiou-Jong; Liang, Kuei-Min; Cheng, Yawen

2015-01-01

Workplace violence is known to pose mental health risks. However, whether or not workplace violence in a surrounding area might further increase the risk of mental distress in workers has rarely been examined. The study subjects were 9,393 male and 7,716 female employees who participated in a nationwide survey in 2010. Their personal experiences of workplace violence over the past 1 year were ascertained by a standardized questionnaire. Also assessed were their psychosocial work characteristics and mental distress problems. Neighborhood-level workplace violence was computed based on aggregated data at the county level and was categorized into low-, medium-, and high-level categories. Multilevel logistic regression models were constructed to examine the associations between neighborhood-level workplace violence and individual-level mental distress problems, with adjustment of individual-level experience of workplace violence. The neighborhood-level prevalence of workplace violence ranged from 4.7 to 14.7% in men and from 6.4 to 14.8% in women across 22 counties. As compared with those who live in counties of the lowest tertile of workplace violence, female workers who lived in counties of the highest tertile of workplace violence had a 1.72-fold increased risk for mental distress problems after controlling for individual experience of workplace violence and other psychosocial work characteristics. Neighborhood-level workplace violence was associated with poor mental health in female workers. Preventative strategies targeting workplace violence should pay attention to neighborhood factors and gender-specific effects that might influence societal tolerance of abusive work practices and workers' vulnerability to mental health impacts of workplace violence.

Utilization of focused antenatal care in Zambia: examining individual- and community-level factors using a multilevel analysis.

PubMed

Chama-Chiliba, Chitalu M; Koch, Steven F

2015-02-01

We examine the individual- and community-level factors associated with the utilization of antenatal care, following the adoption of the focused antenatal care (FANC) approach in Zambia. Using the 2007 Zambia Demographic and Health Survey, linked with administrative and health facility census data, we specify two multilevel logistic models to assess the factors associated with (1) the inadequate use of antenatal care (ANC) (defined as three or fewer visits) and (2) the non-use of ANC in the first trimester of pregnancy. Although all women in the selected sample had at least one ANC visit, 40% did not have the minimum number required (four), whereas more than 80% of the initial check-ups did not occur in the first trimester. At the individual level, the woman's employment status, quality of ANC received and the husband's educational attainment are negatively associated, while parity, the household childcare burden and wealth are positively associated with inadequate utilization of ANC. Both individual- and community-level characteristics influence inadequate use and non-use of ANC in the first trimester; however, community-level factors are relatively stronger in rural areas. The results suggest that improving the content of care during ANC visits may foster adequate use of ANC and encourage early initiation of ANC visits. Furthermore, health promotion programmes need to further encourage male involvement in pregnant women's decision to seek ANC to encourage adequate use of services. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2013; all rights reserved.

Associations between physical activity and the neighbourhood social environment: baseline results from the HABITAT multilevel study.

PubMed

Rachele, Jerome N; Ghani, Fatima; Loh, Venurs H Y; Brown, Wendy J; Turrell, Gavin

2016-12-01

Limitations have arisen when measuring associations between the neighbourhood social environment and physical activity, including same-source bias, and the reliability of aggregated neighbourhood-level social environment measures. This study examines cross-sectional associations between the neighbourhood social environment (perceptions of incivilities, crime, and social cohesion) and self-reported physical activity, while accounting for same-source bias and reliability of neighbourhood-level exposure measures, using data from a large population-based clustered sample. This investigation included 11,035 residents aged 40-65years from 200 neighbourhoods in Brisbane, Australia, in 2007. Respondents self-reported their physical activity and perceptions of the social environment (neighbourhood incivilities, crime and safety, and social cohesion). Models were adjusted for individual-level education, occupation, and household income, and neighbourhood disadvantage. Exposure measures were generated via split clusters and an empirical Bayes estimation procedure. Data were analysed in 2016 using multilevel multinomial logistic regression. Residents of neighbourhoods with the highest incivilities and crime, and lowest social cohesion were reference categories. Individuals were more likely to be in the higher physical activity categories if they were in neighbourhoods with the lowest incivilities and the lowest crime. No associations were found between social cohesion and physical activity. This study provides a basis from which to gain a clearer understanding of the relationship between the neighbourhood social environment and individual physical activity. Further work is required to explore the pathways between perceptions of the neighbourhood social environment and physical activity. Copyright © 2016 Elsevier Inc. All rights reserved.

Are tuition-free primary education policies associated with lower infant and neonatal mortality in low- and middle-income countries?

PubMed

Quamruzzaman, Amm; Mendoza Rodríguez, José M; Heymann, Jody; Kaufman, Jay S; Nandi, Arijit

2014-11-01

Robust evidence from low- and middle-income countries (LMICs) suggests that maternal education is associated with better child health outcomes. However, whether or not policies aimed at increasing access to education, including tuition-free education policies, contribute to lower infant and neonatal mortality has not been empirically tested. We joined country-level data on national education policies for 37 LMICs to information on live births to young mothers aged 15-21 years, who were surveyed as part of the population-based Demographic and Health Surveys. We used propensity scores to match births to mothers who were exposed to a tuition-free primary education policy with births to mothers who were not, based on individual-level, household, and country-level characteristics, including GDP per capita, urbanization, and health expenditures per capita. Multilevel logistic regression models, fitted using generalized estimating equations, were used to estimate the effect of exposure to tuition-free primary education policies on the risk of infant and neonatal mortality. We also tested whether this effect was modified by household socioeconomic status. The propensity score matched samples for analyses of infant and neonatal mortality comprised 24,396 and 36,030 births, respectively, from 23 countries. Multilevel regression analyses showed that, on average, exposure to a tuition-free education policy was associated with 15 (95% CI=-32, 1) fewer infant and 5 (95% CI=-13, 4) fewer neonatal deaths per 1000 live births. We found no strong evidence of heterogeneity of this effect by socioeconomic level. Copyright © 2014. Published by Elsevier Ltd.

The Downside of Marketization: A Multilevel Analysis of Housing Tenure and Types in Reform-era Urban China

PubMed Central

Fu, Qiang; Zhu, Yushu; Ren, Qiang

2015-01-01

Based on data from the 2005 National Population Sample Survey and compiled covariates of 205 prefectures, this research adopted principal-component and multilevel-logistic analyses to study homeownership in urban China. Although the housing reform has severed the link between work units and residence, working in state sectors (government, state-owned enterprises and collective firms) remained significant in determining a household’s entitlement to reform-era housing with heavy subsidies or better qualities. While the prefecture-level index of marketization reduced local homeownership of self-built housing, affordable housing and privatized housing, its effect is moderated by cross-level interactions with income, education and working in state sectors across different types of housing. Meanwhile, the index of political and market connections promoted all types of homeownership except for self-built housing. By situating the downside of marketization within a context of urban transformation, this research not only challenges the teleological premise of the neoliberal market transition theory but calls for research on institutional dynamics and social consequences of urban transformation in China. PMID:25432608

Determinants of Zambian men's extra-marital sex: a multi-level analysis.

PubMed

Benefo, Kofi D

2008-08-01

Research interest in extra-marital sex has increased as scholars have become aware of its role in sustaining epidemics of STDs in sub-Saharan Africa and elsewhere. While most research has used the socioeconomic and demographic features of individuals as determinants of extra-marital sexual behavior, this study examined the role played by community characteristics. Using data from the 2003 Zambian Sexual Behavior Survey for a sample of 1,118 men aged 15-59 and multilevel logistic regression techniques, the study analyzed the effects of community social and demographic characteristics on involvement in extra-marital sex while controlling for the men's individual-level characteristics. Men's involvement in extra-marital sex was found to vary with the characteristics of communities. The chances of men's involvement in extra-marital sex increased with community-level ethnic heterogeneity and urbanization, decreased in commercial centers, and in communities with a demographic surplus of males, health workers active in AIDS prevention, and access to the mass media. These results show that scholars trying to understand the motivations for extra-marital sex must pay attention to the characteristics of both individuals and communities.

The downside of marketization: a multilevel analysis of housing tenure and types in reform-era urban China.

PubMed

Fu, Qiang; Zhu, Yushu; Ren, Qiang

2015-01-01

Based on data from the 2005 National Population Sample Survey and compiled covariates of 205 prefectures, this research adopted principal-component and multilevel-logistic analyses to study homeownership in urban China. Although the housing reform has severed the link between work units and residence, working in state sectors (government, state-owned enterprises and collective firms) remained significant in determining a household's entitlement to reform-era housing with heavy subsidies or better qualities. While the prefecture-level index of marketization reduced local homeownership of self-built housing, affordable housing and privatized housing, its effect is moderated by cross-level interactions with income, education and working in state sectors across different types of housing. Meanwhile, the index of political and market connections promoted all types of homeownership except for self-built housing. By situating the downside of marketization within a context of urban transformation, this research not only challenges the teleological premise of the neoliberal market transition theory but calls for research on institutional dynamics and social consequences of urban transformation in China. Copyright © 2014 Elsevier Inc. All rights reserved.

Deconvolution of mixing time series on a graph

PubMed Central

Blocker, Alexander W.; Airoldi, Edoardo M.

2013-01-01

In many applications we are interested in making inference on latent time series from indirect measurements, which are often low-dimensional projections resulting from mixing or aggregation. Positron emission tomography, super-resolution, and network traffic monitoring are some examples. Inference in such settings requires solving a sequence of ill-posed inverse problems, yt = Axt, where the projection mechanism provides information on A. We consider problems in which A specifies mixing on a graph of times series that are bursty and sparse. We develop a multilevel state-space model for mixing times series and an efficient approach to inference. A simple model is used to calibrate regularization parameters that lead to efficient inference in the multilevel state-space model. We apply this method to the problem of estimating point-to-point traffic flows on a network from aggregate measurements. Our solution outperforms existing methods for this problem, and our two-stage approach suggests an efficient inference strategy for multilevel models of multivariate time series. PMID:25309135

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

PubMed Central

Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems. PMID:27187178

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

PubMed

Pârvu, Ovidiu; Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems.

Multi-level manual and autonomous control superposition for intelligent telerobot

NASA Technical Reports Server (NTRS)

Hirai, Shigeoki; Sato, T.

1989-01-01

Space telerobots are recognized to require cooperation with human operators in various ways. Multi-level manual and autonomous control superposition in telerobot task execution is described. The object model, the structured master-slave manipulation system, and the motion understanding system are proposed to realize the concept. The object model offers interfaces for task level and object level human intervention. The structured master-slave manipulation system offers interfaces for motion level human intervention. The motion understanding system maintains the consistency of the knowledge through all the levels which supports the robot autonomy while accepting the human intervention. The superposing execution of the teleoperational task at multi-levels realizes intuitive and robust task execution for wide variety of objects and in changeful environment. The performance of several examples of operating chemical apparatuses is shown.

Extending the Multi-level Method for the Simulation of Stochastic Biological Systems.

PubMed

Lester, Christopher; Baker, Ruth E; Giles, Michael B; Yates, Christian A

2016-08-01

The multi-level method for discrete-state systems, first introduced by Anderson and Higham (SIAM Multiscale Model Simul 10(1):146-179, 2012), is a highly efficient simulation technique that can be used to elucidate statistical characteristics of biochemical reaction networks. A single point estimator is produced in a cost-effective manner by combining a number of estimators of differing accuracy in a telescoping sum, and, as such, the method has the potential to revolutionise the field of stochastic simulation. In this paper, we present several refinements of the multi-level method which render it easier to understand and implement, and also more efficient. Given the substantial and complex nature of the multi-level method, the first part of this work reviews existing literature, with the aim of providing a practical guide to the use of the multi-level method. The second part provides the means for a deft implementation of the technique and concludes with a discussion of a number of open problems.

Multi-level Hierarchical Poly Tree computer architectures

NASA Technical Reports Server (NTRS)

Padovan, Joe; Gute, Doug

1990-01-01

Based on the concept of hierarchical substructuring, this paper develops an optimal multi-level Hierarchical Poly Tree (HPT) parallel computer architecture scheme which is applicable to the solution of finite element and difference simulations. Emphasis is given to minimizing computational effort, in-core/out-of-core memory requirements, and the data transfer between processors. In addition, a simplified communications network that reduces the number of I/O channels between processors is presented. HPT configurations that yield optimal superlinearities are also demonstrated. Moreover, to generalize the scope of applicability, special attention is given to developing: (1) multi-level reduction trees which provide an orderly/optimal procedure by which model densification/simplification can be achieved, as well as (2) methodologies enabling processor grading that yields architectures with varying types of multi-level granularity.

Familial and Religious Influences on Adolescent Alcohol Use: A Multi-Level Study of Students and School Communities

ERIC Educational Resources Information Center

Bjarnason, Thoroddur; Thorlindsson, Thorolfur; Sigfusdottir, Inga D.; Welch, Michael R.

2005-01-01

A multi-level Durkheimian theory of familial and religious influences on adolescent alcohol use is developed and tested with hierarchical linear modeling of data from Icelandic schools and students. On the individual level, traditional family structure, parental monitoring, parental support, religious participation, and perceptions of divine…

Help Seeking in Online Collaborative Groupwork: A Multilevel Analysis

ERIC Educational Resources Information Center

Du, Jianxia; Xu, Jianzhong; Fan, Xitao

2015-01-01

This study examined predictive models for students' help seeking in the context of online collaborative groupwork. Results from multilevel analysis revealed that most of the variance in help seeking was at the individual student level, and multiple variables at the individual level were predictive of help-seeking behaviour. Help seeking was…

A Multi-Level Examination of College and Its Influence on Ecumenical Worldview Development

ERIC Educational Resources Information Center

Mayhew, Matthew J.

2012-01-01

This multi-level, longitudinal study investigated the ecumenical worldview development of 13,932 students enrolled in one of 126 institutions. Results indicated that the final hierarchical linear model, consisting of institution-and-student-level predictors as well as slopes explaining the relationships among some of these predictors, explained…

Managing Money in Marriage: Multilevel and Cross-National Effects of the Breadwinner Role

ERIC Educational Resources Information Center

Yodanis, Carrie; Lauer, Sean

2007-01-01

We examine whether institutionalized practices and beliefs regarding breadwinning roles are associated with the choice of more or less equal money management strategies in marriage. Using cross-national data from 21 country contexts in the International Social Survey Programme and multilevel modeling, we find that in contexts of shared…

A Multilevel Evaluation of a Comprehensive Child Abuse Prevention Program

ERIC Educational Resources Information Center

Lawson, Michael A.; Alameda-Lawson, Tania; Byrnes, Edward C.

2012-01-01

Objectives: The purpose of this study is to examine the extent to which participation in a county-wide prevention program leads to improvements in protective factors associated with child abuse prevention (CAP) and whether improvements in measured protective factors relate to decreased odds of child abuse. Method: Using multilevel growth modeling,…

Multilevel Exploration of Factors Contributing to the Overrepresentation of Black Students in Office Disciplinary Referrals

ERIC Educational Resources Information Center

Bradshaw, Catherine P.; Mitchell, Mary M.; O'Brennan, Lindsey M.; Leaf, Philip J.

2010-01-01

Although there is increasing awareness of the overrepresentation of ethic minority students--particularly Black students--in disciplinary actions, the extant research has rarely empirically examined potential factors that may contribute to these disparities. The current study used a multilevel modeling approach to examine factors at the child…

Multiple Imputation of Multilevel Missing Data-Rigor versus Simplicity

ERIC Educational Resources Information Center

Drechsler, Jörg

2015-01-01

Multiple imputation is widely accepted as the method of choice to address item-nonresponse in surveys. However, research on imputation strategies for the hierarchical structures that are typically found in the data in educational contexts is still limited. While a multilevel imputation model should be preferred from a theoretical point of view if…

"Using Power Tables to Compute Statistical Power in Multilevel Experimental Designs"

ERIC Educational Resources Information Center

Konstantopoulos, Spyros

2009-01-01

Power computations for one-level experimental designs that assume simple random samples are greatly facilitated by power tables such as those presented in Cohen's book about statistical power analysis. However, in education and the social sciences experimental designs have naturally nested structures and multilevel models are needed to compute the…

Pre- and Postnatal Women's Leisure Time Physical Activity Patterns: A Multilevel Longitudinal Analysis

ERIC Educational Resources Information Center

Cramp, Anita G.; Bray, Steven R.

2009-01-01

The purpose of this study was to examine women's leisure time physical activity (LTPA) before pregnancy, during pregnancy, and through the first 7 months postnatal. Pre- and postnatal women (n = 309) completed the 12-month Modifiable Activity Questionnaire and demographic information. Multilevel modeling was used to estimate a growth curve…

Does the Organization Matter? A Multilevel Analysis of Organizational Effects in Homeless Service Innovations

ERIC Educational Resources Information Center

Cronley, Courtney; Patterson, David A.

2012-01-01

This study examined the effects of organizational culture on staff members' use of management information systems ("N" = 142) within homeless service organizations ("N" = 24), using a multilevel model. The Organizational Social Context Questionnaire was used to measure organizational culture, defined by three sub-constructs: (1) proficiency, (2)…

Identifying Synergies in Multilevel Interventions: The Convergence Strategy

ERIC Educational Resources Information Center

Lewis, Megan A.; Fitzgerald, Tania M.; Zulkiewicz, Brittany; Peinado, Susana; Williams, Pamela A.

2017-01-01

Social ecological models of health often describe multiple levels of influence that interact to influence health. However, it is still common for interventions to target only one or two of these levels, perhaps owing in part to a lack of guidance on how to design multilevel interventions to achieve optimal impact. The convergence strategy…

What affects response rates in primary healthcare-based programmes? An analysis of individual and unit-related factors associated with increased odds of non-response based on HCV screening in the general population in Poland

PubMed Central

Parda, Natalia; Stępień, Małgorzata; Zakrzewska, Karolina; Madaliński, Kazimierz; Kołakowska, Agnieszka; Godzik, Paulina; Rosińska, Magdalena

2016-01-01

Objectives Response rate in public health programmes may be a limiting factor. It is important to first consider their delivery and acceptability for the target. This study aimed at determining individual and unit-related factors associated with increased odds of non-response based on hepatitis C virus screening in primary healthcare. Design Primary healthcare units (PHCUs) were extracted from the Register of Health Care Centres. Each of the PHCUs was to enrol adult patients selected on a random basis. Data on the recruitment of PHCUs and patients were analysed. Multilevel modelling was applied to investigate individual and unit-related factors associated with non-response. Multilevel logistic model was developed with fixed effects and only a random intercept for the unit. Preliminary analysis included a random effect for unit and each of the individual or PHCU covariates separately. For each of the PHCU covariates, we applied a two-level model with individual covariates, unit random effect and a single fixed effect of this unit covariate. Setting This study was conducted in primary care units in selected provinces in Poland. Participants A total of 242 PHCUs and 24 480 adults were invited. Of them, 44 PHCUs and 20 939 patients agreed to participate. Both PHCUs and patients were randomly selected. Results Data on 44 PHCUs and 24 480 patients were analysed. PHCU-level factors and recruitment strategies were important predictors of non-response. Unit random effect was significant in all models. Larger and private units reported higher non-response rates, while for those with a history of running public health programmes the odds of non-response was lower. Proactive recruitment, more working hours devoted to the project and patient resulted in higher acceptance of the project. Higher number of personnel had no such effect. Conclusions Prior to the implementation of public health programme, several factors that could hinder its execution should be addressed. PMID:27927665

What affects response rates in primary healthcare-based programmes? An analysis of individual and unit-related factors associated with increased odds of non-response based on HCV screening in the general population in Poland.

PubMed

Parda, Natalia; Stępień, Małgorzata; Zakrzewska, Karolina; Madaliński, Kazimierz; Kołakowska, Agnieszka; Godzik, Paulina; Rosińska, Magdalena

2016-12-07

Response rate in public health programmes may be a limiting factor. It is important to first consider their delivery and acceptability for the target. This study aimed at determining individual and unit-related factors associated with increased odds of non-response based on hepatitis C virus screening in primary healthcare. Primary healthcare units (PHCUs) were extracted from the Register of Health Care Centres. Each of the PHCUs was to enrol adult patients selected on a random basis. Data on the recruitment of PHCUs and patients were analysed. Multilevel modelling was applied to investigate individual and unit-related factors associated with non-response. Multilevel logistic model was developed with fixed effects and only a random intercept for the unit. Preliminary analysis included a random effect for unit and each of the individual or PHCU covariates separately. For each of the PHCU covariates, we applied a two-level model with individual covariates, unit random effect and a single fixed effect of this unit covariate. This study was conducted in primary care units in selected provinces in Poland. A total of 242 PHCUs and 24 480 adults were invited. Of them, 44 PHCUs and 20 939 patients agreed to participate. Both PHCUs and patients were randomly selected. Data on 44 PHCUs and 24 480 patients were analysed. PHCU-level factors and recruitment strategies were important predictors of non-response. Unit random effect was significant in all models. Larger and private units reported higher non-response rates, while for those with a history of running public health programmes the odds of non-response was lower. Proactive recruitment, more working hours devoted to the project and patient resulted in higher acceptance of the project. Higher number of personnel had no such effect. Prior to the implementation of public health programme, several factors that could hinder its execution should be addressed. 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/.

Vaccine coverage and determinants of incomplete vaccination in children aged 12-23 months in Dschang, West Region, Cameroon: a cross-sectional survey during a polio outbreak.

PubMed

Russo, Gianluca; Miglietta, Alessandro; Pezzotti, Patrizio; Biguioh, Rodrigue Mabvouna; Bouting Mayaka, Georges; Sobze, Martin Sanou; Stefanelli, Paola; Vullo, Vincenzo; Rezza, Giovanni

2015-07-10

Inadequate immunization coverage with increased risk of vaccine preventable diseases outbreaks remains a problem in Africa. Moreover, different factors contribute to incomplete vaccination status. This study was performed in Dschang (West Region, Cameroon), during the polio outbreak occurred in October 2013, in order to estimate the immunization coverage among children aged 12-23 months, to identify determinants for incomplete vaccination status and to assess the risk of poliovirus spread in the study population. A cross-sectional household survey was conducted in November-December 2013, using the WHO two-stage sampling design. An interviewer-administered questionnaire was used to obtain information from consenting parents of children aged 12-23 months. Vaccination coverage was assessed by vaccination card and parents' recall. Chi-square test and multilevel logistic regression model were used to identify the determinants of incomplete immunization status. Statistical significance was set at p < 0.05. Overall, 3248 households were visited and 502 children were enrolled. Complete immunization coverage was 85.9% and 84.5%, according to card plus parents' recall and card only, respectively. All children had received at least one routine vaccination, the OPV-3 (Oral Polio Vaccine) coverage was >90%, and 73.4% children completed the recommended vaccinations before 1-year of age. In the final multilevel logistic regression model, factors significantly associated with incomplete immunization status were: retention of immunization card (AOR: 7.89; 95% CI: 1.08-57.37), lower mothers' utilization of antenatal care (ANC) services (AOR:1.25; 95% CI: 1.07-63.75), being the ≥ 3(rd) born child in the family (AOR: 425.4; 95% CI: 9.6-18,808), younger mothers' age (AOR: 49.55; 95% CI: 1.59-1544), parents' negative attitude towards immunization (AOR: 20.2; 95% CI: 1.46-278.9), and poorer parents' exposure to information on vaccination (AOR: 28.07; 95 % CI: 2.26-348.1). Longer distance from the vaccination centers was marginally significant (p = 0.05). Vaccination coverage was high; however, 1 out of 7 children was partially vaccinated, and 1 out of 4 did not complete timely the recommended vaccinations. In order to improve the immunization coverage, it is necessary to strengthen ANC services, and to improve parents' information and attitude towards immunization, targeting younger parents and families living far away from vaccination centers, using appropriate communication strategies. Finally, the estimated OPV-3 coverage is reassuring in relation to the ongoing polio outbreak.

Assessing variance components in multilevel linear models using approximate Bayes factors: A case study of ethnic disparities in birthweight

PubMed Central

Saville, Benjamin R.; Herring, Amy H.; Kaufman, Jay S.

2013-01-01

Racial/ethnic disparities in birthweight are a large source of differential morbidity and mortality worldwide and have remained largely unexplained in epidemiologic models. We assess the impact of maternal ancestry and census tract residence on infant birth weights in New York City and the modifying effects of race and nativity by incorporating random effects in a multilevel linear model. Evaluating the significance of these predictors involves the test of whether the variances of the random effects are equal to zero. This is problematic because the null hypothesis lies on the boundary of the parameter space. We generalize an approach for assessing random effects in the two-level linear model to a broader class of multilevel linear models by scaling the random effects to the residual variance and introducing parameters that control the relative contribution of the random effects. After integrating over the random effects and variance components, the resulting integrals needed to calculate the Bayes factor can be efficiently approximated with Laplace’s method. PMID:24082430

Measures of clustering and heterogeneity in multilevel Poisson regression analyses of rates/count data

PubMed Central

Austin, Peter C.; Stryhn, Henrik; Leckie, George; Merlo, Juan

2017-01-01

Multilevel data occur frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models. These models incorporate cluster‐specific random effects that allow one to partition the total variation in the outcome into between‐cluster variation and between‐individual variation. The magnitude of the effect of clustering provides a measure of the general contextual effect. When outcomes are binary or time‐to‐event in nature, the general contextual effect can be quantified by measures of heterogeneity like the median odds ratio or the median hazard ratio, respectively, which can be calculated from a multilevel regression model. Outcomes that are integer counts denoting the number of times that an event occurred are common in epidemiological and medical research. The median (incidence) rate ratio in multilevel Poisson regression for counts that corresponds to the median odds ratio or median hazard ratio for binary or time‐to‐event outcomes respectively is relatively unknown and is rarely used. The median rate ratio is the median relative change in the rate of the occurrence of the event when comparing identical subjects from 2 randomly selected different clusters that are ordered by rate. We also describe how the variance partition coefficient, which denotes the proportion of the variation in the outcome that is attributable to between‐cluster differences, can be computed with count outcomes. We illustrate the application and interpretation of these measures in a case study analyzing the rate of hospital readmission in patients discharged from hospital with a diagnosis of heart failure. PMID:29114926

Multilevel Optimization Framework for Hierarchical Stiffened Shells Accelerated by Adaptive Equivalent Strategy

NASA Astrophysics Data System (ADS)

Wang, Bo; Tian, Kuo; Zhao, Haixin; Hao, Peng; Zhu, Tianyu; Zhang, Ke; Ma, Yunlong

2017-06-01

In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy.

Contextual effects and cancer outcomes in the United States: a systematic review of characteristics in multilevel analyses.

PubMed

Zahnd, Whitney E; McLafferty, Sara L

2017-11-01

There is increasing call for the utilization of multilevel modeling to explore the relationship between place-based contextual effects and cancer outcomes in the United States. To gain a better understanding of how contextual factors are being considered, we performed a systematic review. We reviewed studies published between January 1, 2002 and December 31, 2016 and assessed the following attributes: (1) contextual considerations such as geographic scale and contextual factors used; (2) methods used to quantify contextual factors; and (3) cancer type and outcomes. We searched PubMed, Scopus, and Web of Science and initially identified 1060 studies. One hundred twenty-two studies remained after exclusions. Most studies utilized a two-level structure; census tracts were the most commonly used geographic scale. Socioeconomic factors, health care access, racial/ethnic factors, and rural-urban status were the most common contextual factors addressed in multilevel models. Breast and colorectal cancers were the most common cancer types, and screening and staging were the most common outcomes assessed in these studies. Opportunities for future research include deriving contextual factors using more rigorous approaches, considering cross-classified structures and cross-level interactions, and using multilevel modeling to explore understudied cancers and outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.

To center or not to center? Investigating inertia with a multilevel autoregressive model.

PubMed

Hamaker, Ellen L; Grasman, Raoul P P P

2014-01-01

Whether level 1 predictors should be centered per cluster has received considerable attention in the multilevel literature. While most agree that there is no one preferred approach, it has also been argued that cluster mean centering is desirable when the within-cluster slope and the between-cluster slope are expected to deviate, and the main interest is in the within-cluster slope. However, we show in a series of simulations that if one has a multilevel autoregressive model in which the level 1 predictor is the lagged outcome variable (i.e., the outcome variable at the previous occasion), cluster mean centering will in general lead to a downward bias in the parameter estimate of the within-cluster slope (i.e., the autoregressive relationship). This is particularly relevant if the main question is whether there is on average an autoregressive effect. Nonetheless, we show that if the main interest is in estimating the effect of a level 2 predictor on the autoregressive parameter (i.e., a cross-level interaction), cluster mean centering should be preferred over other forms of centering. Hence, researchers should be clear on what is considered the main goal of their study, and base their choice of centering method on this when using a multilevel autoregressive model.

To center or not to center? Investigating inertia with a multilevel autoregressive model

PubMed Central

Hamaker, Ellen L.; Grasman, Raoul P. P. P.

2015-01-01

Whether level 1 predictors should be centered per cluster has received considerable attention in the multilevel literature. While most agree that there is no one preferred approach, it has also been argued that cluster mean centering is desirable when the within-cluster slope and the between-cluster slope are expected to deviate, and the main interest is in the within-cluster slope. However, we show in a series of simulations that if one has a multilevel autoregressive model in which the level 1 predictor is the lagged outcome variable (i.e., the outcome variable at the previous occasion), cluster mean centering will in general lead to a downward bias in the parameter estimate of the within-cluster slope (i.e., the autoregressive relationship). This is particularly relevant if the main question is whether there is on average an autoregressive effect. Nonetheless, we show that if the main interest is in estimating the effect of a level 2 predictor on the autoregressive parameter (i.e., a cross-level interaction), cluster mean centering should be preferred over other forms of centering. Hence, researchers should be clear on what is considered the main goal of their study, and base their choice of centering method on this when using a multilevel autoregressive model. PMID:25688215

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications

PubMed Central

Austin, Peter C.

2017-01-01

Summary Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log–log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata). PMID:29307954

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications.

PubMed

Austin, Peter C

2017-08-01

Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log-log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata).

Exploring the impact of different multi-level measures of physician communities in patient-centric care networks on healthcare outcomes: A multi-level regression approach.

PubMed

Uddin, Shahadat

2016-02-04

A patient-centric care network can be defined as a network among a group of healthcare professionals who provide treatments to common patients. Various multi-level attributes of the members of this network have substantial influence to its perceived level of performance. In order to assess the impact different multi-level attributes of patient-centric care networks on healthcare outcomes, this study first captured patient-centric care networks for 85 hospitals using health insurance claim dataset. From these networks, this study then constructed physician collaboration networks based on the concept of patient-sharing network among physicians. A multi-level regression model was then developed to explore the impact of different attributes that are organised at two levels on hospitalisation cost and hospital length of stay. For Level-1 model, the average visit per physician significantly predicted both hospitalisation cost and hospital length of stay. The number of different physicians significantly predicted only the hospitalisation cost, which has significantly been moderated by age, gender and Comorbidity score of patients. All Level-1 findings showed significance variance across physician collaboration networks having different community structure and density. These findings could be utilised as a reflective measure by healthcare decision makers. Moreover, healthcare managers could consider them in developing effective healthcare environments.

mlCAF: Multi-Level Cross-Domain Semantic Context Fusioning for Behavior Identification.

PubMed

Razzaq, Muhammad Asif; Villalonga, Claudia; Lee, Sungyoung; Akhtar, Usman; Ali, Maqbool; Kim, Eun-Soo; Khattak, Asad Masood; Seung, Hyonwoo; Hur, Taeho; Bang, Jaehun; Kim, Dohyeong; Ali Khan, Wajahat

2017-10-24

The emerging research on automatic identification of user's contexts from the cross-domain environment in ubiquitous and pervasive computing systems has proved to be successful. Monitoring the diversified user's contexts and behaviors can help in controlling lifestyle associated to chronic diseases using context-aware applications. However, availability of cross-domain heterogeneous contexts provides a challenging opportunity for their fusion to obtain abstract information for further analysis. This work demonstrates extension of our previous work from a single domain (i.e., physical activity) to multiple domains (physical activity, nutrition and clinical) for context-awareness. We propose multi-level Context-aware Framework (mlCAF), which fuses the multi-level cross-domain contexts in order to arbitrate richer behavioral contexts. This work explicitly focuses on key challenges linked to multi-level context modeling, reasoning and fusioning based on the mlCAF open-source ontology. More specifically, it addresses the interpretation of contexts from three different domains, their fusioning conforming to richer contextual information. This paper contributes in terms of ontology evolution with additional domains, context definitions, rules and inclusion of semantic queries. For the framework evaluation, multi-level cross-domain contexts collected from 20 users were used to ascertain abstract contexts, which served as basis for behavior modeling and lifestyle identification. The experimental results indicate a context recognition average accuracy of around 92.65% for the collected cross-domain contexts.

mlCAF: Multi-Level Cross-Domain Semantic Context Fusioning for Behavior Identification

PubMed Central

Villalonga, Claudia; Lee, Sungyoung; Akhtar, Usman; Ali, Maqbool; Kim, Eun-Soo; Khattak, Asad Masood; Seung, Hyonwoo; Hur, Taeho; Kim, Dohyeong; Ali Khan, Wajahat

2017-01-01

The emerging research on automatic identification of user’s contexts from the cross-domain environment in ubiquitous and pervasive computing systems has proved to be successful. Monitoring the diversified user’s contexts and behaviors can help in controlling lifestyle associated to chronic diseases using context-aware applications. However, availability of cross-domain heterogeneous contexts provides a challenging opportunity for their fusion to obtain abstract information for further analysis. This work demonstrates extension of our previous work from a single domain (i.e., physical activity) to multiple domains (physical activity, nutrition and clinical) for context-awareness. We propose multi-level Context-aware Framework (mlCAF), which fuses the multi-level cross-domain contexts in order to arbitrate richer behavioral contexts. This work explicitly focuses on key challenges linked to multi-level context modeling, reasoning and fusioning based on the mlCAF open-source ontology. More specifically, it addresses the interpretation of contexts from three different domains, their fusioning conforming to richer contextual information. This paper contributes in terms of ontology evolution with additional domains, context definitions, rules and inclusion of semantic queries. For the framework evaluation, multi-level cross-domain contexts collected from 20 users were used to ascertain abstract contexts, which served as basis for behavior modeling and lifestyle identification. The experimental results indicate a context recognition average accuracy of around 92.65% for the collected cross-domain contexts. PMID:29064459

Health risk factors as predictors of workers' compensation claim occurrence and cost

PubMed Central

Schwatka, Natalie V; Atherly, Adam; Dally, Miranda J; Fang, Hai; vS Brockbank, Claire; Tenney, Liliana; Goetzel, Ron Z; Jinnett, Kimberly; Witter, Roxana; Reynolds, Stephen; McMillen, James; Newman, Lee S

2017-01-01

Objective The objective of this study was to examine the predictive relationships between employee health risk factors (HRFs) and workers' compensation (WC) claim occurrence and costs. Methods Logistic regression and generalised linear models were used to estimate the predictive association between HRFs and claim occurrence and cost among a cohort of 16 926 employees from 314 large, medium and small businesses across multiple industries. First, unadjusted (HRFs only) models were estimated, and second, adjusted (HRFs plus demographic and work organisation variables) were estimated. Results Unadjusted models demonstrated that several HRFs were predictive of WC claim occurrence and cost. After adjusting for demographic and work organisation differences between employees, many of the relationships previously established did not achieve statistical significance. Stress was the only HRF to display a consistent relationship with claim occurrence, though the type of stress mattered. Stress at work was marginally predictive of a higher odds of incurring a WC claim (p<0.10). Stress at home and stress over finances were predictive of higher and lower costs of claims, respectively (p<0.05). Conclusions The unadjusted model results indicate that HRFs are predictive of future WC claims. However, the disparate findings between unadjusted and adjusted models indicate that future research is needed to examine the multilevel relationship between employee demographics, organisational factors, HRFs and WC claims. PMID:27530688

Do Robotic Surgical Systems Improve Profit Margins? A Cross-Sectional Analysis of California Hospitals.

PubMed

Shih, Ya-Chen Tina; Shen, Chan; Hu, Jim C

2017-09-01

The aim of this study was to examine the association between ownership of robotic surgical systems and hospital profit margins. This study used hospital annual utilization data, annual financial data, and discharge data for year 2011 from the California Office of Statewide Health Planning and Development. We first performed bivariate analysis to compare mean profit margin by hospital and market characteristics and to examine whether these characteristics differed between hospitals that had one or more robotic surgical systems in 2011 and those that did not. We applied the t test and the F test to compare mean profit margin between two groups and among three or more groups, respectively. We then conducted multilevel logistic regression to determine the association between ownership of robotic surgical systems and having a positive profit margin after controlling for other hospital and market characteristics and accounting for possible correlation among hospitals located within the same market. The study sample included 167 California hospitals with valid financial information. Hospitals with robotic surgical systems tended to report more favorable profit margins. However, multilevel logistic regression showed that this relationship (an association, not causality) became only marginally significant (odds ratio [OR] = 6.2; P = 0.053) after controlling for other hospital characteristics, such as ownership type, teaching status, bed size, and surgical volumes, and market characteristics, such as total number of robotic surgical systems owned by other hospitals in the same market area. As robotic surgical systems become widely disseminated, hospital decision makers should carefully evaluate the financial and clinical implications before making a capital investment in this technology. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Institutional delivery in India, 2004-14: unravelling the equity-enhancing contributions of the public sector.

PubMed

Joe, William; Perkins, Jessica M; Kumar, Saroj; Rajpal, Sunil; Subramanian, S V

2018-06-01

To achieve faster and equitable improvements in maternal and child health outcomes, the government of India launched the National Rural Health Mission in 2005. This paper describes the equity-enhancing role of the public sector in increasing use of institutional delivery care services in India between 2004 and 2014. Information on 24 661 births from nationally representative survey data for 2004 and 2014 is analysed. Concentration index is computed to describe socioeconomic-rank-related relative inequalities in institutional delivery and decomposition is used to assess the contributions of public and private sectors in overall socioeconomic inequality. Multilevel logistic regression is applied to examine the changes in socioeconomic gradient between 2004 and 2014. The analysis finds that utilization of institutional delivery care in India increased from 43% in 2004 to 83% in 2014. The bulk of the increase was in public sector use (21% in 2004 to 53% in 2014) with a modest increase in private sector use (22% in 2004 to 30% in 2014). The shift from a pro-rich to pro-poor distribution of public sector use is confirmed. Decomposition analysis indicates that 51% of these reductions in socioeconomic inequality are associated with improved pro-poor distribution of public sector births. Multilevel logistic regressions confirm the disappearance of a wealth-based gradient in public sector births between 2004 and 2014. We conclude that public health investments in India have significantly contributed towards an equitable increase in the coverage of institutional delivery care. Sustained policy efforts are necessary, however, with an emphasis on education, sociocultural and geographical factors to ensure universal coverage of institutional delivery care services in India.

Do counselor techniques predict quitting during smoking cessation treatment? A component analysis of telephone-delivered Acceptance and Commitment Therapy

PubMed Central

Vilardaga, Roger; Heffner, Jaimee L.; Mercer, Laina D.; Bricker, Jonathan

2014-01-01

No studies to date have examined the effect of counselor techniques on smoking cessation over the course of treatment. To address this gap, we examined the degree to which the use of specific Acceptance and Commitment Therapy (ACT) counseling techniques in a given session predicted smoking cessation reported at the next session. The data came from the ACT arm of a randomized controlled trial of a telephone-delivered smoking cessation intervention. Trained raters coded 139 counseling sessions across 44 participants. The openness, awareness and activation components of the ACT model were rated for each telephone counseling session. Multilevel logistic regression models were used to estimate the predictive relationship between each component during any given telephone session and smoking cessation at the following telephone session. For every 1-unit increase in counselors’ use of openness and awareness techniques there were 42% and 52% decreases in the odds of smoking at the next counseling session, respectively. However, there was no significant predictive relationship between counselors’ use of activation techniques and smoking cessation. Overall, results highlight the theoretical and clinical value of examining therapists’ techniques as predictors of outcome during the course of treatment. PMID:25156397

Association Between Neighborhood-Level Smoking and Individual Smoking Risk: Maternal Smoking Among Latina Women in Pennsylvania.

PubMed

Chesnokova, Arina; French, Benjamin; Weibe, Douglas; Camenga, Deepa R; Yun, Katherine

2015-01-01

We examined whether or not high maternal smoking rates at the neighborhood level increase the likelihood of individual smoking by Latina women in the three months prior to and during pregnancy, independent of other individual and neighborhood factors. This study was observational in nature, using linked vital statistics records for 24,443 Latina women in Pennsylvania (2009-2010) and U.S. Census data for 2,398 census tracts. We used multilevel logistic regression models to determine the individual odds of self-reported maternal smoking given different census tract-level rates of maternal smoking in the previous three years (2006-2008), adjusting for maternal and census-tract characteristics, including ethnic density, population density, and poverty. Higher levels of maternal smoking at the census-tract level were associated with increased individual odds of smoking among Latina mothers. In the fully adjusted model, a 10% increase in the neighborhood smoking rate was associated with a 1.28 (95% confidence interval 1.22, 1.34) increase in the individual odds of smoking. Latina women living in census tracts where more women have smoked during or immediately prior to pregnancy are themselves at higher risk of smoking during this period.

The influence of the social environment on youth smoking status.

PubMed

Bellatorre, Anna; Choi, Kelvin; Bernat, Debra

2015-12-01

Youth smoking is complex with multilevel influences. While much is known about certain levels of influence on youth smoking, the lack of focus on institutional influences is notable. This study evaluated the effects of ambient smoking attitudes and behaviors in schools on individual youth smoking. Data from the 2012 Florida Youth Tobacco Survey (n=67,460) were analyzed. Multinomial logistic regression was used to investigate individual and aggregated school-level factors that were associated with a youth being classified as a "susceptible nonsmoker" (SN) or "current smoker" (CS) relative to a "non-susceptible nonsmoker" (NN). The aggregated percentage of regular smokers at a school, ambient school level positive smoking perceptions, and the standardized difference between individual and school-level positive smoking perceptions were statistically significant in the fully adjusted model. We also found an increased risk of being a SN relative to a NN for Hispanic youth. Moreover, our approach to modeling institutional-level factors raised the pseudo r-squared from 0.05 to 0.14. These findings suggest the importance of ambient smoking attitudes and behaviors on youth smoking. Prevention efforts affecting ambient smoking attitudes may be beneficial. Published by Elsevier Inc.

Sexual-orientation disparities in school: the mediational role of indicators of victimization in achievement and truancy because of feeling unsafe.

PubMed

Birkett, Michelle; Russell, Stephen T; Corliss, Heather L

2014-06-01

We examined sexual-orientation identity disparities in truancy and academic achievement, and the mediational role of victimization in a large high-school sample. We utilized pooled data, measuring sexual identity, from the 2005 and 2007 Youth Risk Behavioral Surveillance System Surveys. Multilevel logistic regression modeling estimated the odds of low grades and truancy because of feeling unsafe comparing lesbian/gay, bisexual, (LGB) and unsure students to heterosexuals. We stratified models by gender. Indicators of victimization were examined to mediate the relationship between identifying as a sexual minority and school achievement or truancy. LGB-identified youths reported significantly elevated odds of truancy and low grades (odds ratios = 1.6-3.2; all P < .05). Additionally, both genders noting uncertainty about their sexual identity showed increased odds of truancy. Victimization indicators mediated the relationship between identifying as a sexual minority and experiencing negative school outcomes, with greater victimization indicators being associated with increased truancy and lower grades, and the extent of mediation differed by gender. As early disparities in academic achievement and school engagement have indicated a lifetime of increased health and behavioral risk factors, early intervention targeting school victimization is necessary.

Psychosocial work factors and long sickness absence in Europe.

PubMed

Slany, Corinna; Schütte, Stefanie; Chastang, Jean-François; Parent-Thirion, Agnès; Vermeylen, Greet; Niedhammer, Isabelle

2014-01-01

Studies exploring a wide range of psychosocial work factors separately and together in association with long sickness absence are still lacking. The objective of this study was to explore the associations between psychosocial work factors measured following a comprehensive instrument (Copenhagen psychosocial questionnaire, COPSOQ) and long sickness absence (> 7 days/year) in European employees of 34 countries. An additional objective was to study the differences in these associations according to gender and countries. The study population consisted of 16 120 male and 16 588 female employees from the 2010 European working conditions survey. Twenty-five psychosocial work factors were explored. Statistical analysis was performed using multilevel logistic regression models and interaction testing. When studied together in the same model, factors related to job demands (quantitative demands and demands for hiding emotions), possibilities for development, social relationships (role conflicts, quality of leadership, social support, and sense of community), workplace violence (physical violence, bullying, and discrimination), shift work, and job promotion were associated with long sickness absence. Almost no difference was observed according to gender and country. Comprehensive prevention policies oriented to psychosocial work factors may be useful to prevent long sickness absence at European level.

Age differences in daily predictors of forgetting to take medication: the importance of context and cognition.

PubMed

Neupert, Shevaun D; Patterson, Taryn R; Davis, Agnes A; Allaire, Jason C

2011-07-01

The present study examined age differences in the within-person daily associations of basic cognition, everyday cognition, and busyness with forgetting to take medication. The authors extend previous interindividual difference findings by conducting a daily diary study of a baseline assessment and 8 consecutive days of 40 older adults (age = 60-89 years, M = 74.86) and 31 younger adults (age = 18-20 years, M = 18.30) where basic cognition, everyday cognition, busyness, and forgetting medication were assessed each day and entered simultaneously into one model. Results from a logistic multilevel model indicated that performance on Letter Series was beneficial for both age groups, but the role of fluctuations in busyness on forgetting to take medications was opposite for younger and older adults. Younger adults remembered to take their medication the most on days when they had high everyday cognition and were busier. Older adults remembered to take their medication the most on days when they had high everyday cognition but were less busy. These findings highlight the importance of contextual variation in busyness in relation to daily medication adherence for younger and older adults.

Psychosocial work factors and long sickness absence in Europe

PubMed Central

Slany, Corinna; Schütte, Stefanie; Chastang, Jean-François; Parent-Thirion, Agnès; Vermeylen, Greet; Niedhammer, Isabelle

2014-01-01

Background: Studies exploring a wide range of psychosocial work factors separately and together in association with long sickness absence are still lacking. Objectives: The objective of this study was to explore the associations between psychosocial work factors measured following a comprehensive instrument (Copenhagen psychosocial questionnaire, COPSOQ) and long sickness absence (>7 days/year) in European employees of 34 countries. An additional objective was to study the differences in these associations according to gender and countries. Methods: The study population consisted of 16 120 male and 16 588 female employees from the 2010 European working conditions survey. Twenty-five psychosocial work factors were explored. Statistical analysis was performed using multilevel logistic regression models and interaction testing. Results: When studied together in the same model, factors related to job demands (quantitative demands and demands for hiding emotions), possibilities for development, social relationships (role conflicts, quality of leadership, social support, and sense of community), workplace violence (physical violence, bullying, and discrimination), shift work, and job promotion were associated with long sickness absence. Almost no difference was observed according to gender and country. Conclusions: Comprehensive prevention policies oriented to psychosocial work factors may be useful to prevent long sickness absence at European level. PMID:24176393

Macro-actor execution on multilevel data-driven architectures

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

Gaudiot, J.L.; Najjar, W.

1988-12-31

The data-flow model of computation brings to multiprocessors high programmability at the expense of increased overhead. Applying the model at a higher level leads to better performance but also introduces loss of parallelism. We demonstrate here syntax directed program decomposition methods for the creation of large macro-actors in numerical algorithms. In order to alleviate some of the problems introduced by the lower resolution interpretation, we describe a multi-level of resolution and analyze the requirements for its actual hardware and software integration.

Multilevel Multidimensional Item Response Model with a Multilevel Latent Covariate

ERIC Educational Resources Information Center

Cho, Sun-Joo; Bottge, Brian A.

2015-01-01

In a pretest-posttest cluster-randomized trial, one of the methods commonly used to detect an intervention effect involves controlling pre-test scores and other related covariates while estimating an intervention effect at post-test. In many applications in education, the total post-test and pre-test scores that ignores measurement error in the…