Who will volunteer? Analysing individual and structural factors of volunteering in Swiss sports clubs.

PubMed

Schlesinger, Torsten; Nagel, Siegfried

2013-01-01

This article analyses the conditions influencing volunteering in sports clubs. It focuses not only on individual characteristics of volunteers but also on the corresponding structural conditions of sports clubs. It proposes a model of voluntary work in sports clubs based on economic behaviour theory. The influences of both the individual and context levels on the decision to engage in voluntary work are estimated in different multilevel models. Results of these multilevel analyses indicate that volunteering is not just an outcome of individual characteristics such as lower workloads, higher income, children belonging to the sports club, longer club memberships, or a strong commitment to the club. It is also influenced by club-specific structural conditions; volunteering is more probable in rural sports clubs whereas growth-oriented goals in clubs have a destabilising effect.

National and School Policies on Restrictions of Teacher Smoking: A Multilevel Analysis of Student Exposure to Teacher Smoking in Seven European Countries

ERIC Educational Resources Information Center

Wold, Bente; Torsheim, Torbjorn; Currie, Candace; Roberts, Chris

2004-01-01

The paper examines the association between restrictions on teacher tobacco smoking at school and student exposure to teachers who smoke during school hours. The data are taken from a European Commission-funded study "Control of Adolescent Smoking" (the CAS study) in seven European countries. Multilevel modelling analyses were applied to…

Equity in the Turkish Education System: A Multilevel Analysis of Social Background Influences on the Mathematics Performance of 15-Year-Old Students

ERIC Educational Resources Information Center

Özdemir, Caner

2016-01-01

This paper aims to discover the level of equity in the Turkish education system using maths outcomes of 15-year-old students in the Programme for International Student Assessment (PISA) exam. In order to do that, associations between various social background variables and student performance are analysed via multilevel models. Female pupils,…

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.

Impact of Contextual Factors on Prostate Cancer Risk and Outcomes

DTIC Science & Technology

2013-07-01

framework with random effects (“frailty models”) while the case-control analyses (Aim 4) will use multilevel unconditional logistic regression models...contextual-level SES on prostate cancer risk within racial/ethnic groups. The survival analyses (Aims 1-3) will utilize a proportional hazards regression

Crush Analyses of Multi-Level Equipment

DOT National Transportation Integrated Search

2006-11-06

Non-linear large deformation crush analyses were conducted on a multi-level cab car typical of those in operation by the Southern California Regional Rail Authority (SCRRA) in California. The motivation for these analyses was a collision, which occur...

Advanced development of atmospheric models. [SEASAT Program support

NASA Technical Reports Server (NTRS)

Kesel, P. G.; Langland, R. A.; Stephens, P. L.; Welleck, R. E.; Wolff, P. M.

1979-01-01

A set of atmospheric analysis and prediction models was developed in support of the SEASAT Program existing objective analysis models which utilize a 125x125 polar stereographic grid of the Northern Hemisphere, which were modified in order to incorporate and assess the impact of (real or simulated) satellite data in the analysis of a two-day meteorological scenario in January 1979. Program/procedural changes included: (1) a provision to utilize winds in the sea level pressure and multi-level height analyses (1000-100 MBS); (2) The capability to perform a pre-analysis at two control levels (1000 MBS and 250 MBS); (3) a greater degree of wind- and mass-field coupling, especially at these controls levels; (4) an improved facility to bogus the analyses based on results of the preanalysis; and (5) a provision to utilize (SIRS) satellite thickness values and cloud motion vectors in the multi-level height analysis.

A multilevel modelling approach to analysis of patient costs under managed care.

PubMed

Carey, K

2000-07-01

The growth of the managed care model of health care delivery in the USA has led to broadened interest in the performance of health care providers. This paper uses multilevel modelling to analyse the effects of managed care penetration on patient level costs for a sample of 24 medical centres operated by the Veterans Health Administration (VHA). The appropriateness of a two level approach to this problem over ordinary least squares (OLS) is demonstrated. Results indicate a modicum of difference in institutions' performance after controlling for patient effects. Facilities more heavily penetrated by the managed care model may be more effective at controlling costs of their sicker patients. Copyright 2000 John Wiley & Sons, Ltd.

Longitudinal analysis of the strengths and difficulties questionnaire scores of the Millennium Cohort Study children in England using M-quantile random-effects regression.

PubMed

Tzavidis, Nikos; Salvati, Nicola; Schmid, Timo; Flouri, Eirini; Midouhas, Emily

2016-02-01

Multilevel modelling is a popular approach for longitudinal data analysis. Statistical models conventionally target a parameter at the centre of a distribution. However, when the distribution of the data is asymmetric, modelling other location parameters, e.g. percentiles, may be more informative. We present a new approach, M -quantile random-effects regression, for modelling multilevel data. The proposed method is used for modelling location parameters of the distribution of the strengths and difficulties questionnaire scores of children in England who participate in the Millennium Cohort Study. Quantile mixed models are also considered. The analyses offer insights to child psychologists about the differential effects of risk factors on children's outcomes.

Analyzing Longitudinal Data with Multilevel Models: An Example with Individuals Living with Lower Extremity Intra-articular Fractures

PubMed Central

Kwok, Oi-Man; Underhill, Andrea T.; Berry, Jack W.; Luo, Wen; Elliott, Timothy R.; Yoon, Myeongsun

2008-01-01

The use and quality of longitudinal research designs has increased over the past two decades, and new approaches for analyzing longitudinal data, including multi-level modeling (MLM) and latent growth modeling (LGM), have been developed. The purpose of this paper is to demonstrate the use of MLM and its advantages in analyzing longitudinal data. Data from a sample of individuals with intra-articular fractures of the lower extremity from the University of Alabama at Birmingham’s Injury Control Research Center is analyzed using both SAS PROC MIXED and SPSS MIXED. We start our presentation with a discussion of data preparation for MLM analyses. We then provide example analyses of different growth models, including a simple linear growth model and a model with a time-invariant covariate, with interpretation for all the parameters in the models. More complicated growth models with different between- and within-individual covariance structures and nonlinear models are discussed. Finally, information related to MLM analysis such as online resources is provided at the end of the paper. PMID:19649151

Revised Models and Conceptualisation of Successful School Principalship for Improved Student Outcomes

ERIC Educational Resources Information Center

Mulford, Bill; Silins, Halia

2011-01-01

Purpose: This study aims to present revised models and a reconceptualisation of successful school principalship for improved student outcomes. Design/methodology/approach: The study's approach is qualitative and quantitative, culminating in model building and multi-level statistical analyses. Findings: Principals who promote both capacity building…

Relations of alpine plant communities across environmental gradients: Multilevel versus multiscale analyses

USGS Publications Warehouse

Malanson, George P.; Zimmerman, Dale L.; Kinney, Mitch; Fagre, Daniel B.

2017-01-01

Alpine plant communities vary, and their environmental covariates could influence their response to climate change. A single multilevel model of how alpine plant community composition is determined by hierarchical relations is compared to a separate examination of those relations at different scales. Nonmetric multidimensional scaling of species cover for plots in four regions across the Rocky Mountains created dependent variables. Climate variables are derived for the four regions from interpolated data. Plot environmental variables are measured directly and the presence of thirty-seven site characteristics is recorded and used to create additional independent variables. Multilevel and best subsets regressions are used to determine the strength of the hypothesized relations. The ordinations indicate structure in the assembly of plant communities. The multilevel analyses, although revealing significant relations, provide little explanation; of the site variables, those related to site microclimate are most important. In multiscale analyses (whole and separate regions), different variables are better explanations within the different regions. This result indicates weak environmental niche control of community composition. The weak relations of the structure in the patterns of species association to the environment indicates that either alpine vegetation represents a case of the neutral theory of biogeography being a valid explanation or that it represents disequilibrium conditions. The implications of neutral theory and disequilibrium explanations are similar: Response to climate change will be difficult to quantify above equilibrium background turnover.

Clarifying the Use of Aggregated Exposures in Multilevel Models: Self-Included vs. Self-Excluded Measures

PubMed Central

Suzuki, Etsuji; Yamamoto, Eiji; Takao, Soshi; Kawachi, Ichiro; Subramanian, S. V.

2012-01-01

Background Multilevel analyses are ideally suited to assess the effects of ecological (higher level) and individual (lower level) exposure variables simultaneously. In applying such analyses to measures of ecologies in epidemiological studies, individual variables are usually aggregated into the higher level unit. Typically, the aggregated measure includes responses of every individual belonging to that group (i.e. it constitutes a self-included measure). More recently, researchers have developed an aggregate measure which excludes the response of the individual to whom the aggregate measure is linked (i.e. a self-excluded measure). In this study, we clarify the substantive and technical properties of these two measures when they are used as exposures in multilevel models. Methods Although the differences between the two aggregated measures are mathematically subtle, distinguishing between them is important in terms of the specific scientific questions to be addressed. We then show how these measures can be used in two distinct types of multilevel models—self-included model and self-excluded model—and interpret the parameters in each model by imposing hypothetical interventions. The concept is tested on empirical data of workplace social capital and employees' systolic blood pressure. Results Researchers assume group-level interventions when using a self-included model, and individual-level interventions when using a self-excluded model. Analytical re-parameterizations of these two models highlight their differences in parameter interpretation. Cluster-mean centered self-included models enable researchers to decompose the collective effect into its within- and between-group components. The benefit of cluster-mean centering procedure is further discussed in terms of hypothetical interventions. Conclusions When investigating the potential roles of aggregated variables, researchers should carefully explore which type of model—self-included or self-excluded—is suitable for a given situation, particularly when group sizes are relatively small. PMID:23251609

Explaining Differences in Subjective Well-Being Across 33 Nations Using Multilevel Models: Universal Personality, Cultural Relativity, and National Income.

PubMed

Cheng, Cecilia; Cheung, Mike W-L; Montasem, Alex

2016-02-01

This multinational study simultaneously tested three prominent hypotheses--universal disposition, cultural relativity, and livability--that explained differences in subjective well-being across nations. We performed multilevel structural equation modeling to examine the hypothesized relationships at both individual and cultural levels in 33 nations. Participants were 6,753 university students (2,215 men; 4,403 women; 135 did not specify), and the average age of the entire sample was 20.97 years (SD = 2.39). Both individual- and cultural-level analyses supported the universal disposition and cultural relativity hypotheses by revealing significant associations of subjective well-being with Extraversion, Neuroticism, and independent self-construal. In addition, interdependent self-construal was positively related to life satisfaction at the individual level only, whereas aggregated negative affect was positively linked with aggregate levels of Extraversion and interdependent self-construal at the cultural level only. Consistent with the livability hypothesis, gross national income (GNI) was related to aggregate levels of negative affect and life satisfaction. There was also a quadratic relationship between GNI and aggregated positive affect. Our findings reveal that universal disposition, cultural self-construal, and national income can elucidate differences in subjective well-being, but the multilevel analyses advance the literature by yielding new findings that cannot be identified in studies using individual-level analyses alone. © 2014 Wiley Periodicals, Inc.

Is job a viable unit of analysis? A multilevel analysis of demand-control-support models.

PubMed

Morrison, David; Payne, Roy L; Wall, Toby D

2003-07-01

The literature has ignored the fact that the demand-control (DC) and demand-control-support (DCS) models of stress are about jobs and not individuals' perceptions of their jobs. Using multilevel modeling, the authors report results of individual- and job-level analyses from a study of over 6,700 people in 81 different jobs. Support for additive versions of the models came when individuals were the unit of analysis. DC and DCS models are only helpful for understanding the effects of individual perceptions of jobs and their relationship to psychological states. When job perceptions are aggregated and their relationship to the collective experience of jobholders is assessed, the models prove of little value. Role set may be a better unit of analysis.

Avoiding Boundary Estimates in Hierarchical Linear Models through Weakly Informative Priors

ERIC Educational Resources Information Center

Chung, Yeojin; Rabe-Hesketh, Sophia; Gelman, Andrew; Dorie, Vincent; Liu, Jinchen

2012-01-01

Hierarchical or multilevel linear models are widely used for longitudinal or cross-sectional data on students nested in classes and schools, and are particularly important for estimating treatment effects in cluster-randomized trials, multi-site trials, and meta-analyses. The models can allow for variation in treatment effects, as well as…

Theoretical and software considerations for general dynamic analysis using multilevel substructured models

NASA Technical Reports Server (NTRS)

Schmidt, R. J.; Dodds, R. H., Jr.

1985-01-01

The dynamic analysis of complex structural systems using the finite element method and multilevel substructured models is presented. The fixed-interface method is selected for substructure reduction because of its efficiency, accuracy, and adaptability to restart and reanalysis. This method is extended to reduction of substructures which are themselves composed of reduced substructures. The implementation and performance of the method in a general purpose software system is emphasized. Solution algorithms consistent with the chosen data structures are presented. It is demonstrated that successful finite element software requires the use of software executives to supplement the algorithmic language. The complexity of the implementation of restart and reanalysis porcedures illustrates the need for executive systems to support the noncomputational aspects of the software. It is shown that significant computational efficiencies can be achieved through proper use of substructuring and reduction technbiques without sacrificing solution accuracy. The restart and reanalysis capabilities and the flexible procedures for multilevel substructured modeling gives economical yet accurate analyses of complex structural systems.

A multilevel model for comorbid outcomes: obesity and diabetes in the US.

PubMed

Congdon, Peter

2010-02-01

Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk.

Using Generalized Additive Models to Analyze Single-Case Designs

ERIC Educational Resources Information Center

Shadish, William; Sullivan, Kristynn

2013-01-01

Many analyses for single-case designs (SCDs)--including nearly all the effect size indicators-- currently assume no trend in the data. Regression and multilevel models allow for trend, but usually test only linear trend and have no principled way of knowing if higher order trends should be represented in the model. This paper shows how Generalized…

Gender Difference Added? Institutional Variations in the Gender Gap in First Class Degree Awards in Mathematical Sciences

ERIC Educational Resources Information Center

Simonite, Vanessa

2005-01-01

This article shows how multilevel modelling can be used to study institutional variations in the gender differences in achievement. The results presented are from analyses of the degree classifications of 22,433 individuals who graduated in mathematical sciences, from universities in the UK, between 1994/95 and 1999/2000. The analyses were…

Integrating the Analysis of Mental Operations into Multilevel Models to Validate an Assessment of Higher Education Students' Competency in Business and Economics

ERIC Educational Resources Information Center

Brückner, Sebastian; Pellegrino, James W.

2016-01-01

The Standards for Educational and Psychological Testing indicate that validation of assessments should include analyses of participants' response processes. However, such analyses typically are conducted only to supplement quantitative field studies with qualitative data, and seldom are such data connected to quantitative data on student or item…

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.

Bottom-Up Analysis of Single-Case Research Designs

ERIC Educational Resources Information Center

Parker, Richard I.; Vannest, Kimberly J.

2012-01-01

This paper defines and promotes the qualities of a "bottom-up" approach to single-case research (SCR) data analysis. Although "top-down" models, for example, multi-level or hierarchical linear models, are gaining momentum and have much to offer, interventionists should be cautious about analyses that are not easily understood, are not governed by…

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).

Development and Validation of a Multidimensional Measure of Family Supportive Supervisor Behaviors (FSSB)

PubMed Central

Hammer, Leslie B.; Kossek, Ellen Ernst; Yragui, Nanette L.; Bodner, Todd E.; Hanson, Ginger C.

2011-01-01

Due to growing work-family demands, supervisors need to effectively exhibit family supportive supervisor behaviors (FSSB). Drawing on social support theory and using data from two samples of lower wage workers, the authors develop and validate a measure of FSSB, defined as behaviors exhibited by supervisors that are supportive of families. FSSB is conceptualized as a multidimensional superordinate construct with four subordinate dimensions: emotional support, instrumental support, role modeling behaviors, and creative work-family management. Results from multilevel confirmatory factor analyses and multilevel regression analyses provide evidence of construct, criterion-related, and incremental validity. The authors found FSSB to be significantly related to work-family conflict, work-family positive spillover, job satisfaction, and turnover intentions over and above measures of general supervisor support. PMID:21660254

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…

A Multilevel Model for Comorbid Outcomes: Obesity and Diabetes in the US

PubMed Central

Congdon, Peter

2010-01-01

Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk. PMID:20616977

Multidisciplinary design and analytic approaches to advance prospective research on the multilevel determinants of child health.

PubMed

Johnson, Sara B; Little, Todd D; Masyn, Katherine; Mehta, Paras D; Ghazarian, Sharon R

2017-06-01

Characterizing the determinants of child health and development over time, and identifying the mechanisms by which these determinants operate, is a research priority. The growth of precision medicine has increased awareness and refinement of conceptual frameworks, data management systems, and analytic methods for multilevel data. This article reviews key methodological challenges in cohort studies designed to investigate multilevel influences on child health and strategies to address them. We review and summarize methodological challenges that could undermine prospective studies of the multilevel determinants of child health and ways to address them, borrowing approaches from the social and behavioral sciences. Nested data, variation in intervals of data collection and assessment, missing data, construct measurement across development and reporters, and unobserved population heterogeneity pose challenges in prospective multilevel cohort studies with children. We discuss innovations in missing data, innovations in person-oriented analyses, and innovations in multilevel modeling to address these challenges. Study design and analytic approaches that facilitate the integration across multiple levels, and that account for changes in people and the multiple, dynamic, nested systems in which they participate over time, are crucial to fully realize the promise of precision medicine for children and adolescents. Copyright © 2017 Elsevier Inc. All rights reserved.

The Economic Cost of Homosexuality: Multilevel Analyses

ERIC Educational Resources Information Center

Baumle, Amanda K.; Poston, Dudley, Jr.

2011-01-01

This article builds on earlier studies that have examined "the economic cost of homosexuality," by using data from the 2000 U.S. Census and by employing multilevel analyses. Our findings indicate that partnered gay men experience a 12.5 percent earnings penalty compared to married heterosexual men, and a statistically insignificant earnings…

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

A Teacher-Focused Intervention to Decrease PE Students' Amotivation by Increasing Need Satisfaction and Decreasing Need Frustration.

PubMed

Cheon, Sung Hyeon; Reeve, Johnmarshall; Song, Yong-Gwan

2016-06-01

Intervention-induced gains in need satisfaction decrease PE students' amotivation. The present study adopted a dual-process model to test whether an intervention could also decrease need frustration and hence provide a second supplemental source to further decrease students' PE amotivation. Using an experimental, longitudinal research design, 19 experienced PE teachers (9 experimental, 10 control) and their 1,017 students participated in an intervention program to help teachers become both more autonomy supportive and less controlling. Multilevel repeated measures analyses showed that students of teachers in the experimental group reported greater T2, T3, and T4 perceived autonomy support, need satisfaction, and engagement and lesser T2, T3, and T4 perceived teacher control, need frustration, and amotivation than did students of teachers in the control group. Multilevel structural equation modeling analyses confirmed the hypothesized dual-process model in which both intervention-induced increases in need satisfaction and intervention-induced decreases need frustration decreased students' end-of-semester amotivation. We discuss the theoretical and practical implications of this new finding on the dual antecedents of diminished amotivation.

Three-level multilevel growth models for nested change data: a guide for group treatment researchers.

PubMed

Tasca, Giorgio A; Illing, Vanessa; Joyce, Anthony S; Ogrodniczuk, John S

2009-07-01

Researchers have known for years about the negative impact on Type I error rates caused by dependencies in hierarchically nested and longitudinal data. Despite this, group treatment researchers do not consistently use methods such as multilevel models (MLMs) to assess dependence and appropriately analyse their nested data. The goals of this study are to review some of the study design issues with regard to hierarchically nested and longitudinal data, discuss MLMs for assessing and handling dependence in data, and present a guide for developing a three-level growth MLM that is appropriate for group treatment data, design, and research questions. The authors present an example from group treatment research to illustrate these issues and methods.

Joint modelling compared with two stage methods for analysing longitudinal data and prospective outcomes: A simulation study of childhood growth and BP.

PubMed

Sayers, A; Heron, J; Smith, Adac; Macdonald-Wallis, C; Gilthorpe, M S; Steele, F; Tilling, K

2017-02-01

There is a growing debate with regards to the appropriate methods of analysis of growth trajectories and their association with prospective dependent outcomes. Using the example of childhood growth and adult BP, we conducted an extensive simulation study to explore four two-stage and two joint modelling methods, and compared their bias and coverage in estimation of the (unconditional) association between birth length and later BP, and the association between growth rate and later BP (conditional on birth length). We show that the two-stage method of using multilevel models to estimate growth parameters and relating these to outcome gives unbiased estimates of the conditional associations between growth and outcome. Using simulations, we demonstrate that the simple methods resulted in bias in the presence of measurement error, as did the two-stage multilevel method when looking at the total (unconditional) association of birth length with outcome. The two joint modelling methods gave unbiased results, but using the re-inflated residuals led to undercoverage of the confidence intervals. We conclude that either joint modelling or the simpler two-stage multilevel approach can be used to estimate conditional associations between growth and later outcomes, but that only joint modelling is unbiased with nominal coverage for unconditional associations.

Multilevel multi-informant structure of the authoritative school climate survey.

PubMed

Konold, Timothy; Cornell, Dewey; Huang, Francis; Meyer, Patrick; Lacey, Anna; Nekvasil, Erin; Heilbrun, Anna; Shukla, Kathan

2014-09-01

The Authoritative School Climate Survey was designed to provide schools with a brief assessment of 2 key characteristics of school climate--disciplinary structure and student support--that are hypothesized to influence 2 important school climate outcomes--student engagement and prevalence of teasing and bullying in school. The factor structure of these 4 constructs was examined with exploratory and confirmatory factor analyses in a statewide sample of 39,364 students (Grades 7 and 8) attending 423 schools. Notably, the analyses used a multilevel structural approach to model the nesting of students in schools for purposes of evaluating factor structure, demonstrating convergent and concurrent validity and gauging the structural invariance of concurrent validity coefficients across gender. These findings provide schools with a core group of school climate measures guided by authoritative discipline theory. PsycINFO Database Record (c) 2014 APA, all rights reserved.

A 2 × 2 taxonomy of multilevel latent contextual models: accuracy-bias trade-offs in full and partial error correction models.

PubMed

Lüdtke, Oliver; Marsh, Herbert W; Robitzsch, Alexander; Trautwein, Ulrich

2011-12-01

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 when estimating contextual effects are distinguished: unreliability that is due to measurement error and unreliability that is due to sampling error. The fact that studies may or may not correct for these 2 types of error can be translated into a 2 × 2 taxonomy of multilevel latent contextual models comprising 4 approaches: an uncorrected approach, partial correction approaches correcting for either measurement or sampling error (but not both), and a full correction approach that adjusts for both sources of error. It is shown mathematically and with simulated data that the uncorrected and partial correction approaches can result in substantially biased estimates of contextual effects, depending on the number of L1 individuals per group, the number of groups, the intraclass correlation, the number of indicators, and the size of the factor loadings. However, the simulation study also shows that partial correction approaches can outperform full correction approaches when the data provide only limited information in terms of the L2 construct (i.e., small number of groups, low intraclass correlation). A real-data application from educational psychology is used to illustrate the different approaches.

Practical Effects of Classwide Mathematics Intervention

ERIC Educational Resources Information Center

VanDerHeyden, Amanda M.; Codding, Robin S.

2015-01-01

The current article presents additional analyses of a classwide mathematics intervention, from a previously reported randomized controlled trial, to offer new information about the treatment and to demonstrate the utility of different types of effect sizes. Multilevel modeling was used to examine treatment effects by race, sex, socioeconomic…

Modeling Students' Interest in Mathematics Homework

ERIC Educational Resources Information Center

Xu, Jianzhong; Yuan, Ruiping; Xu, Brian; Xu, Melinda

2016-01-01

The authors examine the factors influencing mathematics homework interest for Chinese students and compare the findings with a recent study involving U.S. students. The findings from multilevel analyses revealed that some predictors for homework interest functioned similarly (e.g., affective attitude toward homework, learning-oriented reasons,…

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…

Multilevel Motivation and Engagement: Assessing Construct Validity across Students and Schools

ERIC Educational Resources Information Center

Martin, Andrew J.; Malmberg, Lars-Erik; Liem, Gregory Arief D.

2010-01-01

Statistical biases associated with single-level analyses underscore the importance of partitioning variance/covariance matrices into individual and group levels. From a multilevel perspective based on data from 21,579 students in 58 high schools, the present study assesses the multilevel factor structure of motivation and engagement with a…

Virtual Levels and Role Models: N-Level Structural Equations Model of Reciprocal Ratings Data.

PubMed

Mehta, Paras D

2018-01-01

A general latent variable modeling framework called n-Level Structural Equations Modeling (NL-SEM) for dependent data-structures is introduced. NL-SEM is applicable to a wide range of complex multilevel data-structures (e.g., cross-classified, switching membership, etc.). Reciprocal dyadic ratings obtained in round-robin design involve complex set of dependencies that cannot be modeled within Multilevel Modeling (MLM) or Structural Equations Modeling (SEM) frameworks. The Social Relations Model (SRM) for round robin data is used as an example to illustrate key aspects of the NL-SEM framework. NL-SEM introduces novel constructs such as 'virtual levels' that allows a natural specification of latent variable SRMs. An empirical application of an explanatory SRM for personality using xxM, a software package implementing NL-SEM is presented. Results show that person perceptions are an integral aspect of personality. Methodological implications of NL-SEM for the analyses of an emerging class of contextual- and relational-SEMs are discussed.

An investigation of emotion dynamics in major depressive disorder patients and healthy persons using sparse longitudinal networks.

PubMed

de Vos, Stijn; Wardenaar, Klaas J; Bos, Elisabeth H; Wit, Ernst C; Bouwmans, Mara E J; de Jonge, Peter

2017-01-01

Differences in within-person emotion dynamics may be an important source of heterogeneity in depression. To investigate these dynamics, researchers have previously combined multilevel regression analyses with network representations. However, sparse network methods, specifically developed for longitudinal network analyses, have not been applied. Therefore, this study used this approach to investigate population-level and individual-level emotion dynamics in healthy and depressed persons and compared this method with the multilevel approach. Time-series data were collected in pair-matched healthy persons and major depressive disorder (MDD) patients (n = 54). Seven positive affect (PA) and seven negative affect (NA) items were administered electronically at 90 times (30 days; thrice per day). The population-level (healthy vs. MDD) and individual-level time series were analyzed using a sparse longitudinal network model based on vector autoregression. The population-level model was also estimated with a multilevel approach. Effects of different preprocessing steps were evaluated as well. The characteristics of the longitudinal networks were investigated to gain insight into the emotion dynamics. In the population-level networks, longitudinal network connectivity was strongest in the healthy group, with nodes showing more and stronger longitudinal associations with each other. Individually estimated networks varied strongly across individuals. Individual variations in network connectivity were unrelated to baseline characteristics (depression status, neuroticism, severity). A multilevel approach applied to the same data showed higher connectivity in the MDD group, which seemed partly related to the preprocessing approach. The sparse network approach can be useful for the estimation of networks with multiple nodes, where overparameterization is an issue, and for individual-level networks. However, its current inability to model random effects makes it less useful as a population-level approach in case of large heterogeneity. Different preprocessing strategies appeared to strongly influence the results, complicating inferences about network density.

Interactive and independent associations between the socioeconomic and objective built environment on the neighbourhood level and individual health: a systematic review of multilevel studies.

PubMed

Schüle, Steffen Andreas; Bolte, Gabriele

2015-01-01

The research question how contextual factors of neighbourhood environments influence individual health has gained increasing attention in public health research. Both socioeconomic neighbourhood characteristics and factors of the built environment play an important role for health and health-related behaviours. However, their reciprocal relationships have not been systematically reviewed so far. This systematic review aims to identify studies applying a multilevel modelling approach which consider both neighbourhood socioeconomic position (SEP) and factors of the objective built environment simultaneously in order to disentangle their independent and interactive effects on individual health. The three databases PubMed, PsycINFO, and Web of Science were systematically searched with terms for title and abstract screening. Grey literature was not included. Observational studies from USA, Canada, Australia, New Zealand, and Western European countries were considered which analysed simultaneously factors of neighbourhood SEP and the objective built environment with a multilevel modelling approach. Adjustment for individual SEP was a further inclusion criterion. Thirty-three studies were included in qualitative synthesis. Twenty-two studies showed an independent association between characteristics of neighbourhood SEP or the built environment and individual health outcomes or health-related behaviours. Twenty-one studies found cross-level or within-level interactions either between neighbourhood SEP and the built environment, or between neighbourhood SEP or the built environment and individual characteristics, such as sex, individual SEP or ethnicity. Due to the large variation of study design and heterogeneous reporting of results the identification of consistent findings was problematic and made quantitative analysis not possible. There is a need for studies considering multiple neighbourhood dimensions and applying multilevel modelling in order to clarify their causal relationship towards individual health. Especially, more studies using comparable characteristics of neighbourhood SEP and the objective built environment and analysing interactive effects are necessary to disentangle health impacts and identify vulnerable neighbourhoods and population groups.

Interactive and Independent Associations between the Socioeconomic and Objective Built Environment on the Neighbourhood Level and Individual Health: A Systematic Review of Multilevel Studies

PubMed Central

Schüle, Steffen Andreas; Bolte, Gabriele

2015-01-01

Background The research question how contextual factors of neighbourhood environments influence individual health has gained increasing attention in public health research. Both socioeconomic neighbourhood characteristics and factors of the built environment play an important role for health and health-related behaviours. However, their reciprocal relationships have not been systematically reviewed so far. This systematic review aims to identify studies applying a multilevel modelling approach which consider both neighbourhood socioeconomic position (SEP) and factors of the objective built environment simultaneously in order to disentangle their independent and interactive effects on individual health. Methods The three databases PubMed, PsycINFO, and Web of Science were systematically searched with terms for title and abstract screening. Grey literature was not included. Observational studies from USA, Canada, Australia, New Zealand, and Western European countries were considered which analysed simultaneously factors of neighbourhood SEP and the objective built environment with a multilevel modelling approach. Adjustment for individual SEP was a further inclusion criterion. Results Thirty-three studies were included in qualitative synthesis. Twenty-two studies showed an independent association between characteristics of neighbourhood SEP or the built environment and individual health outcomes or health-related behaviours. Twenty-one studies found cross-level or within-level interactions either between neighbourhood SEP and the built environment, or between neighbourhood SEP or the built environment and individual characteristics, such as sex, individual SEP or ethnicity. Due to the large variation of study design and heterogeneous reporting of results the identification of consistent findings was problematic and made quantitative analysis not possible. Conclusions There is a need for studies considering multiple neighbourhood dimensions and applying multilevel modelling in order to clarify their causal relationship towards individual health. Especially, more studies using comparable characteristics of neighbourhood SEP and the objective built environment and analysing interactive effects are necessary to disentangle health impacts and identify vulnerable neighbourhoods and population groups. PMID:25849569

Economic and Sociological Correlates of Suicides: Multilevel Analysis of the Time Series Data in the United Kingdom.

PubMed

Sun, Bruce Qiang; Zhang, Jie

2016-03-01

For the effects of social integration on suicides, there have been different and even contradictive conclusions. In this study, the selected economic and social risks of suicide for different age groups and genders in the United Kingdom were identified and the effects were estimated by the multilevel time series analyses. To our knowledge, there exist no previous studies that estimated a dynamic model of suicides on the time series data together with multilevel analysis and autoregressive distributed lags. The investigation indicated that unemployment rate, inflation rate, and divorce rate are all significantly and positively related to the national suicide rates in the United Kingdom from 1981 to 2011. Furthermore, the suicide rates of almost all groups above 40 years are significantly associated with the risk factors of unemployment and inflation rate, in comparison with the younger groups. © 2016 American Academy of Forensic Sciences.

Differences in within- and between-person factor structure of positive and negative affect: analysis of two intensive measurement studies using multilevel structural equation modeling.

PubMed

Rush, Jonathan; Hofer, Scott M

2014-06-01

The Positive and Negative Affect Schedule (PANAS) is a widely used measure of emotional experience. The factor structure of the PANAS has been examined predominantly with cross-sectional designs, which fails to disaggregate within-person variation from between-person differences. There is still uncertainty as to the factor structure of positive and negative affect and whether they constitute 2 distinct independent factors. The present study examined the within-person and between-person factor structure of the PANAS in 2 independent samples that reported daily affect over 7 and 14 occasions, respectively. Results from multilevel confirmatory factor analyses revealed that a 2-factor structure at both the within-person and between-person levels, with correlated specific factors for overlapping items, provided good model fit. The best-fitting solution was one where within-person factors of positive and negative affect were inversely correlated, but between-person factors were independent. The structure was further validated through multilevel structural equation modeling examining the effects of cognitive interference, daily stress, physical symptoms, and physical activity on positive and negative affect factors.

Subjective Health and Mental Well-Being of Adolescents and the Health Promoting School: A Cross-Sectional Multilevel Analysis

ERIC Educational Resources Information Center

Levin, Kate; Inchley, Jo; Currie, Dorothy; Currie, Candace

2012-01-01

Purpose: The aim of this paper is to examine the impact of the health promoting school (HPS) on adolescent well-being. Design/methodology/approach: Data from the 2006 Health Behaviour in School-aged Children: WHO-collaborative Study in Scotland were analysed using multilevel linear regression analyses for outcome measures: happiness, confidence,…

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…

The Relationship Among School Safety, School Liking, and Students' Self-Esteem: Based on a Multilevel Mediation Model.

PubMed

Zhang, Xinghui; Xuan, Xin; Chen, Fumei; Zhang, Cai; Luo, Yuhan; Wang, Yun

2016-03-01

Perceptions of school safety have an important effect on students' development. Based on the model of "context-process-outcomes," we examined school safety as a context variable to explore how school safety at the school level affected students' self-esteem. We used hierarchical linear modeling to examine the link between school safety at the school level and students' self-esteem, including school liking as a mediator. The data were from the National Children's Study of China (NCSC), in which 6618 fourth- to fifth-grade students in 79 schools were recruited from 100 counties in 31 provinces in China. Multilevel mediation analyses showed that the positive relationship between school safety at the school level and self-esteem was partially mediated by school liking, controlling for demographics at both student and school levels. Furthermore, a sex difference existed in the multilevel mediation model. For boys, school liking fully mediated the relationship between school safety at the school level and self-esteem. However, school liking partially mediated the relationship between school safety at the school level and self-esteem among girls. School safety should receive increasing attention from policymakers because of its impact on students' self-esteem. © 2016, American School Health Association.

Do Some Schools Narrow the Gap? Differential School Effectiveness Revisited

ERIC Educational Resources Information Center

Strand, Steve

2016-01-01

Relatively little research has explored whether schools differ in their effectiveness for different group of pupils (e.g. by ethnicity, poverty or gender), for different curriculum subjects (e.g. English, mathematics or science) or over time (different cohorts). This paper uses multilevel modelling to analyse the national test results at age 7 and…

Positive Affect as a Source of Resilience for Women in Chronic Pain.

ERIC Educational Resources Information Center

Zautra, Alex J.; Johnson, Lisa M.; Davis, Mary C.

2005-01-01

A sample of 124 women with osteoarthritis or fibromyalgia, or both, completed initial assessments for demographic data, health status, and personality traits and 10-12 weekly interviews regarding pain, stress, negative affect, and positive affect. Multilevel modeling analyses indicated that weekly elevations of pain and stress predicted increases…

Do Student Perceptions of Diversity Emphasis Relate to Perceived Learning of Psychology?

ERIC Educational Resources Information Center

Elicker, Joelle D.; Snell, Andrea F.; O'Malley, Alison L.

2010-01-01

We examined the extent to which students' perceived inclusion of diversity issues in the Introduction to Psychology course related to perceptions of learning. Based on the responses of 625 students, multilevel linear modeling analyses revealed that student perceptions of diversity emphasis in the class were positively related to how well students…

Perceptions of Job Security in Europe's Ageing Workforce

ERIC Educational Resources Information Center

Hank, Karsten; Erlinghagen, Marcel

2011-01-01

Using data from the 2004 Survey of Health, Ageing and Retirement in Europe, this paper investigates older workers' perceptions of job security in eleven countries. We describe cross-national patterns and estimate multilevel models to analyse individual and societal determinants of self-perceived job security in the older labour force. While there…

Shift Work, Role Overload, and the Transition to Parenthood

ERIC Educational Resources Information Center

Perry-Jenkins, Maureen; Goldberg, Abbie E.; Pierce, Courtney P.; Sayer, Aline G.

2007-01-01

This article examines how the work hours, work schedules, and role overload of working-class couples are related to depressive symptoms and relationship conflict across the transition to parenthood. Data are from 132 dual-earner couples interviewed 5 times across the transition. Multilevel modeling analyses revealed that working evening or night…

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.

Multilevel Factor Structure and Concurrent Validity of the Teacher Version of the Authoritative School Climate Survey.

PubMed

Huang, Francis L; Cornell, Dewey G; Konold, Timothy; Meyer, Joseph P; Lacey, Anna; Nekvasil, Erin K; Heilbrun, Anna; Shukla, Kathan D

2015-12-01

School climate is well recognized as an important influence on student behavior and adjustment to school, but there is a need for theory-guided measures that make use of teacher perspectives. Authoritative school climate theory hypothesizes that a positive school climate is characterized by high levels of disciplinary structure and student support. A teacher version of the Authoritative School Climate Survey (ASCS) was administered to a statewide sample of 9099 7th- and 8th-grade teachers from 366 schools. The study used exploratory and multilevel confirmatory factor analyses (MCFA) that accounted for the nested data structure and allowed for the modeling of the factor structures at 2 levels. Multilevel confirmatory factor analyses conducted on both an exploratory (N = 4422) and a confirmatory sample (N = 4677) showed good support for the factor structures investigated. Factor correlations at 2 levels indicated that schools with greater levels of disciplinary structure and student support had higher student engagement, less teasing and bullying, and lower student aggression toward teachers. The teacher version of the ASCS can be used to assess 2 key domains of school climate and associated measures of student engagement and aggression toward peers and teachers. © 2015, American School Health Association.

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…

Developmental Trajectories of Motivation in Physical Education: Course, Demographic Differences, and Antecedents

ERIC Educational Resources Information Center

Ntoumanis, Nikos; Barkoukis, Vassilis; Thogersen-Ntoumani, Cecilie

2009-01-01

This study investigated changes in student motivation to participate in physical education and some determinants of these changes over a period of 3 years. Measures were taken twice a year, from age 13 until age 15, from a sample of Greek junior high school students. Multilevel modeling analyses showed significant decreases in task-involving…

Modeling fMRI Data: Challenges and Opportunities

ERIC Educational Resources Information Center

Maydeu-Olivares, Alberto; Brown, Gregory

2013-01-01

We offer an introduction to the five papers that make up this special section. These papers deal with a range of the methodological challenges that face researchers analyzing fMRI data--the spatial, multilevel, and longitudinal nature of the data, the sources of noise, and so on. The papers all provide analyses of data collected by a multi-site…

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…

Associations of Temperament Traits and Mathematics Grades in Adolescents Are Dependent on the Rater but Independent of Motivation and Cognitive Ability

ERIC Educational Resources Information Center

Hintsanen, Mirka; Alatupa, Saija; Jokela, Markus; Lipsanen, Jari; Hintsa, Taina; Leino, Mare

2012-01-01

The current study examines associations between self- and teacher-rated temperament traits (activity, inhibition, negative emotionality, persistence, distractibility, and mood) and mathematics grades. The sample includes 310 ninth grade students (mean age 15.0) from several schools in Finland. Analyses were conducted with multilevel modeling.…

Simulator for multilevel optimization research

NASA Technical Reports Server (NTRS)

Padula, S. L.; Young, K. C.

1986-01-01

A computer program designed to simulate and improve multilevel optimization techniques is described. By using simple analytic functions to represent complex engineering analyses, the simulator can generate and test a large variety of multilevel decomposition strategies in a relatively short time. This type of research is an essential step toward routine optimization of large aerospace systems. The paper discusses the types of optimization problems handled by the simulator and gives input and output listings and plots for a sample problem. It also describes multilevel implementation techniques which have value beyond the present computer program. Thus, this document serves as a user's manual for the simulator and as a guide for building future multilevel optimization applications.

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 of Workplace Social Capital With Work Engagement of Employees in Health Care Settings: A Multilevel Cross-Sectional Analysis.

PubMed

Fujita, Sumiko; Kawakami, Norito; Ando, Emiko; Inoue, Akiomi; Tsuno, Kanami; Kurioka, Sumiko; Kawachi, Ichiro

2016-03-01

The aim of the study was to examine the cross-sectional multilevel association between unit-level workplace social capital and individual-level work engagement among employees in health care settings. The data were collected from employees of a Japanese health care corporation using a questionnaire. The analyses were limited to 440 respondents from 35 units comprising five or more respondents per unit. Unit-level workplace social capital was calculated as an average score of the Workplace Social Capital Scale for each unit. Multilevel regression analysis with a random intercept model was conducted. After adjusting for demographic variables, unit-level workplace social capital was significantly and positively associated with respondents' work engagement (P < 0.001). The association remained significant after additionally adjusting for individual-level perceptions of workplace social capital (P < 0.001). Workplace social capital might exert a positive contextual effect on work engagement of employees in health care settings.

Multi-level functionality of social media in the aftermath of the Great East Japan Earthquake.

PubMed

Jung, Joo-Young; Moro, Munehito

2014-07-01

This study examines the multi-level functionalities of social media in the aftermath of the Great East Japan Earthquake of 11 March 2011. Based on a conceptual model of multi-level story flows of social media (Jung and Moro, 2012), the study analyses the multiple functionalities that were ascribed to social media by individuals, organisations, and macro-level social systems (government and the mass media) after the earthquake. Based on survey data, a review of Twitter timelines and secondary sources, the authors derive five functionalities of social media: interpersonal communications with others (micro level); channels for local governments; organisations and local media (meso level); channels for mass media (macro level); information sharing and gathering (cross level); and direct channels between micro-/meso- and macro-level agents. The study sheds light on the future potential of social media in disaster situations and suggests how to design an effective communication network to prepare for emergency situations. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.

Neighborhood Predictors of Dating Violence Victimization and Perpetration in Young Adulthood: A Multilevel Study

PubMed Central

Buka, Stephen L.; Subramanian, S. V.; Molnar, Beth E.

2010-01-01

Objectives. We examined whether social processes of neighborhoods, such as collective efficacy, during individual's adolescent years affect the likelihood of being involved in physical dating violence during young adulthood. Methods. Using longitudinal data on 633 urban youths aged 13 to 19 years at baseline and data from their neighborhoods (collected by the Project on Human Development in Chicago Neighborhoods), we ran multilevel linear regression models separately by gender to assess the association between collective efficacy and physical dating violence victimization and perpetration, controlling for individual covariates, neighborhood poverty, and perceived neighborhood violence. Results. Females were significantly more likely than were males to be perpetrators of dating violence during young adulthood (38% vs 19%). Multilevel analyses revealed some variation in dating violence at the neighborhood level, partly accounted for by collective efficacy. Collective efficacy was predictive of victimization for males but not females after control for confounders; it was marginally associated with perpetration (P = .07). The effects of collective efficacy varied by neighborhood poverty. Finally, a significant proportion (intraclass correlation = 14%–21%) of the neighborhood-level variation in male perpetration remained unexplained after modeling. Conclusions. Community-level strategies may be useful in preventing dating violence. PMID:20634470

The multilevel determinants of workers' mental health: results from the SALVEO study.

PubMed

Marchand, Alain; Durand, Pierre; Haines, Victor; Harvey, Steve

2015-03-01

This study examined the contribution of work, non-work and individual factors on workers' symptoms of psychological distress, depression and emotional exhaustion based on the multilevel determinants of workers' mental health model. Data from the SALVEO Study were collected in 2009-2012 from a sample of 1,954 employees nested in 63 workplaces in the province of Quebec (Canada). Multilevel regression models were used to analyse the data. Altogether, variables explain 32.2 % of psychological distress, 48.4 % of depression and 48.8 % of emotional exhaustion. Mental health outcomes varied slightly between workplaces and skill utilisation, physical and psychological demands, abusive supervision, interpersonal conflicts and job insecurity are related to the outcomes. Living in couple, having young children at home, family-to-work conflict, work-to-family conflict, strained marital and parental relations, and social support outside the workplace associated with the outcomes. Most of the individual characteristics also correlated with the three outcomes. Importantly, non-work and individual factors modulated the number and type of work factors related to the three outcomes. The results of this study suggest expanding perspectives on occupational mental health that fully recognise the complexity of workers' mental health determinants.

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…

Multilevel covariance regression with correlated random effects in the mean and variance structure.

PubMed

Quintero, Adrian; Lesaffre, Emmanuel

2017-09-01

Multivariate regression methods generally assume a constant covariance matrix for the observations. In case a heteroscedastic model is needed, the parametric and nonparametric covariance regression approaches can be restrictive in the literature. We propose a multilevel regression model for the mean and covariance structure, including random intercepts in both components and allowing for correlation between them. The implied conditional covariance function can be different across clusters as a result of the random effect in the variance structure. In addition, allowing for correlation between the random intercepts in the mean and covariance makes the model convenient for skewedly distributed responses. Furthermore, it permits us to analyse directly the relation between the mean response level and the variability in each cluster. Parameter estimation is carried out via Gibbs sampling. We compare the performance of our model to other covariance modelling approaches in a simulation study. Finally, the proposed model is applied to the RN4CAST dataset to identify the variables that impact burnout of nurses in Belgium. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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…

A multilevel analysis of gatekeeper characteristics and consistent condom use among establishment-based female sex workers in Guangxi, China.

PubMed

Li, Qing; Li, Xiaoming; Stanton, Bonita; Fang, Xiaoyi; Zhao, Ran

2010-11-01

Multilevel analytical techniques are being applied in condom use research to ensure the validity of investigation on environmental/structural influences and clustered data from venue-based sampling. The literature contains reports of consistent associations between perceived gatekeeper support and condom use among entertainment establishment-based female sex workers (FSWs) in Guangxi, China. However, the clustering inherent in the data (FSWs being clustered within establishment) has not been accounted in most of the analyses. We used multilevel analyses to examine perceived features of gatekeepers and individual correlates of consistent condom use among FSWs and to validate the findings in the existing literature. We analyzed cross-sectional data from 318 FSWs from 29 entertainment establishments in Guangxi, China in 2004, with a minimum of 5 FSWs per establishment. The Hierarchical Linear Models program with Laplace estimation was used to estimate the parameters in models containing random effects and binary outcomes. About 11.6% of women reported consistent condom use with clients. The intraclass correlation coefficient indicated 18.5% of the variance in condom use could be attributed to their similarity between FSWs within the same establishments. Women's perceived gatekeeper support and education remained positively associated with condom use (P < 0.05), after controlling for other individual characteristics and clustering. After adjusting for data clustering, perceived gatekeeper support remains associated with consistent condom use with clients among FSWs in China. The results imply that combined interventions to intervene both gatekeepers and individual FSW may effectively promote consistent condom use.

A Multilevel Analysis of Gatekeeper Characteristics and Consistent Condom Use Among Establishment-Based Female Sex Workers in Guangxi, China

PubMed Central

Li, Qing; Li, Xiaoming; Stanton, Bonita; Fang, Xiaoyi; Zhao, Ran

2010-01-01

Background Multilevel analytical techniques are being applied in condom use research to ensure the validity of investigation on environmental/structural influences and clustered data from venue-based sampling. The literature contains reports of consistent associations between perceived gatekeeper support and condom use among entertainments establishment-based female sex workers (FSWs) in Guangxi, China. However, the clustering inherent in the data (FSWs being clustered within establishment) has not been accounted in most of the analyses. We used multilevel analyses to examine perceived features of gatekeepers and individual correlates of consistent condom use among FSWs and to validate the findings in the existing literature. Methods We analyzed cross-sectional data from 318 FSWs from 29 entertainment establishments in Guangxi, China in 2004, with a minimum of 5 FSWs per establishment. The Hierarchical Linear Models program with Laplace estimation was used to estimate the parameters in models containing random effects and binary outcomes. Results About 11.6% of women reported consistent condom use with clients. The intraclass correlation coefficient indicated 18.5% of the variance in condom use could be attributed to their similarity between FSWs within the same establishments. Women’s perceived gatekeeper support and education remained positively associated with condom use (P < 0.05), after controlling for other individual characteristics and clustering. Conclusions After adjusting for data clustering, perceived gatekeeper support remains associated with consistent condom use with clients among FSWs in China. The results imply that combined interventions to intervene both gatekeepers and individual FSW may effectively promote consistent condom use. PMID:20539262

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.

Adult Age Differences and the Role of Cognitive Resources in Perceptual–Motor Skill Acquisition: Application of a Multilevel Negative Exponential Model

PubMed Central

Kennedy, Kristen M.; Rodrigue, Karen M.; Lindenberger, Ulman; Raz, Naftali

2010-01-01

The effects of advanced age and cognitive resources on the course of skill acquisition are unclear, and discrepancies among studies may reflect limitations of data analytic approaches. We applied a multilevel negative exponential model to skill acquisition data from 80 trials (four 20-trial blocks) of a pursuit rotor task administered to healthy adults (19–80 years old). The analyses conducted at the single-trial level indicated that the negative exponential function described performance well. Learning parameters correlated with measures of task-relevant cognitive resources on all blocks except the last and with age on all blocks after the second. Thus, age differences in motor skill acquisition may evolve in 2 phases: In the first, age differences are collinear with individual differences in task-relevant cognitive resources; in the second, age differences orthogonal to these resources emerge. PMID:20047985

Teams as innovative systems: multilevel motivational antecedents of innovation in R&D teams.

PubMed

Chen, Gilad; Farh, Jiing-Lih; Campbell-Bush, Elizabeth M; Wu, Zhiming; Wu, Xin

2013-11-01

Integrating theories of proactive motivation, team innovation climate, and motivation in teams, we developed and tested a multilevel model of motivators of innovative performance in teams. Analyses of multisource data from 428 members of 95 research and development (R&D) teams across 33 Chinese firms indicated that team-level support for innovation climate captured motivational mechanisms that mediated between transformational leadership and team innovative performance, whereas members' motivational states (role-breadth self-efficacy and intrinsic motivation) mediated between proactive personality and individual innovative performance. Furthermore, individual motivational states and team support for innovation climate uniquely promoted individual innovative performance, and, in turn, individual innovative performance linked team support for innovation climate to team innovative performance. (c) 2013 APA, all rights reserved.

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…

Warmth with Mothers and Fathers from Middle Childhood to Late Adolescence: Within- and Between-Families Comparisons

ERIC Educational Resources Information Center

Shanahan, Lilly; McHale, Susan M.; Crouter, Ann C.; Osgood, D. Wayne

2007-01-01

The authors examined siblings' dyadic and differential experiences of parental warmth from 7 to 19 years of age. Participants were first- and second-borns from 201 families who reported on their warmth with each parent in 4 home interviews spaced over 5 years. Supporting an individual development hypothesis, multilevel model analyses revealed…

Implications of Interactions among Society, Education and Technology: A Comparison of Multiple Linear Regression and Multilevel Modeling in Mathematics Achievement Analyses

ERIC Educational Resources Information Center

Deering, Pamela Rose

2014-01-01

This research compares and contrasts two approaches to predictive analysis of three years' of school district data to investigate relationships between student and teacher characteristics and math achievement as measured by the state-mandated Maryland School Assessment mathematics exam. The sample for the study consisted of 3,514 students taught…

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.

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

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…

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…

Family structure and posttraumatic stress reactions: a longitudinal study using multilevel analyses

PubMed Central

2011-01-01

Background There is limited research on the relevance of family structures to the development and maintenance of posttraumatic stress following disasters. We longitudinally studied the effects of marital and parental statuses on posttraumatic stress reactions after the 2004 Southeast Asian tsunami and whether persons in the same households had more shared stress reactions than others. Method The study included a tourist population of 641 Norwegian adult citizens, many of them from families with children. We measured posttraumatic stress symptoms with the Impact of Event Scale-Revised at 6 months and 2 years post-disaster. Analyses included multilevel methods with mixed effects models. Results Results showed that neither marital nor parental status was significantly related to posttraumatic stress. At both assessments, adults living in the same household reported levels of posttraumatic stress that were more similar to one another than adults who were not living together. Between households, disaster experiences were closely related to the variance in posttraumatic stress symptom levels at both assessments. Within households, however, disaster experiences were less related to the variance in symptom level at 2 years than at 6 months. Conclusions These results indicate that adult household members may influence one another's posttraumatic stress reactions as well as their interpretations of the disaster experiences over time. Our findings suggest that multilevel methods may provide important information about family processes after disasters. PMID:22171549

The Use of Biosimulation in the Design of a Novel Multi-level Weight Loss Maintenance Program for Overweight Children

PubMed Central

Wilfley, Denise E.; Van Buren, Dorothy J.; Theim, Kelly R.; Stein, Richard I.; Saelens, Brian E.; Ezzet, Farkad; Russian, Angela C.; Perri, Michael G.; Epstein, Leonard H.

2011-01-01

Objective Weight loss outcomes achieved through conventional behavior change interventions are prone to deterioration over time. Basic learning laboratory studies in the area of behavioral extinction and renewal and multi-level models of weight control offer clues as to why newly acquired weight loss skills are prone to relapse. According to these models, current clinic-based interventions may not be of sufficient duration or scope to allow for the practice of new skills across the multiple community contexts necessary to promote sustainable weight loss. Although longer, more intensive interventions with greater reach may hold the key to improving weight loss outcomes, it is difficult to test these assumptions in a time efficient and cost-effective manner. A research design tool that has been increasingly utilized in other fields (e.g., pharmaceuticals) is the use of biosimulation analyses. The present paper describes our research team's use of computer simulation models to assist in designing a study to test a novel, comprehensive socio-environmental treatment approach to weight loss maintenance in children ages 7 to 12 years. Methods Weight outcome data from the weight loss, weight maintenance, and follow-up phases of a recently completed randomized controlled trial (RCT) were used to describe the time course of a proposed, extended multi-level treatment program. Simulations were then conducted to project the expected changes in child percent overweight trajectories in the proposed study. Results A 12.9% decrease in percent overweight at 30 months was estimated based upon the midway point between models of “best-case” and “worst-case” weight maintenance scenarios. Conclusions Preliminary data and further analyses, including biosimulation projections, suggest that our socio-environmental approach to weight loss maintenance treatment is promising and warrants evaluation in a large-scale RCT. Biosimulation techniques may have utility in the design of future community-level interventions for the treatment and prevention of childhood overweight. PMID:20107468

The role of perceived social support in loneliness and self-esteem among children affected by HIV/AIDS: a longitudinal multilevel analysis in rural China.

PubMed

Qiao, Shan; Li, Xiaoming; Zhao, Guoxiang; Zhao, Junfeng; Stanton, Bonita

2014-07-01

To delineate the trajectories of loneliness and self-esteem over time among children affected by parental HIV and AIDS, and to examine how their perceived social support (PSS) influenced initial scores and change rates of these two psychological outcomes. We collected longitudinal data from children affected by parental HIV/AIDS in rural central China. Children 6-18 years of age at baseline were eligible to participate in the study and were assessed annually for 3 years. Multilevel regression models for change were used to assess the effect of baseline PSS on the trajectories of loneliness and self-esteem over time. We employed maximum likelihood estimates to fit multilevel models and specified the between-individual covariance matrix as 'unstructured' to allow correlation among the different sources of variance. Statistics including -2 Log Likelihood, Akaike Information Criterion and Bayesian Information Criterion were used in evaluating the model fit. The results of multilevel analyses indicated that loneliness scores significantly declined over time. Controlling for demographic characteristics, children with higher PSS reported significantly lower baseline loneliness score and experienced a slower rate of decline in loneliness over time. Children with higher PSS were more likely to report higher self-esteem scores at baseline. However, the self-esteem scores remained stable over time controlling for baseline PSS and all the other variables. The positive effect of PSS on psychological adjustment may imply a promising approach for future intervention among children affected by HIV/AIDS, in which efforts to promote psychosocial well being could focus on children and families with lower social support. We also call for a greater understanding of children's psychological adjustment process in various contexts of social support and appropriate adaptations of evidence-based interventions to meet their diverse needs.

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).

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.

Single-Level and Multilevel Mediation Analysis

ERIC Educational Resources Information Center

Tofighi, Davood; Thoemmes, Felix

2014-01-01

Mediation analysis is a statistical approach used to examine how the effect of an independent variable on an outcome is transmitted through an intervening variable (mediator). In this article, we provide a gentle introduction to single-level and multilevel mediation analyses. Using single-level data, we demonstrate an application of structural…

The Influence of Distributed Leadership on Teachers' Organizational Commitment: A Multilevel Approach

ERIC Educational Resources Information Center

Hulpia, Hester; Devos, Geert; Van Keer, Hilde

2009-01-01

In the present study the effects of a cooperative leadership team, distributed leadership, participative decision-making, and context variables on teachers' organizational commitment are investigated. Multilevel analyses on data from 1522 teachers indicated that 9% of the variance in teachers' organizational commitment is attributable to…

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 Sample Size and Other Factors When Estimating Multilevel Logistic Models

ERIC Educational Resources Information Center

Schoeneberger, Jason A.

2016-01-01

The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…

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…

Capabilities for Learning to Read: An Investigation of Social and Economic Effects for Grade 6 Learners in Southern and East Africa

ERIC Educational Resources Information Center

Smith, Michele; Barrett, Angeline M.

2011-01-01

This paper considers what multilevel modelling approaches to analysing large scale cross-national surveys of education quality can tell us about the capabilities that support primary school children in learning to read. The impact of pupil background characteristics on achievement in reading towards the end of the primary cycle in sub-Saharan…

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 analyses of school and children's characteristics associated with physical activity.

PubMed

Gomes, Thayse Natacha; dos Santos, Fernanda K; Zhu, Weimo; Eisenmann, Joey; Maia, José A R

2014-10-01

Children spend most of their awake time at school, and it is important to identify individual and school-level correlates of their physical activity (PA) levels. This study aimed to identify the between-school variability in Portuguese children PA and to investigate student and school PA correlates using multilevel modeling. The sample included 1075 Portuguese children of both sexes, aged 6-10 years, from 24 schools. Height and weight were measured and body mass index (BMI) was estimated. Physical activity was estimated using the Godin and Shephard questionnaire (total PA score was used); cardiorespiratory fitness was estimated with the 1-mile run/walk test. A structured inventory was used to access information about the school environment. A multilevel analysis (level-1: student-level; level-2: school-level) was used. Student-level variables (age, sex, 1-mile run/walk test) explained 7% of the 64% variance fraction of the individual-level PA; however, school context explained approximately 36% of the total PA variance. Variables included in the model (school size, school setting, playground area, frequency and duration of physical education class, and qualification of physical education teacher) are responsible for 80% of the context variance. School environment is an important correlate of PA among children, enhancing children's opportunities for being active and healthy. © 2014, American School Health Association.

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…

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.

Trauma cognitions are related to symptoms up to 10 years after cognitive behavioral treatment for posttraumatic stress disorder.

PubMed

Scher, Christine D; Suvak, Michael K; Resick, Patricia A

2017-11-01

This study examined (a) relationships between trauma-related cognitions and posttraumatic stress disorder (PTSD) symptoms from pretreatment through a long-term period after cognitive-behavioral therapy (CBT) for PTSD and (b) whether these relationships were impacted by treatment type. Participants were 171 women randomized into treatment for PTSD after rape. Measures of self-reported trauma-related cognitions and interviewer-assessed PTSD symptoms (i.e., Posttraumatic Maladaptive Beliefs Scale, Trauma-Related Guilt Inventory, and Clinician-Administered PTSD Scale) were obtained at pretreatment, posttreatment, and 3-month, 9-month, and 5-10 year follow-ups. Multilevel regression analyses were used to examine relationships between trauma-related cognitions and PTSD symptoms throughout the study period and whether these relationships differed as a function of treatment type (i.e., Cognitive Processing Therapy or Prolonged Exposure). Initial multilevel regression analyses that examined mean within-participant associations suggested that beliefs regarding Reliability and Trustworthiness of Others, Self-Worth and Judgment, Threat of Harm, and Guilt were related to PTSD symptoms throughout follow-up. Growth curve modeling suggested that patterns of belief change throughout follow-up were similar to those previously observed in PTSD symptoms over the same time period. Finally, multilevel mediation analyses that incorporated time further suggested that change in beliefs was related to change in symptoms throughout follow-up. With 1 minor exception, relationships between beliefs and symptoms were not moderated by treatment type. These data suggest that trauma-related cognitions are a potential mechanism for long-term maintenance of treatment gains after CBT for PTSD. Moreover, these cognitions may be a common, rather than specific, treatment maintenance mechanism. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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…

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

PubMed

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

2018-05-10

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

And justice for all: Examining corruption as a contextual source of mental illness.

PubMed

van Deurzen, Ioana

2017-01-01

In the present study, I focus on the relationship between corruption and mental health as measured by the level of depressive symptoms. I use data collected by the European Social Survey in 2006, 2012 and 2014 from 99,159 individuals that lived in 24 European countries. I employ two types of analyses: static analyses, i.e., multilevel models estimated in each wave, and dynamic analyses, i.e., fixed effects models for pseudo-panel data. Both static and dynamic analyses suggested that corruption had a detrimental effect on mental health. However, the results were not robust in models where the country's wealth was accounted for. Furthermore, this study presents evidence that the level of societal corruption is detrimental especially for the mental health of religious persons and individuals that experience material adversity. Regarding a potentially different effect of corruption on mental health between western and eastern European countries, no significant differences were found. Copyright © 2016 Elsevier Ltd. All rights reserved.

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…

Performance of time-varying predictors in multilevel models under an assumption of fixed or random effects.

PubMed

Baird, Rachel; Maxwell, Scott E

2016-06-01

Time-varying predictors in multilevel models are a useful tool for longitudinal research, whether they are the research variable of interest or they are controlling for variance to allow greater power for other variables. However, standard recommendations to fix the effect of time-varying predictors may make an assumption that is unlikely to hold in reality and may influence results. A simulation study illustrates that treating the time-varying predictor as fixed may allow analyses to converge, but the analyses have poor coverage of the true fixed effect when the time-varying predictor has a random effect in reality. A second simulation study shows that treating the time-varying predictor as random may have poor convergence, except when allowing negative variance estimates. Although negative variance estimates are uninterpretable, results of the simulation show that estimates of the fixed effect of the time-varying predictor are as accurate for these cases as for cases with positive variance estimates, and that treating the time-varying predictor as random and allowing negative variance estimates performs well whether the time-varying predictor is fixed or random in reality. Because of the difficulty of interpreting negative variance estimates, 2 procedures are suggested for selection between fixed-effect and random-effect models: comparing between fixed-effect and constrained random-effect models with a likelihood ratio test or fitting a fixed-effect model when an unconstrained random-effect model produces negative variance estimates. The performance of these 2 procedures is compared. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Neighborhood socioeconomic characteristics and differences in the availability of healthy food stores and restaurants in Sao Paulo, Brazil

PubMed Central

Duran, Ana Clara; Diez Roux, Ana V; do Rosario DO Latorre, Maria; Jaime, Patricia C

2013-01-01

Differential access to healthy foods has been hypothesized to contribute to health disparities, but evidence from low and middle-income countries is still scarce. This study examines whether the access of healthy foods varies across store types and neighborhoods of different socioeconomic statuses (SES) in a large Brazilian city. A cross-sectional study was conducted in 2010–2011 across 52 census tracts. Healthy food access was measured by a comprehensive in-store data collection, summarized into two indexes developed for retail food stores (HFSI) and restaurants (HMRI). Descriptive analyses and multilevel models were used to examine associations of store type and neighborhood SES with healthy food access. Fast food restaurants were more likely to be located in low SES neighborhoods whereas supermarkets and full service restaurants were more likely to be found in higher SES neighborhoods. Multilevel analyses showed that both store type and neighborhood SES were independently associated with in-store food measures. We found differences in the availability of healthy food stores and restaurants in Sao Paulo city favoring middle and high SES neighborhoods. PMID:23747923

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

Hierarchical demographic approaches for assessing invasion dynamics of non-indigenous species: An example using northern snakehead (Channa argus)

USGS Publications Warehouse

Jiao, Y.; Lapointe, N.W.R.; Angermeier, P.L.; Murphy, B.R.

2009-01-01

Models of species' demographic features are commonly used to understand population dynamics and inform management tactics. Hierarchical demographic models are ideal for the assessment of non-indigenous species because our knowledge of non-indigenous populations is usually limited, data on demographic traits often come from a species' native range, these traits vary among populations, and traits are likely to vary considerably over time as species adapt to new environments. Hierarchical models readily incorporate this spatiotemporal variation in species' demographic traits by representing demographic parameters as multi-level hierarchies. As is done for traditional non-hierarchical matrix models, sensitivity and elasticity analyses are used to evaluate the contributions of different life stages and parameters to estimates of population growth rate. We applied a hierarchical model to northern snakehead (Channa argus), a fish currently invading the eastern United States. We used a Monte Carlo approach to simulate uncertainties in the sensitivity and elasticity analyses and to project future population persistence under selected management tactics. We gathered key biological information on northern snakehead natural mortality, maturity and recruitment in its native Asian environment. We compared the model performance with and without hierarchy of parameters. Our results suggest that ignoring the hierarchy of parameters in demographic models may result in poor estimates of population size and growth and may lead to erroneous management advice. In our case, the hierarchy used multi-level distributions to simulate the heterogeneity of demographic parameters across different locations or situations. The probability that the northern snakehead population will increase and harm the native fauna is considerable. Our elasticity and prognostic analyses showed that intensive control efforts immediately prior to spawning and/or juvenile-dispersal periods would be more effective (and probably require less effort) than year-round control efforts. Our study demonstrates the importance of considering the hierarchy of parameters in estimating population growth rate and evaluating different management strategies for non-indigenous invasive species. ?? 2009 Elsevier B.V.

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.

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.

Income inequality and mortality: a multilevel prospective study of 521 248 individuals in 50 US states.

PubMed

Backlund, Eric; Rowe, Geoff; Lynch, John; Wolfson, Michael C; Kaplan, George A; Sorlie, Paul D

2007-06-01

Some of the most consistent evidence in favour of an association between income inequality and health has been among US states. However, in multilevel studies of mortality, only two out of five studies have reported a positive relationship with income inequality after adjustment for the compositional characteristics of the state's inhabitants. In this study, we attempt to clarify these mixed results by analysing the relationship within age-sex groups and by applying a previously unused analytical method to a database that contains more deaths than any multilevel study to date. The US National Longitudinal Mortality Study (NLMS) was used to model the relationship between income inequality in US states and mortality using both a novel and previously used methodologies that fall into the general framework of multilevel regression. We adjust age-sex specific models for nine socioeconomic and demographic variables at the individual level and percentage black and region at the state level. The preponderance of evidence from this study suggests that 1990 state-level income inequality is associated with a 40% differential in state level mortality rates (95% CI = 26-56%) for men 25-64 years and a 14% (95% CI = 3-27%) differential for women 25-64 years after adjustment for compositional factors. No such relationship was found for men or women over 65. The relationship between income inequality and mortality is only robust to adjustment for compositional factors in men and women under 65. This explains why income inequality is not a major driver of mortality trends in the United States because most deaths occur at ages 65 and over. This analysis does suggest, however, the certain causes of death that occur primarily in the population under 65 may be associated with income inequality. Comparison of analytical techniques also suggests coefficients for income inequality in previous multilevel mortality studies may be biased, but further research is needed to provide a definitive answer.

Variations in the prevalence of antibody to brucella infection in cattle by farm, area and district in Kenya.

PubMed Central

Kadohira, M.; McDermott, J. J.; Shoukri, M. M.; Kyule, M. N.

1997-01-01

Variations in the sero-prevalence of antibody to brucella infection by cow, farm and area factors were investigated for three contrasting districts in Kenya: Samburu, an arid and pastoral area: Kiambu, a tropical highland area; and Kilifi, a typical tropical coastal area. Cattle were selected by a two-stage cluster sampling procedure and visited once between August 1991 and 1992. Schall's algorithm, a statistical model suitable for multi-level analysis was used. Using this model, older age, free grazing and large herd size (> or = 31) were associated with higher seroprevalence. Also, significant farm-to-farm, area-to-area and district-to-district variations were estimated. The patterns of high risk districts and areas seen were consistent with known animal husbandry and movement risk factors, but the larger than expected farm-to-farm variation within high risk areas and districts could not be explained. Thus, a multi-level method provided additional information beyond conventional analyses of sero-prevalence data. PMID:9042033

The relationship between self-management abilities, quality of chronic care delivery, and wellbeing among patients with chronic obstructive pulmonary disease in The Netherlands

PubMed Central

Cramm, Jane Murray; Nieboer, Anna Petra

2013-01-01

Background This cross-sectional study aimed to identify the relationship between quality of chronic care delivery, self-management abilities, and wellbeing among patients with chronic obstructive pulmonary disease (COPD). Methods The study was conducted in 2012 and included 548 (out of 1303; 42% response rate) patients with COPD enrolled in a COPD care program in the region of Noord-Kennemerland in The Netherlands. We employed a multilevel random-effects model (548 patients nested in 47 healthcare practices) to investigate the relationship between quality of chronic care delivery, self-management abilities, and patients’ wellbeing. In the multilevel analyses we controlled for patients’ background characteristics and health behaviors. Results Multilevel analyses clearly showed a significant relationship between quality of chronic care delivery and wellbeing of patients with COPD (P ≤ 0.001). When self-management abilities were included in the equation while controlling for background characteristics, health behaviors, and quality of chronic care delivery, these abilities were found to have a strong positive relationship with patients’ wellbeing (P ≤ 0.001). Low educational level, single marital status, and physical exercise were not significantly associated with wellbeing when self-management abilities were included in the equation. Conclusion Self-management abilities and the quality of chronic care delivery are important for the wellbeing of patients with COPD. Furthermore, self-management abilities acted as mediators between wellbeing and low educational level, single status, and physical exercise among these patients. PMID:23641152

Marital Status, Marital Process, and Parental Resources in Predicting Adolescents' Emotional Adjustment: A Multilevel Analysis

ERIC Educational Resources Information Center

Vandervalk, Inge; Spruijt, Ed; De Goede, Martijn; Meeus, Wim; Maas, Cora

2004-01-01

This study examined the relationship between adolescent emotional adjustment and the family environment (i.e., family status, family process, and parental resources). This was done by way of multilevel analyses, with a sample of 2,636 parent-child couples of both intact and divorced families. The results indicated that adolescent emotional…

Impact of high-performance work systems on individual- and branch-level performance: test of a multilevel model of intermediate linkages.

PubMed

Aryee, Samuel; Walumbwa, Fred O; Seidu, Emmanuel Y M; Otaye, Lilian E

2012-03-01

We proposed and tested a multilevel model, underpinned by empowerment theory, that examines the processes linking high-performance work systems (HPWS) and performance outcomes at the individual and organizational levels of analyses. Data were obtained from 37 branches of 2 banking institutions in Ghana. Results of hierarchical regression analysis revealed that branch-level HPWS relates to empowerment climate. Additionally, results of hierarchical linear modeling that examined the hypothesized cross-level relationships revealed 3 salient findings. First, experienced HPWS and empowerment climate partially mediate the influence of branch-level HPWS on psychological empowerment. Second, psychological empowerment partially mediates the influence of empowerment climate and experienced HPWS on service performance. Third, service orientation moderates the psychological empowerment-service performance relationship such that the relationship is stronger for those high rather than low in service orientation. Last, ordinary least squares regression results revealed that branch-level HPWS influences branch-level market performance through cross-level and individual-level influences on service performance that emerges at the branch level as aggregated service performance.

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.

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.

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.

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.

The impact of a disease management programme for type 2 diabetes on health-related quality of life: multilevel analysis of a cluster-randomised controlled trial.

PubMed

Panisch, Sigrid; Johansson, Tim; Flamm, Maria; Winkler, Henrike; Weitgasser, Raimund; Sönnichsen, Andreas C

2018-01-01

Type 2 diabetes is a chronic disease associated with poorer health outcomes and decreased health related quality of life (HRQoL). The aim of this analysis was to explore the impact of a disease management programme (DMP) in type 2 diabetes on HRQoL. A multilevel model was used to explain the variation in EQ-VAS. A cluster-randomized controlled trial-analysis of the secondary endpoint HRQoL. Our study population were general practitioners and patients in the province of Salzburg. The DMP "Therapie-Aktiv" was implemented in the intervention group, and controls received usual care. Outcome measure was a change in EQ-VAS after 12 months. For comparison of rates, we used Fisher's Exact test; for continuous variables the independent T test or Welch test were used. In the multilevel modeling, we examined various models, continuously adding variables to explain the variation in the dependent variable, starting with an empty model, including only the random intercept. We analysed random effects parameters in order to disentangle variation of the final EQ-VAS. The EQ-VAS significantly increased within the intervention group (mean difference 2.19, p = 0.005). There was no significant difference in EQ-VAS between groups (mean difference 1.00, p = 0.339). In the intervention group the improvement was more distinct in women (2.46, p = 0.036) compared to men (1.92, p = 0.063). In multilevel modeling, sex, age, family and work circumstances, any macrovascular diabetic complication, duration of diabetes, baseline body mass index and baseline EQ-VAS significantly influence final EQ-VAS, while DMP does not. The final model explains 28.9% (EQ-VAS) of the total variance. Most of the unexplained variance was found on patient-level (95%) and less on GP-level (5%). DMP "Therapie-Aktiv" has no significant impact on final EQ-VAS. The impact of DMPs in type 2 diabetes on HRQoL is still unclear and future programmes should focus on patient specific needs and predictors in order to improve HRQoL. Trial registration Current Controlled trials Ltd., ISRCTN27414162.

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.

Multi-level structure in the large scale distribution of optically luminous galaxies

NASA Astrophysics Data System (ADS)

Deng, Xin-fa; Deng, Zu-gan; Liu, Yong-zhen

1992-04-01

Fractal dimensions in the large scale distribution of galaxies have been calculated with the method given by Wen et al. [1] Samples are taken from CfA redshift survey in northern and southern galactic [2] hemisphere in our analysis respectively. Results from these two regions are compared with each other. There are significant differences between the distributions in these two regions. However, our analyses do show some common features of the distributions in these two regions. All subsamples show multi-level fractal character distinctly. Combining it with the results from analyses of samples given by IRAS galaxies and results from samples given by redshift survey in pencil-beam fields, [3,4] we suggest that multi-level fractal structure is most likely to be a general and important character in the large scale distribution of galaxies. The possible implications of this character are discussed.

Three frameworks to predict physical activity behavior in middle school inclusive physical education: a multilevel analysis.

PubMed

Jin, Jooyeon; Yun, Joonkoo

2013-07-01

The purpose of this study was to examine three frameworks, (a) process-product, (b) student mediation, and (c) classroom ecology, to understand physical activity (PA) behavior of adolescents with and without disabilities in middle school inclusive physical education (PE). A total of 13 physical educators teaching inclusive PE and their 503 students, including 22 students with different disabilities, participated in this study. A series of multilevel regression analyses indicated that physical educators' teaching behavior and students' implementation intentions play important roles in promoting the students' PA in middle school inclusive PE settings when gender, disability, lesson content, instructional model, and class location are considered simultaneously. The findings suggest that the ecological framework should be considered to effectively promote PA of adolescents with and without disabilities in middle school PE classes.

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.

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…

Overweight and obesity in India: policy issues from an exploratory multi-level analysis.

PubMed

Siddiqui, Md Zakaria; Donato, Ronald

2016-06-01

This article analyses a nationally representative household dataset-the National Family Health Survey (NFHS-3) conducted in 2005 to 2006-to examine factors influencing the prevalence of overweight/obesity in India. The dataset was disaggregated into four sub-population groups-urban and rural females and males-and multi-level logit regression models were used to estimate the impact of particular covariates on the likelihood of overweight/obesity. The multi-level modelling approach aimed to identify individual and macro-level contextual factors influencing this health outcome. In contrast to most studies on low-income developing countries, the findings reveal that education for females beyond a particular level of educational attainment exhibits a negative relationship with the likelihood of overweight/obesity. This relationship was not observed for males. Muslim females and all Sikh sub-populations have a higher likelihood of overweight/obesity suggesting the importance of socio-cultural influences. The results also show that the relationship between wealth and the probability of overweight/obesity is stronger for males than females highlighting the differential impact of increasing socio-economic status on gender. Multi-level analysis reveals that states exerted an independent influence on the likelihood of overweight/obesity beyond individual-level covariates, reflecting the importance of spatially related contextual factors on overweight/obesity. While this study does not disentangle macro-level 'obesogenic' environmental factors from socio-cultural network influences, the results highlight the need to refrain from adopting a 'one size fits all' policy approach in addressing the overweight/obesity epidemic facing India. Instead, policy implementation requires a more nuanced and targeted approach to incorporate the growing recognition of socio-cultural and spatial contextual factors impacting on healthy behaviours. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Are Environmental Influences on Physical Activity Distinct for Urban, Suburban, and Rural Schools? A Multilevel Study among Secondary School Students in Ontario, Canada

ERIC Educational Resources Information Center

Hobin, Erin P.; Leatherdale, Scott; Manske, Steve; Dubin, Joel A.; Elliott, Susan; Veugelers, Paul

2013-01-01

Background: This study examined differences in students' time spent in physical activity (PA) across secondary schools in rural, suburban, and urban environments and identified the environment-level factors associated with these between school differences in students' PA. Methods: Multilevel linear regression analyses were used to examine the…

A Multilevel Shape Fit Analysis of Neutron Transmission Data

NASA Astrophysics Data System (ADS)

Naguib, K.; Sallam, O. H.; Adib, M.; Ashry, A.

A multilevel shape fit analysis of neutron transmission data is presented. A multilevel computer code SHAPE is used to analyse clean transmission data obtained from time-of-flight (TOF) measurements. The shape analysis deduces the parameters of the observed resonances in the energy region considered in the measurements. The shape code is based upon a least square fit of a multilevel Briet-Wigner formula and includes both instrumental resolution and Doppler broadenings. Operating the SHAPE code on a test example of a measured transmission data of 151Eu, 153Eu and natural Eu in the energy range 0.025-1 eV accquired a good result for the used technique of analysis.Translated AbstractAnalyse von Neutronentransmissionsdaten mittels einer VielniveauformanpassungNeutronentransmissionsdaten werden in einer Vielniveauformanpassung analysiert. Dazu werden bereinigte Daten aus Flugzeitmessungen mit dem Rechnerprogramm SHAPE bearbeitet. Man erhält die Parameter der beobachteten Resonanzen im gemessenen Energiebereich. Die Formanpassung benutzt eine Briet-Wignerformel und berücksichtigt Linienverbreiterungen infolge sowohl der Meßeinrichtung als auch des Dopplereffekts. Als praktisches Beispiel werden 151Eu, 153Eu und natürliches Eu im Energiebereich 0.025 bis 1 eV mit guter Übereinstimmung theoretischer und experimenteller Werte behandelt.

Predicting the F(ab)-mediated effect of monoclonal antibodies in vivo by combining cell-level kinetic and pharmacokinetic modelling.

PubMed

Krippendorff, Ben-Fillippo; Oyarzún, Diego A; Huisinga, Wilhelm

2012-04-01

Cell-level kinetic models for therapeutically relevant processes increasingly benefit the early stages of drug development. Later stages of the drug development processes, however, rely on pharmacokinetic compartment models while cell-level dynamics are typically neglected. We here present a systematic approach to integrate cell-level kinetic models and pharmacokinetic compartment models. Incorporating target dynamics into pharmacokinetic models is especially useful for the development of therapeutic antibodies because their effect and pharmacokinetics are inherently interdependent. The approach is illustrated by analysing the F(ab)-mediated inhibitory effect of therapeutic antibodies targeting the epidermal growth factor receptor. We build a multi-level model for anti-EGFR antibodies by combining a systems biology model with in vitro determined parameters and a pharmacokinetic model based on in vivo pharmacokinetic data. Using this model, we investigated in silico the impact of biochemical properties of anti-EGFR antibodies on their F(ab)-mediated inhibitory effect. The multi-level model suggests that the F(ab)-mediated inhibitory effect saturates with increasing drug-receptor affinity, thereby limiting the impact of increasing antibody affinity on improving the effect. This indicates that observed differences in the therapeutic effects of high affinity antibodies in the market and in clinical development may result mainly from Fc-mediated indirect mechanisms such as antibody-dependent cell cytotoxicity.

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.

Regular Soda Policies, School Availability, and High School Student Consumption

PubMed Central

Terry-McElrath, Yvonne M.; Chriqui, Jamie F.; O’Malley, Patrick M.; Chaloupka, Frank J.; Johnston, Lloyd D.

2014-01-01

Background Beginning in the 2014–2015 school year, all U.S. schools participating in federally reimbursable meal programs are required to implement new nutrition standards for items sold in competitive venues. Multilevel mediation modeling examining direct, mediated, and indirect pathways between policy, availability, and student consumption might provide insight into possible outcomes of implementing aspects of the new standards. Purpose To employ multilevel mediation modeling using state- and school district–level policies mandating school soda bans, school soda availability, and student soda consumption. Methods The 2010–2012 Monitoring the Future surveys obtained nationally representative data on high school student soda consumption; school administrators provided school soda availability data. State laws and district policies were compiled and coded. Analyses conducted in 2014 controlled for state-, school-, and student-level characteristics. Results State–district–school models found that state bans were associated with significantly lower school soda availability (c, p<0.05) but district bans showed no significant associations. No significant direct, mediated, or indirect associations between state policy and student consumption were observed for the overall sample. Among African American high school students, state policy was associated directly with significantly lower school soda availability (a, p<0.01), and—indirectly through lower school availability—with significantly lower soda consumption (a*b, p<0.05). Conclusions These analyses indicate state policy focused on regular soda strongly affected school soda availability, and worked through changes in school availability to decrease soda consumption among African American students, but not the overall population. PMID:25576493

A d-statistic for single-case designs that is equivalent to the usual between-groups d-statistic.

PubMed

Shadish, William R; Hedges, Larry V; Pustejovsky, James E; Boyajian, Jonathan G; Sullivan, Kristynn J; Andrade, Alma; Barrientos, Jeannette L

2014-01-01

We describe a standardised mean difference statistic (d) for single-case designs that is equivalent to the usual d in between-groups experiments. We show how it can be used to summarise treatment effects over cases within a study, to do power analyses in planning new studies and grant proposals, and to meta-analyse effects across studies of the same question. We discuss limitations of this d-statistic, and possible remedies to them. Even so, this d-statistic is better founded statistically than other effect size measures for single-case design, and unlike many general linear model approaches such as multilevel modelling or generalised additive models, it produces a standardised effect size that can be integrated over studies with different outcome measures. SPSS macros for both effect size computation and power analysis are available.

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

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

SPSS and SAS programs for addressing interdependence and basic levels-of-analysis issues in psychological data.

PubMed

O'Connor, Brian P

2004-02-01

Levels-of-analysis issues arise whenever individual-level data are collected from more than one person from the same dyad, family, classroom, work group, or other interaction unit. Interdependence in data from individuals in the same interaction units also violates the independence-of-observations assumption that underlies commonly used statistical tests. This article describes the data analysis challenges that are presented by these issues and presents SPSS and SAS programs for conducting appropriate analyses. The programs conduct the within-and-between-analyses described by Dansereau, Alutto, and Yammarino (1984) and the dyad-level analyses described by Gonzalez and Griffin (1999) and Griffin and Gonzalez (1995). Contrasts with general multilevel modeling procedures are then discussed.

The Number of Feedbacks Needed for Reliable Evaluation. A Multilevel Analysis of the Reliability, Stability and Generalisability of Students' Evaluation of Teaching

ERIC Educational Resources Information Center

Rantanen, Pekka

2013-01-01

A multilevel analysis approach was used to analyse students' evaluation of teaching (SET). The low value of inter-rater reliability stresses that any solid conclusions on teaching cannot be made on the basis of single feedbacks. To assess a teacher's general teaching effectiveness, one needs to evaluate four randomly chosen course implementations.…

An empirical study of multidimensional fidelity of COMPASS consultation.

PubMed

Wong, Venus; Ruble, Lisa A; McGrew, John H; Yu, Yue

2018-06-01

Consultation is essential to the daily practice of school psychologists (National Association of School Psychologist, 2010). Successful consultation requires fidelity at both the consultant (implementation) and consultee (intervention) levels. We applied a multidimensional, multilevel conception of fidelity (Dunst, Trivette, & Raab, 2013) to a consultative intervention called the Collaborative Model for Promoting Competence and Success (COMPASS) for students with autism. The study provided 3 main findings. First, multidimensional, multilevel fidelity is a stable construct and increases over time with consultation support. Second, mediation analyses revealed that implementation-level fidelity components had distant, indirect effects on student Individualized Education Program (IEP) outcomes. Third, 3 fidelity components correlated with IEP outcomes: teacher coaching responsiveness at the implementation level, and teacher quality of delivery and student responsiveness at the intervention levels. Implications and future directions are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Ecological influences of early childhood obesity: a multilevel analysis.

PubMed

Boonpleng, Wannaporn; Park, Chang Gi; Gallo, Agatha M; Corte, Colleen; McCreary, Linda; Bergren, Martha Dewey

2013-07-01

This study aims to determine the contributing factors for early childhood overweight/obesity within the contexts of the child's home, school, and community, and to determine how much each of the ecological contexts contributes to childhood overweight/obesity. The framework was developed from Bronfenbrenner's ecological systems theory. Data for 2,100 children from the Early Childhood Longitudinal Study, Birth Cohort, were used in a series of multilevel modeling analyses. There was significant variation in childhood overweight/obesity by school and community. The majority of variation in childhood overweight/obesity was explained by the child and family factors in addition to school and community factors. Explained variance of childhood overweight/obesity at the school level was 27% and at the community level, 2%. The variance composition at children's family level alone was 71%. Therefore, overweight/obesity prevention efforts should focus primarily on child, family, and school factors and then community factors, to be more effective.

Longitudinal Trajectories of Parental Involvement in Type 1 Diabetes and Adolescents’ Adherence

PubMed Central

King, Pamela S.; Berg, Cynthia A.; Butner, Jonathan; Butler, Jorie M.; Wiebe, Deborah J.

2016-01-01

Objective The purpose of this study was to examine longitudinal trajectories of parental involvement and adolescent adherence to the Type 1 diabetes regimen, to determine whether changes in multiple facets of parental involvement over time predicted subsequent changes in adolescents’ adherence, and to examine whether adolescent self-efficacy mediated the effect of parental involvement on adherence. Method Two hundred fifty-two adolescents (M age = 12.49 years, SD = 1.53; 53.6% females) diagnosed with Type 1 diabetes mellitus, their mothers, and 188 fathers were enrolled in a 2.5-year longitudinal study. Across 5 time points, up to 252 adolescents and their parents completed measures of adherence, parental involvement (diabetes monitoring, behavioral involvement in diabetes management, and acceptance), and adolescent diabetes self-efficacy. Results Using multilevel modeling, analyses indicated significant average declines over time in adherence and most indicators of parental involvement. Lagged multilevel models indicated that declines in mothers’ and fathers’ acceptance and diabetes monitoring predicted subsequent declines in adolescents’ adherence. Additional analyses revealed that longitudinal associations between both maternal acceptance and diabetes monitoring and subsequent adolescent adherence were mediated by adolescents’ self-efficacy. Conclusions Results of this study, which were largely consistent across reporters, highlight the importance of maintaining parental involvement in diabetes across adolescence and suggest that parental involvement is beneficial for adolescents’ adherence, in part, because it contributes to higher self-efficacy for diabetes management among adolescents. PMID:23795709

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

Neighborhood socioeconomic characteristics and differences in the availability of healthy food stores and restaurants in Sao Paulo, Brazil.

PubMed

Duran, Ana Clara; Diez Roux, Ana V; Latorre, Maria do Rosario D O; Jaime, Patricia Constante

2013-09-01

Differential access to healthy foods has been hypothesized to contribute to health disparities, but evidence from low and middle-income countries is still scarce. This study examines whether the access of healthy foods varies across store types and neighborhoods of different socioeconomic statuses (SES) in a large Brazilian city. A cross-sectional study was conducted in 2010-2011 across 52 census tracts. Healthy food access was measured by a comprehensive in-store data collection, summarized into two indexes developed for retail food stores (HFSI) and restaurants (HMRI). Descriptive analyses and multilevel models were used to examine associations of store type and neighborhood SES with healthy food access. Fast food restaurants were more likely to be located in low SES neighborhoods whereas supermarkets and full service restaurants were more likely to be found in higher SES neighborhoods. Multilevel analyses showed that both store type and neighborhood SES were independently associated with in-store food measures. We found differences in the availability of healthy food stores and restaurants in Sao Paulo city favoring middle and high SES neighborhoods. © 2013 Elsevier Ltd. All rights reserved.

The Importance of Team Health Climate for Health-Related Outcomes of White-Collar Workers.

PubMed

Schulz, Heiko; Zacher, Hannes; Lippke, Sonia

2017-01-01

Occupational health researchers and practitioners have mainly focused on the individual and organizational levels, whereas the team level has been largely neglected. In this study, we define team health climate as employees' shared perceptions of the extent to which their team is concerned, cares, and communicates about health issues. Based on climate, signaling, and social exchange theories, we examined a multilevel model of team health climate and its relationships with five well-established health-related outcomes (i.e., subjective general health, psychosomatic complaints, mental health, work ability, and presenteeism). Results of multilevel analyses of data provided by 6,449 employees in 621 teams of a large organization showed that team health climate is positively related to subjective general health, mental health, and work ability, and negatively related to presenteeism, above and beyond the effects of team size, age, job tenure, job demands, job control, and employees' individual perceptions of health climate. Moreover, additional analyses showed that a positive team health climate buffered the negative relationship between employee age and work ability. Implications for future research on team health climate and suggestions for occupational health interventions in teams are discussed.

The Importance of Team Health Climate for Health-Related Outcomes of White-Collar Workers

PubMed Central

Schulz, Heiko; Zacher, Hannes; Lippke, Sonia

2017-01-01

Occupational health researchers and practitioners have mainly focused on the individual and organizational levels, whereas the team level has been largely neglected. In this study, we define team health climate as employees’ shared perceptions of the extent to which their team is concerned, cares, and communicates about health issues. Based on climate, signaling, and social exchange theories, we examined a multilevel model of team health climate and its relationships with five well-established health-related outcomes (i.e., subjective general health, psychosomatic complaints, mental health, work ability, and presenteeism). Results of multilevel analyses of data provided by 6,449 employees in 621 teams of a large organization showed that team health climate is positively related to subjective general health, mental health, and work ability, and negatively related to presenteeism, above and beyond the effects of team size, age, job tenure, job demands, job control, and employees’ individual perceptions of health climate. Moreover, additional analyses showed that a positive team health climate buffered the negative relationship between employee age and work ability. Implications for future research on team health climate and suggestions for occupational health interventions in teams are discussed. PMID:28194126

Executive functioning as a mediator of conduct problems prevention in children of homeless families residing in temporary supportive housing: a parallel process latent growth modeling approach.

PubMed

Piehler, Timothy F; Bloomquist, Michael L; August, Gerald J; Gewirtz, Abigail H; Lee, Susanne S; Lee, Wendy S C

2014-01-01

A culturally diverse sample of formerly homeless youth (ages 6-12) and their families (n = 223) participated in a cluster randomized controlled trial of the Early Risers conduct problems prevention program in a supportive housing setting. Parents provided 4 annual behaviorally-based ratings of executive functioning (EF) and conduct problems, including at baseline, over 2 years of intervention programming, and at a 1-year follow-up assessment. Using intent-to-treat analyses, a multilevel latent growth model revealed that the intervention group demonstrated reduced growth in conduct problems over the 4 assessment points. In order to examine mediation, a multilevel parallel process latent growth model was used to simultaneously model growth in EF and growth in conduct problems along with intervention status as a covariate. A significant mediational process emerged, with participation in the intervention promoting growth in EF, which predicted negative growth in conduct problems. The model was consistent with changes in EF fully mediating intervention-related changes in youth conduct problems over the course of the study. These findings highlight the critical role that EF plays in behavioral change and lends further support to its importance as a target in preventive interventions with populations at risk for conduct problems.

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.

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…

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

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.

Governance Dynamics and the Application of the Multilevel Governance Approach in Vocational Education and Training (VET) in the European Neighbourhood Countries: The Case of the ENPI South Region

ERIC Educational Resources Information Center

Galvin Arribas, J. Manuel

2016-01-01

This article analyses moves towards good multilevel governance approaches in Vocational Education and Training (VET) as an effective way to improve VET policy making in transition and developing countries, focusing on the Southern Neighbourhood of the EU (ENPI South). The centralised approaches in public administration and to VET governance still…

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.

Utility of the theory of reasoned action and theory of planned behavior for predicting Chinese adolescent smoking.

PubMed

Guo, Qian; Johnson, C Anderson; Unger, Jennifer B; Lee, Liming; Xie, Bin; Chou, Chih-Ping; Palmer, Paula H; Sun, Ping; Gallaher, Peggy; Pentz, MaryAnn

2007-05-01

One third of smokers worldwide live in China. Identifying predictors of smoking is important for prevention program development. This study explored whether the Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB) predict adolescent smoking in China. Data were obtained from 14,434 middle and high school students (48.6% boys, 51.4% girls) in seven geographically varied cities in China. TRA and TPB were tested by multilevel mediation modeling, and compared by multilevel analyses and likelihood ratio tests. Perceived behavioral control was tested as a main effect in TPB and a moderation effect in TRA. The mediation effects of smoking intention were supported in both models (p<0.001). TPB accounted for significantly more variance than TRA (p<0.001). Perceived behavioral control significantly interacted with attitudes and social norms in TRA (p<0.001). Therefore, TRA and TPB are applicable to China to predict adolescent smoking. TPB is superior to TRA for the prediction and TRA can better predict smoking among students with lower than higher perceived behavioral control.

Do high-commitment work systems affect creativity? A multilevel combinational approach to employee creativity.

PubMed

Chang, Song; Jia, Liangding; Takeuchi, Riki; Cai, Yahua

2014-07-01

In this article, some information about the data used in the article and a citation were not included. The details of the corrections are provided.] This study uses 3-level, 2-wave time-lagged data from a random sample of 55 high-technology firms, 238 teams, and 1,059 individuals in China to investigate a multilevel combinational model of employee creativity. First, we hypothesize that firm (macrolevel) high-commitment work systems are conducive to individual (microlevel) creativity. Furthermore, we hypothesize that this positive crosslevel main impact may be combined with middle-level (mesolevel) factors, including team cohesion and team task complexity, such that the positive impact of firm high-commitment work systems on individual creativity is stronger when team cohesion is high and the team task more complex. The findings from random coefficient modeling analyses provide support for our hypotheses. These sets of results offer novel insight into how firms can use macrolevel and mesolevel contextual variables in a systematic manner to promote employee creativity in the workplace, despite its complex nature.

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.

Reducing Alaska Native paediatric oral health disparities: a systematic review of oral health interventions and a case study on multilevel strategies to reduce sugar-sweetened beverage intake

PubMed Central

Chi, Donald L.

2013-01-01

Background Tooth decay is the most common paediatric disease and there is a serious paediatric tooth decay epidemic in Alaska Native communities. When untreated, tooth decay can lead to pain, infection, systemic health problems, hospitalisations and in rare cases death, as well as school absenteeism, poor grades and low quality-of-life. The extent to which population-based oral health interventions have been conducted in Alaska Native paediatric populations is unknown. Objective To conduct a systematic review of oral health interventions aimed at Alaska Native children below age 18 and to present a case study and conceptual model on multilevel intervention strategies aimed at reducing sugar-sweetened beverage (SSB) intake among Alaska Native children. Design Based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Statement, the terms “Alaska Native”, “children” and “oral health” were used to search Medline, Embase, Web of Science, GoogleScholar and health foundation websites (1970–2012) for relevant clinical trials and evaluation studies. Results Eighty-five studies were found in Medline, Embase and Web of Science databases and there were 663 hits in GoogleScholar. A total of 9 publications were included in the qualitative review. These publications describe 3 interventions that focused on: reducing paediatric tooth decay by educating families and communities; providing dental chemotherapeutics to pregnant women; and training mid-level dental care providers. While these approaches have the potential to improve the oral health of Alaska Native children, there are unique challenges regarding intervention acceptability, reach and sustainability. A case study and conceptual model are presented on multilevel strategies to reduce SSB intake among Alaska Native children. Conclusions Few oral health interventions have been tested within Alaska Native communities. Community-centred multilevel interventions are promising approaches to improve the oral and systemic health of Alaska Native children. Future investigators should evaluate the feasibility of implementing multilevel interventions and policies within Alaska Native communities as a way to reduce children's health disparities. PMID:24377091

Reducing Alaska Native paediatric oral health disparities: a systematic review of oral health interventions and a case study on multilevel strategies to reduce sugar-sweetened beverage intake.

PubMed

Chi, Donald L

2013-01-01

Tooth decay is the most common paediatric disease and there is a serious paediatric tooth decay epidemic in Alaska Native communities. When untreated, tooth decay can lead to pain, infection, systemic health problems, hospitalisations and in rare cases death, as well as school absenteeism, poor grades and low quality-of-life. The extent to which population-based oral health interventions have been conducted in Alaska Native paediatric populations is unknown. To conduct a systematic review of oral health interventions aimed at Alaska Native children below age 18 and to present a case study and conceptual model on multilevel intervention strategies aimed at reducing sugar-sweetened beverage (SSB) intake among Alaska Native children. Based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Statement, the terms "Alaska Native", "children" and "oral health" were used to search Medline, Embase, Web of Science, GoogleScholar and health foundation websites (1970-2012) for relevant clinical trials and evaluation studies. Eighty-five studies were found in Medline, Embase and Web of Science databases and there were 663 hits in GoogleScholar. A total of 9 publications were included in the qualitative review. These publications describe 3 interventions that focused on: reducing paediatric tooth decay by educating families and communities; providing dental chemotherapeutics to pregnant women; and training mid-level dental care providers. While these approaches have the potential to improve the oral health of Alaska Native children, there are unique challenges regarding intervention acceptability, reach and sustainability. A case study and conceptual model are presented on multilevel strategies to reduce SSB intake among Alaska Native children. Few oral health interventions have been tested within Alaska Native communities. Community-centred multilevel interventions are promising approaches to improve the oral and systemic health of Alaska Native children. Future investigators should evaluate the feasibility of implementing multilevel interventions and policies within Alaska Native communities as a way to reduce children's health disparities.

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…

An on-demand provision model for geospatial multisource information with active self-adaption services

NASA Astrophysics Data System (ADS)

Fan, Hong; Li, Huan

2015-12-01

Location-related data are playing an increasingly irreplaceable role in business, government and scientific research. At the same time, the amount and types of data are rapidly increasing. It is a challenge how to quickly find required information from this rapidly growing volume of data, as well as how to efficiently provide different levels of geospatial data to users. This paper puts forward a data-oriented access model for geographic information science data. First, we analyze the features of GIS data including traditional types such as vector and raster data and new types such as Volunteered Geographic Information (VGI). Taking into account these analyses, a classification scheme for geographic data is proposed and TRAFIE is introduced to describe the establishment of a multi-level model for geographic data. Based on this model, a multi-level, scalable access system for geospatial information is put forward. Users can select different levels of data according to their concrete application needs. Pull-based and push-based data access mechanisms based on this model are presented. A Service Oriented Architecture (SOA) was chosen for the data processing. The model of this study has been described by providing decision-making process of government departments with a simulation of fire disaster data collection. The use case shows this data model and the data provision system is flexible and has good adaptability.

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

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.

Familial violence socialization in childhood and later life approval of corporal punishment: a cross-cultural perspective.

PubMed

Douglas, Emily M

2006-01-01

The use of corporal punishment has been associated with several negative outcomes for children. As a result, scholars have begun to study factors that are associated with the approval of corporal punishment. Using data from the International Dating Violence Study, the author implemented analysis of covariance and multilevel modeling analyses to determine that there were significant associations among culture, personal and group experiences of familial violence socialization, and attitudes about corporal punishment. 2006 APA, all rights reserved

Research on MMC-SST Oriented AC/DC Distribution System

NASA Astrophysics Data System (ADS)

Xie, Xifeng; Shi, Hua; Zuo, Jianglin; Zhang, Zhigang

2018-01-01

A modular multilevel converter-solid state transformer (MMC-SST) oriented AC/DC Distribution System is designed. Firstly, the topology structure is introduced, MMC is adopted in the input stage, multiple DC-DC converters are adopted in the isolation stage, and a Three-Phase Four-Leg inverter is adopted in the output stage. Then, the control strategy is analysed. Finally, simulation model and an experimental prototype of MMC-SST are built, simulation and experimental results show that topology and control strategy of MMC-SST are feasible.

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).

The multi-level perspective analysis: Indonesia geothermal energy transition study

NASA Astrophysics Data System (ADS)

Wisaksono, A.; Murphy, J.; Sharp, J. H.; Younger, P. L.

2018-01-01

The study adopts a multi-level perspective in technology transition to analyse how the transition process in the development of geothermal energy in Indonesia is able to compete against the incumbent fossil-fuelled energy sources. Three levels of multi-level perspective are socio-technical landscape (ST-landscape), socio-technical regime (ST-regime) and niche innovations in Indonesia geothermal development. The identification, mapping and analysis of the dynamic relationship between each level are the important pillars of the multi-level perspective framework. The analysis considers the set of rules, actors and controversies that may arise in the technological transition process. The identified geothermal resource risks are the basis of the emerging geothermal technological innovations in Indonesian geothermal. The analysis of this study reveals the transition pathway, which yields a forecast for the Indonesian geothermal technology transition in the form of scenarios and probable impacts.

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. ...

Parameter Recovery for the 1-P HGLLM with Non-Normally Distributed Level-3 Residuals

ERIC Educational Resources Information Center

Kara, Yusuf; Kamata, Akihito

2017-01-01

A multilevel Rasch model using a hierarchical generalized linear model is one approach to multilevel item response theory (IRT) modeling and is referred to as a one-parameter hierarchical generalized linear logistic model (1-P HGLLM). Although it has the flexibility to model nested structure of data with covariates, the model assumes the normality…

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.

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.

Daily minority stress and affect among gay and bisexual men: A 30-day diary study.

PubMed

Eldahan, Adam I; Pachankis, John E; Jonathon Rendina, H; Ventuneac, Ana; Grov, Christian; Parsons, Jeffrey T

2016-01-15

This study examined the time-variant association between daily minority stress and daily affect among gay and bisexual men. Tests of time-lagged associations allow for a stronger causal examination of minority stress-affect associations compared with static assessments. Multilevel modeling allows for comparison of associations between minority stress and daily affect when minority stress is modeled as a between-person factor and a within-person time-fluctuating state. 371 gay and bisexual men in New York City completed a 30-day daily diary, recording daily experiences of minority stress and positive affect (PA), negative affect (NA), and anxious affect (AA). Multilevel analyses examined associations between minority stress and affect in both same-day and time-lagged analyses, with minority stress assessed as both a between-person factor and a within-person state. Daily minority stress, modeled as both a between-person and within-person construct, significantly predicted lower PA and higher NA and AA. Daily minority stress also predicted lower subsequent-day PA and higher subsequent-day NA and AA. Self-report assessments and the unique sample may limit generalizability of this study. The time-variant association between sexual minority stress and affect found here substantiates the basic tenet of minority stress theory with a fine-grained analysis of gay and bisexual men's daily experience. Time-lagged effects suggest a potentially causal pathway between minority stress as a social determinant of mood and anxiety disorder symptoms among gay and bisexual men. When modeled as both a between-person factor and within-person state, minority stress demonstrated expected patterns with affect. Copyright © 2015 Elsevier B.V. All rights reserved.

Quality of life in people aged 65+ in Europe: associated factors and models of social welfare-analysis of data from the SHARE project (Wave 5).

PubMed

Conde-Sala, Josep L; Portellano-Ortiz, Cristina; Calvó-Perxas, Laia; Garre-Olmo, Josep

2017-04-01

To analyse the clinical, sociodemographic and socioeconomic factors that influence perceived quality of life (QoL) in a community sample of 33,241 people aged 65+ and to examine the relationship with models of social welfare in Europe. This was a cross-sectional study of data from Wave 5 (2013) of the Survey of Health, Ageing and Retirement in Europe (SHARE). The instruments used in the present study were as follows: sociodemographic data, CASP-12 (QoL), EURO-D (depression), indicators of life expectancy and suicide (WHO), and economic indicators (World Bank). Statistical analysis included bivariate and multilevel analyses. In the multilevel analysis, greater satisfaction in life, less depression, sufficient income, better subjective health, physical activity, an absence of functional impairment, younger age and participation in activities were associated with better QoL in all countries. More education was only associated with higher QoL in Eastern European and Mediterranean countries, and only in the latter was caring for grandchildren also related to better QoL. Socioeconomic indicators were better and QoL scores higher (mean = 38.5 ± 5.8) in countries that had a social democratic (Nordic cluster) or corporatist model (Continental cluster) of social welfare, as compared to Eastern European and Mediterranean countries, which were characterized by poorer socioeconomic conditions, more limited social welfare provision and lower QoL scores (mean = 33.5 ± 6.4). Perceived quality-of-life scores are consistent with the sociodemographic and clinical characteristics of participants, as well as with the socioeconomic indicators and models of social welfare of the countries in which they live.

Daily Minority Stress and Affect among Gay and Bisexual Men: A 30-day Diary Study

PubMed Central

Eldahan, Adam I.; Pachankis, John E.; Rendina, H. Jonathon; Ventuneac, Ana; Grov, Christian; Parsons, Jeffrey T.

2015-01-01

Background This study examined the time-variant association between daily minority stress and daily affect among gay and bisexual men. Tests of time-lagged associations allow for a stronger causal examination of minority stress-affect associations compared with static assessments. Multilevel modeling allows for comparison of associations between minority stress and daily affect when minority stress is modeled as a between-person factor and a within-person time-fluctuating state. Methods 371 gay and bisexual men in New York City completed a 30-day daily diary, recording daily experiences of minority stress and positive affect (PA), negative affect (NA), and anxious affect (AA). Multilevel analyses examined associations between minority stress and affect in both same-day and time-lagged analyses, with minority stress assessed as both a between-person factor and a within-person state. Results Daily minority stress, modeled as both a between-person and within-person construct, significantly predicted lower PA and higher NA and AA. Daily minority stress also predicted lower subsequent-day PA and higher subsequent-day NA and AA. Limitations Self-report assessments and the unique sample may limit generalizability of this study. Conclusions The time-variant association between sexual minority stress and affect found here substantiates the basic tenet of minority stress theory with a fine-grained analysis of gay and bisexual men’s daily experience. Time-lagged effects suggest a potentially causal pathway between minority stress as a social determinant of mood and anxiety disorder symptoms among gay and bisexual men. When modeled as both a between-person factor and within-person state, minority stress demonstrated expected patterns with affect. PMID:26625095

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.

Parent involvement in beginning primary school: Correlates and changes in involvement across the first two years of school in a New Zealand sample.

PubMed

McDowall, Philippa S; Taumoepeau, Mele; Schaughency, Elizabeth

2017-06-01

This study described the relations of parents' and teachers' beliefs and attitudes to forms of parents' involvement in children's first two years of primary school. Parents of children in their first year of primary school (age 5) were recruited from 12 classrooms within four schools in New Zealand; 196 families participated in their child's first year, and 124 families continued to participate in their child's second school year. Parents completed the Family-Involvement Questionnaire, New Zealand, and we archivally collected parent-documented children's oral reading homework. Teachers' rated helpfulness of parents' involvement at school (level 2) and parents' rated teacher invitations to be involved and their perceived time and energy (level 1) contributed to school-based involvement in Year 1 in multilevel models, with parents' rated teacher invitations for involvement also found to predict Year 1 home-school communication in regression analyses. Contributors to Year 1 child-parent reading in multilevel models included level 1 predictors of two or more adults in the home and parents' perceived time and energy. Longitudinal analyses suggested both consistency and change in each form of involvement from Year 1 to Year 2, with increases in each form of involvement found to be associated with increases in parents' and/or teachers' views about involvement in Year 2 in cross-sectional time-series analyses. Implications for schools wanting to engage families are that parents' involvement in children's schooling may be influenced by parents' perceptions of their capacity, teachers' engagement efforts, and the school's climate for involvement. This is a special issue paper "Family Engagement in Education and Intervention". Copyright © 2017 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

A multilevel perspective to explain recycling behaviour in communities.

PubMed

Tabernero, Carmen; Hernández, Bernardo; Cuadrado, Esther; Luque, Bárbara; Pereira, Cícero R

2015-08-15

Previous research on the motivation for environmentally responsible behaviour has focused mainly on individual variables, rather than organizational or collective variables. Therefore, the results of those studies are hardly applicable to environmental management. This study considers individual, collective, and organizational variables together that contribute to the management of environmental waste. The main aim is to identify, through the development of a multilevel model, those predictive variables of recycling behaviour that help organizations to increase the recycling rates in their communities. Individual (age, gender, educational level, self-efficacy with respect to residential recycling, individual recycling behaviour), organizational (satisfaction with the quality of the service provided by a recycling company), and collective (community recycling rates, number of inhabitants, community efficacy beliefs) motivational factors relevant to recycling behaviour were analysed. A sample of 1501 residents from 55 localities was surveyed. The results of multilevel analyses indicated that there was significant variability within and between localities. Interactions between variables at the level of the individual (e.g. satisfaction with service quality) and variables at the level of the collective (e.g. community efficacy) predicted recycling behaviour in localities with low and high community recycling rates and large and small populations. The interactions showed that the relationship between self-efficacy and recycling is stronger in localities with weak community efficacy beliefs than in communities with strong beliefs. The findings show that the relationship between satisfaction with service quality and recycling behaviour is stronger in localities with strong community efficacy beliefs than in communities with weaker beliefs and a smaller population. The results are discussed accordingly in relation to theory and possible contribution to waste management. Those findings may be incorporated in national and international environmental policies in order to promote environmentally responsible behaviour in citizenship. Copyright © 2015 Elsevier Ltd. All rights reserved.

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,…

[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.

Towards people-centred health systems: a multi-level framework for analysing primary health care governance in low- and middle-income countries.

PubMed

Abimbola, Seye; Negin, Joel; Jan, Stephen; Martiniuk, Alexandra

2014-09-01

Although there is evidence that non-government health system actors can individually or collectively develop practical strategies to address primary health care (PHC) challenges in the community, existing frameworks for analysing health system governance largely focus on the role of governments, and do not sufficiently account for the broad range of contribution to PHC governance. This is important because of the tendency for weak governments in low- and middle-income countries (LMICs). We present a multi-level governance framework for use as a thinking guide in analysing PHC governance in LMICs. This framework has previously been used to analyse the governance of common-pool resources such as community fisheries and irrigation systems. We apply the framework to PHC because, like common-pool resources, PHC facilities in LMICs tend to be commonly owned by the community such that individual and collective action is often required to avoid the 'tragedy of the commons'-destruction and degradation of the resource resulting from lack of concern for its continuous supply. In the multi-level framework, PHC governance is conceptualized at three levels, depending on who influences the supply and demand of PHC services in a community and how: operational governance (individuals and providers within the local health market), collective governance (community coalitions) and constitutional governance (governments at different levels and other distant but influential actors). Using the example of PHC governance in Nigeria, we illustrate how the multi-level governance framework offers a people-centred lens on the governance of PHC in LMICs, with a focus on relations among health system actors within and between levels of governance. We demonstrate the potential impact of health system actors functioning at different levels of governance on PHC delivery, and how governance failure at one level can be assuaged by governance at another level. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2014; all rights reserved.

Towards people-centred health systems: a multi-level framework for analysing primary health care governance in low- and middle-income countries

PubMed Central

Abimbola, Seye; Negin, Joel; Jan, Stephen; Martiniuk, Alexandra

2014-01-01

Although there is evidence that non-government health system actors can individually or collectively develop practical strategies to address primary health care (PHC) challenges in the community, existing frameworks for analysing health system governance largely focus on the role of governments, and do not sufficiently account for the broad range of contribution to PHC governance. This is important because of the tendency for weak governments in low- and middle-income countries (LMICs). We present a multi-level governance framework for use as a thinking guide in analysing PHC governance in LMICs. This framework has previously been used to analyse the governance of common-pool resources such as community fisheries and irrigation systems. We apply the framework to PHC because, like common-pool resources, PHC facilities in LMICs tend to be commonly owned by the community such that individual and collective action is often required to avoid the ‘tragedy of the commons’—destruction and degradation of the resource resulting from lack of concern for its continuous supply. In the multi-level framework, PHC governance is conceptualized at three levels, depending on who influences the supply and demand of PHC services in a community and how: operational governance (individuals and providers within the local health market), collective governance (community coalitions) and constitutional governance (governments at different levels and other distant but influential actors). Using the example of PHC governance in Nigeria, we illustrate how the multi-level governance framework offers a people-centred lens on the governance of PHC in LMICs, with a focus on relations among health system actors within and between levels of governance. We demonstrate the potential impact of health system actors functioning at different levels of governance on PHC delivery, and how governance failure at one level can be assuaged by governance at another level. PMID:25274638

A multi-level modeling approach examining PTSD symptom reduction during prolonged exposure therapy: moderating effects of number of trauma types experienced, having an HIV-related index trauma, and years since HIV diagnosis among HIV-positive adults.

PubMed

Junglen, Angela G; Smith, Brian C; Coleman, Jennifer A; Pacella, Maria L; Boarts, Jessica M; Jones, Tracy; Feeny, Norah C; Ciesla, Jeffrey A; Delahanty, Douglas L

2017-11-01

People living with HIV (PLWH) have extensive interpersonal trauma histories and higher rates of posttraumatic stress disorder (PTSD) than the general population. Prolonged exposure (PE) therapy is efficacious in reducing PTSD across a variety of trauma samples; however, research has not examined factors that influence how PTSD symptoms change during PE for PLWH. Using multi-level modeling, we examined the potential moderating effect of number of previous trauma types experienced, whether the index trauma was HIV-related or not, and years since HIV diagnosis on PTSD symptom reduction during a 10-session PE protocol in a sample of 51 PLWH. In general, PTSD symptoms decreased linearly throughout the PE sessions. Experiencing more previous types of traumatic events was associated with a slower rate of PTSD symptom change. In addition, LOCF analyses found that participants with a non-HIV-related versus HIV-related index trauma had a slower rate of change for PTSD symptoms over the course of PE. However, analyses of raw data decreased this finding to marginal. Years since HIV diagnosis did not impact PTSD symptom change. These results provide a better understanding of how to tailor PE to individual clients and aid clinicians in approximating the rate of symptom alleviation. Specifically, these findings underscore the importance of accounting for trauma history and index trauma type when implementing a treatment plan for PTSD in PLWH.

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…

Estimating multilevel logistic regression models when the number of clusters is low: a comparison of different statistical software procedures.

PubMed

Austin, Peter C

2010-04-22

Multilevel logistic regression models are increasingly being used to analyze clustered data in medical, public health, epidemiological, and educational research. Procedures for estimating the parameters of such models are available in many statistical software packages. There is currently little evidence on the minimum number of clusters necessary to reliably fit multilevel regression models. We conducted a Monte Carlo study to compare the performance of different statistical software procedures for estimating multilevel logistic regression models when the number of clusters was low. We examined procedures available in BUGS, HLM, R, SAS, and Stata. We found that there were qualitative differences in the performance of different software procedures for estimating multilevel logistic models when the number of clusters was low. Among the likelihood-based procedures, estimation methods based on adaptive Gauss-Hermite approximations to the likelihood (glmer in R and xtlogit in Stata) or adaptive Gaussian quadrature (Proc NLMIXED in SAS) tended to have superior performance for estimating variance components when the number of clusters was small, compared to software procedures based on penalized quasi-likelihood. However, only Bayesian estimation with BUGS allowed for accurate estimation of variance components when there were fewer than 10 clusters. For all statistical software procedures, estimation of variance components tended to be poor when there were only five subjects per cluster, regardless of the number of clusters.

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…

Seeing the forest and the trees: multilevel models reveal both species and community patterns

Treesearch

Michelle M. Jackson; Monica G. Turner; Scott M. Pearson; Anthony R. Ives

2012-01-01

Studies designed to understand species distributions and community assemblages typically use separate analytical approaches (e.g., logistic regression and ordination) to model the distribution of individual species and to relate community composition to environmental variation. Multilevel models (MLMs) offer a promising strategy for integrating species and community-...

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…

A multilevel meta-analysis of single-case and small-n research on interventions for reducing challenging behavior in persons with intellectual disabilities.

PubMed

Heyvaert, M; Maes, B; Van den Noortgate, W; Kuppens, S; Onghena, P

2012-01-01

The effectiveness of different interventions for challenging behavior (CB) in persons with intellectual disabilities (ID) was reviewed by means of a two-phase study. First, a systematic review of 137 meta-analyses and reviews on group-study interventions for CB in persons with ID was conducted. Based on this review, hypotheses concerning the effectiveness of divergent interventions for CB and concerning the impact of variables moderating treatment effectiveness were systematically generated. Second, these hypotheses were tested by means of a multilevel meta-analysis of single-case and small-n research. Two hundred and eighty-five studies reporting on 598 individuals were examined. The average treatment effect was large and statistically significant. However, this effect varied significantly over the included studies and participants. Compared to the meta-analyses and reviews focusing on group-studies in this research domain, the results of the present multilevel meta-analysis of single-case and small-n intervention research provided more detailed knowledge on which specific CB and intervention components moderate the interventions' effectiveness. Copyright © 2011 Elsevier Ltd. All rights reserved.

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…

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.

The Relative Salience of Daily and Enduring Influences on Off-Job Reactions to Work Stress.

PubMed

Calderwood, Charles; Ackerman, Phillip L

2016-12-01

Work stress is an important determinant of employee health and wellness. The occupational health community is recognizing that one contributor to these relationships may be the presence of negative off-job reactivity to work, which we argue involves continued thoughts directed towards work (cognitive reactivity), continued negative mood stemming from work (affective reactivity), and the alteration of post-work behaviours in response to work factors (behavioural reactivity). We explored the relative contributions of daily work stressors, affective traits, and subjective job stress perceptions to negative off-job reactivity. These relationships were evaluated in a study of hospital nurses (n = 75), who completed trait measures and then provided self-assessments of daily work stress and off-job reactions for four work days. The results of several multilevel analyses indicated that a main-effects model best described the data when predicting cognitive, affective, and behavioural reactivity from daily work stressors, affective traits, and subjective job stress perceptions. A series of multilevel dominance analyses revealed that subjective job stress perceptions dominated the prediction of behavioural reactivity, while trait negative affect dominated the prediction of affective reactivity. Theoretical implications and the relative salience of daily and enduring contributors to negative off-job reactivity are discussed. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Availability of reproductive healthcare services at schools and subsequent birth outcomes among adolescent mothers

PubMed Central

Madkour, Aubrey Spriggs; Xie, Yiqiong; Harville, Emily Wheeler

2016-01-01

BACKGROUND Adverse birth outcomes are more common among adolescent versus adult mothers, but little is known about school-based services that may improve birth outcomes in this group. METHODS Data from Waves I and IV of the National Longitudinal Study of Adolescent Health were analyzed. Girls and women who gave birth to singleton live infants after Wave I and before age 20, were still in secondary school while pregnant, and had complete data (N=402) were included. Mothers reported infants’ birthweight and gestational age. School administrators reported whether family planning counseling, diagnostic screening (including sexually transmitted diseases [STDs]), STD treatment, and prenatal/postpartum healthcare were provided on-site at school at Wave I. Multilevel models adjusted for individual and school characteristics were conducted. RESULTS Few schools offered reproductive healthcare services on-site. In multilevel analyses, availability of family planning counseling (Est. β=0.21, 95% confidence interval [CI] 0.04, 0.38) and prenatal/postpartum healthcare (Est. β=0.21, 95% CI 0.02, 0.40) were significantly associated with increased infant birthweight. No services examined were significantly associated with increased gestational age. CONCLUSIONS Some school-based reproductive health services may improve subsequent birth outcomes among adolescent mothers. Future analyses should examine the mechanisms by which services impact birth outcomes. PMID:27246673

Gender differences in body consciousness and substance use among high-risk adolescents.

PubMed

Black, David Scott; Sussman, Steve; Unger, Jennifer; Pokhrel, Pallav; Sun, Ping

2010-08-01

This study explores the association between private and public body consciousness and past 30-day cigarette, alcohol, marijuana, and hard drug use among adolescents. Self-reported data from alterative high school students in California were analyzed (N = 976) using multilevel regression models to account for student clustering within schools. Separate regression analyses were conducted for males and females. Both cross-sectional baseline data and one-year longitudinal prediction models indicated that body consciousness is associated with specific drug use categories differentially by gender. Findings suggest that body consciousness accounts for additional variance in substance use etiology not explained by previously recognized dispositional variables.

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…

Testing self-regulation interventions to increase walking using factorial randomized N-of-1 trials.

PubMed

Sniehotta, Falko F; Presseau, Justin; Hobbs, Nicola; Araújo-Soares, Vera

2012-11-01

To investigate the suitability of N-of-1 randomized controlled trials (RCTs) as a means of testing the effectiveness of behavior change techniques based on self-regulation theory (goal setting and self-monitoring) for promoting walking in healthy adult volunteers. A series of N-of-1 RCTs in 10 normal and overweight adults ages 19-67 (M = 36.9 years). We randomly allocated 60 days within each individual to text message-prompted daily goal-setting and/or self-monitoring interventions in accordance with a 2 (step-count goal prompt vs. alternative goal prompt) × 2 (self-monitoring: open vs. blinded Omron-HJ-113-E pedometer) factorial design. Aggregated data were analyzed using random intercept multilevel models. Single cases were analyzed individually. The primary outcome was daily pedometer step counts over 60 days. Single-case analyses showed that 4 participants significantly increased walking: 2 on self-monitoring days and 2 on goal-setting days, compared with control days. Six participants did not benefit from the interventions. In aggregated analyses, mean step counts were higher on goal-setting days (8,499.9 vs. 7,956.3) and on self-monitoring days (8,630.3 vs. 7,825.9). Multilevel analyses showed a significant effect of the self-monitoring condition (p = .01), the goal-setting condition approached significance (p = .08), and there was a small linear increase in walking over time (p = .03). N-of-1 randomized trials are a suitable means to test behavioral interventions in individual participants.

A multilevel approach to the relationship between birth order and intelligence.

PubMed

Wichman, Aaron L; Rodgers, Joseph Lee; MacCallum, Robert C

2006-01-01

Many studies show relationships between birth order and intelligence but use cross-sectional designs or manifest other threats to internal validity. Multilevel analyses with a control variable show that when these threats are removed, two major results emerge: (a) birth order has no significant influence on children's intelligence and (b) earlier reported birth order effects on intelligence are attributable to factors that vary between, not within, families. Analyses on 7- to 8 - and 13- to 14-year-old children from the National Longitudinal Survey of Youth support these conclusions. When hierarchical data structures, age variance of children, and within-family versus between-family variance sources are taken into account, previous research is seen in a new light.

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.

Multilevel models in the explanation of the relationship between safety climate and safe behavior.

PubMed

Cheyne, Alistair; Tomás, José M; Oliver, Amparo

2013-01-01

This study examines the relationships between components of organizational safety climate, including employee attitudes to organizational safety issues; perceptions of the physical working environment, and evaluations of worker engagement with safety issues; and relates these to self-reported levels of safety behavior. It attempts to explore the relationships between these variables in 1189 workers across 78 work groups in a large transportation organization. Evaluations of safety climate, the working environment and worker engagement, as well as safe behaviors, were collected using a self report questionnaire. The multilevel analysis showed that both levels of evaluation (the work group and the individual), and some cross-level interactions, were significant in explaining safe behaviors. Analyses revealed that a number of variables, at both levels, were associated with worker engagement and safe behaviors. The results suggest that, while individual evaluations of safety issues are important, there is also a role for the fostering of collective safety climates in encouraging safe behaviors and therefore reducing accidents.

A Bayesian Approach to More Stable Estimates of Group-Level Effects in Contextual Studies.

PubMed

Zitzmann, Steffen; Lüdtke, Oliver; Robitzsch, Alexander

2015-01-01

Multilevel analyses are often used to estimate the effects of group-level constructs. However, when using aggregated individual data (e.g., student ratings) to assess a group-level construct (e.g., classroom climate), the observed group mean might not provide a reliable measure of the unobserved latent group mean. In the present article, we propose a Bayesian approach that can be used to estimate a multilevel latent covariate model, which corrects for the unreliable assessment of the latent group mean when estimating the group-level effect. A simulation study was conducted to evaluate the choice of different priors for the group-level variance of the predictor variable and to compare the Bayesian approach with the maximum likelihood approach implemented in the software Mplus. Results showed that, under problematic conditions (i.e., small number of groups, predictor variable with a small ICC), the Bayesian approach produced more accurate estimates of the group-level effect than the maximum likelihood approach did.

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…

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.

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…

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

Nurses' practice environment and work-family conflict in relation to burn out: a multilevel modelling approach.

PubMed

Leineweber, Constanze; Westerlund, Hugo; Chungkham, Holendro Singh; Lindqvist, Rikard; Runesdotter, Sara; Tishelman, Carol

2014-01-01

To investigate associations between nurse work practice environment measured at department level and individual level work-family conflict on burnout, measured as emotional exhaustion, depersonalization and personal accomplishment among Swedish RNs. A multilevel model was fit with the individual RN at the 1st, and the hospital department at the 2nd level using cross-sectional RN survey data from the Swedish part of RN4CAST, an EU 7th framework project. The data analysed here is based on a national sample of 8,620 RNs from 369 departments in 53 hospitals. Generally, RNs reported high values of personal accomplishment and lower values of emotional exhaustion and depersonalization. High work-family conflict increased the risk for emotional exhaustion, but for neither depersonalization nor personal accomplishment. On department level adequate staffing and good leadership and support for nurses reduced the risk for emotional exhaustion and depersonalization. Personal accomplishment was statistically significantly related to staff adequacy. The findings suggest that adequate staffing, good leadership, and support for nurses are crucial for RNs' mental health. Our findings also highlight the importance of hospital managers developing policies and practices to facilitate the successful combination of work with private life for employees.

Daily stress, coping, and well-being in parents of children with autism: a multilevel modeling approach.

PubMed

Pottie, Colin G; Ingram, Kathleen M

2008-12-01

This study used a repeated daily measurement design to examine the direct and moderating effects of coping on daily psychological distress and well-being in parents of children with Autism Spectrum Disorders (ASD). Twice weekly over a 12-week period, 93 parents provided reports of their daily stress, coping responses, and end-of-day mood. Multilevel modeling analyses identified 5 coping responses (e.g., seeking support, positive reframing) that predicted increased daily positive mood and 4 (e.g., escape, withdrawal) that were associated with decreased positive mood. Similarly, 2 coping responses were associated with decreased daily negative mood and 5 predicted increased negative mood. The moderating effects of gender and the 11 coping responses were also examined. Gender did not moderate the daily coping?mood relationship, however 3 coping responses (emotional regulation, social support, and worrying) were found to moderate the daily stress?mood relationship. Additionally, ASD symptomatology, and time since an ASD diagnosis were not found to predict daily parental mood. This study is perhaps the first to identify coping responses that enhance daily well-being and mitigate daily distress in parents of children with ASD. Copyright 2008 APA, all rights reserved.

Co-occurrences Between Adolescent Substance Use and Academic Performance: School Context Inuences a Multilevel-Longitudinal Perspective

PubMed Central

Andrade, Fernando H.

2014-01-01

A growing body of literature has linked substance use and academic performance exploring substance use as a predictor of academic performance or vice versa. This study uses a different approach conceptualizing substance use and academic performance as parallel outcomes and exploring two topics: its multilevel-longitudinal association and school contextual effects on both outcomes. Using multilevel Confirmatory Factor Analysis and multilevel-longitudinal analyses, the empirical estimates relied on 7843 students nested in 114 schools (Add Health study). The main finding suggests that the correlation between substance use and academic performance was positive at the school level in contraposition to the negative relationship at the individual level. Additional findings suggest a positive effect of a school risk factor on substance use and a positive effect of academic pressure on academic performance. These findings represent a contribution to our understanding of how schools could affect the relationship between academic performance and substance use. PMID:25057764

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.

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…

Developmental Patterns in Decision-Making Autonomy across Middle Childhood and Adolescence: European American Parents’ Perspectives

PubMed Central

Wray-Lake, Laura; Crouter, Ann C.; McHale, Susan M.

2010-01-01

Longitudinal patterns in parents’ reports of youth decision-making autonomy from ages 9 to 20 were examined in a study of 201 European American families with two offspring. Multilevel modeling analyses revealed that decision-making autonomy increased gradually across middle childhood and adolescence before rising sharply in late adolescence. Social domain theory was supported by analyses of eight decision types spanning prudential, conventional, personal, and multifaceted domains. Decision making was higher for girls, youth whom parents perceived as easier to supervise, and youth with better educated parents. Firstborns and secondborns had different age-related trajectories of decision-making autonomy. Findings shed light on the developmental trajectories and family processes associated with adolescents’ fundamental task of gaining autonomy. PMID:20438465

The Relationship between Intimacy Change and Passion: A Dyadic Diary Study.

PubMed

Aykutoğlu, Bülent; Uysal, Ahmet

2017-01-01

In the current study we investigated the association between intimacy and passion by testing whether increases in intimacy generates passion (Baumeister and Bratslavsky, 1999). Furthermore, we examined whether there are partner effects in intimacy change and passion link. Couples ( N = 75) participated in a 14-day long diary study. Dyadic multilevel analyses with residualized intimacy change scores showed that both actors' and partners' intimacy change positively predicted actor's passion. However, analyses also showed that residualized passion change scores positively predicted intimacy. Although these findings provide some empirical evidence for the intimacy change model, in line with the previous research (Rubin and Campbell, 2012), they also suggest that it is not possible to discern whether intimacy increment generates passion or passion increment generates intimacy.

Sierra/Solid Mechanics 4.48 User's Guide.

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

Merewether, Mark Thomas; Crane, Nathan K; de Frias, Gabriel Jose

Sierra/SolidMechanics (Sierra/SM) is a Lagrangian, three-dimensional code for finite element analysis of solids and structures. It provides capabilities for explicit dynamic, implicit quasistatic and dynamic analyses. The explicit dynamics capabilities allow for the efficient and robust solution of models with extensive contact subjected to large, suddenly applied loads. For implicit problems, Sierra/SM uses a multi-level iterative solver, which enables it to effectively solve problems with large deformations, nonlinear material behavior, and contact. Sierra/SM has a versatile library of continuum and structural elements, and a large library of material models. The code is written for parallel computing environments enabling scalable solutionsmore » of extremely large problems for both implicit and explicit analyses. It is built on the SIERRA Framework, which facilitates coupling with other SIERRA mechanics codes. This document describes the functionality and input syntax for Sierra/SM.« less

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…

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.

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.

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…

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

ERIC Educational Resources Information Center

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

2011-01-01

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

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…

A multilevel investigation on nursing turnover intention: the cross-level role of leader-member exchange.

PubMed

Portoghese, Igor; Galletta, Maura; Battistelli, Adalgisa; Leiter, Michael P

2015-09-01

To analyse nursing turnover intention from the unit by using multilevel approach, examining at the individual level, the relationships between job characteristics, job satisfaction and turnover intention, and at the group level the role of leader-member exchange. Research on nursing turnover has given little attention to the effects of multilevel factors. Aggregated data of 935 nurses nested within 74 teams of four Italian hospitals were collected in 2009 via a self-administered questionnaire. Hierarchical linear modelling showed that job satisfaction mediated the relationship between job characteristics and intention to leave at the individual level. At the unit level, leader-member exchange was directly linked to intention to leave. Furthermore, cross-level interaction revealed that leader-member exchange moderated the relationship between job characteristics and job satisfaction. This study supported previous research in single-level turnover studies concerning the key role of job satisfaction, providing evidence that job characteristics are important in creating motivating and satisfying jobs. At the unit-level, leader-member exchange offers an approach to understand the role of unit-specific conditions created by leaders on nurses' workplace wellbeing. This study showed that it is important for nursing managers to recognise the relevance of implementing management practices that foster healthy workplaces centred on high-quality nurse-supervisor relationships. © 2014 John Wiley & Sons Ltd.

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

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,…

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 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.

Family and Motivation Effects on Mathematics Achievement: Analyses of Students in 41 Countries

ERIC Educational Resources Information Center

Chiu, Ming Ming; Xihua, Zeng

2008-01-01

This study examines family and motivation effects on student mathematics achievement across 41 countries. The Rasch estimates of PISA mathematics test scores and questionnaire responses of 107,975 15-year-old students were analyzed via multilevel analyses. Students scored higher in richer or more egalitarian countries; when living with two…

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

Racial discrimination and the stress process.

PubMed

Ong, Anthony D; Fuller-Rowell, Thomas; Burrow, Anthony L

2009-06-01

The unique and combined effects of chronic and daily racial discrimination on psychological distress were examined in a sample of 174 African American doctoral students and graduates. Using a daily process design, 5 models of the stress process were tested. Multilevel random coefficient modeling analyses revealed that chronic exposure to racial discrimination predicted greater daily discrimination and psychological distress. Further, results show that differences in daily discrimination and negative events accounted for meaningful variation in daily distress responses. Finally, findings indicate that daily discrimination and negative events mediated the relationship between chronic discrimination and psychological distress. The study provides support for the need to measure chronic strains as distinctive from daily stressors in the lives of African Americans.

The utility of estimating population-level trajectories of terminal wellbeing decline within a growth mixture modelling framework.

PubMed

Burns, R A; Byles, J; Magliano, D J; Mitchell, P; Anstey, K J

2015-03-01

Mortality-related decline has been identified across multiple domains of human functioning, including mental health and wellbeing. The current study utilised a growth mixture modelling framework to establish whether a single population-level trajectory best describes mortality-related changes in both wellbeing and mental health, or whether subpopulations report quite different mortality-related changes. Participants were older-aged (M = 69.59 years; SD = 8.08 years) deceased females (N = 1,862) from the dynamic analyses to optimise ageing (DYNOPTA) project. Growth mixture models analysed participants' responses on measures of mental health and wellbeing for up to 16 years from death. Multi-level models confirmed overall terminal decline and terminal drop in both mental health and wellbeing. However, modelling data from the same participants within a latent class growth mixture framework indicated that most participants reported stability in mental health (90.3 %) and wellbeing (89.0 %) in the years preceding death. Whilst confirming other population-level analyses which support terminal decline and drop hypotheses in both mental health and wellbeing, we subsequently identified that most of this effect is driven by a small, but significant minority of the population. Instead, most individuals report stable levels of mental health and wellbeing in the years preceding death.

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...

Multi-country health surveys: are the analyses misleading?

PubMed

Masood, Mohd; Reidpath, Daniel D

2014-05-01

The aim of this paper was to review the types of approaches currently utilized in the analysis of multi-country survey data, specifically focusing on design and modeling issues with a focus on analyses of significant multi-country surveys published in 2010. A systematic search strategy was used to identify the 10 multi-country surveys and the articles published from them in 2010. The surveys were selected to reflect diverse topics and foci; and provide an insight into analytic approaches across research themes. The search identified 159 articles appropriate for full text review and data extraction. The analyses adopted in the multi-country surveys can be broadly classified as: univariate/bivariate analyses, and multivariate/multivariable analyses. Multivariate/multivariable analyses may be further divided into design- and model-based analyses. Of the 159 articles reviewed, 129 articles used model-based analysis, 30 articles used design-based analyses. Similar patterns could be seen in all the individual surveys. While there is general agreement among survey statisticians that complex surveys are most appropriately analyzed using design-based analyses, most researchers continued to use the more common model-based approaches. Recent developments in design-based multi-level analysis may be one approach to include all the survey design characteristics. This is a relatively new area, however, and there remains statistical, as well as applied analytic research required. An important limitation of this study relates to the selection of the surveys used and the choice of year for the analysis, i.e., year 2010 only. There is, however, no strong reason to believe that analytic strategies have changed radically in the past few years, and 2010 provides a credible snapshot of current practice.

Performance Analysis of Multilevel Parallel Applications on Shared Memory Architectures

NASA Technical Reports Server (NTRS)

Jost, Gabriele; Jin, Haoqiang; Labarta, Jesus; Gimenez, Judit; Caubet, Jordi; Biegel, Bryan A. (Technical Monitor)

2002-01-01

In this paper we describe how to apply powerful performance analysis techniques to understand the behavior of multilevel parallel applications. We use the Paraver/OMPItrace performance analysis system for our study. This system consists of two major components: The OMPItrace dynamic instrumentation mechanism, which allows the tracing of processes and threads and the Paraver graphical user interface for inspection and analyses of the generated traces. We describe how to use the system to conduct a detailed comparative study of a benchmark code implemented in five different programming paradigms applicable for shared memory

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.

Intergroup contact, attitudes toward homosexuality, and the role of acceptance of gender non-conformity in young adolescents.

PubMed

Collier, Kate L; Bos, Henny M W; Sandfort, Theo G M

2012-08-01

This study explored how contact with gay and lesbian persons affects adolescents' attitudes toward them, and whether this association is mediated or moderated by one's acceptance of gender non-conformity. We analyzed survey responses from 456 Dutch adolescents aged 12-15 who reported having no same-sex attractions. Data were collected in 2008 at 8 schools in Amsterdam, the Netherlands. Preliminary analyses showed that contact with lesbian/gay persons outside of school was positively associated with attitudes toward lesbians and gay men. Multilevel analyses showed that acceptance of gender non-conformity mediated rather than moderated the relationship between intergroup contact and sexual prejudice in males. The effect of intergroup contact on females' attitudes toward lesbian women was no longer significant in multilevel analyses. The findings suggest that attention to both intergroup contact and acceptance of gender non-conformity would enhance our understanding of attitudes toward homosexuality in adolescents. Copyright © 2011 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Changes in the Associations of Heavy Drinking and Drug Use with Intimate Partner Violence in Early Adulthood

PubMed Central

Feingold, Alan; Washburn, Isaac J.; Tiberio, Stacey S.; Capaldi, Deborah M.

2013-01-01

The hypothesis that the disinhibitory effects induced by alcohol consumption contribute to domestic violence has gained support from meta-analyses of mainly cross-sectional studies that examined the association between alcohol abuse and perpetration of intimate partner violence (IPV). However, findings from multilevel analyses of longitudinal data investigating the time-varying effects of heavy episodic drinking (HED) on physical IPV have been equivocal. This 12-year prospective study used multilevel analysis to examine the effects of HED and illicit drug use on perpetration of both physical and psychological IPV during early adulthood. Participants were 157 romantic couples who were assessed biennially 2 to 6 times for substance misuse and IPV. The analyses found no significant main effect of either HED or drug use on perpetration of IPV but there were significant interactions of both HED and drug use with age. Moreover, the developmental trends in substance use effects on IPV typically varied by gender and type of IPV. PMID:25678737

Intergroup contact, attitudes toward homosexuality, and the role of acceptance of gender non-conformity in young adolescents

PubMed Central

Collier, Kate L.; Bos, Henny M.W.; Sandfort, Theo G.M.

2012-01-01

This study explored how contact with gay and lesbian persons affects adolescents' attitudes toward them, and whether this association is mediated or moderated by one's acceptance of gender non-conformity. We analyzed survey responses from 456 Dutch adolescents aged 12 to 15 who reported having no same-sex attractions. Data were collected in 2008 at 8 schools in Amsterdam, the Netherlands. Preliminary analyses showed that contact with lesbian/gay persons outside of school was positively associated with attitudes toward lesbians and gay men. Multilevel analyses showed that acceptance of gender non-conformity mediated rather than moderated the relationship between intergroup contact and sexual prejudice in males. The effect of intergroup contact on females' attitudes toward lesbian women was no longer significant in multilevel analyses. The findings suggest that attention to both intergroup contact and acceptance of gender non-conformity would enhance our understanding of attitudes toward homosexuality in adolescents. PMID:22243627

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.

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.

Studying physician effects on patient outcomes: physician interactional style and performance on quality of care indicators.

PubMed

Franks, Peter; Jerant, Anthony F; Fiscella, Kevin; Shields, Cleveland G; Tancredi, Daniel J; Epstein, Ronald M

2006-01-01

Many prior studies which suggest a relationship between physician interactional style and patient outcomes may have been confounded by relying solely on patient reports, examining very few patients per physician, or not demonstrating evidence of a physician effect on the outcomes. We examined whether physician interactional style, measured both by patient report and objective encounter ratings, is related to performance on quality of care indicators. We also tested for the presence of physician effects on the performance indicators. Using data on 100 US primary care physician (PCP) claims data on 1,21,606 of their managed care patients, survey data on 4746 of their visiting patients, and audiotaped encounters of 2 standardized patients with each physician, we examined the relationships between claims-based quality of care indicators and both survey-derived patient perceptions of their physicians and objective ratings of interactional style in the audiotaped standardized patient encounters. Multi-level models examined whether physician effects (variance components) on care indicators were mediated by patient perceptions or objective ratings of interactional style. We found significant physician effects associated with glycohemoglobin and cholesterol testing. There was also a clinically significant association between better patient perceptions of their physicians and more glycohemoglobin testing. Multi-level analyses revealed, however, that the physician effect on glycohemoglobin testing was not mediated by patient perceived physician interaction style. In conclusion, similar to prior studies, we found evidence of an apparent relationship between patient perceptions of their physician and patient outcomes. However, the apparent relationships found in this study between patient perceptions of their physicians and patient care processes do not reflect physician style, but presumably reflect unmeasured patient confounding. Multi-level modeling may contribute to better understanding of the relationships between physician style and patient outcomes.

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…

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…

The Relationship between Intimacy Change and Passion: A Dyadic Diary Study

PubMed Central

Aykutoğlu, Bülent; Uysal, Ahmet

2017-01-01

In the current study we investigated the association between intimacy and passion by testing whether increases in intimacy generates passion (Baumeister and Bratslavsky, 1999). Furthermore, we examined whether there are partner effects in intimacy change and passion link. Couples (N = 75) participated in a 14-day long diary study. Dyadic multilevel analyses with residualized intimacy change scores showed that both actors’ and partners’ intimacy change positively predicted actor’s passion. However, analyses also showed that residualized passion change scores positively predicted intimacy. Although these findings provide some empirical evidence for the intimacy change model, in line with the previous research (Rubin and Campbell, 2012), they also suggest that it is not possible to discern whether intimacy increment generates passion or passion increment generates intimacy. PMID:29312093

Co-occurrences between adolescent substance use and academic performance: school context influences a multilevel-longitudinal perspective.

PubMed

Andrade, Fernando H

2014-08-01

A growing body of literature has linked substance use and academic performance exploring substance use as a predictor of academic performance or vice versa. This study uses a different approach conceptualizing substance use and academic performance as parallel outcomes and exploring two topics: its multilevel-longitudinal association and school contextual effects on both outcomes. Using multilevel Confirmatory Factor Analysis and multilevel-longitudinal analyses, the empirical estimates relied on 7843 students nested in 114 schools (Add Health study). The main finding suggests that the correlation between substance use and academic performance was positive at the school level in contraposition to the negative relationship at the individual level. Additional findings suggest a positive effect of a school risk factor on substance use and a positive effect of academic pressure on academic performance. These findings represent a contribution to our understanding of how schools could affect the relationship between academic performance and substance use. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

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.

Does Anger Regulation Mediate the Discrimination-Mental Health Link among Mexican-Origin Adolescents? A Longitudinal Mediation Analysis Using Multilevel Modeling

PubMed Central

Park, Irene J. K.; Wang, Lijuan; Williams, David R.; Alegría, Margarita

2016-01-01

Although prior research has consistently documented the association between racial/ethnic discrimination and poor mental health outcomes, the mechanisms that underlie this link are still unclear. The present three-wave longitudinal study tested the mediating role of anger regulation in the discrimination—mental health link among 269 Mexican-origin adolescents (Mage = 14.1 years, SD = 1.6; 57% girls), 12 – 17 years old. Three competing anger regulation variables were tested as potential mediators: outward anger expression, anger suppression, and anger control. Longitudinal mediation analyses were conducted using multilevel modeling that disaggregated within-person effects from between-person effects. Results indicated that outward anger expression was a significant mediator; anger suppression and anger control were not significant mediators. Within a given individual, greater racial/ethnic discrimination was associated with more frequent outward anger expression. In turn, more frequent outward anger expression was associated with higher levels of anxiety and depression at a given time point. Gender, age, and nativity status were not significant moderators of the hypothesized mediation models. By identifying outward anger expression as an explanatory mechanism in the discrimination-distress link among Latino youths, this study points to a malleable target for prevention and intervention efforts aimed at mitigating the detrimental impact of racism on Latino youths’ mental health during the developmentally critical period of adolescence. PMID:27893238

Using multi-level data to estimate the effect of an 'alcogenic' environment on hazardous alcohol consumption in the former Soviet Union.

PubMed

Murphy, Adrianna; Roberts, Bayard; Ploubidis, George B; Stickley, Andrew; McKee, Martin

2014-05-01

The purpose of this study was to assess whether alcohol-related community characteristics act collectively to influence individual-level alcohol consumption in the former Soviet Union (fSU). Using multi-level data from nine countries in the fSU we conducted a factor analysis of seven alcohol-related community characteristics. The association between any latent factors underlying these characteristics and two measures of hazardous alcohol consumption was then analysed using a population average regression modelling approach. Our factor analysis produced one factor with an eigenvalue >1 (EV=1.28), which explained 94% of the variance. This factor was statistically significantly associated with increased odds of CAGE problem drinking (OR=1.40 (1.08-1.82)). The estimated association with EHD was not statistically significant (OR=1.10 (0.85-1.44)). Our findings suggest that a high number of beer, wine and spirit advertisements and high alcohol outlet density may work together to create an 'alcogenic' environment that encourages hazardous alcohol consumption in the fSU. Copyright © 2014 Elsevier Ltd. All rights reserved.

Political violence, collective functioning and health: a review of the literature.

PubMed

Sousa, Cindy A

2013-01-01

Political violence is implicated in a range of mental health outcomes, including PTSD, depression, and anxiety. The social and political contexts of people's lives, however, offer considerable protection from the mental health effects of political violence. In spite of the importance of people's social and political environments for health, there is limited scholarship on how political violence compromises necessary social and political systems and inhibits individuals from participating in social and political life. Drawing on literature from multiple disciplines, including public health, anthropology, and psychology, this narrative review uses a multi-level, social ecological framework to enhance current knowledge about the ways that political violence affects health. Findings from over 50 studies were analysed and used to build a conceptual model demonstrating how political violence threatens three inter-related domains of functioning: individual functioning in relationship to their environment; community functioning and social fabric; and governmental functioning and delivery of services to populations. Results illustrate the need for multilevel frameworks that move beyond individual pathology towards more nuanced conceptualizations about how political violence affects health; findings contribute to the development of prevention programmes addressing political violence.

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 multilevel cross-lagged structural equation analysis for reciprocal relationship between social capital and health.

PubMed

Yu, Ge; Sessions, John G; Fu, Yu; Wall, Martin

2015-10-01

We investigated the reciprocal relationship between individual social capital and perceived mental and physical health in the UK. Using data from the British Household Panel Survey from 1991 to 2008, we fitted cross-lagged structural equation models that include three indicators of social capital vis. social participation, social network, and loneliness. Given that multiple measurement points (level 1) are nested within individuals (level 2), we also applied a multilevel model to allow for residual variation in the outcomes at the occasion and individual levels. Controlling for gender, age, employment status, educational attainment, marital status, household wealth, and region, our analyses suggest that social participation predicts subsequent change in perceived mental health, and vice versa. However, whilst loneliness is found to be significantly related to perceived mental and physical health, reciprocal causality is not found for perceived mental health. Furthermore, we find evidence for reverse effects with both perceived mental and physical health appearing to be the dominant causal factor with respect to the prospective level of social network. Our findings thus shed further light on the importance of social participation and social inclusion in health promotion and aid the development of more effective public health policies in the UK. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nurses' Practice Environment and Work-Family Conflict in Relation to Burn Out: A Multilevel Modelling Approach

PubMed Central

Leineweber, Constanze; Westerlund, Hugo; Chungkham, Holendro Singh; Lindqvist, Rikard; Runesdotter, Sara; Tishelman, Carol

2014-01-01

Objectives To investigate associations between nurse work practice environment measured at department level and individual level work-family conflict on burnout, measured as emotional exhaustion, depersonalization and personal accomplishment among Swedish RNs. Methods A multilevel model was fit with the individual RN at the 1st, and the hospital department at the 2nd level using cross-sectional RN survey data from the Swedish part of RN4CAST, an EU 7th framework project. The data analysed here is based on a national sample of 8,620 RNs from 369 departments in 53 hospitals. Results Generally, RNs reported high values of personal accomplishment and lower values of emotional exhaustion and depersonalization. High work-family conflict increased the risk for emotional exhaustion, but for neither depersonalization nor personal accomplishment. On department level adequate staffing and good leadership and support for nurses reduced the risk for emotional exhaustion and depersonalization. Personal accomplishment was statistically significantly related to staff adequacy. Conclusions The findings suggest that adequate staffing, good leadership, and support for nurses are crucial for RNs' mental health. Our findings also highlight the importance of hospital managers developing policies and practices to facilitate the successful combination of work with private life for employees. PMID:24820972

Capacity of clinical pathways--a strategic multi-level evaluation tool.

PubMed

Cardoen, Brecht; Demeulemeester, Erik

2008-12-01

In this paper we strategically evaluate the efficiency of clinical pathways and their complex interdependencies with respect to joint resource usage and patient throughput. We propose a discrete-event simulation approach that allows for the simultaneous evaluation of multiple clinical pathways and the inherent uncertainty (resource, duration and arrival) that accompanies medical processes. Both the consultation suite and the surgery suite may be modeled and examined in detail by means of sensitivity or scenario analyses. Since each medical facility can somehow be represented as a combination of clinical pathways, i.e. they are conceptually similar, the simulation model is generic in nature. Next to the formulation of the model, we illustrate its applicability by means of a case study that was conducted in a Belgian hospital.

Within-person variation in security of attachment: a self-determination theory perspective on attachment, need fulfillment, and well-being.

PubMed

La Guardia, J G; Ryan, R M; Couchman, C E; Deci, E L

2000-09-01

Attachment research has traditionally focused on individual differences in global patterns of attachment to important others. The current research instead focuses primarily on within-person variability in attachments across relational partners. It was predicted that within-person variability would be substantial, even among primary attachment figures of mother, father, romantic partner, and best friend. The prediction was supported in three studies. Furthermore, in line with self-determination theory, multilevel modeling and regression analyses showed that, at the relationship level, individuals' experience of fulfillment of the basic needs for autonomy, competence, and relatedness positively predicted overall attachment security, model of self, and model of other. Relations of both attachment and need satisfaction to well-being were also explored.

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.

Analyzing longitudinal data with the linear mixed models procedure in SPSS.

PubMed

West, Brady T

2009-09-01

Many applied researchers analyzing longitudinal data share a common misconception: that specialized statistical software is necessary to fit hierarchical linear models (also known as linear mixed models [LMMs], or multilevel models) to longitudinal data sets. Although several specialized statistical software programs of high quality are available that allow researchers to fit these models to longitudinal data sets (e.g., HLM), rapid advances in general purpose statistical software packages have recently enabled analysts to fit these same models when using preferred packages that also enable other more common analyses. One of these general purpose statistical packages is SPSS, which includes a very flexible and powerful procedure for fitting LMMs to longitudinal data sets with continuous outcomes. This article aims to present readers with a practical discussion of how to analyze longitudinal data using the LMMs procedure in the SPSS statistical software package.

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.

Is multi-level marketing of nutrition supplements a legal and an ethical practice?

PubMed

Cardenas, Diana; Fuchs-Tarlovsky, Vanessa

2018-06-01

Multi-level marketing (MLM) of nutrition products has experienced dramatic growth in recent decades. 'Wellness' is the second most popular niche in the MLM industry and represents 35% of sales among all the products in 2016. This category includes dietary supplements, weight management and sports nutrition products. The aim of this paper is to analyse whether this practice is legal and ethical. An analysis of available documentary information about the legal aspects of Multi-level marketing business was performed. Ethical reflexion was based on the "principlism" approach. We argue that, while being a controversial business model, MLM is not fraudulent from a legal point of view. However, it is an unethical strategy obviating all the principles of beneficence, nonmaleficence and autonomy. What is at stake is the possible economic scam and the potential harm those products could cause due to unproven efficacy, exceeding daily nutrient requirements and potential toxicity. The sale of dietary and nutrition supplements products by physicians and dieticians presents a conflict of interests that can undermine the primary obligation of physicians to serve the interests of their patients before their own. While considering that MLM of dietary supplements and other nutrition products are a legal business strategy, we affirm that it is an unethical practice. MLM products that have nutritional value or promoted as remedies may be unnecessary and intended for conditions that are unsuitable for self-prescription as well. Copyright © 2018 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights reserved.

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.

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.

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.

Characterization of biosurfactant produced by petrofilic bacteria isolated from hydrocarbon impacted soil and its potential application in bioremediation

NASA Astrophysics Data System (ADS)

Arsyah, D. M.; Kardena, E.; Helmy, Q.

2018-01-01

The study adopts a multi-level perspective in technology transition to analyse how the transition process in the development of geothermal energy in Indonesia is able to compete against the incumbent fossil-fuelled energy sources. Three levels of multi-level perspective are socio-technical landscape (ST-landscape), socio-technical regime (ST-regime) and niche innovations in Indonesia geothermal development. The identification, mapping and analysis of the dynamic relationship between each level are the important pillars of the multi-level perspective framework. The analysis considers the set of rules, actors and controversies that may arise in the technological transition process. The identified geothermal resource risks are the basis of the emerging geothermal technological innovations in Indonesian geothermal. The analysis of this study reveals the transition pathway, which yields a forecast for the Indonesian geothermal technology transition in the form of scenarios and probable impacts.

Cross-National Differences in the Association Between Parental Work Hours and Time with Children in Europe: A Multilevel Analysis.

PubMed

Roeters, Anne

2013-01-01

This study investigates cross-national differences in the association between parental work hours and parent-child interaction time and explains differences in this individual-level association on the basis of country characteristics. It extends prior research by testing the moderating effects of country characteristics through multilevel analyses and by considering the possibility of selection effects. The presumption was that parents employ strategies to protect family life from work encroachments and that these strategies are enhanced by reconciliation policies, stronger parenthood ideologies, access to part-time work and higher income levels. Multilevel analyses were based on a subset of 5.183 parents in 23 countries from the 2005 European Working Conditions Survey that was complemented with country-level data. The negative association between parental work hours and parent-child time indeed varied significantly across countries and was weaker in countries where formal child care coverage was higher, part-time work was less prevalent, and earnings were lower. The effects of part-time work and earnings mainly applied to mothers. These findings suggest that child care coverage limits the availability of children and that differences in parent-child time between parents who work short and long hours are more pronounced when part-time work is more accessible and affordable.

Mind the Gap! A Multilevel Analysis of Factors Related to Variation in Published Cost-Effectiveness Estimates within and between Countries.

PubMed

Boehler, Christian E H; Lord, Joanne

2016-01-01

Published cost-effectiveness estimates can vary considerably, both within and between countries. Despite extensive discussion, little is known empirically about factors relating to these variations. To use multilevel statistical modeling to integrate cost-effectiveness estimates from published economic evaluations to investigate potential causes of variation. Cost-effectiveness studies of statins for cardiovascular disease prevention were identified by systematic review. Estimates of incremental costs and effects were extracted from reported base case, sensitivity, and subgroup analyses, with estimates grouped in studies and in countries. Three bivariate models were developed: a cross-classified model to accommodate data from multinational studies, a hierarchical model with multinational data allocated to a single category at country level, and a hierarchical model excluding multinational data. Covariates at different levels were drawn from a long list of factors suggested in the literature. We found 67 studies reporting 2094 cost-effectiveness estimates relating to 23 countries (6 studies reporting for more than 1 country). Data and study-level covariates included patient characteristics, intervention and comparator cost, and some study methods (e.g., discount rates and time horizon). After adjusting for these factors, the proportion of variation attributable to countries was negligible in the cross-classified model but moderate in the hierarchical models (14%-19% of total variance). Country-level variables that improved the fit of the hierarchical models included measures of income and health care finance, health care resources, and population risks. Our analysis suggested that variability in published cost-effectiveness estimates is related more to differences in study methods than to differences in national context. Multinational studies were associated with much lower country-level variation than single-country studies. These findings are for a single clinical question and may be atypical. © The Author(s) 2015.

Understanding Statistical Power in Cluster Randomized Trials: Challenges Posed by Differences in Notation and Terminology

ERIC Educational Resources Information Center

Spybrook, Jessaca; Hedges, Larry; Borenstein, Michael

2014-01-01

Research designs in which clusters are the unit of randomization are quite common in the social sciences. Given the multilevel nature of these studies, the power analyses for these studies are more complex than in a simple individually randomized trial. Tools are now available to help researchers conduct power analyses for cluster randomized…

Individual, household, programme and community effects on childhood malnutrition in rural India.

PubMed

Rajaram, S; Zottarelli, Lisa K; Sunil, T S

2007-04-01

The children living in rural areas of India disproportionately suffer from malnutrition compared with their urban counterparts. The present article analyses the individual, household, community and programme factors on nutritional status of children in rural India. Additionally, we consider the random variances at village and state levels after introducing various observed individual-, household- and programme-level characteristics in the model. A multilevel model is conducted using data from the National Family and Health Survey 2. The results show that maternal characteristics, such as socio-economic and behavioural factors, are more influential in determining childhood nutritional status than the prevalence of programme factors. Also, it was found that individual factors show evidence of state- and village-level clustering of malnutrition.

Processes of change in a school-based mindfulness programme: cognitive reactivity and self-coldness as mediators.

PubMed

Van der Gucht, Katleen; Takano, Keisuke; Raes, Filip; Kuppens, Peter

2018-05-01

The underlying mechanisms of the effectiveness of mindfulness-based interventions for emotional well-being remain poorly understood. Here, we examined the potential mediating effects of cognitive reactivity and self-compassion on symptoms of depression, anxiety and stress using data from an earlier randomised controlled school trial. A moderated time-lagged mediation model based on multilevel modelling was used to analyse the data. The findings showed that post-treatment changes in cognitive reactivity and self-coldness, an aspect of self-compassion, mediated subsequent changes in symptoms of depression, anxiety and stress. These results suggest that cognitive reactivity and self-coldness may be considered as transdiagnostic mechanisms of change of a mindfulness-based intervention programme for youth.

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…

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 Regression Framework for Effect Size Assessments in Longitudinal Modeling of Group Differences

PubMed Central

Feingold, Alan

2013-01-01

The use of growth modeling analysis (GMA)--particularly multilevel analysis and latent growth modeling--to test the significance of intervention effects has increased exponentially in prevention science, clinical psychology, and psychiatry over the past 15 years. Model-based effect sizes for differences in means between two independent groups in GMA can be expressed in the same metric (Cohen’s d) commonly used in classical analysis and meta-analysis. This article first reviews conceptual issues regarding calculation of d for findings from GMA and then introduces an integrative framework for effect size assessments that subsumes GMA. The new approach uses the structure of the linear regression model, from which effect sizes for findings from diverse cross-sectional and longitudinal analyses can be calculated with familiar statistics, such as the regression coefficient, the standard deviation of the dependent measure, and study duration. PMID:23956615

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...

[Multilevel analyses of labour market and return to work after vocational retraining].

PubMed

Hetzel, C

2015-02-01

is to test individual level and regional labour market hypotheses about return to work (RTW) after vocational retraining derived from matching theory. In multilevel analyses individual data of graduates in 2006 (n=3620) by the association of German "Berufsförderungswerke" and for contextual level the regional unemployment rates in 2007 (n=159 Federal Employment Agency of Germany districts) are used. Probability of RTW rises with decreasing regional unemployment. There's an age effect only in context of high unemployment. In context of low unemployment partnership promotes RTW - but in context of high unemployment only for men and not for women. It's compatible with matching theory because family obligations lead to high individual reservation wages and entry wages are to low. Direct and indirect effects of labour market should be taken into account in research on effectiveness and in comparative evaluation on intervention quality. © Georg Thieme Verlag KG Stuttgart · New York.

Multi-level omics analysis in a murine model of dystrophin loss and therapeutic restoration.

PubMed

Roberts, Thomas C; Johansson, Henrik J; McClorey, Graham; Godfrey, Caroline; Blomberg, K Emelie M; Coursindel, Thibault; Gait, Michael J; Smith, C I Edvard; Lehtiö, Janne; El Andaloussi, Samir; Wood, Matthew J A

2015-12-01

Duchenne muscular dystrophy (DMD) is a classical monogenic disorder, a model disease for genomic studies and a priority candidate for regenerative medicine and gene therapy. Although the genetic cause of DMD is well known, the molecular pathogenesis of disease and the response to therapy are incompletely understood. Here, we describe analyses of protein, mRNA and microRNA expression in the tibialis anterior of the mdx mouse model of DMD. Notably, 3272 proteins were quantifiable and 525 identified as differentially expressed in mdx muscle (P < 0.01). Therapeutic restoration of dystrophin by exon skipping induced widespread shifts in protein and mRNA expression towards wild-type expression levels, whereas the miRNome was largely unaffected. Comparison analyses between datasets showed that protein and mRNA ratios were only weakly correlated (r = 0.405), and identified a multitude of differentially affected cellular pathways, upstream regulators and predicted miRNA-target interactions. This study provides fundamental new insights into gene expression and regulation in dystrophic muscle. © The Author 2015. Published by Oxford University Press.

Neighborhood deprivation is strongly associated with participation in a population-based health check.

PubMed

Bender, Anne Mette; Kawachi, Ichiro; Jørgensen, Torben; Pisinger, Charlotta

2015-01-01

We sought to examine whether neighborhood deprivation is associated with participation in a large population-based health check. Such analyses will help answer the question whether health checks, which are designed to meet the needs of residents in deprived neighborhoods, may increase participation and prove to be more effective in preventing disease. In Europe, no study has previously looked at the association between neighborhood deprivation and participation in a population-based health check. The study population comprised 12,768 persons invited for a health check including screening for ischemic heart disease and lifestyle counseling. The study population was randomly drawn from a population of 179,097 persons living in 73 neighborhoods in Denmark. Data on neighborhood deprivation (percentage with basic education, with low income and not in work) and individual socioeconomic position were retrieved from national administrative registers. Multilevel regression analyses with log links and binary distributions were conducted to obtain relative risks, intraclass correlation coefficients and proportional change in variance. Large differences between neighborhoods existed in both deprivation levels and neighborhood health check participation rate (mean 53%; range 35-84%). In multilevel analyses adjusted for age and sex, higher levels of all three indicators of neighborhood deprivation and a deprivation score were associated with lower participation in a dose-response fashion. Persons living in the most deprived neighborhoods had up to 37% decreased probability of participating compared to those living in the least deprived neighborhoods. Inclusion of individual socioeconomic position in the model attenuated the neighborhood deprivation coefficients, but all except for income deprivation remained statistically significant. Neighborhood deprivation was associated with participation in a population-based health check in a dose-response manner, in which increasing neighborhood deprivation was associated with decreasing participation. This suggests the need to develop preventive health checks tailored to deprived neighborhoods.

Using a dyadic logistic multilevel model to analyze couple data.

PubMed

Preciado, Mariana A; Krull, Jennifer L; Hicks, Andrew; Gipson, Jessica D

2016-02-01

There is growing recognition within the sexual and reproductive health field of the importance of incorporating both partners' perspectives when examining sexual and reproductive health behaviors. Yet, the analytical approaches to address couple data have not been readily integrated and utilized within the demographic and public health literature. This paper seeks to provide readers unfamiliar with analytical approaches to couple data an applied example of the use of dyadic logistic multilevel modeling, a useful approach to analyzing couple data to assess the individual, partner and couple characteristics that are related to individuals' reproductively relevant beliefs, attitudes and behaviors. The use of multilevel models in reproductive health research can help researchers develop a more comprehensive picture of the way in which individuals' reproductive health outcomes are situated in a larger relationship and cultural context. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Income Inequality or Performance Gap? A Multilevel Study of School Violence in 52 Countries.

PubMed

Contreras, Dante; Elacqua, Gregory; Martinez, Matias; Miranda, Álvaro

2015-11-01

The purpose of the study was to examine the association between income inequality and school violence and between the performance inequality and school violence in two international samples. The study used data from Trends in International Mathematics and Science Study 2011 and from the Central Intelligence Agency of United States which combined information about academic performance and students' victimization (physical and social) for 269,456 fourth-grade students and 261,747 eighth-grade students, with gross domestic product and income inequality data in 52 countries. Ecological correlations tested associations between income inequality and victimization and between school performance inequality and victimization among countries. Multilevel ordinal regression and multilevel regression analyses tested the strength of these associations when controlling for socioeconomic and academic performance inequality at school level and family socioeconomic status and academic achievement at student level. Income inequality was associated with victimization rates in both fourth and eighth grade (r ≈ .60). Performance inequality shows stronger association with victimization among eighth graders (r ≈ .46) compared with fourth graders (r ≈ .30). Multilevel analyses indicate that both an increase in the income inequality in the country and school corresponds with more frequent physical and social victimization. On the other hand, an increase in the performance inequality at the system level shows no consistent association to victimization. However, school performance inequality seems related to an increase in both types of victimizations. Our results contribute to the finding that income inequality is a determinant of school violence. This result holds regardless of the national performance inequality between students. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

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

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…

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

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

Measurement Development and Validation of the Family Supportive Supervisor Behavior Short-Form (FSSB-SF)

PubMed Central

Hammer, Leslie B.; Kossek, Ellen Ernst; Bodner, Todd; Crain, Tori

2013-01-01

Recently, scholars have demonstrated the importance of Family Supportive Supervisor Behaviors (FSSB), defined as behaviors exhibited by supervisors that are supportive of employees’ family roles, in relation to health, well-being, and organizational outcomes. FSSB was originally conceptualized as a multidimensional, superordinate construct with four subordinate dimensions assessed with 14 items: emotional support, instrumental support, role modeling behaviors, and creative work-family management. Retaining one item from each dimension, two studies were conducted to support the development and use of a new FSSB-Short Form (FSSB-SF). Study 1 draws on the original data from the FSSB validation study of retail employees to determine if the results using the 14-item measure replicate with the shorter 4-item measure. Using data from a sample of 823 information technology professionals and their 219 supervisors, Study 2 extends the validation of the FSSB-SF to a new sample of professional workers and new outcome variables. Results from multilevel confirmatory factor analyses and multilevel regression analyses provide evidence of construct and criterion-related validity of the FSSB-SF, as it was significantly related to work-family conflict, job satisfaction, turnover intentions, control over work hours, obligation to work when sick, perceived stress, and reports of family time adequacy. We argue that it is important to develop parsimonious measures of work-family specific support to ensure supervisor support for work and family is mainstreamed into organizational research and practice. PMID:23730803

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.

The gender gap in self-rated health and education in Spain. A multilevel analysis.

PubMed

Pinillos-Franco, Sara; García-Prieto, Carmen

2017-01-01

Women tend to report poorer self-rated health than men. It is also well established that education has a positive effect on health. However, the issue of how the benefits of education on health differ between men and women has not received enough attention and the few existing studies which do focus on the subject do not draw a clear conclusion. Therefore, this study aims to analyse whether the positive influence of educational attainment on health is higher for women and whether education helps to overcome the gender gap in self-rated health. We analyse cross-sectional data from the 2012 European Union statistics on income and living conditions. We use a logit regression model with odds ratios and a multilevel perspective to carry out a study which includes several individual and contextual control variables. We focused our study on the working population in Spain aged between 25 and 65. The final sample considered is composed of 14,120 subjects: 7,653 men and 6,467 women. There is a gender gap in self-rated health only for the less educated. This gap is not statistically significant among more highly educated individuals. Attaining a high level of education has the same positive effect on both women's and men's self-rated health. Although we did not find gender disparities when considering the effect of education on health, we show that women's health is poorer among the less educated, mainly due to labour precariousness and household conditions.

Measurement development and validation of the Family Supportive Supervisor Behavior Short-Form (FSSB-SF).

PubMed

Hammer, Leslie B; Ernst Kossek, Ellen; Bodner, Todd; Crain, Tori

2013-07-01

Recently, scholars have demonstrated the importance of Family Supportive Supervisor Behaviors (FSSB), defined as behaviors exhibited by supervisors that are supportive of employees' family roles, in relation to health, well-being, and organizational outcomes. FSSB was originally conceptualized as a multidimensional, superordinate construct with four subordinate dimensions assessed with 14 items: emotional support, instrumental support, role modeling behaviors, and creative work-family management. Retaining one item from each dimension, two studies were conducted to support the development and use of a new FSSB-Short Form (FSSB-SF). Study 1 draws on the original data from the FSSB validation study of retail employees to determine whether the results using the 14-item measure replicate with the shorter 4-item measure. Using data from a sample of 823 information technology professionals and their 219 supervisors, Study 2 extends the validation of the FSSB-SF to a new sample of professional workers and new outcome variables. Results from multilevel confirmatory factor analyses and multilevel regression analyses provide evidence of construct and criterion-related validity of the FSSB-SF, as it was significantly related to work-family conflict, job satisfaction, turnover intentions, control over work hours, obligation to work when sick, perceived stress, and reports of family time adequacy. We argue that it is important to develop parsimonious measures of work-family specific support to ensure supervisor support for work and family is mainstreamed into organizational research and practice. PsycINFO Database Record (c) 2013 APA, all rights reserved.

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

Contextual determinants of neonatal mortality using two analysis methods, Rio Grande do Sul, Brazil.

PubMed

Zanini, Roselaine Ruviaro; Moraes, Anaelena Bragança de; Giugliani, Elsa Regina Justo; Riboldi, João

2011-02-01

To analyze neonatal mortality determinants using multilevel logistic regression and classic hierarchical models. Cohort study including 138,407 live births with birth certificates and 1,134 neonatal deaths recorded in 2003, in the state of Rio Grande do Sul, Southern Brazil. The Information System on Live Births and mortality records were linked for gathering information on individual-level exposures. Sociodemographic data and information on the pregnancy, childbirth care and characteristics of the children at birth were collected. The associated factors were estimated and compared by traditional and multilevel logistic regression analysis. The neonatal mortality rate was 8.19 deaths per 1,000 live births. Low birth weight, 1- and 5-minute Apgar score below eight, congenital malformation, pre-term birth and previous fetal loss were associated with neonatal death in the traditional model. Elective cesarean section had a protective effect. Previous fetal loss did not remain significant in the multilevel model, but the inclusion of a contextual variable (poverty rate) showed that 15% of neonatal mortality variation can be explained by varying poverty rates in the microregions. The use of multilevel models showed a small effect of contextual determinants on the neonatal mortality rate. There was found a positive association with the poverty rate in the general model, and the proportion of households with water supply among preterm newborns.

Whose health is affected by income inequality? A multilevel interaction analysis of contemporaneous and lagged effects of state income inequality on individual self-rated health in the United States.

PubMed

Subramanian, S V; Kawachi, Ichiro

2006-06-01

The empirical relationship between income inequality and health has been much debated and discussed. Recent reviews suggest that the current evidence is mixed, with the relationship between state income inequality and health in the United States (US) being perhaps the most robust. In this paper, we examine the multilevel interactions between state income inequality, individual poor self-rated health, and a range of individual demographic and socioeconomic markers in the US. We use the pooled data from the 1995 and 1997 Current Population Surveys, and the data on state income inequality (represented using Gini coefficient) from the 1990, 1980, and 1970 US Censuses. Utilizing a cross-sectional multilevel design of 201,221 adults nested within 50 US states we calibrated two-level binomial hierarchical mixed models (with states specified as a random effect). Our analyses suggest that for a 0.05 change in the state income inequality, the odds ratio (OR) of reporting poor health was 1.30 (95% CI: 1.17-1.45) in a conditional model that included individual age, sex, race, marital status, education, income, and health insurance coverage as well as state median income. With few exceptions, we did not find strong statistical support for differential effects of state income inequality across different population groups. For instance, the relationship between state income inequality and poor health was steeper for whites compared to blacks (OR=1.34; 95% CI: 1.20-1.48) and for individuals with incomes greater than $75,000 compared to less affluent individuals (OR=1.65; 95% CI: 1.26-2.15). Our findings, however, primarily suggests an overall (as opposed to differential) contextual effect of state income inequality on individual self-rated poor health. To the extent that contemporaneous state income inequality differentially affects population sub-groups, our analyses suggest that the adverse impact of inequality is somewhat stronger for the relatively advantaged socioeconomic groups. This pattern was found to be consistent regardless of whether we consider contemporaneous or lagged effects of state income inequality on health. At the same time, the contemporaneous main effect of state income inequality remained statistically significant even when conditioned for past levels of income inequality and median income of states.

Exploring the potential of a multi-level approach to improve capability for continuous organizational improvement and learning in a Swedish healthcare region.

PubMed

Nyström, M E; Höög, E; Garvare, R; Andersson Bäck, M; Terris, D D; Hansson, J

2018-05-24

Eldercare and care of people with functional impairments is organized by the municipalities in Sweden. Improving care in these areas is complex, with multiple stakeholders and organizations. Appropriate strategies to develop capability for continuing organizational improvement and learning (COIL) are needed. The purpose of our study was to develop and pilot-test a flexible, multilevel approach for COIL capability building and to identify what it takes to achieve changes in key actors' approaches to COIL. The approach, named "Sustainable Improvement and Development through Strategic and Systematic Approaches" (SIDSSA), was applied through an action-research and action-learning intervention. The SIDSSA approach was tested in a regional research and development (R&D) unit, and in two municipalities handling care of the elderly and people with functional impairments. Our approach included a multilevel strategy, development loops of five flexible phases, and an action-learning loop. The approach was designed to support systems understanding, strategic focus, methodological practices, and change process knowledge - all of which required double-loop learning. Multiple qualitative methods, i.e., repeated interviews, process diaries, and documents, provided data for conventional content analyses. The new approach was successfully tested on all cases and adopted and sustained by the R&D unit. Participants reported new insights and skills. The development loop facilitated a sense of coherence and control during uncertainty, improved planning and problem analysis, enhanced mapping of context and conditions, and supported problem-solving at both the individual and unit levels. The systems-level view and structured approach helped participants to explain, motivate, and implement change initiatives, especially after working more systematically with mapping, analyses, and goal setting. An easily understood and generalizable model internalized by key organizational actors is an important step before more complex development models can be implemented. SIDSSA facilitated individual and group learning through action-learning and supported systems-level views and structured approaches across multiple organizational levels. Active involvement of diverse organizational functions and levels in the learning process was facilitated. However, the time frame was too short to fully test all aspects of the approach, specifically in reaching beyond the involved managers to front-line staff and patients.

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…

Influence of Leaders' Psychological Capital on Their Followers: Multilevel Mediation Effect of Organizational Identification

PubMed Central

Chen, Qishan; Wen, Zhonglin; Kong, Yurou; Niu, Jun; Hau, Kit-Tai

2017-01-01

We investigated the relationships between leaders' and their followers' psychological capital and organizational identification in a Chinese community. Participants included 423 followers on 34 work teams, each with its respective team leader. Hierarchical linear models (HLM) were used in the analyses to delineate the relationships among participants' demographic background (gender, age, marital status, and educational level), human capital, and tenure. The results revealed that leaders' psychological capital positively influenced their followers' psychological capital through the mediation effect of enhancing followers' organizational identification. The implications of these findings, the study's limitations, and directions for future research are discussed. PMID:29075218

Does it get better? A longitudinal analysis of psychological distress and victimization in lesbian, gay, bisexual, transgender, and questioning youth.

PubMed

Birkett, Michelle; Newcomb, Michael E; Mustanski, Brian

2015-03-01

The mental health and victimization of lesbian, gay, bisexual, transgender, and questioning (LGBTQ) youth have garnered media attention with the "It Gets Better Project." Despite this popular interest, there is an absence of empirical evidence evaluating a possible developmental trajectory in LGBTQ distress and the factors that might influence distress over time. This study used an accelerated longitudinal design and multilevel modeling to examine a racially/ethnically diverse analytic sample of 231 LGBTQ adolescents aged 16-20 years at baseline, across six time points, and over 3.5 years. Results indicated that both psychological distress and victimization decreased across adolescence and into early adulthood. Furthermore, time-lagged analyses and mediation analyses suggested that distress was related to prior experiences of victimization, with greater victimization leading to greater distress. Support received from parents, peers, and significant others was negatively correlated with psychological distress in the cross-sectional model but did not reach significance in the time-lagged model. Analyses suggest that psychological distress might "get better" when adolescents encounter less victimization and adds to a growing literature indicating that early experiences of stress impact the mental health of LGBTQ youth. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Communication Efficacy and Couples’ Cancer Management: Applying a Dyadic Appraisal Model

PubMed Central

Magsamen-Conrad, Kate; Checton, Maria G.; Venetis, Maria K.; Greene, Kathryn

2014-01-01

The purpose of the present study was to apply Berg and Upchurch’s (2007) developmental-conceptual model to understand better how couples cope with cancer. Specifically, we hypothesized a dyadic appraisal model in which proximal factors (relational quality), dyadic appraisal (prognosis uncertainty), and dyadic coping (communication efficacy) predicted adjustment (cancer management). The study was cross-sectional and included 83 dyads in which one partner had been diagnosed with and/or treated for cancer. For both patients and partners, multilevel analyses using the actor-partner interdependence model (APIM) indicated that proximal contextual factors predicted dyadic appraisal and dyadic coping. Dyadic appraisal predicted dyadic coping, which then predicted dyadic adjustment. Patients’ confidence in their ability to talk about the cancer predicted their own cancer management. Partners’ confidence predicted their own and the patient’s ability to cope with cancer, which then predicted patients’ perceptions of their general health. Implications and future research are discussed. PMID:25983382

Communication Efficacy and Couples' Cancer Management: Applying a Dyadic Appraisal Model.

PubMed

Magsamen-Conrad, Kate; Checton, Maria G; Venetis, Maria K; Greene, Kathryn

2015-06-01

The purpose of the present study was to apply Berg and Upchurch's (2007) developmental-conceptual model to understand better how couples cope with cancer. Specifically, we hypothesized a dyadic appraisal model in which proximal factors (relational quality), dyadic appraisal (prognosis uncertainty), and dyadic coping (communication efficacy) predicted adjustment (cancer management). The study was cross-sectional and included 83 dyads in which one partner had been diagnosed with and/or treated for cancer. For both patients and partners, multilevel analyses using the actor-partner interdependence model (APIM) indicated that proximal contextual factors predicted dyadic appraisal and dyadic coping. Dyadic appraisal predicted dyadic coping, which then predicted dyadic adjustment. Patients' confidence in their ability to talk about the cancer predicted their own cancer management. Partners' confidence predicted their own and the patient's ability to cope with cancer, which then predicted patients' perceptions of their general health. Implications and future research are discussed.

A tutorial on count regression and zero-altered count models for longitudinal substance use data

PubMed Central

Atkins, David C.; Baldwin, Scott A.; Zheng, Cheng; Gallop, Robert J.; Neighbors, Clayton

2012-01-01

Critical research questions in the study of addictive behaviors concern how these behaviors change over time - either as the result of intervention or in naturalistic settings. The combination of count outcomes that are often strongly skewed with many zeroes (e.g., days using, number of total drinks, number of drinking consequences) with repeated assessments (e.g., longitudinal follow-up after intervention or daily diary data) present challenges for data analyses. The current article provides a tutorial on methods for analyzing longitudinal substance use data, focusing on Poisson, zero-inflated, and hurdle mixed models, which are types of hierarchical or multilevel models. Two example datasets are used throughout, focusing on drinking-related consequences following an intervention and daily drinking over the past 30 days, respectively. Both datasets as well as R, SAS, Mplus, Stata, and SPSS code showing how to fit the models are available on a supplemental website. PMID:22905895

Publication bias in obesity treatment trials?

PubMed

Allison, D B; Faith, M S; Gorman, B S

1996-10-01

The present investigation examined the extent of publication bias (namely the tendency to publish significant findings and file away non-significant findings) within the obesity treatment literature. Quantitative literature synthesis of four published meta-analyses from the obesity treatment literature. Interventions in these studies included pharmacological, educational, child, and couples treatments. To assess publication bias, several regression procedures (for example weighted least-squares, random-effects multi-level modeling, and robust regression methods) were used to regress effect sizes onto their standard errors, or proxies thereof, within each of the four meta-analysis. A significant positive beta weight in these analyses signified publication bias. There was evidence for publication bias within two of the four published meta-analyses, such that reviews of published studies were likely to overestimate clinical efficacy. The lack of evidence for publication bias within the two other meta-analyses might have been due to insufficient statistical power rather than the absence of selection bias. As in other disciplines, publication bias appears to exist in the obesity treatment literature. Suggestions are offered for managing publication bias once identified or reducing its likelihood in the first place.

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

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…

A computer simulator for development of engineering system design methodologies

NASA Technical Reports Server (NTRS)

Padula, S. L.; Sobieszczanski-Sobieski, J.

1987-01-01

A computer program designed to simulate and improve engineering system design methodology is described. The simulator mimics the qualitative behavior and data couplings occurring among the subsystems of a complex engineering system. It eliminates the engineering analyses in the subsystems by replacing them with judiciously chosen analytical functions. With the cost of analysis eliminated, the simulator is used for experimentation with a large variety of candidate algorithms for multilevel design optimization to choose the best ones for the actual application. Thus, the simulator serves as a development tool for multilevel design optimization strategy. The simulator concept, implementation, and status are described and illustrated with examples.

Design and Fabrication of Orthotropic Deck Details

DOT National Transportation Integrated Search

2016-02-01

The objectives of the research were to verify the design and fabrication of the orthotropic deck details proposed for the lift bridge, for infinite fatigue life. Multi-level 3D finite element analyses (FEA) of the proposed deck were performed to dete...

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.

Oxytocin Augmentation in Spontaneously Laboring, Nulliparous Women: Multilevel Assessment of Maternal BMI and Oxytocin Dose

PubMed Central

Carlson, Nicole S.; Corwin, Elizabeth J.; Lowe, Nancy K.

2017-01-01

Background Synthetic oxytocin, the primary tool for labor augmentation, is less effective among obese women, leading to more unplanned cesarean deliveries for slow labor progress. It is not known if obese women require higher doses of oxytocin due to maternal, fetal, or labor factors related to maternal obesity. Objectives This study had two main objectives: 1) Examine the influence of maternal body mass index (BMI) on hourly doses of oxytocin from augmentation initiation until vaginal delivery in obese women; and 2) Examine the influence of other maternal, fetal, and labor factors on hourly doses of oxytocin in obese women. Study design Longitudinal study of a cohort (N = 136) of healthy, nulliparous, spontaneously laboring obese women (BMI ≥ 30 kg/m2) who received oxytocin augmentation and achieved vaginal delivery. We performed iterative multilevel analyses to examine the influence of maternal BMI and other factors on hourly oxytocin doses. Results Maternal BMI explained 16.56% (95% CI [13.7-20.04], p < 0.001) of the variance in hourly oxytocin doses received in a multilevel model controlling for influence of maternal, fetal, and labor characteristics. Maternal age, gestational age, status of amniotic membranes at hospital admission, and admission cervical dilation examination were not significant; however, neonatal birthweight and cervical dilation at oxytocin initiation were significant predictors of hourly oxytocin dose in these women (p < 0.001). Conclusions Even when parturition preparation has progressed adequately for spontaneous labor initiation, there still may be some obesity-related blunting of myometrial contractility and response to oxytocin used for augmentation. PMID:28347147

Oxytocin Augmentation in Spontaneously Laboring, Nulliparous Women: Multilevel Assessment of Maternal BMI and Oxytocin Dose.

PubMed

Carlson, Nicole S; Corwin, Elizabeth J; Lowe, Nancy K

2017-07-01

Synthetic oxytocin, the primary tool for labor augmentation, is less effective among obese women, leading to more unplanned cesarean deliveries for slow labor progress. It is not known if obese women require higher doses of oxytocin due to maternal, fetal, or labor factors related to maternal obesity. This study had two main objectives: (1) examine the influence of maternal body mass index (BMI) on hourly doses of oxytocin from augmentation initiation until vaginal delivery in obese women; and (2) examine the influence of other maternal, fetal, and labor factors on hourly doses of oxytocin in obese women. Longitudinal study of a cohort ( N = 136) of healthy, nulliparous, spontaneously laboring obese women (BMI ≥ 30 kg/m 2 ) who received oxytocin augmentation and achieved vaginal delivery. We performed iterative multilevel analyses to examine the influence of maternal BMI and other factors on hourly oxytocin doses. Maternal BMI explained 16.56% (95% confidence interval [CI] = [13.7, 20.04], p < .001) of the variance in hourly oxytocin doses received in a multilevel model controlling for influence of maternal, fetal, and labor characteristics. Maternal age, gestational age, status of amniotic membranes at hospital admission, and admission cervical dilation examination were not significant; however, neonatal birthweight and cervical dilation at oxytocin initiation were significant predictors of hourly oxytocin dose in these women ( p < .001). Even when parturition preparation has progressed adequately for spontaneous labor initiation, there still may be some obesity-related blunting of myometrial contractility and response to oxytocin used for augmentation.

[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.

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.

The effects of sports participation on the development of left ventricular mass in adolescent boys.

PubMed

Valente-Dos-Santos, João; Coelho-E-Silva, Manuel J; Castanheira, Joaquim; Machado-Rodrigues, Aristides M; Cyrino, Edilson S; Sherar, Lauren B; Esliger, Dale W; Elferink-Gemser, Marije T; Malina, Robert M

2015-01-01

To examine the contribution of body size, biological maturation, and nonelite sports participation to longitudinal changes of left ventricular mass (LVM) in healthy boys. One hundred and ten boys (11.0-14.5 years at baseline) were assessed biannually for 2 years. Stature, body mass, and four skinfolds were measured. Lean body mass (LBM) was estimated. Biological maturation was assessed as years from age at peak height velocity (APHV). Sports participation was assessed by questionnaire. LVM was obtained from M-mode echocardiograms using two-dimensional images. To account for the repeated measures within individual nature of longitudinal data, multilevel random effects regression analyses were used in the analysis. LVM increased on average 42 ± 18 g from 11 to 15 years (P < 0.05) and 76 ± 14 g from 3.5 years pre-APHV to 1.5 years post-APHV (P < 0.05). The multilevel model with the best statistical fit (Model B) showed that changes of 1 cm in stature, 1 year post-APHV, and 1 kg of LBM predicts 4.7, 0.5, and 1 g of LVM (P < 0.05), respectively. Among healthy, male adolescents aged 11-15 years individual differences in growth and biological maturation influence growth of LVM. Subcutaneous adiposity and sports participation were not associated with greater LVM. © 2015 Wiley Periodicals, Inc.

Mental health of lesbian, gay, bisexual, and heterosexual siblings: effects of gender, sexual orientation, and family.

PubMed

Balsam, Kimberly F; Beauchaine, Theodore P; Mickey, Ruth M; Rothblum, Esther D

2005-08-01

Self-identified lesbian, gay male, and bisexual (LGB) individuals were recruited via convenience sampling, and they in turn recruited their siblings (79% heterosexual, 19% LGB). The resulting sample of 533 heterosexual, 558 lesbian or gay male, and 163 bisexual participants was compared on mental health variables and their use of mental health services. Multilevel modeling analyses revealed that sexual orientation predicted suicidal ideation, suicide attempts, self-injurious behavior, use of psychotherapy, and use of psychiatric medications over and above the effects of family adjustment. Sexual orientation was unrelated to current psychological distress, psychiatric hospitalizations, and self-esteem. This is the 1st study to model family effects on the mental health of LGB participants and their siblings. Copyright (c) 2005 APA, all rights reserved.

Attitude similarity and familiarity and their links to mental health: An examination of potential interpersonal mediators.

PubMed

Moore, Shannon M; Uchino, Bert N; Baucom, Brian R W; Behrends, Arwen A; Sanbonmatsu, David

2017-01-01

Similarity and familiarity with partner's attitudes are linked to positive relationship outcomes, while interpersonal variables have been linked to mental health. Using multilevel models (MLMs), we modeled the associations between these attitudinal variables and mental health outcomes in 74 married couples. We found that higher levels of attitude similarity in couples were linked to lower depression, while higher levels of attitude familiarity in couples were associated with greater satisfaction with life. Mediational analyses indicated marital satisfaction and interpersonal stress mediated the link between attitude similarity and depression. Marital satisfaction also mediated the link between familiarity and satisfaction with life. This study is the first linking attitude familiarity to mental health and provides evidence that familiarity and similarity have mental health effects partly due to their interpersonal consequences.

Differential Effects of Arousal in Positive and Negative Autobiographical Memories

PubMed Central

Ford, Jaclyn Hennessey; Addis, Donna Rose; Giovanello, Kelly S.

2014-01-01

Autobiographical memories are characterized by a range of emotions and emotional reactions. Recent research has demonstrated that differences in emotional valence (positive v. negative emotion) and arousal (the degree of emotional intensity) differentially influence the retrieved memory narrative. Although the mnemonic effects of valence and arousal have both been heavily studied, it is currently unclear whether the effects of emotional arousal are equivalent for positive and negative autobiographical events. In the current study, multilevel models were used to examine differential effects emotional valence and arousal on the richness of autobiographical memory retrieval both between and within subjects. Thirty-four young adults were asked to retrieve personal autobiographical memories associated with popular musical cues and to rate the valence, arousal, and richness of these events. The multilevel analyses identified independent influences of valence and intensity upon retrieval characteristics at the within and between subject levels. In addition, the within subject interactions between valence and arousal highlighted differential effects of arousal for positive and negative memories. These findings have important implications for future studies of emotion and memory, highlighting the importance of considering both valence and arousal when examining the role emotion plays in the richness of memory representation. PMID:22873402

Differential effects of arousal in positive and negative autobiographical memories.

PubMed

Ford, Jaclyn Hennessey; Addis, Donna Rose; Giovanello, Kelly S

2012-01-01

Autobiographical memories are characterised by a range of emotions and emotional reactions. Recent research has demonstrated that differences in emotional valence (positive vs. negative emotion) and arousal (the degree of emotional intensity) differentially influence the retrieved memory narrative. Although the mnemonic effects of valence and arousal have both been heavily studied, it is currently unclear whether the effects of emotional arousal are equivalent for positive and negative autobiographical events. In the current study, multilevel models were used to examine differential effects of emotional valence and arousal on the richness of autobiographical memory retrieval both between and within subjects. Thirty-four young adults were asked to retrieve personal autobiographical memories associated with popular musical cues and to rate the valence, arousal and richness of these events. The multilevel analyses identified independent influences of valence and intensity upon retrieval characteristics at the within- and between-subject levels. In addition, the within-subject interactions between valence and arousal highlighted differential effects of arousal for positive and negative memories. These findings have important implications for future studies of emotion and memory, highlighting the importance of considering both valence and arousal when examining the role emotion plays in the richness of memory representation.

School Contextual Features of Social Disorder and Mental Health Complaints—A Multilevel Analysis of Swedish Sixth-Grade Students

PubMed Central

Modin, Bitte; Plenty, Stephanie; Låftman, Sara B.; Bergström, Malin; Berlin, Marie; Hjern, Anders

2018-01-01

This study addressed school-contextual features of social disorder in relation to sixth-grade students’ experiences of bullying victimization and mental health complaints. It investigated, firstly, whether the school’s concentrations of behavioural problems were associated with individual students’ likelihood of being bullied, and secondly, whether the school’s concentrations of behavioural problems and bullying victimization predicted students’ emotional and psychosomatic health complaints. The data were derived from the Swedish National Survey of Mental Health among Children and Young People, carried out among sixth-grade students (approximately 12–13 years old) in Sweden in 2009. The analyses were based on information from 59,510 students distributed across 1999 schools. The statistical method used was multilevel modelling. While students’ own behavioural problems were associated with an elevated risk of being bullied, attending a school with a higher concentration of students with behavioural problems also increased the likelihood of being bullied. Attending a school with higher levels of bullying victimization and behavioural problems predicted more emotional and psychosomatic complaints, even when adjusting for their individual level analogues. The findings indicate that school-level features of social disorder influence bullying victimization and mental health complaints among students. PMID:29351244

Athletes' perceptions of role ambiguity and coaching competency in sport teams: a multilevel analysis.

PubMed

Bosselut, Grégoire; Heuzé, Jean-Philippe; Eys, Mark A; Fontayne, Paul; Sarrazin, Philippe

2012-06-01

The purpose of this study was to examine the relationship between athletes' perceptions of role ambiguity and two theoretically derived dimensions of coaching competency (i.e., game strategy and technique competencies). A total of 243 players from 26 teams representing various interdependent sports completed French versions of the Role Ambiguity Scale and the Coaching Competency Scale. Multilevel analyses supported the existence of relationships between the four dimensions of role ambiguity and the two dimensions of coaching competency at both individual and team levels. When the levels were considered jointly, athletes perceiving greater ambiguity in their role in both offensive and defensive contexts were more critical of their coach's capacities to lead their team during competitions and to diagnose or formulate instructions during training sessions. The results also indicated that the dimension of scope of responsibilities was the main contributor to the relationship with coaching competency at an individual level, whereas role evaluation was the main contributor to this relationship at a group level. Findings are discussed in relation to the role episode model, the role ambiguity dimensions involved in the relationships according to the level of analysis considered, and the salience of ambiguity perceptions in the offensive context.

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.

Psychological distress in the workforce: a multilevel and longitudinal analysis of the case of regulated occupations in Canada.

PubMed

Cadieux, Nathalie; Marchand, Alain

2014-08-07

This study uses a multidimensional theoretical model to evaluate the role of regulated occupations and working conditions in explaining psychological distress. Various multilevel regression analyses were conducted on longitudinal data for which measures repeated over time (n1 = 36,166) were nested in individuals (n2 = 7007). Results showed that when we controlled for working conditions, family situation, the social network outside the workplace, and personal characteristics, the level of psychological distress was significantly lower among professional workers in regulated occupations than among professionals not in regulated occupations. Among the working conditions studied, skill utilisation, psychological demands, and job insecurity were positively associated with psychological distress levels, whereas social support in the workplace was inversely related to distress. Finally, our results suggest that self-esteem reduced the effect of social support in the workplace on psychological distress levels in the workforce. These results support our hypothesis that working in regulated occupations exerts a direct effect on mental health. These results also make clear the importance of developing new tools for measuring psychological distress among upper-level professional workers. Such tools will be much better suited to the realities characterising today's knowledge-based economies.

The educational gradient in marriage: a comparison of 25 European countries.

PubMed

Kalmijn, Matthijs

2013-08-01

Previous research has suggested that a new marriage gradient has emerged in the United States, with marriage becoming increasingly the privilege of the better-educated. This article examines whether this is true for Europe and explores differences in the marriage gradient among 25 European countries, using multilevel models. The focus is on the chances of living in a marital (or cohabiting) union during midlife (ages 40-49). Multilevel analyses show that the direction and strength of the gradient depend on the societal context. In countries where gender roles are traditional, better-educated women are less likely to be married than less-educated women; in gender-egalitarian countries, better-educated women are more likely to be married. For men, the educational effect on marriage is absent in traditional countries but becomes positive as gender roles become more equal. Inequality in a society also modifies the gradient: if the degree of economic inequality between educational groups in a society is strong, better-educated men are more likely to be married than less-educated men. In general, the results suggest that there may be an accumulation of social and economic disadvantages for the less well educated in more-developed countries.

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.

Nurses' practice environment and satisfaction with schedule flexibility is related to intention to leave due to dissatisfaction: A multi-country, multilevel study.

PubMed

Leineweber, Constanze; Chungkham, Holendro Singh; Lindqvist, Rikard; Westerlund, Hugo; Runesdotter, Sara; Smeds Alenius, Lisa; Tishelman, Carol

2016-06-01

Nursing turnover is a major issue for health care managers, notably during the global nursing workforce shortage. Despite the often hierarchical structure of the data used in nursing studies, few studies have investigated the impact of the work environment on intention to leave using multilevel techniques. Also, differences between intentions to leave the current workplace or to leave the profession entirely have rarely been studied. The aim of the current study was to investigate how aspects of the nurse practice environment and satisfaction with work schedule flexibility measured at different organisational levels influenced the intention to leave the profession or the workplace due to dissatisfaction. Multilevel models were fitted using survey data from the RN4CAST project, which has a multi-country, multilevel, cross-sectional design. The data analysed here are based on a sample of 23,076 registered nurses from 2020 units in 384 hospitals in 10 European countries (overall response rate: 59.4%). Four levels were available for analyses: country, hospital, unit, and individual registered nurse. Practice environment and satisfaction with schedule flexibility were aggregated and studied at the unit level. Gender, experience as registered nurse, full vs. part-time work, as well as individual deviance from unit mean in practice environment and satisfaction with work schedule flexibility, were included at the individual level. Both intention to leave the profession and the hospital due to dissatisfaction were studied. Regarding intention to leave current workplace, there is variability at both country (6.9%) and unit (6.9%) level. However, for intention to leave the profession we found less variability at the country (4.6%) and unit level (3.9%). Intention to leave the workplace was strongly related to unit level variables. Additionally, individual characteristics and deviance from unit mean regarding practice environment and satisfaction with schedule flexibility were related to both outcomes. Major limitations of the study are its cross-sectional design and the fact that only turnover intention due to dissatisfaction was studied. We conclude that measures aiming to improve the practice environment and schedule flexibility would be a promising approach towards increased retention of registered nurses in both their current workplaces and the nursing profession as a whole and thus a way to counteract the nursing shortage across European countries. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

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.

A multilevel reuse system with source separation process for printing and dyeing wastewater treatment: A case study.

PubMed

Wang, Rui; Jin, Xin; Wang, Ziyuan; Gu, Wantao; Wei, Zhechao; Huang, Yuanjie; Qiu, Zhuang; Jin, Pengkang

2018-01-01

This paper proposes a new system of multilevel reuse with source separation in printing and dyeing wastewater (PDWW) treatment in order to dramatically improve the water reuse rate to 35%. By analysing the characteristics of the sources and concentrations of pollutants produced in different printing and dyeing processes, special, highly, and less contaminated wastewaters (SCW, HCW, and LCW, respectively) were collected and treated separately. Specially, a large quantity of LCW was sequentially reused at multiple levels to meet the water quality requirements for different production processes. Based on this concept, a multilevel reuse system with a source separation process was established in a typical printing and dyeing enterprise. The water reuse rate increased dramatically to 62%, and the reclaimed water was reused in different printing and dyeing processes based on the water quality. This study provides promising leads in water management for wastewater reclamation. Copyright © 2017 Elsevier Ltd. All rights reserved.

From deindustrialization to individual health-related quality of life: multilevel evidence of contextual predictors, mediators and modulators across French regions, 2003.

PubMed

Audureau, Etienne; Rican, Stéphane; Coste, Joël

2013-07-01

Although small area effects on health-related quality of life (HRQoL) have been extensively studied, less is known at the regional level, particularly in France where no multilevel evidence is available. Using data from a large representative cross-sectional survey conducted in 2003 (N=16 732), this study explores individual and regional determinants of the SF-36 Physical Functioning and Mental Health subscales. We considered a causal pathway leading from deindustrialization to HRQoL and assessed the roles of net migratory flows, deprivation, and the social and physical environments. Worse HRQoL results were found in regions most affected by deindustrialization, with evidence for mediating effects of migration, voter abstention rate and individual health-related behaviors. Cross-level interactions and intraregional heterogeneity were also found, confirming the complexity of individual-area relationships and the need for carefully conceptualized multilevel analyses to guide health policies effectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

Defending Victims of Bullying in Early Adolescence: A Multilevel Analysis.

PubMed

Yun, Hye-Young; Graham, Sandra

2018-05-29

Adolescents' defending behaviors in school bullying situations is likely determined by individual characteristics, social status variables, and classroom/school contextual factors operating simultaneously in the peer ecology. However, there is little research on defending behavior that utilizes this multilevel approach. This study investigated how students' willingness to defend victims of bullying was affected by feelings of empathy, perceived popularity, and classroom-level perceived prosocial norms. Participants were 1373 adolescents (40% girls, Mage: 14 yrs) from 54 classrooms in six middle schools in South Korea. These youth reported on their feelings of empathy and how prosocial they perceived their classmates to be. Peer-ratings and peer nominations were used to estimate defending behaviors and which students were perceived as popular. Multilevel analyses showed that participants were more likely to defend victims when they had greater empathy and perceived popularity and when classroom-level prosocial norms were higher. The findings have implications for interventions to reduce school bullying and for studying defending behavior in multiple cultural contexts.

Reducing Children’s Behavior Problems through Social Capital: A Causal Assessment

PubMed Central

López Turley, Ruth N.; Gamoran, Adam; McCarty, Alyn Turner; Fish, Rachel

2016-01-01

Behavior problems among young children have serious detrimental effects on short and long-term educational outcomes. An especially promising prevention strategy may be one that focuses on strengthening the relationships among families in schools, or social capital. However, empirical research on social capital has been constrained by conceptual and causal ambiguity. This study attempts to construct a more focused conceptualization of social capital and aims to determine the causal effects of social capital on children’s behavior. Using data from a cluster randomized trial of 52 elementary schools, we apply several multilevel models to assess the causal relationship, including intent to treat and treatment on the treated analyses. Taken together, these analyses provide stronger evidence than previous studies that social capital improves children’s behavioral outcomes and that these improvements are not simply a result of selection into social relations but result from the social relations themselves. PMID:27886729

Conflicting social motives in negotiating groups.

PubMed

Weingart, Laurie R; Brett, Jeanne M; Olekalns, Mara; Smith, Philip L

2007-12-01

Negotiators' social motives (cooperative vs. individualistic) influence their strategic behaviors. In this study, the authors used multilevel modeling and analyses of strategy sequences to test hypotheses regarding how negotiators' social motives and the composition of the group influence group members' negotiation strategies. Four-person groups negotiating a 5-issue mixed-motive decision-making task were videotaped, and the tapes were transcribed and coded. Group composition included 2 homogeneous conditions (all cooperators and all individualists) and 3 heterogeneous conditions (3 cooperators and 1 individualist, 2 cooperators and 2 individualists, 1 cooperator and 3 individualists). Results showed that cooperative negotiators adjusted their use of integrative and distributive strategies in response to the social-motive composition of the group, but individualistic negotiators did not. Results from analyses of strategy sequences showed that cooperators responded more systematically to others' behaviors than did individualists. They also redirected the negotiation depending on group composition. (c) 2007 APA, all rights reserved.

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…

Association between tobacco control policies and smoking behaviour among adolescents in 29 European countries.

PubMed

Hublet, Anne; Schmid, Holger; Clays, Els; Godeau, Emmanuelle; Gabhainn, Saoirse Nic; Joossens, Luk; Maes, Lea

2009-11-01

To investigate the associations between well-known, cost-effective tobacco control policies at country level and smoking prevalence among 15-year-old adolescents. Multi-level modelling based on the 2005-06 Health Behaviour in School-aged Children Study, a cross-national study at individual level, and with country-level variables from the Tobacco Control Scale and published country-level databases. Twenty-nine European countries. A total of 25 599 boys and 26 509 girls. Self-reported regular smoking defined as at least weekly smoking, including daily smoking (dichotomous). Interaction effects between gender and smoking policies were identified, therefore boys and girls were analysed separately. Large cross-national differences in smoking prevalence were documented. Intraclass correlations (ICC) of 0.038 (boys) and 0.035 (girls) were found. In the final multi-level model for boys, besides the significance of the individual variables such as family affluence, country-level affluence and the legality of vending machines were related significantly to regular smoking [b(country affluence) = -0.010; b(partial restriction vending machines) = -0.366, P < 0.05]. Price policy was of borderline significance [b(price policy) = -0.026, P = 0.050]. All relationships were in the expected direction. The model fit is not as good for girls; only the legality of vending machines had a borderline significance in the final model [b(total ban vending machines) = -0.372, P = 0.06]. For boys, some of the currently recommended tobacco control policies may help to reduce smoking prevalence. However, the model is less suitable for girls, indicating gender differences in the potential efficacy of smoking policies. Future research should address this issue.

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

Fast food purchasing and access to fast food restaurants: a multilevel analysis of VicLANES.

PubMed

Thornton, Lukar E; Bentley, Rebecca J; Kavanagh, Anne M

2009-05-27

While previous research on fast food access and purchasing has not found evidence of an association, these studies have had methodological problems including aggregation error, lack of specificity between the exposures and outcomes, and lack of adjustment for potential confounding. In this paper we attempt to address these methodological problems using data from the Victorian Lifestyle and Neighbourhood Environments Study (VicLANES) - a cross-sectional multilevel study conducted within metropolitan Melbourne, Australia in 2003. The VicLANES data used in this analysis included 2547 participants from 49 census collector districts in metropolitan Melbourne, Australia. The outcome of interest was the total frequency of fast food purchased for consumption at home within the previous month (never, monthly and weekly) from five major fast food chains (Red Rooster, McDonalds, Kentucky Fried Chicken, Hungry Jacks and Pizza Hut). Three measures of fast food access were created: density and variety, defined as the number of fast food restaurants and the number of different fast food chains within 3 kilometres of road network distance respectively, and proximity defined as the road network distance to the closest fast food restaurant.Multilevel multinomial models were used to estimate the associations between fast food restaurant access and purchasing with never purchased as the reference category. Models were adjusted for confounders including determinants of demand (attitudes and tastes that influence food purchasing decisions) as well as individual and area socio-economic characteristics. Purchasing fast food on a monthly basis was related to the variety of fast food restaurants (odds ratio 1.13; 95% confidence interval 1.02 - 1.25) after adjusting for individual and area characteristics. Density and proximity were not found to be significant predictors of fast food purchasing after adjustment for individual socio-economic predictors. Although we found an independent association between fast food purchasing and access to a wider variety of fast food restaurant, density and proximity were not significant predictors. The methods used in our study are an advance on previous analyses.

Alcohol and liver cirrhosis mortality in the United States: comparison of methods for the analyses of time-series panel data models.

PubMed

Ye, Yu; Kerr, William C

2011-01-01

To explore various model specifications in estimating relationships between liver cirrhosis mortality rates and per capita alcohol consumption in aggregate-level cross-section time-series data. Using a series of liver cirrhosis mortality rates from 1950 to 2002 for 47 U.S. states, the effects of alcohol consumption were estimated from pooled autoregressive integrated moving average (ARIMA) models and 4 types of panel data models: generalized estimating equation, generalized least square, fixed effect, and multilevel models. Various specifications of error term structure under each type of model were also examined. Different approaches controlling for time trends and for using concurrent or accumulated consumption as predictors were also evaluated. When cirrhosis mortality was predicted by total alcohol, highly consistent estimates were found between ARIMA and panel data analyses, with an average overall effect of 0.07 to 0.09. Less consistent estimates were derived using spirits, beer, and wine consumption as predictors. When multiple geographic time series are combined as panel data, none of existent models could accommodate all sources of heterogeneity such that any type of panel model must employ some form of generalization. Different types of panel data models should thus be estimated to examine the robustness of findings. We also suggest cautious interpretation when beverage-specific volumes are used as predictors. Copyright © 2010 by the Research Society on Alcoholism.

Promoting and Protecting Against Stigma in Assisted Living and Nursing Homes

PubMed Central

Zimmerman, Sheryl; Dobbs, Debra; Roth, Erin G.; Goldman, Susan; Peeples, Amanda D.; Wallace, Brandy

2016-01-01

Purpose of the Study: To determine the extent to which structures and processes of care in multilevel settings (independent living, assisted living, and nursing homes) result in stigma in assisted living and nursing homes. Design and Methods: Ethnographic in-depth interviews were conducted in 5 multilevel settings with 256 residents, families, and staff members. Qualitative analyses identified the themes that resulted when examining text describing either structures of care or processes of care in relation to 7 codes associated with stigma. Results: Four themes related to structures of care and stigma were identified, including the physical environment, case mix, staff training, and multilevel settings; five themes related to processes of care and stigma, including dining, independence, respect, privacy, and care provision. For each theme, examples were identified illustrating how structures and processes of care can potentially promote or protect against stigma. Implications: In no instance were examples or themes identified that suggested the staff intentionally promoted stigma; on the other hand, there was indication that some structures and processes were intentionally in place to protect against stigma. Perhaps the most important theme is the stigma related to multilevel settings, as it has the potential to reduce individuals’ likelihood to seek and accept necessary care. Results suggest specific recommendations to modify care and reduce stigma. PMID:24928555

The care unit in nursing home research: evidence in support of a definition.

PubMed

Estabrooks, Carole A; Morgan, Debra G; Squires, Janet E; Boström, Anne-Marie; Slaughter, Susan E; Cummings, Greta G; Norton, Peter G

2011-04-14

Defining what constitutes a resident care unit in nursing home research is both a conceptual and practical challenge. The aim of this paper is to provide evidence in support of a definition of care unit in nursing homes by demonstrating: (1) its feasibility for use in data collection, (2) the acceptability of aggregating individual responses to the unit level, and (3) the benefit of including unit level data in explanatory models. An observational study design was used. Research (project) managers, healthcare aides, care managers, nursing home administrators and directors of care from thirty-six nursing homes in the Canadian prairie provinces of Alberta, Saskatchewan and Manitoba provided data for the study. A definition of care unit was developed and applied in data collection and analyses. A debriefing session was held with research managers to investigate their experiences with using the care unit definition. In addition, survey responses from 1258 healthcare aides in 25 of the 36 nursing homes in the study, that had more than one care unit, were analyzed using a multi-level modeling approach. Trained field workers administered the Alberta Context Tool (ACT), a 58-item self-report survey reflecting 10 organizational context concepts, to healthcare aides using computer assisted personal interviews. To assess the appropriateness of obtaining unit level scores, we assessed aggregation statistics (ICC(1), ICC(2), η², and ω²), and to assess the value of using the definition of unit in explanatory models, we performed multi-level modeling. In 10 of the 36 nursing homes, the care unit definition developed was used to align the survey data (for analytic purposes) to specific care units as designated by our definition, from that reported by the facility administrator. The aggregation statistics supported aggregating the healthcare aide responses on the ACT to the realigned unit level. Findings from the multi-level modeling further supported unit level aggregation. A significantly higher percentage of variance was explained in the ACT concepts at the unit level compared to the individual and/or nursing home levels. The statistical results support the use of our definition of care unit in nursing home research in the Canadian prairie provinces. Beyond research convenience however, the results also support the resident unit as an important Clinical Microsystem to which future interventions designed to improve resident quality of care and staff (healthcare aide) worklife should be targeted.

Predicting research use in nursing organizations: a multilevel analysis.

PubMed

Estabrooks, Carole A; Midodzi, William K; Cummings, Greta G; Wallin, Lars

2007-01-01

No empirical literature was found that explained how organizational context (operationalized as a composite of leadership, culture, and evaluation) influences research utilization. Similarly, no work was found on the interaction of individuals and contextual factors, or the relative importance or contribution of forces at different organizational levels to either such proposed interactions or, ultimately, to research utilization. To determine independent factors that predict research utilization among nurses, taking into account influences at individual nurse, specialty, and hospital levels. Cross-sectional survey data for 4,421 registered nurses in Alberta, Canada were used in a series of multilevel (three levels) modeling analyses to predict research utilization. A multilevel model was developed in MLwiN version 2.0 and used to: (a) estimate simultaneous effects of several predictors and (b) quantify the amount of explained variance in research utilization that could be apportioned to individual, specialty, and hospital levels. There was significant variation in research utilization (p <.05). Factors (remaining in the final model at statistically significant levels) found to predict more research utilization at the three levels of analysis were as follows. At the individual nurse level (Level 1): time spent on the Internet and lower levels of emotional exhaustion. At the specialty level (Level 2): facilitation, nurse-to-nurse collaboration, a higher context (i.e., of nursing culture, leadership, and evaluation), and perceived ability to control policy. At the hospital level (Level 3): only hospital size was significant in the final model. The total variance in research utilization was 1.04, and the intraclass correlations (the percent contribution by contextual factors) were 4% (variance = 0.04, p <.01) at the hospital level and 8% (variance = 0.09, p <.05) at the specialty level. The contribution attributable to individual factors alone was 87% (variance = 0.91, p <.01). Variation in research utilization was explained mainly by differences in individual characteristics, with specialty- and organizational-level factors contributing relatively little by comparison. Among hospital-level factors, hospital size was the only significant determinant of research utilization. Although organizational determinants explained less variance in the model, they were still statistically significant when analyzed alone. These findings suggest that investigations into mechanisms that influence research utilization must address influences at multiple levels of the organization. Such investigations will require careful attention to both methodological and interpretative challenges present when dealing with multiple units of analysis.

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.

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

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

PREDICTING INDIVIDUAL WELL-BEING THROUGH THE LANGUAGE OF SOCIAL MEDIA.

PubMed

Schwartz, H Andrew; Sap, Maarten; Kern, Margaret L; Eichstaedt, Johannes C; Kapelner, Adam; Agrawal, Megha; Blanco, Eduardo; Dziurzynski, Lukasz; Park, Gregory; Stillwell, David; Kosinski, Michal; Seligman, Martin E P; Ungar, Lyle H

2016-01-01

We present the task of predicting individual well-being, as measured by a life satisfaction scale, through the language people use on social media. Well-being, which encompasses much more than emotion and mood, is linked with good mental and physical health. The ability to quickly and accurately assess it can supplement multi-million dollar national surveys as well as promote whole body health. Through crowd-sourced ratings of tweets and Facebook status updates, we create message-level predictive models for multiple components of well-being. However, well-being is ultimately attributed to people, so we perform an additional evaluation at the user-level, finding that a multi-level cascaded model, using both message-level predictions and userlevel features, performs best and outperforms popular lexicon-based happiness models. Finally, we suggest that analyses of language go beyond prediction by identifying the language that characterizes well-being.

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/.

The influence of gender equality policies on gender inequalities in health in Europe.

PubMed

Palència, Laia; Malmusi, Davide; De Moortel, Deborah; Artazcoz, Lucía; Backhans, Mona; Vanroelen, Christophe; Borrell, Carme

2014-09-01

Few studies have addressed the effect of gender policies on women's health and gender inequalities in health. This study aims to analyse the relationship between the orientation of public gender equality policies and gender inequalities in health in European countries, and whether this relationship is mediated by gender equality at country level or by other individual social determinants of health. A multilevel cross-sectional study was performed using individual-level data extracted from the European Social Survey 2010. The study sample consisted of 23,782 men and 28,655 women from 26 European countries. The dependent variable was self-perceived health. Individual independent variables were gender, age, immigrant status, educational level, partner status and employment status. The main contextual independent variable was a modification of Korpi's typology of family policy models (Dual-earner, Traditional-Central, Traditional-Southern, Market-oriented and Contradictory). Other contextual variables were the Gender Empowerment Measure (GEM), to measure country-level gender equality, and the Gross Domestic Product (GDP). For each country and country typology the prevalence of fair/poor health by gender was calculated and prevalence ratios (PR, women compared to men) and 95% confidence intervals (CI) were computed. Multilevel robust Poisson regression models were fitted. Women had poorer self-perceived health than men in countries with traditional family policies (PR = 1.13, 95%CI: 1.07-1.21 in Traditional-Central and PR = 1.27, 95%CI: 1.19-1.35 in Traditional-Southern) and in Contradictory countries (PR = 1.08, 95%CI: 1.05-1.11). In multilevel models, only gender inequalities in Traditional-Southern countries were significantly higher than those in Dual-earner countries. Gender inequalities in self-perceived health were higher, women reporting worse self-perceived health than men, in countries with family policies that were less oriented to gender equality (especially in the Traditional-Southern country-group). This was partially explained by gender inequalities in the individual social determinants of health but not by GEM or GDP. Copyright © 2014 Elsevier Ltd. All rights reserved.

Impact of primary care nursing workforce characteristics on the control of high-blood pressure: a multilevel analysis

PubMed Central

Parro-Moreno, Ana; Serrano-Gallardo, Pilar; Díaz-Holgado, Antonio; Aréjula-Torres, Jose L; Abraira, Victor; Santiago-Pérez, Isolina M; Morales-Asencio, Jose M

2015-01-01

Objective To determine the impact of Primary Health Care (PHC) nursing workforce characteristics and of the clinical practice environment (CPE) perceived by nurses on the control of high-blood pressure (HBP). Design Cross-sectional analytical study. Setting Administrative and clinical registries of hypertensive patients from PHC information systems and questionnaire from PHC nurses. Participants 76 797 hypertensive patients in two health zones within the Community of Madrid, North-West Zone (NWZ) with a higher socioeconomic situation and South-West Zone (SWZ) with a lower socioeconomic situation, and 442 reference nurses. Segmented analyses by area were made due to their different socioeconomic characteristics. Primary outcome measure: Poor HBP control (adequate figures below the value 140/90 mm Hg) associated with the characteristics of the nursing workforce and self-perceived CPE. Results The prevalence of poor HBP control, estimated by an empty multilevel model, was 33.5% (95% CI 31.5% to 35.6%). In the multilevel multivariate regression models, the perception of a more favourable CPE was associated with a reduction in poor control in NWZ men and SWZ women (OR=0.99 (95% CI 0.98 to 0.99)); the economic immigration conditions increased poor control in NWZ women (OR=1.53 (95% CI 1.24 to 1.89)) and in SWZ, both men (OR=1.89 (95% CI 1.43 to 2.51)) and women (OR=1.39 (95% CI 1.09 to 1.76)). In all four models, increasing the annual number of patient consultations was associated with a reduction in poor control (NWZ women: OR=0.98 (95% CI0.98 to 0.99); NWZ men: OR=0.98 (95% CI 0.97 to 0.99); SWZ women: OR=0.98 (95% CI 0.97 to 0.99); SWZ men: OR=0.99 (95% CI 0.97 to 0.99). Conclusions A CPE, perceived by PHC nurses as more favourable, and more patient–nurse consultations, contribute to better HBP control. Economic immigration condition is a risk factor for poor HBP control. Health policies oriented towards promoting positive environments for nursing practice are needed. PMID:26644122

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.

Immigrants' health in Europe: a cross-classified multilevel approach to examine origin country, destination country, and community effects.

PubMed

Huijts, Tim; Kraaykamp, Gerbert

2012-01-01

In this study, we examined origin, destination, and community effects on first- and second-generation immigrants' health in Europe. We used information from the European Social Surveys (2002–2008) on 19,210 immigrants from 123 countries of origin, living in 31 European countries. Cross-classified multilevel regression analyses reveal that political suppression in the origin country and living in countries with large numbers of immigrant peers have a detrimental influence on immigrants' health. Originating from predominantly Islamic countries and good average health among natives in the destination country appear to be beneficial. Additionally, the results point toward health selection mechanisms into migration.

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…

A Multilevel Analysis of Japanese Middle School Student and School Socioeconomic Status Influence on Mathematics Achievement

ERIC Educational Resources Information Center

Takashiro, Naomi

2017-01-01

The author examined the simultaneous influence of Japanese middle school student and school socioeconomic status (SES) on student math achievement with two-level multilevel analysis models by utilizing the Trends in International Mathematics and Science Study (TIMSS) Japan data sets. The theoretical framework used in this study was…

When Cannabis Is Available and Visible at School--A Multilevel Analysis of Students' Cannabis Use

ERIC Educational Resources Information Center

Kuntsche, Emmanuel

2010-01-01

Aims: To investigate the links between the visibility of cannabis use in school (measured by teachers' reports of students being under the influence of cannabis on school premises), the proportion of cannabis users in the class, perceived availability of cannabis, as well as adolescent cannabis use. Methods: A multilevel regression model was…

A Multilevel Analysis of the Relationship between Shared Leadership and Creativity in Inter-Organizational Teams

ERIC Educational Resources Information Center

Gu, Jibao; Chen, Zhi; Huang, Qian; Liu, Hefu; Huang, Shenglan

2018-01-01

An inter-organizational team, which consists of diverse members from different organizations to conduct an initiative, has been widely treated as a critical method to improve organizational innovation. This study proposes a multilevel model to test the relationship between shared leadership and creativity at both team- and individual level in the…

Multilevel Dynamic Systems Affecting Introduction of HIV/STI Prevention Innovations among Chinese Women in Sex Work Establishments

ERIC Educational Resources Information Center

Weeks, Margaret R.; Li, Jianghong; Liao, Susu; Zhang, Qingning; Dunn, Jennifer; Wang, Yanhong; Jiang, Jingmei

2013-01-01

Social and public health scientists are increasingly interested in applying system dynamics theory to improve understanding and to harness the forces of change within complex, multilevel systems that affect community intervention implementation, effects, and sustainability. Building a system dynamics model based on ethnographic case study has the…

Role of Linguistic and Sociocultural Diversity in Reading Literacy Achievement: A Multilevel Approach

ERIC Educational Resources Information Center

Netten, Andrea; Luyten, Hans; Droop, Mienke; Verhoeven, Ludo

2016-01-01

This study examined how linguistic and sociocultural diversity have an impact on the reading literacy outcomes of a representative sample of 3,549 first-language (L1) and 208 second-language (L2) fourth-grade students in the Netherlands. A multilevel modelling analysis was conducted using Progress in International Reading Literacy Study 2006 data…

Synthesis of Single-Case Experimental Data: A Comparison of Alternative Multilevel Approaches

ERIC Educational Resources Information Center

Ferron, John; Van den Noortgate, Wim; Beretvas, Tasha; Moeyaert, Mariola; Ugille, Maaike; Petit-Bois, Merlande; Baek, Eun Kyeng

2013-01-01

Single-case or single-subject experimental designs (SSED) are used to evaluate the effect of one or more treatments on a single case. Although SSED studies are growing in popularity, the results are in theory case-specific. One systematic and statistical approach for combining single-case data within and across studies is multilevel modeling. The…

Teamwork Satisfaction: Exploring the Multilevel Interaction of Teamwork Interest and Group Extraversion

ERIC Educational Resources Information Center

French, Kimberly A.; Kottke, Janet L.

2013-01-01

Multilevel modeling is used to examine the impact of teamwork interest and group extraversion on group satisfaction. Participants included 206 undergraduates in 65 groups who were surveyed at the beginning and end of a requisite term-length group project for an upper-division university course. We hypothesized that teamwork interest and both…

Incorporating Gender Specific Approaches for Incarcerated Female Adolescents: Multilevel Risk Model for Practice

ERIC Educational Resources Information Center

Welch, Chiquitia L.; Roberts-Lewis, Amelia C.; Parker, Sharon

2009-01-01

The rise in female delinquency has resulted in large numbers of girls being incarcerated in Youth Development Centers (YDC). However, there are few gender specific treatment programs for incarcerated female adolescent offenders, particularly for those with a history of substance dependency. In this article, we present a Multi-level Risk Model…

School Climate as a Predictor of Incivility and Bullying among Public School Employees: A Multilevel Analysis

ERIC Educational Resources Information Center

Powell, Joshua E.; Powell, Anna L.; Petrosko, Joseph M.

2015-01-01

We surveyed public school educators on the workplace incivility and workplace bullying they experienced and obtained their ratings of the organizational climate of the school. We used multilevel modeling to determine the effects of individual-level and school-level predictors. Ratings of school climate were significantly related to incivility and…

ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

PubMed

Bittig, Arne T; Uhrmacher, Adelinde M

2017-01-01

Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

A Bayesian Multilevel Model for Microcystin Prediction in ...

EPA Pesticide Factsheets

The frequency of cyanobacteria blooms in North American lakes is increasing. A major concernwith rising cyanobacteria blooms is microcystin, a common cyanobacterial hepatotoxin. Toexplore the conditions that promote high microcystin concentrations, we analyzed the US EPANational Lake Assessment (NLA) dataset collected in the summer of 2007. The NLA datasetis reported for nine eco-regions. We used the results of random forest modeling as a means ofvariable selection from which we developed a Bayesian multilevel model of microcystin concentrations.Model parameters under a multilevel modeling framework are eco-region specific, butthey are also assumed to be exchangeable across eco-regions for broad continental scaling. Theexchangeability assumption ensures that both the common patterns and eco-region specific featureswill be reflected in the model. Furthermore, the method incorporates appropriate estimatesof uncertainty. Our preliminary results show associations between microcystin and turbidity, totalnutrients, and N:P ratios. The NLA 2012 will be used for Bayesian updating. The results willhelp develop management strategies to alleviate microcystin impacts and improve lake quality. This work provides a probabilistic framework for predicting microcystin presences in lakes. It would allow for insights to be made about how changes in nutrient concentrations could potentially change toxin levels.

Relating Measurement Invariance, Cross-Level Invariance, and Multilevel Reliability.

PubMed

Jak, Suzanne; Jorgensen, Terrence D

2017-01-01

Data often have a nested, multilevel structure, for example when data are collected from children in classrooms. This kind of data complicate the evaluation of reliability and measurement invariance, because several properties can be evaluated at both the individual level and the cluster level, as well as across levels. For example, cross-level invariance implies equal factor loadings across levels, which is needed to give latent variables at the two levels a similar interpretation. Reliability at a specific level refers to the ratio of true score variance over total variance at that level. This paper aims to shine light on the relation between reliability, cross-level invariance, and strong factorial invariance across clusters in multilevel data. Specifically, we will illustrate how strong factorial invariance across clusters implies cross-level invariance and perfect reliability at the between level in multilevel factor models.

An Evaluation of Six Brief Interventions that Target Drug-Related Problems in Correctional Populations

PubMed Central

JOE, GEORGE W.; KNIGHT, KEVIN; SIMPSON, D. DWAYNE; FLYNN, PATRICK M.; MOREY, JANIS T.; BARTHOLOMEW, NORMA G.; TINDALL, MICHELE STATON; BURDON, WILLIAM M.; HALL, ELIZABETH A.; MARTIN, STEVE S.; O’CONNELL, DANIEL J.

2012-01-01

Finding brief effective treatments for criminal justice populations is a major public need. The CJ-DATS Targeted Intervention for Corrections (TIC), which consists of six brief interventions (Communication, Anger, Motivation, Criminal Thinking, Social Networks, and HIV/Sexual Health), were tested in separate federally-funded randomized control studies. In total, 1,573 criminal justice-involved individuals from 20 correction facilities participated (78% males; 54% white). Multi-level repeated measures analyses found significant gains in knowledge, attitudes, and psychosocial functioning (criteria basic to Knowledge, Attitude, and Practices (KAP) and TCU Treatment Process Models). While improvements were less consistent in criminal thinking, overall evidence supported efficacy for the TIC interventions. PMID:22547911

Gender inequality in the welfare state: sex segregation in housework, 1965-2003.

PubMed

Hook, Jennifer L

2010-03-01

National context may influence sex segregation of household tasks through both pragmatic decision making and the normative context in which decision making is embedded. This study utilizes 36 time use surveys from 19 countries (spanning 1965-2003) combined with original national-level data in multilevel models to examine household task segregation. Analyses reveal that men do less and women do more time-inflexible housework in nations where work hours and parental leave are long. Women do less of this work where there is more public child care and men are eligible to take parental leave. National context affects the character of gender inequality in the home through individual- and national-level pathways.

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.

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.

Introduction--Understanding Education, Fragility and Conflict

ERIC Educational Resources Information Center

Buchert, Lene

2013-01-01

This Introduction discusses approaches to and perspectives on analyzing the complex relationship between education, fragility, and conflict and its underlying causes and dynamics. It argues for the need for contextual and time-bound multi-level analyses of interlinked societal dimensions in order to address the ultimate purposes of education…

Bullying Victims' Perceptions of Classroom Interaction

ERIC Educational Resources Information Center

Havik, Trude

2017-01-01

This study investigated bullying victims' perceptions of their teachers' support and monitoring when controlling for level of mental health problems, peer relationships, gender, and grade level. Given the nested structure of the data, multilevel analyses were employed to examine these associations. The quality of classroom interaction is highly…

Gain and power optimization of the wireless optical system with multilevel modulation.

PubMed

Liu, Xian

2008-06-01

When used in an outdoor environment to expedite networking access, the performance of wireless optical communication systems is affected by transmitter sway. In the design of such systems, much attention has been paid to developing power-efficient schemes. However, the bandwidth efficiency is also an important issue. One of the most natural approaches to promote bandwidth efficiency is to use multilevel modulation. This leads to multilevel pulse amplitude modulation in the context of intensity modulation and direct detection. We develop a model based on the four-level pulse amplitude modulation. We show that the model can be formulated as an optimization problem in terms of the transmitter power, bit error probability, transmitter gain, and receiver gain. The technical challenges raised by modeling and solving the problem include the analytical and numerical treatments for the improper integrals of the Gaussian functions coupled with the erfc function. The results demonstrate that, at the optimal points, the power penalty paid to the doubled bandwidth efficiency is around 3 dB.

A new rational-based optimal design strategy of ship structure based on multi-level analysis and super-element modeling method

NASA Astrophysics Data System (ADS)

Sun, Li; Wang, Deyu

2011-09-01

A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of high time cost in adopting a rational-based optimal design method for ship structural design. Furthermore, the method was verified by its effective application in optimization of the mid-ship section of a container ship. A full 3-D FEM model of a ship, suffering static and quasi-static loads, was used as the analyzing object for evaluating the structural performance of the mid-ship module, including static strength and buckling performance. Research results reveal that this new method could substantially reduce the computational cost of the rational-based optimization problem without decreasing its accuracy, which increases the feasibility and economic efficiency of using a rational-based optimal design method in ship structural design.

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

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. PMID:27537692

Excess mortality in persons with severe mental disorders: a multilevel intervention framework and priorities for clinical practice, policy and research agendas

PubMed Central

Liu, Nancy H.; Daumit, Gail L.; Dua, Tarun; Aquila, Ralph; Charlson, Fiona; Cuijpers, Pim; Druss, Benjamin; Dudek, Kenn; Freeman, Melvyn; Fujii, Chiyo; Gaebel, Wolfgang; Hegerl, Ulrich; Levav, Itzhak; Munk Laursen, Thomas; Ma, Hong; Maj, Mario; Elena Medina‐Mora, Maria; Nordentoft, Merete; Prabhakaran, Dorairaj; Pratt, Karen; Prince, Martin; Rangaswamy, Thara; Shiers, David; Susser, Ezra; Thornicroft, Graham; Wahlbeck, Kristian; Fekadu Wassie, Abe; Whiteford, Harvey; Saxena, Shekhar

2017-01-01

Excess mortality in persons with severe mental disorders (SMD) is a major public health challenge that warrants action. The number and scope of truly tested interventions in this area remain limited, and strategies for implementation and scaling up of programmes with a strong evidence base are scarce. Furthermore, the majority of available interventions focus on a single or an otherwise limited number of risk factors. Here we present a multilevel model highlighting risk factors for excess mortality in persons with SMD at the individual, health system and socio‐environmental levels. Informed by that model, we describe a comprehensive framework that may be useful for designing, implementing and evaluating interventions and programmes to reduce excess mortality in persons with SMD. This framework includes individual‐focused, health system‐focused, and community level and policy‐focused interventions. Incorporating lessons learned from the multilevel model of risk and the comprehensive intervention framework, we identify priorities for clinical practice, policy and research agendas. PMID:28127922

Contemporary multilevel analysis of the effectiveness of water fluoridation in Australia.

PubMed

Do, Loc; Spencer, A John

2015-02-01

Water fluoridation was extended in Queensland, Australia, across 2009-2011. A research program was commenced to inform the rationale for and the outcome of this program, to estimate the effectiveness of water fluoridation in preventing caries and to predict changes in caries experience as a result of the extension of fluoridation. Queensland children were selected through a stratified random sample selection in 2010-2012. Oral epidemiological examinations provided individual-level outcomes for decayed, missing or filled primary or permanent tooth surfaces: dmfs (among 5-8-year-olds) and DMFS (9-14-year-olds). Explanatory factors at the individual-level, school-level and area-level fluoridation status were derived. Data were weighted to represent the population. Three-level multilevel multivariable models were sequentially specified for negative binomial distribution of dmfs/DMFS to estimate rate ratios (RR). The effectiveness of area-level water fluoridation was evaluated in the full models controlling for other factors. Data from 2,214 5-8 year-olds and 3,186 9-14 year-olds from 207 schools in 16 areas were analysed. Queensland's average dmfs was 4.23 and DMFS 1.47. The lowest levels of dental caries were observed in long-term fluoridated Townsville. In the full models, Townsville children had significantly lower caries experience (RR for dmfs: 0.61 (95%CI: 0.44-0.82); RR for DMFS 0.60 (95%CI: 0.42-0.88)) compared with children in non-fluoridated areas. Comparison of caries experience of children at the time of the extension of water fluoridation supported the rationale for this population health measure. © 2014 Public Health Association of Australia.

The Role of Practitioner Resilience and Mindfulness in Effective Practice: A Practice-Based Feasibility Study.

PubMed

Pereira, Jo-Ann; Barkham, Michael; Kellett, Stephen; Saxon, David

2017-09-01

A growing body of literature attests to the existence of therapist effects with little explanation of this phenomenon. This study therefore investigated the role of resilience and mindfulness as factors related to practitioner wellbeing and associated effective practice. Data comprised practitioners (n = 37) and their patient outcome data (n = 4980) conducted within a stepped care model of service delivery. Analyses employed benchmarking and multilevel modeling to identify more and less effective practitioners via yoking of therapist factors and nested patient outcomes. A therapist effect of 6.7 % was identified based on patient depression (PHQ-9) outcome scores. More effective practitioners compared to less effective practitioners displayed significantly higher levels of mindfulness as well as resilience and mindfulness combined. Implications for policy, research and practice are discussed.

Evaluation of the durability of composite tidal turbine blades.

PubMed

Davies, Peter; Germain, Grégory; Gaurier, Benoît; Boisseau, Amélie; Perreux, Dominique

2013-02-28

The long-term reliability of tidal turbines is critical if these structures are to be cost effective. Optimized design requires a combination of material durability models and structural analyses. Composites are a natural choice for turbine blades, but there are few data available to predict material behaviour under coupled environmental and cycling loading. The present study addresses this problem, by introducing a multi-level framework for turbine blade qualification. At the material scale, static and cyclic tests have been performed, both in air and in sea water. The influence of ageing in sea water on fatigue performance is then quantified, and much lower fatigue lives are measured after ageing. At a higher level, flume tank tests have been performed on three-blade tidal turbines. Strain gauging of blades has provided data to compare with numerical models.

Mind the Gap! A Multilevel Analysis of Factors Related to Variation in Published Cost-Effectiveness Estimates within and between Countries

PubMed Central

Boehler, Christian E. H.; Lord, Joanne

2016-01-01

Background. Published cost-effectiveness estimates can vary considerably, both within and between countries. Despite extensive discussion, little is known empirically about factors relating to these variations. Objectives. To use multilevel statistical modeling to integrate cost-effectiveness estimates from published economic evaluations to investigate potential causes of variation. Methods. Cost-effectiveness studies of statins for cardiovascular disease prevention were identified by systematic review. Estimates of incremental costs and effects were extracted from reported base case, sensitivity, and subgroup analyses, with estimates grouped in studies and in countries. Three bivariate models were developed: a cross-classified model to accommodate data from multinational studies, a hierarchical model with multinational data allocated to a single category at country level, and a hierarchical model excluding multinational data. Covariates at different levels were drawn from a long list of factors suggested in the literature. Results. We found 67 studies reporting 2094 cost-effectiveness estimates relating to 23 countries (6 studies reporting for more than 1 country). Data and study-level covariates included patient characteristics, intervention and comparator cost, and some study methods (e.g., discount rates and time horizon). After adjusting for these factors, the proportion of variation attributable to countries was negligible in the cross-classified model but moderate in the hierarchical models (14%−19% of total variance). Country-level variables that improved the fit of the hierarchical models included measures of income and health care finance, health care resources, and population risks. Conclusions. Our analysis suggested that variability in published cost-effectiveness estimates is related more to differences in study methods than to differences in national context. Multinational studies were associated with much lower country-level variation than single-country studies. These findings are for a single clinical question and may be atypical. PMID:25878194

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

Multilevel Latent Class Analysis for Large-Scale Educational Assessment Data: Exploring the Relation between the Curriculum and Students' Mathematical Strategies

ERIC Educational Resources Information Center

Fagginger Auer, Marije F.; Hickendorff, Marian; Van Putten, Cornelis M.; Béguin, Anton A.; Heiser, Willem J.

2016-01-01

A first application of multilevel latent class analysis (MLCA) to educational large-scale assessment data is demonstrated. This statistical technique addresses several of the challenges that assessment data offers. Importantly, MLCA allows modeling of the often ignored teacher effects and of the joint influence of teacher and student variables.…

Teachers' Self-Efficacy in Relation to Individual Students with a Variety of Social-Emotional Behaviors: A Multilevel Investigation

ERIC Educational Resources Information Center

Zee, Marjolein; de Jong, Peter F.; Koomen, Helma M. Y.

2016-01-01

The present study examined teachers' domain-specific self-efficacy (TSE) in relation to individual students with a variety of social-emotional behaviors in class. Using a sample of 526 third- to sixth-grade students and 69 teachers, multilevel modeling was conducted to examine students' externalizing, internalizing, and prosocial behaviors as…

Multilevel Analysis of the Effects of Antidiscrimination Policies on Earnings by Sexual Orientation

ERIC Educational Resources Information Center

Klawitter, Marieka

2011-01-01

This study uses the 2000 U.S. Census data to assess the impact of antidiscrimination policies for sexual orientation on earnings for gays and lesbians. Using a multilevel model allows estimation of the effects of state and local policies on earnings and of variation in the effects of sexual orientation across local labor markets. The results…

Fluid Intelligence as a Predictor of Learning: A Longitudinal Multilevel Approach Applied to Math

ERIC Educational Resources Information Center

Primi, Ricardo; Ferrao, Maria Eugenia; Almeida, Leandro S.

2010-01-01

The association between fluid intelligence and inter-individual differences was investigated using multilevel growth curve modeling applied to data measuring intra-individual improvement on math achievement tests. A sample of 166 students (88 boys and 78 girls), ranging in age from 11 to 14 (M = 12.3, SD = 0.64), was tested. These individuals took…

Examining the Rule of Thumb of Not Using Multilevel Modeling: The "Design Effect Smaller than Two" Rule

ERIC Educational Resources Information Center

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

2015-01-01

Educational researchers commonly use the rule of thumb of "design effect smaller than 2" as the justification of not accounting for the multilevel or clustered structure in their data. The rule, however, has not yet been systematically studied in previous research. In the present study, we generated data from three different models…

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

Examination of the Gender-Student Engagement Relationship at One University

ERIC Educational Resources Information Center

Tison, Emilee B.; Bateman, Tanner; Culver, Steven M.

2011-01-01

Research examining the relationship between gender and student engagement at the post secondary level has provided mixed results. The current study explores two possible reasons for lack of clarity regarding this relationship: improper parameter estimation resulting from a lack of multi-level analyses and inconsistent conceptions/measures of…

Community Influence on Adolescent Obesity: Race/Ethnic Differences

ERIC Educational Resources Information Center

Wickrama, K. A. Thulitha; Wickrama, K. A. S.; Bryant, Chalandra M.

2006-01-01

Using a sample of 20,000 adolescents (Add Health data), this study examined the influences of community poverty and race/ethnicity on adolescent obesity. Multilevel analyses revealed strong evidence for the unique influences of community poverty and race/ethnicity on adolescent obesity net of family characteristics. The prevalence of obesity is…