Detecting a Change in School Performance: A Bayesian Analysis for a Multilevel Join Point Problem. CSE Technical Report 542.

ERIC Educational Resources Information Center

Thum, Yeow Meng; Bhattacharya, Suman Kumar

To better describe individual behavior within a system, this paper uses a sample of longitudinal test scores from a large urban school system to consider hierarchical Bayes estimation of a multilevel linear regression model in which each individual regression slope of test score on time switches at some unknown point in time, "kj."…

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

Predicting Depression among Patients with Diabetes Using Longitudinal Data. A Multilevel Regression Model.

PubMed

Jin, H; Wu, S; Vidyanti, I; Di Capua, P; Wu, B

2015-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". Depression is a common and often undiagnosed condition for patients with diabetes. It is also a condition that significantly impacts healthcare outcomes, use, and cost as well as elevating suicide risk. Therefore, a model to predict depression among diabetes patients is a promising and valuable tool for providers to proactively assess depressive symptoms and identify those with depression. This study seeks to develop a generalized multilevel regression model, using a longitudinal data set from a recent large-scale clinical trial, to predict depression severity and presence of major depression among patients with diabetes. Severity of depression was measured by the Patient Health Questionnaire PHQ-9 score. Predictors were selected from 29 candidate factors to develop a 2-level Poisson regression model that can make population-average predictions for all patients and subject-specific predictions for individual patients with historical records. Newly obtained patient records can be incorporated with historical records to update the prediction model. Root-mean-square errors (RMSE) were used to evaluate predictive accuracy of PHQ-9 scores. The study also evaluated the classification ability of using the predicted PHQ-9 scores to classify patients as having major depression. Two time-invariant and 10 time-varying predictors were selected for the model. Incorporating historical records and using them to update the model may improve both predictive accuracy of PHQ-9 scores and classification ability of the predicted scores. Subject-specific predictions (for individual patients with historical records) achieved RMSE about 4 and areas under the receiver operating characteristic (ROC) curve about 0.9 and are better than population-average predictions. The study developed a generalized multilevel regression model to predict depression and demonstrated that using generalized multilevel regression based on longitudinal patient records can achieve high predictive ability.

An empirical study of statistical properties of variance partition coefficients for multi-level logistic regression models

USGS Publications Warehouse

Li, Ji; Gray, B.R.; Bates, D.M.

2008-01-01

Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.

Multilevel Models for Binary Data

ERIC Educational Resources Information Center

Powers, Daniel A.

2012-01-01

The methods and models for categorical data analysis cover considerable ground, ranging from regression-type models for binary and binomial data, count data, to ordered and unordered polytomous variables, as well as regression models that mix qualitative and continuous data. This article focuses on methods for binary or binomial data, which are…

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.

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.

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…

Analyzing Multilevel Data: Comparing Findings from Hierarchical Linear Modeling and Ordinary Least Squares Regression

ERIC Educational Resources Information Center

Rocconi, Louis M.

2013-01-01

This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student…

Mapping Regional Impervious Surface Distribution from Night Time Light: The Variability across Global Cities

NASA Astrophysics Data System (ADS)

Lin, M.; Yang, Z.; Park, H.; Qian, S.; Chen, J.; Fan, P.

2017-12-01

Impervious surface area (ISA) has become an important indicator for studying urban environments, but mapping ISA at the regional or global scale is still challenging due to the complexity of impervious surface features. The Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime light data is (NTL) and Resolution Imaging Spectroradiometer (MODIS) are the major remote sensing data source for regional ISA mapping. A single regression relationship between fractional ISA and NTL or various index derived based on NTL and MODIS vegetation index (NDVI) data was established in many previous studies for regional ISA mapping. However, due to the varying geographical, climatic, and socio-economic characteristics of different cities, the same regression relationship may vary significantly across different cities in the same region in terms of both fitting performance (i.e. R2) and the rate of change (Slope). In this study, we examined the regression relationship between fractional ISA and Vegetation Adjusted Nighttime light Urban Index (VANUI) for 120 randomly selected cities around the world with a multilevel regression model. We found that indeed there is substantial variability of both the R2 (0.68±0.29) and slopes (0.64±0.40) among individual regressions, which suggests that multilevel/hierarchical models are needed for accuracy improvement of future regional ISA mapping .Further analysis also let us find the this substantial variability are affected by climate conditions, socio-economic status, and urban spatial structures. However, all these effects are nonlinear rather than linear, thus could not modeled explicitly in multilevel linear regression models.

A Primer for Analyzing Nested Data: Multilevel Modeling in SPSS Using an Example from a REL Study. REL 2015-046

ERIC Educational Resources Information Center

O'Dwyer, Laura M.; Parker, Caroline E.

2014-01-01

Analyzing data that possess some form of nesting is often challenging for applied researchers or district staff who are involved in or in charge of conducting data analyses. This report provides a description of the challenges for analyzing nested data and provides a primer of how multilevel regression modeling may be used to resolve these…

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.

Analyzing Multilevel Data: An Empirical Comparison of Parameter Estimates of Hierarchical Linear Modeling and Ordinary Least Squares Regression

ERIC Educational Resources Information Center

Rocconi, Louis M.

2011-01-01

Hierarchical linear models (HLM) solve the problems associated with the unit of analysis problem such as misestimated standard errors, heterogeneity of regression and aggregation bias by modeling all levels of interest simultaneously. Hierarchical linear modeling resolves the problem of misestimated standard errors by incorporating a unique random…

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.

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…

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.

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.

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications

PubMed Central

Austin, Peter C.

2017-01-01

Summary Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log–log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata). PMID:29307954

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications.

PubMed

Austin, Peter C

2017-08-01

Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log-log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata).

Exploring the impact of different multi-level measures of physician communities in patient-centric care networks on healthcare outcomes: A multi-level regression approach.

PubMed

Uddin, Shahadat

2016-02-04

A patient-centric care network can be defined as a network among a group of healthcare professionals who provide treatments to common patients. Various multi-level attributes of the members of this network have substantial influence to its perceived level of performance. In order to assess the impact different multi-level attributes of patient-centric care networks on healthcare outcomes, this study first captured patient-centric care networks for 85 hospitals using health insurance claim dataset. From these networks, this study then constructed physician collaboration networks based on the concept of patient-sharing network among physicians. A multi-level regression model was then developed to explore the impact of different attributes that are organised at two levels on hospitalisation cost and hospital length of stay. For Level-1 model, the average visit per physician significantly predicted both hospitalisation cost and hospital length of stay. The number of different physicians significantly predicted only the hospitalisation cost, which has significantly been moderated by age, gender and Comorbidity score of patients. All Level-1 findings showed significance variance across physician collaboration networks having different community structure and density. These findings could be utilised as a reflective measure by healthcare decision makers. Moreover, healthcare managers could consider them in developing effective healthcare environments.

Many-level multilevel structural equation modeling: An efficient evaluation strategy.

PubMed

Pritikin, Joshua N; Hunter, Michael D; von Oertzen, Timo; Brick, Timothy R; Boker, Steven M

2017-01-01

Structural equation models are increasingly used for clustered or multilevel data in cases where mixed regression is too inflexible. However, when there are many levels of nesting, these models can become difficult to estimate. We introduce a novel evaluation strategy, Rampart, that applies an orthogonal rotation to the parts of a model that conform to commonly met requirements. This rotation dramatically simplifies fit evaluation in a way that becomes more potent as the size of the data set increases. We validate and evaluate the implementation using a 3-level latent regression simulation study. Then we analyze data from a state-wide child behavioral health measure administered by the Oklahoma Department of Human Services. We demonstrate the efficiency of Rampart compared to other similar software using a latent factor model with a 5-level decomposition of latent variance. Rampart is implemented in OpenMx, a free and open source software.

The Norwegian Healthier Goats program--modeling lactation curves using a multilevel cubic spline regression model.

PubMed

Nagel-Alne, G E; Krontveit, R; Bohlin, J; Valle, P S; Skjerve, E; Sølverød, L S

2014-07-01

In 2001, the Norwegian Goat Health Service initiated the Healthier Goats program (HG), with the aim of eradicating caprine arthritis encephalitis, caseous lymphadenitis, and Johne's disease (caprine paratuberculosis) in Norwegian goat herds. The aim of the present study was to explore how control and eradication of the above-mentioned diseases by enrolling in HG affected milk yield by comparison with herds not enrolled in HG. Lactation curves were modeled using a multilevel cubic spline regression model where farm, goat, and lactation were included as random effect parameters. The data material contained 135,446 registrations of daily milk yield from 28,829 lactations in 43 herds. The multilevel cubic spline regression model was applied to 4 categories of data: enrolled early, control early, enrolled late, and control late. For enrolled herds, the early and late notations refer to the situation before and after enrolling in HG; for nonenrolled herds (controls), they refer to development over time, independent of HG. Total milk yield increased in the enrolled herds after eradication: the total milk yields in the fourth lactation were 634.2 and 873.3 kg in enrolled early and enrolled late herds, respectively, and 613.2 and 701.4 kg in the control early and control late herds, respectively. Day of peak yield differed between enrolled and control herds. The day of peak yield came on d 6 of lactation for the control early category for parities 2, 3, and 4, indicating an inability of the goats to further increase their milk yield from the initial level. For enrolled herds, on the other hand, peak yield came between d 49 and 56, indicating a gradual increase in milk yield after kidding. Our results indicate that enrollment in the HG disease eradication program improved the milk yield of dairy goats considerably, and that the multilevel cubic spline regression was a suitable model for exploring effects of disease control and eradication on milk yield. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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

A Multilevel Multivariate Analysis of Academic Performances in College Based on NCAA Student-Athletes

ERIC Educational Resources Information Center

McArdle, John J.; Paskus, Thomas S.; Boker, Steven M.

2013-01-01

This is an application of contemporary multilevel regression modeling to the prediction of academic performances of 1st-year college students. At a first level of analysis, the data come from N greater than 16,000 students who were college freshman in 1994-1995 and who were also participants in high-level college athletics. At a second level of…

Retention of Children and Their Families in the Longitudinal Outcome Study of the Comprehensive Community Mental Health Services for Children and Their Families Program: A Multilevel Analysis

ERIC Educational Resources Information Center

Gebreselassie, Tesfayi; Stephens, Robert L.; Maples, Connie J.; Johnson, Stacy F.; Tucker, Alyce L.

2014-01-01

Predictors of retention of participants in a longitudinal study and heterogeneity between communities were investigated using a multilevel logistic regression model. Data from the longitudinal outcome study of the national evaluation of the Comprehensive Community Mental Health Services for Children and Their Families program and information on…

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.

The Role of Individual Correlates and Class Norms in Defending and Passive Bystanding Behavior in Bullying: A Multilevel Analysis

ERIC Educational Resources Information Center

Pozzoli, Tiziana; Gini, Gianluca; Vieno, Alessio

2012-01-01

This study investigates possible individual and class correlates of defending and passive bystanding behavior in bullying, in a sample of 1,825 Italian primary school (mean age = 10 years 1 month) and middle school (mean age = 13 years 2 months) students. The findings of a series of multilevel regression models show that both individual (e.g.,…

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.

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.

A Noncentral "t" Regression Model for Meta-Analysis

ERIC Educational Resources Information Center

Camilli, Gregory; de la Torre, Jimmy; Chiu, Chia-Yi

2010-01-01

In this article, three multilevel models for meta-analysis are examined. Hedges and Olkin suggested that effect sizes follow a noncentral "t" distribution and proposed several approximate methods. Raudenbush and Bryk further refined this model; however, this procedure is based on a normal approximation. In the current research literature, this…

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.

Use of multilevel logistic regression to identify the causes of differential item functioning.

PubMed

Balluerka, Nekane; Gorostiaga, Arantxa; Gómez-Benito, Juana; Hidalgo, María Dolores

2010-11-01

Given that a key function of tests is to serve as evaluation instruments and for decision making in the fields of psychology and education, the possibility that some of their items may show differential behaviour is a major concern for psychometricians. In recent decades, important progress has been made as regards the efficacy of techniques designed to detect this differential item functioning (DIF). However, the findings are scant when it comes to explaining its causes. The present study addresses this problem from the perspective of multilevel analysis. Starting from a case study in the area of transcultural comparisons, multilevel logistic regression is used: 1) to identify the item characteristics associated with the presence of DIF; 2) to estimate the proportion of variation in the DIF coefficients that is explained by these characteristics; and 3) to evaluate alternative explanations of the DIF by comparing the explanatory power or fit of different sequential models. The comparison of these models confirmed one of the two alternatives (familiarity with the stimulus) and rejected the other (the topic area) as being a cause of differential functioning with respect to the compared groups.

Modeling Joint Exposures and Health Outcomes for Cumulative Risk Assessment: The Case of Radon and Smoking

PubMed Central

Chahine, Teresa; Schultz, Bradley D.; Zartarian, Valerie G.; Xue, Jianping; Subramanian, SV; Levy, Jonathan I.

2011-01-01

Community-based cumulative risk assessment requires characterization of exposures to multiple chemical and non-chemical stressors, with consideration of how the non-chemical stressors may influence risks from chemical stressors. Residential radon provides an interesting case example, given its large attributable risk, effect modification due to smoking, and significant variability in radon concentrations and smoking patterns. In spite of this fact, no study to date has estimated geographic and sociodemographic patterns of both radon and smoking in a manner that would allow for inclusion of radon in community-based cumulative risk assessment. In this study, we apply multi-level regression models to explain variability in radon based on housing characteristics and geological variables, and construct a regression model predicting housing characteristics using U.S. Census data. Multi-level regression models of smoking based on predictors common to the housing model allow us to link the exposures. We estimate county-average lifetime lung cancer risks from radon ranging from 0.15 to 1.8 in 100, with high-risk clusters in areas and for subpopulations with high predicted radon and smoking rates. Our findings demonstrate the viability of screening-level assessment to characterize patterns of lung cancer risk from radon, with an approach that can be generalized to multiple chemical and non-chemical stressors. PMID:22016710

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…

Multilevel regression models describing regional patterns of invertebrate and algal responses to urbanization across the USA

USGS Publications Warehouse

Cuffney, T.F.; Kashuba, R.; Qian, S.S.; Alameddine, I.; Cha, Y.K.; Lee, B.; Coles, J.F.; McMahon, G.

2011-01-01

Multilevel hierarchical regression was used to examine regional patterns in the responses of benthic macroinvertebrates and algae to urbanization across 9 metropolitan areas of the conterminous USA. Linear regressions established that responses (intercepts and slopes) to urbanization of invertebrates and algae varied among metropolitan areas. Multilevel hierarchical regression models were able to explain these differences on the basis of region-scale predictors. Regional differences in the type of land cover (agriculture or forest) being converted to urban and climatic factors (precipitation and air temperature) accounted for the differences in the response of macroinvertebrates to urbanization based on ordination scores, total richness, Ephemeroptera, Plecoptera, Trichoptera richness, and average tolerance. Regional differences in climate and antecedent agriculture also accounted for differences in the responses of salt-tolerant diatoms, but differences in the responses of other diatom metrics (% eutraphenic, % sensitive, and % silt tolerant) were best explained by regional differences in soils (mean % clay soils). The effects of urbanization were most readily detected in regions where forest lands were being converted to urban land because agricultural development significantly degraded assemblages before urbanization and made detection of urban effects difficult. The effects of climatic factors (temperature, precipitation) on background conditions (biogeographic differences) and rates of response to urbanization were most apparent after accounting for the effects of agricultural development. The effects of climate and land cover on responses to urbanization provide strong evidence that monitoring, mitigation, and restoration efforts must be tailored for specific regions and that attainment goals (background conditions) may not be possible in regions with high levels of prior disturbance (e.g., agricultural development). ?? 2011 by The North American Benthological Society.

Role Stress and Emotional Exhaustion Among Health Care Workers: The Buffering Effect of Supportive Coworker Climate in a Multilevel Perspective.

PubMed

Portoghese, Igor; Galletta, Maura; Burdorf, Alex; Cocco, Pierluigi; D'Aloja, Ernesto; Campagna, Marcello

2017-10-01

The aim of the study was to examine the relationship between role stress, emotional exhaustion, and a supportive coworker climate among health care workers, by adopting a multilevel perspective. Aggregated data of 738 health care workers nested within 67 teams of three Italian hospitals were collected. Multilevel regression analysis with a random intercept model was used. Hierarchical linear modeling showed that a lack of role clarity was significantly linked to emotional exhaustion at the individual level. At the unit level, the cross-level interaction revealed that a supportive coworker climate moderated the relationship between lack of role clarity and emotional exhaustion. This study supports previous results of single-level burnout studies, extending the existing literature with evidence on the multidimensional and cross-level interaction associations of a supportive coworker climate as a key aspect of job resources on burnout.

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.

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

PubMed

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

2014-04-01

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

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

A Multilevel Assessment of Differential Item Functioning.

ERIC Educational Resources Information Center

Shen, Linjun

A multilevel approach was proposed for the assessment of differential item functioning and compared with the traditional logistic regression approach. Data from the Comprehensive Osteopathic Medical Licensing Examination for 2,300 freshman osteopathic medical students were analyzed. The multilevel approach used three-level hierarchical generalized…

Educational Investment, Family Context, and Children's Math and Reading Growth from Kindergarten through the Third Grade

ERIC Educational Resources Information Center

Cheadle, Jacob E.

2008-01-01

Drawing on longitudinal data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-1999, this study used IRT modeling to operationalize a measure of parental educational investments based on Lareau's notion of concerted cultivation. It used multilevel piece-wise growth models regressing children's math and reading achievement…

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.

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

PubMed

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

2016-05-01

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

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

PubMed

Mills, Melinda; Begall, Katia

2010-03-01

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

Studying Individual Differences in Predictability with Gamma Regression and Nonlinear Multilevel Models

ERIC Educational Resources Information Center

Culpepper, Steven Andrew

2010-01-01

Statistical prediction remains an important tool for decisions in a variety of disciplines. An equally important issue is identifying factors that contribute to more or less accurate predictions. The time series literature includes well developed methods for studying predictability and volatility over time. This article develops…

Student and School SES, Gender, Strategy Use, and Achievement

ERIC Educational Resources Information Center

Callan, Gregory L.; Marchant, Gregory J.; Finch, W. Holmes; Flegge, Lindsay

2017-01-01

A multilevel mediated regression model was fit to Programme for International Student Assessment achievement, strategy use, gender, and family- and school-level socioeconomic status (SES). Two metacognitive strategies (i.e., understanding and summarizing) and one learning strategy (i.e., control strategies) were found to relate significantly and…

[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.

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

Does the "Pupil Enterprise Programme" Influence Grades among Pupils with Special Needs?

ERIC Educational Resources Information Center

Johansen, Vegard; Somby, Hege M.

2016-01-01

This paper asks whether the Pupil Enterprise Programme (PEP) is a suitable working method for improving academic performance among pupils with special needs. Overall, 20% of pupils participate in PEP at some point during lower secondary school. Results from multilevel regression modelling indicate that pupils with special needs who have…

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

ERIC Educational Resources Information Center

Zvoch, Keith

2006-01-01

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

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

PubMed

Huang, Francis L

2018-04-01

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

Addictive internet use among Korean adolescents: a national survey.

PubMed

Heo, Jongho; Oh, Juhwan; Subramanian, S V; Kim, Yoon; Kawachi, Ichiro

2014-01-01

A psychological disorder called 'Internet addiction' has newly emerged along with a dramatic increase of worldwide Internet use. However, few studies have used population-level samples nor taken into account contextual factors on Internet addiction. We identified 57,857 middle and high school students (13-18 year olds) from a Korean nationally representative survey, which was surveyed in 2009. To identify associated factors with addictive Internet use, two-level multilevel regression models were fitted with individual-level responses (1st level) nested within schools (2nd level) to estimate associations of individual and school characteristics simultaneously. Gender differences of addictive Internet use were estimated with the regression model stratified by gender. Significant associations were found between addictive Internet use and school grade, parental education, alcohol use, tobacco use, and substance use. Female students in girls' schools were more likely to use Internet addictively than those in coeducational schools. Our results also revealed significant gender differences of addictive Internet use in its associated individual- and school-level factors. Our results suggest that multilevel risk factors along with gender differences should be considered to protect adolescents from addictive Internet use.

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

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

PubMed

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

2017-01-31

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

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

PubMed

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

2018-01-01

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

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

ERIC Educational Resources Information Center

Law, Philip; Yuen, Desmond

2012-01-01

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

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.

Placing Families in Context: Challenges for Cross-National Family Research

PubMed Central

Yu, Wei-hsin

2015-01-01

Cross-national comparisons constitute a valuable strategy to assess how broader cultural, political, and institutional contexts shape family outcomes. One typical approach of cross-national family research is to use comparable data from a limited number of countries, fit similar regression models for each country, and compare results across country-specific models. Increasingly, researchers are adopting a second approach, which requires merging data from many more societies and testing multilevel models using the pooled sample. Although the second approach has the advantage of allowing direct estimates of the effects of nation-level characteristics, it is more likely to suffer from the problems of omitted-variable bias, influential cases, and measurement and construct nonequivalence. I discuss ways to improve the first approach's ability to infer macrolevel influences, as well as how to deal with challenges associated with the second one. I also suggest choosing analytical strategies according to whether the data meet multilevel models’ assumptions. PMID:25999603

Multilevel joint competing risk models

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Objectively measured sedentary time and academic achievement in schoolchildren.

PubMed

Lopes, Luís; Santos, Rute; Mota, Jorge; Pereira, Beatriz; Lopes, Vítor

2017-03-01

This study aimed to evaluate the relationship between objectively measured total sedentary time and academic achievement (AA) in Portuguese children. The sample comprised of 213 children (51.6% girls) aged 9.46 ± 0.43 years, from the north of Portugal. Sedentary time was measured with accelerometry, and AA was assessed using the Portuguese Language and Mathematics National Exams results. Multilevel linear regression models were fitted to assess regression coefficients predicting AA. The results showed that objectively measured total sedentary time was not associated with AA, after adjusting for potential confounders.

Multilevel Effects of Wealth on Women's Contraceptive Use in Mozambique

PubMed Central

Dias, José G.; de Oliveira, Isabel Tiago

2015-01-01

Objective This paper analyzes the impact of wealth on the use of contraception in Mozambique unmixing the contextual effects due to community wealth from the individual effects associated with the women's situation within the community of residence. Methods Data from the 2011 Mozambican Demographic and Health Survey on women who are married or living together are analyzed for the entire country and also for the rural and urban areas separately. We used single level and multilevel probit regression models. Findings A single level probit regression reveals that region, religion, age, previous fertility, education, and wealth impact contraceptive behavior. The multilevel analysis shows that average community wealth and the women’s relative socioeconomic position within the community have significant positive effects on the use of modern contraceptives. The multilevel framework proved to be necessary in rural settings but not relevant in urban areas. Moreover, the contextual effects due to community wealth are greater in rural than in urban areas and this feature is associated with the higher socioeconomic heterogeneity within the richest communities. Conclusion This analysis highlights the need for the studies on contraceptive behavior to specifically address the individual and contextual effects arising from the poverty-wealth dimension in rural and urban areas separately. The inclusion in a particular community of residence is not relevant in urban areas, but it is an important feature in rural areas. Although the women's individual position within the community of residence has a similar effect on contraceptive adoption in rural and urban settings, the impact of community wealth is greater in rural areas and smaller in urban areas. PMID:25786228

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

PubMed Central

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

2002-01-01

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

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

PubMed

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

2013-01-01

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

[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.

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.

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

PubMed

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

2015-11-01

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

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…

Exploring the Ups and Downs of Mathematics Engagement in the Middle Years of School

ERIC Educational Resources Information Center

Martin, Andrew J.; Way, Jennifer; Bobis, Janette; Anderson, Judy

2015-01-01

This study of 1,601 students in the middle years of schooling (Grades 5-8, each student measured twice, 1 year apart) from 200 classrooms in 44 schools sought to identify factors explaining gains and declines in mathematics engagement at key transition points. In multilevel regression modeling, findings showed that compared with Grade 6 students…

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

ERIC Educational Resources Information Center

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

2011-01-01

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

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

PubMed

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

2018-05-03

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

Addictive Internet Use among Korean Adolescents: A National Survey

PubMed Central

Heo, Jongho; Oh, Juhwan; Subramanian, S. V.; Kim, Yoon; Kawachi, Ichiro

2014-01-01

Background A psychological disorder called ‘Internet addiction’ has newly emerged along with a dramatic increase of worldwide Internet use. However, few studies have used population-level samples nor taken into account contextual factors on Internet addiction. Methods and Findings We identified 57,857 middle and high school students (13–18 year olds) from a Korean nationally representative survey, which was surveyed in 2009. To identify associated factors with addictive Internet use, two-level multilevel regression models were fitted with individual-level responses (1st level) nested within schools (2nd level) to estimate associations of individual and school characteristics simultaneously. Gender differences of addictive Internet use were estimated with the regression model stratified by gender. Significant associations were found between addictive Internet use and school grade, parental education, alcohol use, tobacco use, and substance use. Female students in girls' schools were more likely to use Internet addictively than those in coeducational schools. Our results also revealed significant gender differences of addictive Internet use in its associated individual- and school-level factors. Conclusions Our results suggest that multilevel risk factors along with gender differences should be considered to protect adolescents from addictive Internet use. PMID:24505318

Individual-Level Influences on Perceptions of Neighborhood Disorder: A Multilevel Analysis

ERIC Educational Resources Information Center

Latkin, Carl A.; German, Danielle; Hua, Wei; Curry, Aaron D.

2009-01-01

Health outcomes are associated with aggregate neighborhood measures and individual neighborhood perceptions. In this study, the authors sought to delineate individual, social network, and spatial factors that may influence perceptions of neighborhood disorder. Multilevel regression analysis showed that neighborhood perceptions were more negative…

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

PubMed

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

2016-09-01

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

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

PubMed

Nkansah-Amankra, Stephen

2010-08-01

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

Realist explanatory theory building method for social epidemiology: a protocol for a mixed method multilevel study of neighbourhood context and postnatal depression.

PubMed

Eastwood, John G; Jalaludin, Bin B; Kemp, Lynn A

2014-01-01

A recent criticism of social epidemiological studies, and multi-level studies in particular has been a paucity of theory. We will present here the protocol for a study that aims to build a theory of the social epidemiology of maternal depression. We use a critical realist approach which is trans-disciplinary, encompassing both quantitative and qualitative traditions, and that assumes both ontological and hierarchical stratification of reality. We describe a critical realist Explanatory Theory Building Method comprising of an: 1) emergent phase, 2) construction phase, and 3) confirmatory phase. A concurrent triangulated mixed method multilevel cross-sectional study design is described. The Emergent Phase uses: interviews, focus groups, exploratory data analysis, exploratory factor analysis, regression, and multilevel Bayesian spatial data analysis to detect and describe phenomena. Abductive and retroductive reasoning will be applied to: categorical principal component analysis, exploratory factor analysis, regression, coding of concepts and categories, constant comparative analysis, drawing of conceptual networks, and situational analysis to generate theoretical concepts. The Theory Construction Phase will include: 1) defining stratified levels; 2) analytic resolution; 3) abductive reasoning; 4) comparative analysis (triangulation); 5) retroduction; 6) postulate and proposition development; 7) comparison and assessment of theories; and 8) conceptual frameworks and model development. The strength of the critical realist methodology described is the extent to which this paradigm is able to support the epistemological, ontological, axiological, methodological and rhetorical positions of both quantitative and qualitative research in the field of social epidemiology. The extensive multilevel Bayesian studies, intensive qualitative studies, latent variable theory, abductive triangulation, and Inference to Best Explanation provide a strong foundation for Theory Construction. The study will contribute to defining the role that realism and mixed methods can play in explaining the social determinants and developmental origins of health and disease.

College on Credit: A Multilevel Analysis of Student Loan Default

ERIC Educational Resources Information Center

Hillman, Nicholas W.

2014-01-01

This study updates and expands the literature on student loan default. By applying multilevel regression to the Beginning Postsecondary Students survey, four key findings emerge. First, attending proprietary institutions is strongly associated with default, even after accounting for students' socioeconomic and academic backgrounds. Second,…

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.

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.

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…

Mixed effect Poisson log-linear models for clinical and epidemiological sleep hypnogram data

PubMed Central

Swihart, Bruce J.; Caffo, Brian S.; Crainiceanu, Ciprian; Punjabi, Naresh M.

2013-01-01

Bayesian Poisson log-linear multilevel models scalable to epidemiological studies are proposed to investigate population variability in sleep state transition rates. Hierarchical random effects are used to account for pairings of subjects and repeated measures within those subjects, as comparing diseased to non-diseased subjects while minimizing bias is of importance. Essentially, non-parametric piecewise constant hazards are estimated and smoothed, allowing for time-varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming exponentially distributed survival times. Such re-derivation allows synthesis of two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed. Supplementary material includes the analyzed data set as well as the code for a reproducible analysis. PMID:22241689

Multilevel Vehicle Design: Fuel Economy, Mobility and Safety Considerations, Part B. Ground Vehicle Weight and Occupant Safety Under Blast Loading

DTIC Science & Technology

2010-05-11

UNCLASSIFIED 11 Occupant Model Inputs: Blast Pulse (apeak) Seat Cushion Foam Stiffness (sc) Seat EA System Stiffness (sEA) Outputs: Upper Neck Axial Force...Floor Pad Surrogate model from linear regression on 300 data points: Inputs: Blast Pulse (apeak) Seat Cushion Foam Stiffness (sc) Seat EA System...B Ground Vehicle Weight and Occupant Safety Under Blast Loading Steven Hoffenson, presenter (U of M) Panos Papalambros, PI (U of M) Michael

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

PubMed

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

2014-12-01

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

Macroeconomic Knowledge of Higher Education Students in Germany and Japan--A Multilevel Analysis of Contextual and Personal Effects

ERIC Educational Resources Information Center

Zlatkin-Troitschanskaia, Olga; Schmidt, Susanne; Brückner, Sebastian; Förster, Manuel; Yamaoka, Michio; Asano, Tadayoshi

2016-01-01

Recent trends towards harmonising and internationalising business and economics studies in higher education are affecting the structure and content of programmes and courses, and necessitate more transparent and comparable information on students' economic knowledge and skills. In this study, we examine by linear multilevel regression modelling…

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

A dynamic multi-level optimal design method with embedded finite-element modeling for power transformers

NASA Astrophysics Data System (ADS)

Zhang, Yunpeng; Ho, Siu-lau; Fu, Weinong

2018-05-01

This paper proposes a dynamic multi-level optimal design method for power transformer design optimization (TDO) problems. A response surface generated by second-order polynomial regression analysis is updated dynamically by adding more design points, which are selected by Shifted Hammersley Method (SHM) and calculated by finite-element method (FEM). The updating stops when the accuracy requirement is satisfied, and optimized solutions of the preliminary design are derived simultaneously. The optimal design level is modulated through changing the level of error tolerance. Based on the response surface of the preliminary design, a refined optimal design is added using multi-objective genetic algorithm (MOGA). The effectiveness of the proposed optimal design method is validated through a classic three-phase power TDO problem.

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

NASA Astrophysics Data System (ADS)

Sun, Yuan; Bhattacherjee, Anol

2011-11-01

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

Formulation and Application of the Generalized Multilevel Facets Model

ERIC Educational Resources Information Center

Wang, Wen-Chung; Liu, Chih-Yu

2007-01-01

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

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.

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,…

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…

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

ERIC Educational Resources Information Center

Leatherdale, Scott T.

2010-01-01

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

Aircraft Anomaly Detection Using Performance Models Trained on Fleet Data

NASA Technical Reports Server (NTRS)

Gorinevsky, Dimitry; Matthews, Bryan L.; Martin, Rodney

2012-01-01

This paper describes an application of data mining technology called Distributed Fleet Monitoring (DFM) to Flight Operational Quality Assurance (FOQA) data collected from a fleet of commercial aircraft. DFM transforms the data into aircraft performance models, flight-to-flight trends, and individual flight anomalies by fitting a multi-level regression model to the data. The model represents aircraft flight performance and takes into account fixed effects: flight-to-flight and vehicle-to-vehicle variability. The regression parameters include aerodynamic coefficients and other aircraft performance parameters that are usually identified by aircraft manufacturers in flight tests. Using DFM, the multi-terabyte FOQA data set with half-million flights was processed in a few hours. The anomalies found include wrong values of competed variables, (e.g., aircraft weight), sensor failures and baises, failures, biases, and trends in flight actuators. These anomalies were missed by the existing airline monitoring of FOQA data exceedances.

Bayesian function-on-function regression for multilevel functional data.

PubMed

Meyer, Mark J; Coull, Brent A; Versace, Francesco; Cinciripini, Paul; Morris, Jeffrey S

2015-09-01

Medical and public health research increasingly involves the collection of complex and high dimensional data. In particular, functional data-where the unit of observation is a curve or set of curves that are finely sampled over a grid-is frequently obtained. Moreover, researchers often sample multiple curves per person resulting in repeated functional measures. A common question is how to analyze the relationship between two functional variables. We propose a general function-on-function regression model for repeatedly sampled functional data on a fine grid, presenting a simple model as well as a more extensive mixed model framework, and introducing various functional Bayesian inferential procedures that account for multiple testing. We examine these models via simulation and a data analysis with data from a study that used event-related potentials to examine how the brain processes various types of images. © 2015, The International Biometric Society.

Ciliary Body Thickness and Refractive Error in Children

PubMed Central

Bailey, Melissa D.; Sinnott, Loraine T.; Mutti, Donald O.

2010-01-01

Purpose To determine whether ciliary body thickness (CBT) is related to refractive error in school-age children. Methods Fifty-three children, 8 to 15 years of age, were recruited. CBT was measured from anterior segment OCT images (Visante; Carl Zeiss Meditec, Inc., Dublin, CA) at 1 (CBT1), 2 (CBT2) and 3 (CBT3) mm posterior to the scleral spur. Cycloplegic refractive error was measured with an autorefractor, and axial length was measured with an optical biometer. Multilevel regression models determined the relationship between CBT measurements and refractive error or axial length. A Bland-Altman analysis was used to assess the between-visit repeatability of the ciliary body measurements. Results The between-visits coefficients of repeatability for CBT1, -2, and -3 were 148.04, 165.68, and 110.90, respectively. Thicker measurements at CBT2 (r = −0.29, P = 0.03) and CBT3 (r = −0.38, P = 0.005) were associated with increasingly myopic refractive errors (multilevel model: P < 0.001). Thicker measurements at CBT2 (r = 0.40, P = 0.003) and CBT3 (r = 0.51, P < 0.001) were associated with longer axial lengths (multilevel model: P < 0.001). Conclusions Thicker ciliary body measurements were associated with myopia and a longer axial length. Future studies should determine whether this relationship is also present in animal models of myopia and determine the temporal relationship between thickening of the ciliary muscle and the onset of myopia. PMID:18566470

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.

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

PubMed

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

2010-05-01

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

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

PubMed

Pastor, Dena A; Lazowski, Rory A

2018-01-01

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

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.

Racial/Ethnic Differences in Cigarette Smoking Initiation and Progression to Daily Smoking: A Multilevel Analysis

PubMed Central

Kandel, Denise B.; Kiros, Gebre-Egziabher; Schaffran, Christine; Hu, Mei-Chen

2004-01-01

Objectives. We sought to identify individual and contextual predictors of adolescent smoking initiation and progression to daily smoking by race/ethnicity. Methods. We used data from the National Longitudinal Study of Adolescent Health to estimate the effects of individual (adolescent, family, peer) and contextual (school and state) factors on smoking onset among nonsmokers (n = 5374) and progression to daily smoking among smokers (n = 4474) with multilevel regression models. Results. Individual factors were more important predictors of smoking behaviors than were contextual factors. Predictors of smoking behaviors were mostly common across racial/ethnic groups. Conclusions. The few identified racial/ethnic differences in predictors of smoking behavior suggest that universal prevention and intervention efforts could reach most adolescents regardless of race/ethnicity. With 2 exceptions, important contextual factors remain to be identified. PMID:14713710

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…

Approximate l-fold cross-validation with Least Squares SVM and Kernel Ridge Regression

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

Edwards, Richard E; Zhang, Hao; Parker, Lynne Edwards

2013-01-01

Kernel methods have difficulties scaling to large modern data sets. The scalability issues are based on computational and memory requirements for working with a large matrix. These requirements have been addressed over the years by using low-rank kernel approximations or by improving the solvers scalability. However, Least Squares Support VectorMachines (LS-SVM), a popular SVM variant, and Kernel Ridge Regression still have several scalability issues. In particular, the O(n^3) computational complexity for solving a single model, and the overall computational complexity associated with tuning hyperparameters are still major problems. We address these problems by introducing an O(n log n) approximate l-foldmore » cross-validation method that uses a multi-level circulant matrix to approximate the kernel. In addition, we prove our algorithm s computational complexity and present empirical runtimes on data sets with approximately 1 million data points. We also validate our approximate method s effectiveness at selecting hyperparameters on real world and standard benchmark data sets. Lastly, we provide experimental results on using a multi-level circulant kernel approximation to solve LS-SVM problems with hyperparameters selected using our method.« less

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

PubMed Central

Frølich, Anne; Merlo, Juan

2017-01-01

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

An Approximate Approach to Automatic Kernel Selection.

PubMed

Ding, Lizhong; Liao, Shizhong

2016-02-02

Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.

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

PubMed

Adesanya, Oluwafunmilade A; Chiao, Chi

2016-08-25

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

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

PubMed

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

2015-12-01

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

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.

Dynamic networks of PTSD symptoms during conflict.

PubMed

Greene, Talya; Gelkopf, Marc; Epskamp, Sacha; Fried, Eiko

2018-02-28

Conceptualizing posttraumatic stress disorder (PTSD) symptoms as a dynamic system of causal elements could provide valuable insights into the way that PTSD develops and is maintained in traumatized individuals. We present the first study to apply a multilevel network model to produce an exploratory empirical conceptualization of dynamic networks of PTSD symptoms, using data collected during a period of conflict. Intensive longitudinal assessment data were collected during the Israel-Gaza War in July-August 2014. The final sample (n = 96) comprised a general population sample of Israeli adult civilians exposed to rocket fire. Participants completed twice-daily reports of PTSD symptoms via smartphone for 30 days. We used a multilevel vector auto-regression model to produce contemporaneous and temporal networks, and a partial correlation network model to obtain a between-subjects network. Multilevel network analysis found strong positive contemporaneous associations between hypervigilance and startle response, avoidance of thoughts and avoidance of reminders, and between flashbacks and emotional reactivity. The temporal network indicated the central role of startle response as a predictor of future PTSD symptomatology, together with restricted affect, blame, negative emotions, and avoidance of thoughts. There were some notable differences between the temporal and contemporaneous networks, including the presence of a number of negative associations, particularly from blame. The between-person network indicated flashbacks and emotional reactivity to be the most central symptoms. This study suggests various symptoms that could potentially be driving the development of PTSD. We discuss clinical implications such as identifying particular symptoms as targets for interventions.

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.

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.

Modeling Longitudinal Data Containing Non-Normal Within Subject Errors

NASA Technical Reports Server (NTRS)

Feiveson, Alan; Glenn, Nancy L.

2013-01-01

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

Exploring unobserved household living conditions in multilevel choice modeling: An application to contraceptive adoption by Indian women.

PubMed

Dias, José G; de Oliveira, Isabel Tiago

2018-01-01

This research analyzes the effect of the poverty-wealth dimension on contraceptive adoption by Indian women when no direct measures of income/expenditures are available to use as covariates. The index-Household Living Conditions (HLC)-is based on household assets and dwelling characteristics and is computed by an item response model simultaneously with the choice model in a new single-step approach. That is, the HLC indicator is treated as a latent covariate measured by a set of items, it depends on a set of concomitant variables, and explains contraceptive choices in a probit regression. Additionally, the model accounts for complex survey design and sample weights in a multilevel framework. Regarding our case study on contraceptive adoption by Indian women, results show that women with better household living conditions tend to adopt contraception more often than their counterparts. This effect is significant after controlling other factors such as education, caste, and religion. The external validation of the indicator shows that it can also be used at aggregate levels of analysis (e.g., county or state) whenever no other indicators of household living conditions are available.

Exploring unobserved household living conditions in multilevel choice modeling: An application to contraceptive adoption by Indian women

PubMed Central

2018-01-01

This research analyzes the effect of the poverty-wealth dimension on contraceptive adoption by Indian women when no direct measures of income/expenditures are available to use as covariates. The index–Household Living Conditions (HLC)–is based on household assets and dwelling characteristics and is computed by an item response model simultaneously with the choice model in a new single-step approach. That is, the HLC indicator is treated as a latent covariate measured by a set of items, it depends on a set of concomitant variables, and explains contraceptive choices in a probit regression. Additionally, the model accounts for complex survey design and sample weights in a multilevel framework. Regarding our case study on contraceptive adoption by Indian women, results show that women with better household living conditions tend to adopt contraception more often than their counterparts. This effect is significant after controlling other factors such as education, caste, and religion. The external validation of the indicator shows that it can also be used at aggregate levels of analysis (e.g., county or state) whenever no other indicators of household living conditions are available. PMID:29385187

A menu-driven software package of Bayesian nonparametric (and parametric) mixed models for regression analysis and density estimation.

PubMed

Karabatsos, George

2017-02-01

Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected functionals and values of covariates. The software is illustrated through the BNP regression analysis of real data.

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…

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

PubMed

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

2012-07-01

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

Effects of Youth Participation in Extra-Curricular Sport Programs on Perceived Self-Efficacy: A Multilevel Analysis.

PubMed

Reverdito, Riller S; Carvalho, Humberto M; Galatti, Larissa R; Scaglia, Alcides J; Gonçalves, Carlos E; Paes, Roberto R

2017-06-01

The present study examined extracurricular sport participation variables and developmental context in relationship to perceived self-efficacy among underserved adolescents. Participants ( n = 821, 13.6 ± 1.5 years) completed the Youth Experience in Sport questionnaire and General Self-Efficacy Scale. We used the Human Development Index (HDI) to characterize developmental contexts. Multilevel regression models were used to explore the relative contributions of age, sex, years of participation in extracurricular sport, HDI, and perceived positive experience in sport. Our results highlight that positive experience alone and in interaction with length of participation in the program fostered perceived self-efficacy. Participants from higher HDI contexts remained longer in the program. An implication of our research is that variables linked to positive sport experiences and perceived self-efficacy can be used as markers to evaluate the outcomes and impact of sport participation programs aimed at promoting positive youth development.

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

PubMed

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

2014-09-01

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

[Ecological Correlates of Cardiovascular Disease Risk in Korean Blue-collar Workers: A Multi-level Study].

PubMed

Hwang, Won Ju; Park, Yunhee

2015-12-01

The purpose of this study was to investigate individual and organizational level of cardiovascular disease (CVD) risk factors associated with CVD risk in Korean blue-collar workers working in small sized companies. Self-report questionnaires and blood sampling for lipid and glucose were collected from 492 workers in 31 small sized companies in Korea. Multilevel modeling was conducted to estimate effects of related factors at the individual and organizational level. Multilevel regression analysis showed that workers in the workplace having a cafeteria had 1.81 times higher CVD risk after adjusting for factors at the individual level (p=.022). The explanatory power of variables related to organizational level variances in CVD risk was 17.1%. The results of this study indicate that differences in the CVD risk were related to organizational factors. It is necessary to consider not only individual factors but also organizational factors when planning a CVD risk reduction program. The factors caused by having cafeteria in the workplace can be reduced by improvement in the CVD-related risk environment, therefore an organizational-level intervention approach should be available to reduce CVD risk of workers in small sized companies in Korea.

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

PubMed

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

2013-09-01

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

Neighborhood social capital and crime victimization: comparison of spatial regression analysis and hierarchical regression analysis.

PubMed

Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro

2012-11-01

Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

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…

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.

Health of midlife and older adults in China: the role of regional economic development, inequality, and institutional setting.

PubMed

Ding, Xuejie; Billari, Francesco C; Gietel-Basten, Stuart

2017-11-01

To document the association between economic development, income inequality, and health-related public infrastructure, and health outcomes among Chinese adults in midlife and older age. We use a series of multi-level regression models with individual-level baseline data from the China Health and Retirement Longitudinal Survey (CHARLS). Provincial-level data are obtained both from official statistics and from CHARLS itself. Multi-level models are estimated with different subjective and objective health outcomes. Economic growth is associated with better self-rated health, but also with obesity. Better health infrastructure tends to be negatively associated with health outcomes, indicating the likely presence of reverse causality. No supportive evidence is found for the hypothesis that income inequality leads to worse health outcomes. Our study shows that on top of individual characteristics, provincial variations in economic development, income inequality, and health infrastructure are associated with a range of health outcomes for Chinese midlife and older adults. Economic development in China might also bring adverse health outcomes for this age group; as such specific policy responses need to be developed.

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.

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).

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

PubMed

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

2017-05-01

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

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

PubMed

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

2018-05-25

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

Multi-level modeling of social factors and preterm delivery in Santiago de Chile

PubMed Central

Kaufman, Jay S; Alonso, Faustino T; Pino, Paulina

2008-01-01

Background Birth before the 37th week of gestation (preterm birth) is an important cause of infant and neonatal mortality, but has been little studied outside of wealthy nations. Chile is an urbanized Latin American nation classified as "middle-income" based on its annual income per capita of about $6000. Methods We studied the relations between maternal social status and neighborhood social status on risk of preterm delivery in this setting using multilevel regression analyses of vital statistics data linked to geocoded decennial census data. The analytic data set included 56,970 births from 2004 in the metropolitan region of Santiago, which constitutes about 70% of all births in the study area and about 25% of all births in Chile that year. Dimensionality of census data was reduced using principal components analysis, with regression scoring to create a single index of community socioeconomic advantage. This was modeled along with years of maternal education in order to predict preterm birth and preterm low birthweight. Results Births in Santiago displayed an advantaged pattern of preterm risk, with only 6.4% of births delivering before 37 weeks. Associations were observed between risk of outcomes and individual and neighborhood factors, but the magnitudes of these associations were much more modest than reported in North America. Conclusion While several potential explanations for this relatively flat social gradient might be considered, one possibility is that Chile's egalitarian approach to universal prenatal care may have reduced social inequalities in these reproductive outcomes. PMID:18842145

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

PubMed

Lindström, Martin; Moghaddassi, Mahnaz; Merlo, Juan

2004-07-01

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

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

PubMed Central

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

2015-01-01

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

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…

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

PubMed

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

2009-03-15

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

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

Method of Grassland Information Extraction Based on Multi-Level Segmentation and Cart Model

NASA Astrophysics Data System (ADS)

Qiao, Y.; Chen, T.; He, J.; Wen, Q.; Liu, F.; Wang, Z.

2018-04-01

It is difficult to extract grassland accurately by traditional classification methods, such as supervised method based on pixels or objects. This paper proposed a new method combing the multi-level segmentation with CART (classification and regression tree) model. The multi-level segmentation which combined the multi-resolution segmentation and the spectral difference segmentation could avoid the over and insufficient segmentation seen in the single segmentation mode. The CART model was established based on the spectral characteristics and texture feature which were excavated from training sample data. Xilinhaote City in Inner Mongolia Autonomous Region was chosen as the typical study area and the proposed method was verified by using visual interpretation results as approximate truth value. Meanwhile, the comparison with the nearest neighbor supervised classification method was obtained. The experimental results showed that the total precision of classification and the Kappa coefficient of the proposed method was 95 % and 0.9, respectively. However, the total precision of classification and the Kappa coefficient of the nearest neighbor supervised classification method was 80 % and 0.56, respectively. The result suggested that the accuracy of classification proposed in this paper was higher than the nearest neighbor supervised classification method. The experiment certificated that the proposed method was an effective extraction method of grassland information, which could enhance the boundary of grassland classification and avoid the restriction of grassland distribution scale. This method was also applicable to the extraction of grassland information in other regions with complicated spatial features, which could avoid the interference of woodland, arable land and water body effectively.

School-level economic disadvantage and obesity in middle school children in central Texas, USA: a cross-sectional study

PubMed Central

2015-01-01

Background Although children of lower socio-economic status (SES) in the United States have generally been found to be at greater risk for obesity, the SES-obesity association varies when stratified by racial/ethnic groups-with no consistent association found for African American and Hispanic children. Research on contextual and setting-related factors may provide further insights into ethnic and SES disparities in obesity. We examined whether obesity levels among central Texas 8th grade students (n=2682) vary by school-level economic disadvantage across individual-level family SES and racial/ethnicity groups. As a secondary aim, we compared the association of school-level economic disadvantage and obesity by language spoken with parents (English or Spanish) among Hispanic students. Methods Multilevel regression models stratified by family SES and ethnicity were run using cross-sectional baseline data from five school districts participating in the Central Texas CATCH Middle School project. For family SES, independent multi-level logistic regression models were run for total sample and by gender for each family SES stratum (poor/near poor/just getting by, living comfortably, and very well off), adjusting for age, ethnicity, and gender. Similarly, multi-level regression models were run by race/ethnic group (African American, Hispanic, and White), adjusting for age, family SES, and gender. Results Students attending highly economically disadvantaged (ED) schools were between 1.7 (95% CI: 1.1-2.6) and 2.4 (95% CI: 1.2-4.8) times more likely to be obese as students attending low ED schools across family SES groups (p<.05). African American (ORAdj =3.4, 95% CI: 1.1-11.4), Hispanic (ORAdj=1.8, 95% CI 1.1-3.0) and White (ORAdj=3.8, 95% CI: 1.6-8.9) students attending high ED schools were more likely to be obese as counterparts at low ED schools (p<.05). Gender-stratified findings were similar to findings for total sample, although fewer results reached significance. While no obesity differences across school ED categories were found for Hispanic Spanish-speaking students, Hispanic English-speaking students (HES) attending high ED schools were 2.4 times more likely to be obese as HES students at low ED schools (p=.003). Conclusion Findings support the need to prioritize economically disadvantaged schools for obesity prevention efforts and support further exploration of school SES context in shaping children’s physical activity and dietary behaviors. PMID:26222099

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

PubMed

Nam, Woo Dong; Cho, Jae Hwan

2015-03-01

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

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

PubMed Central

Nam, Woo Dong

2015-01-01

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

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

PubMed

Spence, Nicholas D

2016-03-01

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

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

ERIC Educational Resources Information Center

Li, Xin; Beretvas, S. Natasha

2013-01-01

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

Multilevel modelling: Beyond the basic applications.

PubMed

Wright, Daniel B; London, Kamala

2009-05-01

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

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

PubMed

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

2018-01-01

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

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

ERIC Educational Resources Information Center

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

2016-01-01

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

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).

Modeling developmental changes in functional capacities and soccer-specific skills in male players aged 11-17 years.

PubMed

Valente-dos-Santos, João; Coelho-e-Silva, Manuel J; Simões, Filipe; Figueiredo, Antonio J; Leite, Neiva; Elferink-Gemser, Marije T; Malina, Robert M; Sherar, Lauren

2012-11-01

This study evaluates the contributions of age, growth, skeletal maturation, playing position and training to longitudinal changes in functional and skill performance in male youth soccer. Players were annually followed over 5 years (n = 83, 4.4 measurements per player). Composite scores for functional and skill domains were calculated to provide an overall estimate of performance. Players were also classified by maturity status and playing position at baseline. After testing for multicollinearity, two-level multilevel (longitudinal) regression models were obtained for functional and skill composite scores. The scores improved with age and training. Body mass was an additional predictor in both models [functional (late maturing): 13.48 + 1.05 × centered on chronological age (CA)-0.01 × centered CA(2)-0.19 × fat mass (FM) + 0.004 × annual volume training-1.04 × dribbling speed; skills (defenders): 7.62 + 0.62 × centered CA-0.06 × centered CA(2) + 0.04 × fat-free mass-0.03 x FM + 0.005 × annual volume training-0.19 × repeated-sprint ability + 0.02 × aerobic endurance]. Skeletal maturity status was a significant predictor of functional capacities and playing position of skill performance. Sound accuracy of each multilevel model was demonstrated on an independent cross-sectional sample (n = 52).

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…

A Multilevel Study of Students in Vietnam: Drinking Motives and Drinking Context as Predictors of Alcohol Consumption

PubMed Central

Diep, Pham Bich; Tan, Frans E. S.; Knibbe, Ronald A.; De Vries, Nanne

2016-01-01

Background: This study used multi-level analysis to estimate which type of factor explains most of the variance in alcohol consumption of Vietnamese students. Methods: Data were collected among 6011 students attending 12 universities/faculties in four provinces in Vietnam. The three most recent drinking occasions were investigated per student, resulting in 12,795 drinking occasions among 4265 drinkers. Students reported on 10 aspects of the drinking context per drinking occasion. A multi-level mixed-effects linear regression model was constructed in which aspects of drinking context composed the first level; the age of students and four drinking motives comprised the second level. The dependent variable was the number of drinks. Results: Of the aspects of context, drinking duration had the strongest association with alcohol consumption while, at the individual level, coping motive had the strongest association. The drinking context characteristics explained more variance than the individual characteristics in alcohol intake per occasion. Conclusions: These findings suggest that, among students in Vietnam, the drinking context explains a larger proportion of the variance in alcohol consumption than the drinking motives. Therefore, measures that reduce the availability of alcohol in specific drinking situations are an essential part of an effective prevention policy. PMID:27420089

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.

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/.

Friendship networks of inner-city adults: a latent class analysis and multi-level regression of supporter types and the association of supporter latent class membership with supporter and recipient drug use.

PubMed

Bohnert, Amy S B; German, Danielle; Knowlton, Amy R; Latkin, Carl A

2010-03-01

Social support is a multi-dimensional construct that is important to drug use cessation. The present study identified types of supportive friends among the social network members in a community-based sample and examined the relationship of supporter-type classes with supporter, recipient, and supporter-recipient relationship characteristics. We hypothesized that the most supportive network members and their support recipients would be less likely to be current heroin/cocaine users. Participants (n=1453) were recruited from low-income neighborhoods with a high prevalence of drug use. Participants identified their friends via a network inventory, and all nominated friends were included in a latent class analysis and grouped based on their probability of providing seven types of support. These latent classes were included as the dependent variable in a multi-level regression of supporter drug use, recipient drug use, and other characteristics. The best-fitting latent class model identified five support patterns: friends who provided Little/No Support, Low/Moderate Support, High Support, Socialization Support, and Financial Support. In bivariate models, friends in the High, Low/Moderate, and Financial Support were less likely to use heroin or cocaine and had less conflict with and were more trusted by the support recipient than friends in the Low/No Support class. Individuals with supporters in those same support classes compared to the Low/No Support class were less likely to use heroin or cocaine, or to be homeless or female. Multivariable models suggested similar trends. Those with current heroin/cocaine use were less likely to provide or receive comprehensive support from friends. Published by Elsevier Ireland Ltd.

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…

Perceptions of community, social capital, and how they affect self-reported health: a multilevel analysis.

PubMed

Dziadkowiec, O; Meissen, G J; Merkle, E C

2017-11-01

The link between social capital and self-reported health has been widely explored. On the other hand, we know less about the relationship between social capital, community socioeconomic characteristics, and non-social capital-related individual differences, and about their impact on self-reported health in community settings. Cross-sectional study design with a proportional sample of 7965 individuals from 20 US communities were analyzed using multilevel linear regression models, where individuals were nested within communities. The response rates ranged from 13.5% to 25.4%. Findings suggest that perceptions of the community and individual level socioeconomic characteristics were stronger predictors of self-reported health than were social capital or community socioeconomic characteristics. Policy initiatives aimed at increasing social capital should first assess community member's perceptions of their communities to uncover potential assets to help increase social capital. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2010-01-01

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

Examining the Association between School Context, Educational Capacity, and Student Achievement: A Regression Discontinuity Approach

ERIC Educational Resources Information Center

Moriyama, Karen Ito

2009-01-01

In this era of accountability, there is a need to fairly and accurately document the ways that educational systems contribute to student achievement. This study used the regression discontinuity design within a multilevel framework as an alternative approach to estimate school effectiveness by examining the effect of the value added to students'…

Introducing the Event Related Fixed Interval Area (ERFIA) Multilevel Technique: a Method to Analyze the Complete Epoch of Event-Related Potentials at Single Trial Level

PubMed Central

Vossen, Catherine J.; Vossen, Helen G. M.; Marcus, Marco A. E.; van Os, Jim; Lousberg, Richel

2013-01-01

In analyzing time-locked event-related potentials (ERPs), many studies have focused on specific peaks and their differences between experimental conditions. In theory, each latency point after a stimulus contains potentially meaningful information, regardless of whether it is peak-related. Based on this assumption, we introduce a new concept which allows for flexible investigation of the whole epoch and does not primarily focus on peaks and their corresponding latencies. For each trial, the entire epoch is partitioned into event-related fixed-interval areas under the curve (ERFIAs). These ERFIAs, obtained at single trial level, act as dependent variables in a multilevel random regression analysis. The ERFIA multilevel method was tested in an existing ERP dataset of 85 healthy subjects, who underwent a rating paradigm of 150 painful and non-painful somatosensory electrical stimuli. We modeled the variability of each consecutive ERFIA with a set of predictor variables among which were stimulus intensity and stimulus number. Furthermore, we corrected for latency variations of the P2 (260 ms). With respect to known relationships between stimulus intensity, habituation, and pain-related somatosensory ERP, the ERFIA method generated highly comparable results to those of commonly used methods. Notably, effects on stimulus intensity and habituation were also observed in non-peak-related latency ranges. Further, cortical processing of actual stimulus intensity depended on the intensity of the previous stimulus, which may reflect pain-memory processing. In conclusion, the ERFIA multilevel method is a promising tool that can be used to study event-related cortical processing. PMID:24224018

Validity analysis on merged and averaged data using within and between analysis: focus on effect of qualitative social capital on self-rated health.

PubMed

Shin, Sang Soo; Shin, Young-Jeon

2016-01-01

With an increasing number of studies highlighting regional social capital (SC) as a determinant of health, many studies are using multi-level analysis with merged and averaged scores of community residents' survey responses calculated from community SC data. Sufficient examination is required to validate if the merged and averaged data can represent the community. Therefore, this study analyzes the validity of the selected indicators and their applicability in multi-level analysis. Within and between analysis (WABA) was performed after creating community variables using merged and averaged data of community residents' responses from the 2013 Community Health Survey in Korea, using subjective self-rated health assessment as a dependent variable. Further analysis was performed following the model suggested by WABA result. Both E-test results (1) and WABA results (2) revealed that single-level analysis needs to be performed using qualitative SC variable with cluster mean centering. Through single-level multivariate regression analysis, qualitative SC with cluster mean centering showed positive effect on self-rated health (0.054, p<0.001), although there was no substantial difference in comparison to analysis using SC variables without cluster mean centering or multi-level analysis. As modification in qualitative SC was larger within the community than between communities, we validate that relational analysis of individual self-rated health can be performed within the group, using cluster mean centering. Other tests besides the WABA can be performed in the future to confirm the validity of using community variables and their applicability in multi-level analysis.

Violence Among Men and Women in Substance Use Disorder Treatment: A Multi-level Event-based Analysis

PubMed Central

Chermack, Stephen T.; Grogan-Kaylor, Andy; Perron, Brian E.; Murray, Regan L.; De Chavez, Peter; Walton, Maureen A.

2010-01-01

Background This study examined associations between acute alcohol and drug use and violence towards others in conflict incidents (overall, partner, and non-partner conflict incidents) by men and women recruited from substance use disorder (SUD) treatment. Methods Semi-structured interviews were used to obtain details about interpersonal conflict incidents (substance use, whether specific conflicts were with intimate partners or non-partners) in the 180 days pre-treatment. Participants for this study were selected for screening positive for past-year violence (N = 160; 77% men, 23% women). Results Multilevel multinomial regression models showed that after adjusting for clustering within individual participants, the most consistent predictors of violence across models were acute cocaine use (significant for overall, intimate partner and non-partner models), acute heavy alcohol use (significant for overall and non-partner models), and male gender (significant in all models). Conclusions This study was the first to explicitly examine the role of acute alcohol and drug use across overall, partner and non-partner conflict incidents. Consistent with prior studies using a variety of methodologies, alcohol, cocaine use and male gender were most consistently and positively related to violence severity (e.g., resulting in injury). The results provide important and novel event-level information regarding the relationship between acute alcohol and specific drug use and the severity of violence in interpersonal conflict incidents. PMID:20667666

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

PubMed Central

2012-01-01

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

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

PubMed

Resche-Rigon, Matthieu; White, Ian R

2018-06-01

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

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

ERIC Educational Resources Information Center

Park, Jungkyu; Yu, Hsiu-Ting

2016-01-01

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

Developing soft skill training for salespersons to increase total sales

NASA Astrophysics Data System (ADS)

Mardatillah, A.; Budiman, I.; Tarigan, U. P. P.; Sembiring, A. C.; Hendi

2018-04-01

This research was conducted in the multilevel marketing industry. Unprofessional salespersons behavior and responsibility can ruin the image of the multilevel marketing industry and distrust to the multilevel marketing industry. This leads to decreased company revenue due to lack of public interest in multilevel marketing products. Seeing these conditions, researcher develop training programs to improve the competence of salespersons in making sales. It was done by looking at factors that affect the level of salespersons sales. The research analyzes several factors that influence the salesperson’s sales level: presentation skills, questioning ability, adaptability, technical knowledge, self-control, interaction involvement, sales environment, and intrapersonal skills. Through the analysis of these factors with One Sample T-Test and Multiple Linear Regression methods, researchers design a training program for salespersons to increase their sales. The developed training for salespersons is basic training and special training and before training was given, salespersons need to be assessed for the effectivity and efficiency reasons.

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

PubMed

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

2011-06-01

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

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.

Multilevel Higher-Order Item Response Theory Models

ERIC Educational Resources Information Center

Huang, Hung-Yu; Wang, Wen-Chung

2014-01-01

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

Conducting Multilevel Analyses in Medical Education

ERIC Educational Resources Information Center

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

2008-01-01

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

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

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

PubMed

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

2003-01-01

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

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

PubMed

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

2018-06-08

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

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

PubMed

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

2015-03-01

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

Multilevel regularized regression for simultaneous taxa selection and network construction with metagenomic count data.

PubMed

Liu, Zhenqiu; Sun, Fengzhu; Braun, Jonathan; McGovern, Dermot P B; Piantadosi, Steven

2015-04-01

Identifying disease associated taxa and constructing networks for bacteria interactions are two important tasks usually studied separately. In reality, differentiation of disease associated taxa and correlation among taxa may affect each other. One genus can be differentiated because it is highly correlated with another highly differentiated one. In addition, network structures may vary under different clinical conditions. Permutation tests are commonly used to detect differences between networks in distinct phenotypes, and they are time-consuming. In this manuscript, we propose a multilevel regularized regression method to simultaneously identify taxa and construct networks. We also extend the framework to allow construction of a common network and differentiated network together. An efficient algorithm with dual formulation is developed to deal with the large-scale n ≪ m problem with a large number of taxa (m) and a small number of samples (n) efficiently. The proposed method is regularized with a general Lp (p ∈ [0, 2]) penalty and models the effects of taxa abundance differentiation and correlation jointly. We demonstrate that it can identify both true and biologically significant genera and network structures. Software MLRR in MATLAB is available at http://biostatistics.csmc.edu/mlrr/. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

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

PubMed Central

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

2015-01-01

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

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.

Return to Work and Multilevel Versus Single-Level Cervical Fusion for Radiculopathy in a Workers' Compensation Setting.

PubMed

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

2017-01-15

Retrospective comparative cohort study. Examine the impact of multilevel fusion on return to work (RTW) status and compare RTW status after multi- versus single-level cervical fusion for patients with work-related injury. Patients with work-related injuries in the workers' compensation systems have less favorable surgical outcomes. Cervical fusion provides a greater than 90% likelihood of relieving radiculopathy and stabilizing or improving myelopathy. However, more levels fused at index surgery are reportedly associated with poorer surgical outcomes than single-level fusion. Data was collected from the Ohio Bureau of Workers' Compensation (BWC) between 1993 and 2011. The study population included patients who underwent cervical fusion for radiculopathy. Two groups were constructed (multilevel fusion [MLF] vs. single-level fusion [SLF]). Outcomes measures evaluated were: RTW criteria, RTW <1year, reoperation, surgical complication, disability, and legal litigation after surgery. After accounting for a number of independent variables in the regression model, multilevel fusion was a negative predictor of successful RTW status within 3-year follow-up after surgery (OR = 0.82, 95% CI: 0.70-0.95, P <0.05).RTW criteria were met 62.9% of SLF group compared with 54.8% of MLF group. The odds of having a stable RTW for MLF patients were 0.71% compared with the SLF patients (95% CI: 0.61-0.83; P: 0.0001).At 1 year after surgery, RTW rate was 53.1% for the SLF group compared with 43.7% for the MLF group. The odds of RTW within 1 year after surgery for the MLF group were 0.69% compared with SLF patients (95% CI: 0.59-0.80; P: 0.0001).Higher rate of disability after surgery was observed in the MLF group compared with the SLF group (P: 0.0001) CONCLUSION.: Multilevel cervical fusion for radiculopathy was associated with poor return to work profile after surgery. Multilevel cervical fusion was associated with lower RTW rates, less likelihood of achieving stable return to work, and higher rate of disability after surgery. 3.

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.

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.

Establishing a Mathematical Equations and Improving the Production of L-tert-Leucine by Uniform Design and Regression Analysis.

PubMed

Jiang, Wei; Xu, Chao-Zhen; Jiang, Si-Zhi; Zhang, Tang-Duo; Wang, Shi-Zhen; Fang, Bai-Shan

2017-04-01

L-tert-Leucine (L-Tle) and its derivatives are extensively used as crucial building blocks for chiral auxiliaries, pharmaceutically active ingredients, and ligands. Combining with formate dehydrogenase (FDH) for regenerating the expensive coenzyme NADH, leucine dehydrogenase (LeuDH) is continually used for synthesizing L-Tle from α-keto acid. A multilevel factorial experimental design was executed for research of this system. In this work, an efficient optimization method for improving the productivity of L-Tle was developed. And the mathematical model between different fermentation conditions and L-Tle yield was also determined in the form of the equation by using uniform design and regression analysis. The multivariate regression equation was conveniently implemented in water, with a space time yield of 505.9 g L -1  day -1 and an enantiomeric excess value of >99 %. These results demonstrated that this method might become an ideal protocol for industrial production of chiral compounds and unnatural amino acids such as chiral drug intermediates.

Robust Mediation Analysis Based on Median Regression

PubMed Central

Yuan, Ying; MacKinnon, David P.

2014-01-01

Mediation analysis has many applications in psychology and the social sciences. The most prevalent methods typically assume that the error distribution is normal and homoscedastic. However, this assumption may rarely be met in practice, which can affect the validity of the mediation analysis. To address this problem, we propose robust mediation analysis based on median regression. Our approach is robust to various departures from the assumption of homoscedasticity and normality, including heavy-tailed, skewed, contaminated, and heteroscedastic distributions. Simulation studies show that under these circumstances, the proposed method is more efficient and powerful than standard mediation analysis. We further extend the proposed robust method to multilevel mediation analysis, and demonstrate through simulation studies that the new approach outperforms the standard multilevel mediation analysis. We illustrate the proposed method using data from a program designed to increase reemployment and enhance mental health of job seekers. PMID:24079925

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

ERIC Educational Resources Information Center

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

2011-01-01

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

The development of video game enjoyment in a role playing game.

PubMed

Wirth, Werner; Ryffel, Fabian; von Pape, Thilo; Karnowski, Veronika

2013-04-01

This study examines the development of video game enjoyment over time. The results of a longitudinal study (N=62) show that enjoyment increases over several sessions. Moreover, results of a multilevel regression model indicate a causal link between the dependent variable video game enjoyment and the predictor variables exploratory behavior, spatial presence, competence, suspense and solution, and simulated experiences of life. These findings are important for video game research because they reveal the antecedents of video game enjoyment in a real-world longitudinal setting. Results are discussed in terms of the dynamics of video game enjoyment under real-world conditions.

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

PubMed

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

2018-06-14

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

Face-Referenced Measurement of Perioral Stiffness and Speech Kinematics in Parkinson's Disease

PubMed Central

Barlow, Steven M.; Lee, Jaehoon

2015-01-01

Purpose Perioral biomechanics, labial kinematics, and associated electromyographic signals were sampled and characterized in individuals with Parkinson's disease (PD) as a function of medication state. Method Passive perioral stiffness was sampled using the OroSTIFF system in 10 individuals with PD in a medication ON and a medication OFF state and compared to 10 matched controls. Perioral stiffness, derived as the quotient of resultant force and interoral angle span, was modeled with regression techniques. Labial movement amplitudes and integrated electromyograms from select lip muscles were evaluated during syllable production using a 4-D computerized motion capture system. Results Multilevel regression modeling showed greater perioral stiffness in patients with PD, consistent with the clinical correlate of rigidity. In the medication-OFF state, individuals with PD manifested greater integrated electromyogram levels for the orbicularis oris inferior compared to controls, which increased further after consumption of levodopa. Conclusions This study illustrates the application of biomechanical, electrophysiological, and kinematic methods to better understand the pathophysiology of speech motor control in PD. PMID:25629806

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…

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

PubMed Central

Sharafi, Zahra

2017-01-01

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

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

PubMed

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

2017-01-01

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

Community-level income inequality and HIV prevalence among persons who inject drugs in Thai Nguyen, Vietnam.

PubMed

Lim, Travis W; Frangakis, Constantine; Latkin, Carl; Ha, Tran Viet; Minh, Nguyen Le; Zelaya, Carla; Quan, Vu Minh; Go, Vivian F

2014-01-01

Socioeconomic status has a robust positive relationship with several health outcomes at the individual and population levels, but in the case of HIV prevalence, income inequality may be a better predictor than absolute level of income. Most studies showing a relationship between income inequality and HIV have used entire countries as the unit of analysis. In this study, we examine the association between income inequality at the community level and HIV prevalence in a sample of persons who inject drugs (PWID) in a concentrated epidemic setting. We recruited PWID and non-PWID community participants in Thai Nguyen, Vietnam, and administered a cross-sectional questionnaire; PWID were tested for HIV. We used ecologic regression to model HIV burden in our PWID study population on GINI indices of inequality calculated from total reported incomes of non-PWID community members in each commune. We also modeled HIV burden on interaction terms between GINI index and median commune income, and finally used a multi-level model to control for community level inequality and individual level income. HIV burden among PWID was significantly correlated with the commune GINI coefficient (r = 0.53, p = 0.002). HIV burden was also associated with GINI coefficient (β = 0.082, p = 0.008) and with median commune income (β = -0.018, p = 0.023) in ecological regression. In the multi-level model, higher GINI coefficient at the community level was associated with higher odds of individual HIV infection in PWID (OR = 1.46 per 0.01, p = 0.003) while higher personal income was associated with reduced odds of infection (OR = 0.98 per $10, p = 0.022). This study demonstrates a context where income inequality is associated with HIV prevalence at the community level in a concentrated epidemic. It further suggests that community level socioeconomic factors, both contextual and compositional, could be indirect determinants of HIV infection in PWID.

Community-Level Income Inequality and HIV Prevalence among Persons Who Inject Drugs in Thai Nguyen, Vietnam

PubMed Central

Lim, Travis W.; Frangakis, Constantine; Latkin, Carl; Ha, Tran Viet; Minh, Nguyen Le; Zelaya, Carla; Quan, Vu Minh; Go, Vivian F.

2014-01-01

Socioeconomic status has a robust positive relationship with several health outcomes at the individual and population levels, but in the case of HIV prevalence, income inequality may be a better predictor than absolute level of income. Most studies showing a relationship between income inequality and HIV have used entire countries as the unit of analysis. In this study, we examine the association between income inequality at the community level and HIV prevalence in a sample of persons who inject drugs (PWID) in a concentrated epidemic setting. We recruited PWID and non-PWID community participants in Thai Nguyen, Vietnam, and administered a cross-sectional questionnaire; PWID were tested for HIV. We used ecologic regression to model HIV burden in our PWID study population on GINI indices of inequality calculated from total reported incomes of non-PWID community members in each commune. We also modeled HIV burden on interaction terms between GINI index and median commune income, and finally used a multi-level model to control for community level inequality and individual level income. HIV burden among PWID was significantly correlated with the commune GINI coefficient (r = 0.53, p = 0.002). HIV burden was also associated with GINI coefficient (β = 0.082, p = 0.008) and with median commune income (β = −0.018, p = 0.023) in ecological regression. In the multi-level model, higher GINI coefficient at the community level was associated with higher odds of individual HIV infection in PWID (OR = 1.46 per 0.01, p = 0.003) while higher personal income was associated with reduced odds of infection (OR = 0.98 per $10, p = 0.022). This study demonstrates a context where income inequality is associated with HIV prevalence at the community level in a concentrated epidemic. It further suggests that community level socioeconomic factors, both contextual and compositional, could be indirect determinants of HIV infection in PWID. PMID:24618892

Growth in Reading Performance during the First Four Years in School. Research Report. ETS RR-07-39

ERIC Educational Resources Information Center

Rock, Donald A.

2007-01-01

This study addressed concerns about the potential for differential gains in reading during the first 2 years of formal schooling (K-1) versus the next 2 years of schooling (1st-3rd grade). A multilevel piecewise regression with a node at spring 1st grade was used in order to define separate regressions for the two time periods. Empirical Bayes…

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.

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.

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

PubMed Central

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

2016-01-01

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

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

Using multilevel models for assessing the variability of multinational resource use and cost data.

PubMed

Grieve, Richard; Nixon, Richard; Thompson, Simon G; Normand, Charles

2005-02-01

Multinational economic evaluations often calculate a single measure of cost-effectiveness using cost data pooled across several countries. To assess the validity of pooling international cost data the reasons for cost variation across countries need to be assessed. Previously, ordinary least-squares (OLS) regression models have been used to identify factors associated with variability in resource use and total costs. However, multilevel models (MLMs), which accommodate the hierarchical structure of the data, may be more appropriate. This paper compares these different techniques using a multinational dataset comprising case-mix, resource use and cost data on 1300 stroke admissions from 13 centres in 11 European countries. OLS and MLMs were used to estimate the effect of patient and centre-level covariates on the total length of hospital stay (LOS) and total cost. MLMs with normal and gamma distributions for the data within centres were compared. The results from the OLS model showed that both patient and centre-level covariates were associated with LOS and total cost. The estimates from the MLMs showed that none of the centre-level characteristics were associated with LOS, and the level of spending on health was the centre-level variable most highly associated with total cost. We conclude that using OLS models for assessing international variation can lead to incorrect inferences, and that MLMs are more appropriate for assessing why resource use and costs vary across centres. Copyright (c) 2004 John Wiley & Sons, Ltd.

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

Pathological Narcissism and Interpersonal Behavior in Daily Life

PubMed Central

Roche, Michael J.; Pincus, Aaron L.; Conroy, David E.; Hyde, Amanda L.; Ram, Nilam

2014-01-01

The Cognitive-Affective Processing System (CAPS) has been proposed as a useful meta-framework for integrating contextual differences in situations with individual differences in personality pathology. In this article, we evaluated the potential of combining the CAPS meta-framework and contemporary interpersonal theory to investigate how individual differences in pathological narcissism influenced interpersonal functioning in daily life. University students (N = 184) completed event-contingent reports about interpersonal interactions across a 7-day diary study. Using multilevel regression models, we found that combinations of narcissistic expression (grandiosity, vulnerability) were associated with different interpersonal behavior patterns reflective of interpersonal dysfunction. These results are among the first to empirically demonstrate the usefulness of the CAPS model to conceptualize personality pathology through the patterning of if-then interpersonal processes. PMID:23205698

School gardens and adolescent nutrition and BMI: Results from a national, multilevel study.

PubMed

Utter, Jennifer; Denny, Simon; Dyson, Ben

2016-02-01

The aim of the current study was to determine the impact of school gardens on student eating behaviors, physical activity and BMI in New Zealand secondary schools. The current study also aimed to determine if school gardens could buffer the association between household poverty and adolescent BMI. Data were drawn from a national study of the health and wellbeing of New Zealand secondary school students (n=8500) conducted in 2012. Multilevel regression models were used to determine the association between school gardens (school-level) and student nutrition behaviors, physical activity and measured BMI (student-level). Approximately half of secondary schools had a fruit/vegetable garden for students to participate in. School gardens were associated with lower student BMI (p=0.01) and lower prevalence of overweight (p<0.01). School gardens appear to have a positive impact on student health. Future research may explore how school gardens are implemented to better understand their impact and to extend the benefits beyond the school community. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

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

PubMed

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

2010-06-01

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

Race, Employment Disadvantages, and Heavy Drinking: A Multilevel Model.

PubMed

Lo, Celia C; Cheng, Tyrone C

2015-01-01

We intended to determine (1) whether stress from employment disadvantages led to increased frequency of heavy drinking and (2) whether race had a role in the relationship between such disadvantages and heavy drinking. Study data came from the National Longitudinal Survey of Youth, a prospective study that has followed a representative sample of youth since 1979. Our study employed data from 11 particular years, during which the survey included items measuring respondents' heavy drinking. Our final sample numbered 10,171 respondents, which generated 75,394 person-waves for data analysis. Both of our hypotheses were supported by results from multilevel mixed-effects linear regression capturing the time-varying nature of three employment disadvantages and of the heavy-drinking outcome. Results show that more-frequent heavy drinking was associated with employment disadvantages, and that disadvantages' effects on drinking were stronger for Blacks and Hispanics than for Whites. That worsening employment disadvantages have worse effects on minority groups' heavy drinking (compared to Whites) probably contributes to the racial health disparities in our nation. Policies and programs addressing such disparities are especially important during economic downturns.

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

DTIC Science & Technology

1980-03-01

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

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

ERIC Educational Resources Information Center

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

2006-01-01

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

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.

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

PubMed

Lamidi, Esther O

2015-01-01

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

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.

Editorial highlighting and highly cited papers

NASA Astrophysics Data System (ADS)

Antonoyiannakis, Manolis

Editorial highlighting-the process whereby journal editors select, at the time of publication, a small subset of papers that are ostensibly of higher quality, importance or interest-is by now a widespread practice among major scientific journal publishers. Depending on the venue, and the extent to which editorial resources are invested in the process, highlighted papers appear as News & Views, Research Highlights, Perspectives, Editors' Choice, IOP Select, Editors' Summary, Spotlight on Optics, Editors' Picks, Viewpoints, Synopses, Editors' Suggestions, etc. Here, we look at the relation between highlighted papers and highly influential papers, which we define at two levels: having received enough citations to be among the (i) top few percent of their journal, and (ii) top 1% of all physics papers. Using multiple linear regression and multilevel regression modeling we examine the parameters associated with highly influential papers. We briefly comment on cause and effect relationships between citedness and highlighting of papers.

Teaching quality: High school students' autonomy and competence.

PubMed

León, Jaime; Medina-Garrido, Elena; Ortega, Miriam

2018-05-01

How teachers manage class learning and interact with students affects students’ motivation and engagement. However, it could be that the effect of students’ representation of teaching quality on the students’ motivation varies between classes. Students from 90 classes participated in the study. We used multilevel random structural equation modeling to analyze whether the relationship of the students’ perception of teaching quality (as an indicator of the students’ mental representation) and students’ motivation varies between classes, and if this variability depends on the class assessment of teaching quality (as an indicator of teaching quality). The effect of teachers’ structure on the regression slope of student perception of student competence was .127. The effect of teachers’ autonomy support on the regression slope of student perception of student autonomy was .066. With this study we contribute a more detailed description of the relationship between teaching quality, competence and autonomy.

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…

[Homicides involving firearms in Argentina between 1991 and 2006: a multilevel analysis].

PubMed

Zunino, Marina Gabriela; Diez Roux, Ana Victoria; de Souza, Edinilsa Ramos

2012-12-01

The influence of variables at different levels of organization and the effect of time on the occurrence of firearm-related homicides (FRH) in Argentina between 1991 and 2006 was analyzed using multilevel analysis. A three-level Poisson regression model was used. The first level corresponded to the distribution of the number of FRH by sex and age group for each administrative region and (four-year) period; the second corresponded to the variation over time in the interior of each administrative region; the third modeled the variation between administrative regions in accordance with the Level of Urbanization, Percentage of Homes with Unsatisfied Basic Needs and the Percentage of Working Adults. There were 15,067 FRH in persons aged 14 and over between 1991 and 2006 in the 493 administrative regions. The risk of death was higher in males and persons of 15 to 29 years of age; ages above that were associated with a lower risk. The influence of age was greater in central-urban zones and between 1999 and 2002 than during other periods. The level of urbanization was the socioeconomic variable most strongly associated with FRH risk. The risk of death from FRH was 1.6 times higher in central-urban zones compared with non-central zones. In both zones, the risk was highest between 1999 and 2002.

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

PubMed

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

2017-03-30

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

Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008–2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion

PubMed Central

Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

2016-01-01

Background Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. Methods The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008–2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. Results The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse “V” shape and “V” shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. Conclusion We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across provinces. Future research should explore the risk factors that cause spatial correlated structure or high variation of HFMD incidence which can be explained by temperature. When analyzing association between HFMD incidence and climatic variables, spatial heterogeneity among provinces should be evaluated. Moreover, the extra-Poisson multilevel model was capable of modeling the association between overdispersion of HFMD incidence and climatic variables. PMID:26808311

Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008-2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion.

PubMed

Liao, Jiaqiang; Yu, Shicheng; Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

2016-01-01

Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008-2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse "V" shape and "V" shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across provinces. Future research should explore the risk factors that cause spatial correlated structure or high variation of HFMD incidence which can be explained by temperature. When analyzing association between HFMD incidence and climatic variables, spatial heterogeneity among provinces should be evaluated. Moreover, the extra-Poisson multilevel model was capable of modeling the association between overdispersion of HFMD incidence and climatic variables.

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

Achieving recommended daily physical activity levels through commuting by public transportation: unpacking individual and contextual influences.

PubMed

Wasfi, Rania A; Ross, Nancy A; El-Geneidy, Ahmed M

2013-09-01

This paper estimates the amount of daily walking associated with using public transportation in a large metropolitan area and examines individual and contextual characteristics associated with walking distances. Total walking distance to and from transit was calculated from a travel diary survey for 6913 individuals. Multilevel regression modelling was used to examine the underlying factors associated with walking to public transportation. The physical activity benefits of public transportation varied along gender and socio-economic lines. Recommended minutes of daily physical activity can be achieved for public transportation users, especially train users living in affluent suburbs. Copyright © 2013 Elsevier Ltd. All rights reserved.

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…

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

PubMed

Jesmin, Syeda S; Cready, Cynthia M

2016-02-01

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

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.

Associations between macrolevel economic factors and weight distributions in low- and middle-income countries: a multilevel analysis of 200,000 adults in 40 countries.

PubMed

Nandi, Arijit; Sweet, Elizabeth; Kawachi, Ichiro; Heymann, Jody; Galea, Sandro

2014-02-01

We examined associations between macrolevel economic factors hypothesized to drive changes in distributions of weight and body mass index (BMI) in a representative sample of 200,796 men and women from 40 low- and middle-income countries. We used meta-regressions to describe ecological associations between macrolevel factors and mean BMIs across countries. Multilevel regression was used to assess the relation between macrolevel economic characteristics and individual odds of underweight and overweight relative to normal weight. In multilevel analyses adjusting for individual-level characteristics, a 1-standard-deviation increase in trade liberalization was associated with 13% (95% confidence interval [CI] = 0.76, 0.99), 17% (95% CI = 0.71, 0.96), 13% (95% CI = 0.76, 1.00), and 14% (95% CI = 0.75, 0.99) lower odds of underweight relative to normal weight among rural men, rural women, urban men, and urban women, respectively. Economic development was consistently associated with higher odds of overweight relative to normal weight. Among rural men, a 1-standard-deviation increase in foreign direct investment was associated with 17% (95% CI = 1.02, 1.35) higher odds of overweight relative to normal weight. Macrolevel economic factors may be implicated in global shifts in epidemiological patterns of weight.

Associations Between Macrolevel Economic Factors and Weight Distributions in Low- and Middle-Income Countries: A Multilevel Analysis of 200 000 Adults in 40 Countries

PubMed Central

Sweet, Elizabeth; Kawachi, Ichiro; Heymann, Jody; Galea, Sandro

2014-01-01

Objectives. We examined associations between macrolevel economic factors hypothesized to drive changes in distributions of weight and body mass index (BMI) in a representative sample of 200 796 men and women from 40 low- and middle-income countries. Methods. We used meta-regressions to describe ecological associations between macrolevel factors and mean BMIs across countries. Multilevel regression was used to assess the relation between macrolevel economic characteristics and individual odds of underweight and overweight relative to normal weight. Results. In multilevel analyses adjusting for individual-level characteristics, a 1–standard-deviation increase in trade liberalization was associated with 13% (95% confidence interval [CI] = 0.76, 0.99), 17% (95% CI = 0.71, 0.96), 13% (95% CI = 0.76, 1.00), and 14% (95% CI = 0.75, 0.99) lower odds of underweight relative to normal weight among rural men, rural women, urban men, and urban women, respectively. Economic development was consistently associated with higher odds of overweight relative to normal weight. Among rural men, a 1–standard-deviation increase in foreign direct investment was associated with 17% (95% CI = 1.02, 1.35) higher odds of overweight relative to normal weight. Conclusions. Macrolevel economic factors may be implicated in global shifts in epidemiological patterns of weight. PMID:24228649

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

ERIC Educational Resources Information Center

Ryu, Ehri; West, Stephen G.

2009-01-01

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2018-04-01

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

An ensemble Kalman filter for statistical estimation of physics constrained nonlinear regression models

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

Harlim, John, E-mail: jharlim@psu.edu; Mahdi, Adam, E-mail: amahdi@ncsu.edu; Majda, Andrew J., E-mail: jonjon@cims.nyu.edu

2014-01-15

A central issue in contemporary science is the development of nonlinear data driven statistical–dynamical models for time series of noisy partial observations from nature or a complex model. It has been established recently that ad-hoc quadratic multi-level regression models can have finite-time blow-up of statistical solutions and/or pathological behavior of their invariant measure. Recently, a new class of physics constrained nonlinear regression models were developed to ameliorate this pathological behavior. Here a new finite ensemble Kalman filtering algorithm is developed for estimating the state, the linear and nonlinear model coefficients, the model and the observation noise covariances from available partialmore » noisy observations of the state. Several stringent tests and applications of the method are developed here. In the most complex application, the perfect model has 57 degrees of freedom involving a zonal (east–west) jet, two topographic Rossby waves, and 54 nonlinearly interacting Rossby waves; the perfect model has significant non-Gaussian statistics in the zonal jet with blocked and unblocked regimes and a non-Gaussian skewed distribution due to interaction with the other 56 modes. We only observe the zonal jet contaminated by noise and apply the ensemble filter algorithm for estimation. Numerically, we find that a three dimensional nonlinear stochastic model with one level of memory mimics the statistical effect of the other 56 modes on the zonal jet in an accurate fashion, including the skew non-Gaussian distribution and autocorrelation decay. On the other hand, a similar stochastic model with zero memory levels fails to capture the crucial non-Gaussian behavior of the zonal jet from the perfect 57-mode model.« less

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

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

PubMed

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

2017-05-01

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

Bayesian Correction for Misclassification in Multilevel Count Data Models.

PubMed

Nelson, Tyler; Song, Joon Jin; Chin, Yoo-Mi; Stamey, James D

2018-01-01

Covariate misclassification is well known to yield biased estimates in single level regression models. The impact on hierarchical count models has been less studied. A fully Bayesian approach to modeling both the misclassified covariate and the hierarchical response is proposed. Models with a single diagnostic test and with multiple diagnostic tests are considered. Simulation studies show the ability of the proposed model to appropriately account for the misclassification by reducing bias and improving performance of interval estimators. A real data example further demonstrated the consequences of ignoring the misclassification. Ignoring misclassification yielded a model that indicated there was a significant, positive impact on the number of children of females who observed spousal abuse between their parents. When the misclassification was accounted for, the relationship switched to negative, but not significant. Ignoring misclassification in standard linear and generalized linear models is well known to lead to biased results. We provide an approach to extend misclassification modeling to the important area of hierarchical generalized linear models.

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).

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.

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

PubMed

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

2015-12-07

Despite the growing body of research on quality and safety in healthcare, there is little evidence of the association between the way hospitals are organised for quality and patient factors, limiting our understanding of how to effect large-scale change. The 'Deepening our Understanding of Quality in Australia' (DUQuA) study aims to measure and examine relationships between (1) organisation and department-level quality management systems (QMS), clinician leadership and culture, and (2) clinical treatment processes, clinical outcomes and patient-reported perceptions of care within Australian hospitals. The DUQuA project is a national, multilevel, cross-sectional study with data collection at organisation (hospital), department, professional and patient levels. Sample size calculations indicate a minimum of 43 hospitals are required to adequately power the study. To allow for rejection and attrition, 70 hospitals across all Australian jurisdictions that meet the inclusion criteria will be invited to participate. Participants will consist of hospital quality management professionals; clinicians; and patients with stroke, acute myocardial infarction and hip fracture. Organisation and department-level QMS, clinician leadership and culture, patient perceptions of safety, clinical treatment processes, and patient outcomes will be assessed using validated, evidence-based or consensus-based measurement tools. Data analysis will consist of simple correlations, linear and logistic regression and multilevel modelling. Multilevel modelling methods will enable identification of the amount of variation in outcomes attributed to the hospital and department levels, and the factors contributing to this variation. Ethical approval has been obtained. Results will be disseminated to individual hospitals in de-identified national and international benchmarking reports with data-driven recommendations. This ground-breaking national study has the potential to influence decision-making on the implementation of quality and safety systems and processes in Australian and international hospitals. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

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. ...

Can we get some cooperation around here? The mediating role of group norms on the relationship between team personality and individual helping behaviors.

PubMed

Gonzalez-Mulé, Erik; DeGeest, David S; McCormick, Brian W; Seong, Jee Young; Brown, Kenneth G

2014-09-01

Drawing on the group-norms theory of organizational citizenship behaviors and person-environment fit theory, we introduce and test a multilevel model of the effects of additive and dispersion composition models of team members' personality characteristics on group norms and individual helping behaviors. Our model was tested using regression and random coefficients modeling on 102 research and development teams. Results indicated that high mean levels of extraversion are positively related to individual helping behaviors through the mediating effect of cooperative group norms. Further, low variance on agreeableness (supplementary fit) and high variance on extraversion (complementary fit) promote the enactment of individual helping behaviors, but only the effects of extraversion were mediated by cooperative group norms. Implications of these findings for theories of helping behaviors in teams are discussed. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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

Integrative eQTL analysis of tumor and host omics data in individuals with bladder cancer.

PubMed

Pineda, Silvia; Van Steen, Kristel; Malats, Núria

2017-09-01

Integrative analyses of several omics data are emerging. The data are usually generated from the same source material (i.e., tumor sample) representing one level of regulation. However, integrating different regulatory levels (i.e., blood) with those from tumor may also reveal important knowledge about the human genetic architecture. To model this multilevel structure, an integrative-expression quantitative trait loci (eQTL) analysis applying two-stage regression (2SR) was proposed. This approach first regressed tumor gene expression levels with tumor markers and the adjusted residuals from the previous model were then regressed with the germline genotypes measured in blood. Previously, we demonstrated that penalized regression methods in combination with a permutation-based MaxT method (Global-LASSO) is a promising tool to fix some of the challenges that high-throughput omics data analysis imposes. Here, we assessed whether Global-LASSO can also be applied when tumor and blood omics data are integrated. We further compared our strategy with two 2SR-approaches, one using multiple linear regression (2SR-MLR) and other using LASSO (2SR-LASSO). We applied the three models to integrate genomic, epigenomic, and transcriptomic data from tumor tissue with blood germline genotypes from 181 individuals with bladder cancer included in the TCGA Consortium. Global-LASSO provided a larger list of eQTLs than the 2SR methods, identified a previously reported eQTLs in prostate stem cell antigen (PSCA), and provided further clues on the complexity of APBEC3B loci, with a minimal false-positive rate not achieved by 2SR-MLR. It also represents an important contribution for omics integrative analysis because it is easy to apply and adaptable to any type of data. © 2017 WILEY PERIODICALS, INC.

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…

On the application of multilevel modeling in environmental and ecological studies

USGS Publications Warehouse

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

2010-01-01

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

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

ERIC Educational Resources Information Center

Sridharan, Bhavani; Leitch, Shona; Watty, Kim

2015-01-01

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

Examining Elementary Social Studies Marginalization: A Multilevel Model

ERIC Educational Resources Information Center

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

2014-01-01

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

Handling Correlations between Covariates and Random Slopes in Multilevel Models

ERIC Educational Resources Information Center

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

2014-01-01

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

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

PubMed

Cho, Sun-Joo; Goodwin, Amanda P

2016-04-01

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

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.

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,…

Administrative Climate and Novices' Intent to Remain Teaching

ERIC Educational Resources Information Center

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

2012-01-01

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

Foreign-Born Concentration and Acculturation to Volunteering among Immigrant Youth

ERIC Educational Resources Information Center

Tong, Yuying

2010-01-01

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

Collegial Climate and Novice Teachers' Intent to Remain Teaching

ERIC Educational Resources Information Center

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

2013-01-01

Using survey data from novice teachers across 99 schools, we estimated multilevel regressions to identify the association between novices' intent to remain teaching within their schools and their perceptions of the collegial climate. The results suggest that novice teachers who perceive a more positive collegial climate marked by higher degrees…

Optimal Design for Regression Discontinuity Studies with Clustering

ERIC Educational Resources Information Center

Rhoads, Christopher; Dye, Charles

2014-01-01

Recent years have seen an increased interest in quantitative educational research studies that use random assignment (RA) to evaluate the causal impacts of educational interventions (Angrist, 2004). The multi-level structure of the public education system in the United States often leads to experimental designs where naturally occurring clusters…

Optimal Design for Two-Level Random Assignment and Regression Discontinuity Studies

ERIC Educational Resources Information Center

Rhoads, Christopher H.; Dye, Charles

2016-01-01

An important concern when planning research studies is to obtain maximum precision of an estimate of a treatment effect given a budget constraint. When research designs have a "multilevel" or "hierarchical" structure changes in sample size at different levels of the design will impact precision differently. Furthermore, there…

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…

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

PubMed Central

2013-01-01

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

Cancer patients use hospital-based care until death: a further analysis of the Dutch Bone Metastasis Study.

PubMed

Meeuse, Jan J; van der Linden, Yvette M; Post, Wendy J; Wanders, Rinus; Gans, Rijk O B; Leer, Jan Willem H; Reyners, Anna K L

2011-10-01

To describe health care utilization (HCU) at the end of life in cancer patients. These data are relevant to plan palliative care services, and to develop training programs for involved health care professionals. The Dutch Bone Metastasis Study (DBMS) was a nationwide study proving equal effectiveness of single fraction palliative radiotherapy compared with multiple fractions for painful bone metastases in 1157 patients. The 860 (74%) patients who died during follow-up were included in the current analysis. The main outcome was the frequency of hospital-based (outpatient contact or admission) and/or general practitioner (GP) contact during the last 12 weeks of life. Changes in HCU towards death were related to data on quality of life and pain intensity using a multilevel regression model. Hospital-based HCU was reported in 1801 (63%) returned questionnaires, whereas GP contact was stated in 1246 (43%). In 573 (20%) questionnaires, both types of HCU were reported. In multilevel regression analyses, the frequency of outpatient contacts remained constant during the weeks towards death, whereas the frequency of GP contacts increased. Lower valuation of quality of life was related to both GP- and hospital-based HCU. There was a high consumption of hospital-based HCU in the last 12 weeks of life of cancer patients with bone metastases. Hospital-based HCU did not decrease during the weeks towards death, despite an increase in GP contacts. Future planning of palliative care and training programs should encompass close collaboration between medical specialists and GPs to optimize end-of-life care.

Passive Suicide Ideation Among Older Adults in Europe: A Multilevel Regression Analysis of Individual and Societal Determinants in 12 Countries (SHARE).

PubMed

Stolz, Erwin; Fux, Beat; Mayerl, Hannes; Rásky, Éva; Freidl, Wolfgang

2016-09-01

Passive suicide ideation (PSI) is common among older adults, but prevalences have been reported to vary considerably across European countries. The goal of this study was to assess the role of individual-level risk factors and societal contextual factors associated with PSI in old age. We analyzed longitudinal data from the Survey of Health, Ageing, and Retirement in Europe (SHARE) on 6,791 community-dwelling respondents (75+) from 12 countries. Bayesian logistic multilevel regression models were used to assess variance components, individual-level and country-level risk factors. About 4% of the total variance of PSI was located at the country level, a third of which was attributable to compositional effects of individual-level predictors. Predictors for the development of PSI at the individual level were female gender, depression, older age, poor health, smaller social network size, loneliness, nonreligiosity, and low perceived control (R (2) = 25.8%). At the country level, cultural acceptance of suicide, religiosity, and intergenerational cohabitation were associated with the rates of PSI. Cross-national variation in old-age PSI is mostly attributable to individual-level determinants and compositional differences, but there is also evidence for contextual effects of country-level characteristics. Suicide prevention programs should be intensified in high-risk countries and attitudes toward suicide should be addressed in information campaigns. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Self-reported illness and household strategies for coping with health-care payments in Bangladesh

PubMed Central

Gilmour, Stuart; Saito, Eiko; Sultana, Papia; Shibuya, Kenji

2013-01-01

Abstract Objective To investigate self-reported illness and household strategies for coping with payments for health care in a city in Bangladesh. Methods A cluster-sampled probability survey of 1593 households in the city of Rajshahi, Bangladesh, was conducted in 2011. Multilevel logistic regression – with adjustment for any clustering within households – was used to examine the risk of self-reported illness in the previous 30 days. A multilevel Poisson regression model, with adjustment for clustering within households and individuals, was used to explore factors potentially associated with the risk of health-care-related “distress” financing (e.g. paying for health care by borrowing, selling, reducing food expenditure, removing children from school or performing additional paid work). Findings According to the interviewees, about 45% of the surveyed individuals had suffered at least one episode of illness in the previous 30 days. The most frequently reported illnesses among children younger than 5 years and adults were common tropical infections and noncommunicable diseases, respectively. The risks of self-reported illness in the previous 30 days were relatively high for adults older than 44 years, women and members of households in the poorest quintile. Distress financing, which had been implemented to cover health-care payments associated with 13% of the reported episodes, was significantly associated with heart and liver disease, asthma, typhoid, inpatient care, the use of public outpatient facilities, and poverty at the household level. Conclusion Despite the subsidization of public health services in Bangladesh, high prevalences of distress financing – and illness – were detected in the surveyed, urban households. PMID:24052682

Quantitative analysis of organizational culture in occupational health research: a theory-based validation in 30 workplaces of the organizational culture profile instrument.

PubMed

Marchand, Alain; Haines, Victor Y; Dextras-Gauthier, Julie

2013-05-04

This study advances a measurement approach for the study of organizational culture in population-based occupational health research, and tests how different organizational culture types are associated with psychological distress, depression, emotional exhaustion, and well-being. Data were collected over a sample of 1,164 employees nested in 30 workplaces. Employees completed the 26-item OCP instrument. Psychological distress was measured with the General Health Questionnaire (12-item); depression with the Beck Depression Inventory (21-item); and emotional exhaustion with five items from the Maslach Burnout Inventory general survey. Exploratory factor analysis evaluated the dimensionality of the OCP scale. Multilevel regression models estimated workplace-level variations, and the contribution of organizational culture factors to mental health and well-being after controlling for gender, age, and living with a partner. Exploratory factor analysis of OCP items revealed four factors explaining about 75% of the variance, and supported the structure of the Competing Values Framework. Factors were labeled Group, Hierarchical, Rational and Developmental. Cronbach's alphas were high (0.82-0.89). Multilevel regression analysis suggested that the four culture types varied significantly between workplaces, and correlated with mental health and well-being outcomes. The Group culture type best distinguished between workplaces and had the strongest associations with the outcomes. This study provides strong support for the use of the OCP scale for measuring organizational culture in population-based occupational health research in a way that is consistent with the Competing Values Framework. The Group organizational culture needs to be considered as a relevant factor in occupational health studies.

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.

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

USDA-ARS?s Scientific Manuscript database

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

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

ERIC Educational Resources Information Center

Huang, Francis L.; Cornell, Dewey G.

2016-01-01

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

Cross-Classified Random Effects Models in Institutional Research

ERIC Educational Resources Information Center

Meyers, Laura E.

2012-01-01

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

Outward Bound Outcome Model Validation and Multilevel Modeling

ERIC Educational Resources Information Center

Luo, Yuan-Chun

2011-01-01

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

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

ERIC Educational Resources Information Center

Sulis, Isabella; Toland, Michael D.

2017-01-01

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

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

ERIC Educational Resources Information Center

Lu, Xingjiang; Yao, Chen; Zheng, Jianmin

2013-01-01

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

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

ERIC Educational Resources Information Center

Zhu, Xiaoshu

2013-01-01

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

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

ERIC Educational Resources Information Center

Kennedy, Eugene; And Others

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

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…

Multilevel Correlates of Satisfaction with Neighborhood Availability of Fresh Fruits and Vegetables

PubMed Central

Zenk, Shannon N.; Schulz, Amy J.; Lachance, Laurie L.; Mentz, Graciela; Kannan, Srimathi; Ridella, William; Galea, Sandro

2009-01-01

Background Little is known about influences on perceptions of neighborhood food environments, despite their relevance for food-shopping behaviors and food choices. Purpose This study examined relationships between multilevel factors (neighborhood structure, independently observed neighborhood food environment, individual socioeconomic position) and satisfaction with neighborhood availability of fruits and vegetables. Methods The multilevel regression analysis drew on data from a community survey of urban adults, in-person audit and mapping of food stores, and the 2000 Census. Results Satisfaction with neighborhood availability of fruits and vegetables was lower in neighborhoods that were further from a supermarket and that had proportionately more African-American residents. Neighborhood poverty and independently observed neighborhood fruit and vegetable characteristics (variety, prices, quality) were not associated with satisfaction. Individual education modified relationships between neighborhood availability of smaller food stores (small grocery stores, convenience stores, liquor stores) and satisfaction. Conclusions Individual-level and neighborhood-level factors affect perceptions of neighborhood food environments. PMID:19809859

Contextual and individual determinants of periodontal disease: Multilevel analysis based on Andersen's model.

PubMed

Valente, Maria I B; Vettore, Mario V

2018-04-01

To investigate the relationship of contextual and individual factors with periodontal disease in dentate adults and older people using the Andersen's behavioural model. Secondary individual data from 6011 adults and 2369 older people from the Brazilian Oral Health Survey (2010) were combined with contextual data for 27 cities. Attachment loss (AL) categories for each sextant were coded and summed to obtain the periodontal disease measure. The association of predisposing, enabling and need characteristics at city and individual level with periodontal disease was assessed using an adapted version of the Andersen's behavioural model. Multilevel Poisson regression was used to estimate rate ratios (RR) and 95% CIs. Periodontal disease was associated with contextual predisposing (RR 0.93; 95% CI = 0.87-0.99) and enabling factors (RR 0.99; 95% CI = 0.98-0.99) in adults. Contextual predisposing was also associated with periodontal disease in older people (RR 0.82; 95% CI = 0.73-0.92). Individual predisposing (age, sex and schooling) and need characteristics (perceived treatment need) were common predictors of periodontal disease in adults and older people. Periodontal disease was also associated with behaviours in the latter age group. Contextual predisposing factors and individual characteristics influenced periodontal disease experience in adults and older people. Contextual enabling factors were also meaningful determinants of periodontal disease in the former age group. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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.

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…

Relationship Between T1 Slope and Cervical Alignment Following Multilevel Posterior Cervical Fusion Surgery: Impact of T1 Slope Minus Cervical Lordosis.

PubMed

Hyun, Seung-Jae; Kim, Ki-Jeong; Jahng, Tae-Ahn; Kim, Hyun-Jib

2016-04-01

Retrospective study. To assess the relationship between sagittal alignment of the cervical spine and patient-reported health-related quality-of-life scores following multilevel posterior cervical fusion, and to explore whether an analogous relationship exists in the cervical spine using T1 slope minus C2-C7 lordosis (T1S-CL). A recent study demonstrated that, similar to the thoracolumbar spine, the severity of disability increases with sagittal malalignment following cervical reconstruction surgery. From 2007 to 2013, 38 consecutive patients underwent multilevel posterior cervical fusion for cervical stenosis, myelopathy, and deformities. Radiographic measurements included C0-C2 lordosis, C2-C7 lordosis, C2-C7 sagittal vertical axis (SVA), T1 slope, and T1S-CL. Pearson correlation coefficients were calculated between pairs of radiographic measures and health-related quality-of-life. C2-C7 SVA positively correlated with neck disability index (NDI) scores (r = 0.495). C2-C7 lordosis (P = 0.001) and T1S-CL (P = 0.002) changes correlated with NDI score changes after surgery. For significant correlations between C2-C7 SVA and NDI scores, regression models predicted a threshold C2-C7 SVA value of 50 mm, beyond which correlations were most significant. The T1S-CL also correlated positively with C2-C7 SVA and NDI scores (r = 0.871 and r = 0.470, respectively). Results of the regression analysis indicated that a C2-C7 SVA value of 50 mm corresponded to a T1S-CL value of 26.1°. This study showed that disability of the neck increased with cervical sagittal malalignment following surgical reconstruction and a greater T1S-CL mismatch was associated with a greater degree of cervical malalignment. Specifically, a mismatch greater than 26.1° corresponded to positive cervical sagittal malalignment, defined as C2-C7 SVA greater than 50 mm. 3.

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…

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

PubMed

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

2017-01-01

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

Acceptability of Partner Violence in 51 Societies: The Role of Sexism and Attitudes Toward Violence in Social Relationships.

PubMed

Herrero, Juan; Rodríguez, Francisco J; Torres, Andrea

2016-04-27

Sexist attitudes have been claimed to play an important role in acceptability of intimate partner violence (IPV). Empirical evidence suggests that sexist individuals are also more accepting of violence in social relationships than non-sexist individuals. Results from multilevel regression models of data from 72,730 respondents of 51 countries around the world showed that (a) both sexism and acceptability of general violence in social relationships were positively related to acceptability of IPV and (b) the highest levels of acceptability of IPV were found among those sexist individuals who also present positive attitudes toward the use of violence in social relationships. © The Author(s) 2016.

Inequitable childhood immunization uptake in Nigeria: a multilevel analysis of individual and contextual determinants

PubMed Central

2009-01-01

Background Immunization coverage in many parts of Nigeria is far from optimal, and far from equitable. Nigeria accounts for half of the deaths from Measles in Africa, the highest prevalence of circulating wild poliovirus in the world, and the country is among the ten countries in the world with vaccine coverage below 50 percent. Studies focusing on community-level determinants therefore have serious policy implications Methods Multilevel multivariable regression analysis was used on a nationally-representative sample of women aged 15-49 years from the 2003 Nigeria Demographic and Health Survey. Multilevel regression analysis was performed with children (level 1) nested within mothers (level 2), who were in turn nested within communities (level 3). Results Results show that the pattern of full immunization clusters within families and communities, and that socio-economic characteristics are important in explaining the differentials in full immunization among the children in the study. At the individual level, ethnicity, mothers' occupation, and mothers' household wealth were characteristics of the mothers associated with full immunization of the children. At the community level, the proportion of mothers that had hospital delivery was a determinant of full immunization status. Conclusion Significant community-level variation remaining after having controlled for child- and mother-level characteristics is indicative of a need for further research on community-levels factors, which would enable extensive tailoring of community-level interventions aimed at improving full immunization and other child health outcomes. PMID:19930573

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

PubMed

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

2012-11-01

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

Immigrant Integration policies and perceived Group Threat: A Multilevel Study of 27 Western and Eastern European Countries.

PubMed

Schlueter, Elmar; Meuleman, Bart; Davidov, Eldad

2013-05-01

Although immigrant integration policies have long been hypothesized to be associated with majority members' anti-immigrant sentiments, systematic empirical research exploring this relationship is largely absent. To address this gap in the literature, the present research takes a cross-national perspective. Drawing from theory and research on group conflict and intergroup norms, we conduct two studies to examine whether preexisting integration policies that are more permissive promote or impede majority group members' subsequent negative attitudes regarding immigrants. For several Western and Eastern European countries, we link country-level information on immigrant integration policies from 2006 with individual-level survey data from the Eurobarometer 71.3 collected in 2009 (Study 1) and from the fourth wave of the European Value Study collected between 2008 and 2009 (Study 2). For both studies, the results from multilevel regression models demonstrate that immigrant integration policies that are more permissive are associated with decreased perceptions of group threat from immigrants. These findings suggest that immigrant integration policies are of key importance in improving majority members' attitudes regarding immigrants, which is widely considered desirable in modern immigrant-receiving societies. Copyright © 2012 Elsevier Inc. All rights reserved.

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

PubMed

Lindström, Martin; Moghaddassi, Mahnaz; Merlo, Juan

2006-01-01

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

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

PubMed

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

2013-09-01

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

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.

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.

Collective-efficacy as a mediator of the relationship of leaders' personality traits and team performance: A cross-level analysis.

PubMed

Li, Xiaoshan; Zhou, Mingjie; Zhao, Na; Zhang, Shanshan; Zhang, Jianxin

2015-06-01

The relationship between a leader's personality and his team's performance has been established in organisational research, but the underlying process and mechanism responsible for this effect have not been fully explored. Both the traditional multiple linear regression and the multilevel structural equation model approaches were used in this study to test a proposed mediating model of subordinates' perception of collective efficacy between leader personality and team performance. The results show that the team leader's extraversion and conscientiousness personality traits were related positively to both the team-average (individual) perception of collective efficacy and team performance, and the collective efficacy mediated the relationship of the leader's personality traits and team performance. This study also discusses how Chinese cultural elements play a role in such a mediating model. © 2014 International Union of Psychological Science.

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

The influence of compositional and contextual factors on non-receipt of basic vaccines among children of 12-23-month old in India: a multilevel analysis.

PubMed

Sissoko, Daouda; Trottier, Helen; Malvy, Denis; Johri, Mira

2014-01-01

Children unreached by vaccination are at higher risk of poor health outcomes and India accounts for nearly a quarter of unvaccinated children worldwide. The objective of this study was to investigate compositional and contextual determinants of non-receipt of childhood vaccines in India using multilevel modelling. We studied characteristics of unvaccinated children using the District Level Health and Facility Survey 3, a nationally representative probability sample containing 65 617 children aged 12-23 months from 34 Indian states and territories. We developed four-level Bayesian binomial regression models to examine the determinants of non-vaccination. The analysis considered two outcomes: completely unvaccinated (CUV) children who had not received any of the eight vaccine doses recommended by India's Universal Immunization Programme, and children who had not received any dose from routine immunisation services (no RI). The no RI category includes CUV children and those who received only polio doses administered via mass campaigns. Overall, 4.83% (95% CI: 4.62-5.06) of children were CUV while 12.01% (11.68-12.35) had received no RI. Individual compositional factors strongly associated with CUV were: non-receipt of tetanus immunisation for mothers during pregnancy (OR = 3.65 [95% CrI: 3.30-4.02]), poorest household wealth index (OR = 2.44 [1.81-3.22] no maternal schooling (OR = 2.43 [1.41-4.05]) and no paternal schooling (OR = 1.83 [1.30-2.48]). In rural settings, the influence of maternal illiteracy disappeared whereas the role of household wealth index was reinforced. Factors associated with no RI were similar to those for CUV, but effect sizes for individual compositional factors were generally larger. Low maternal education was the strongest risk factor associated with no RI in all models. All multilevel models found significant variability at community, district, and state levels net of compositional factors. Non-vaccination in India is strongly related to compositional characteristics and is geographically distinct. Tailored strategies are required to overcome current barriers to immunisation.

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…

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.

Multilevel lumbar fusion and postoperative physiotherapy rehabilitation in a patient with persistent pain.

PubMed

Pons, Tracey; Shipton, Edward A

2011-04-01

There are no comparative randomised controlled trials of physiotherapy modalities for chronic low back and radicular pain associated with multilevel fusion. Physiotherapy-based rehabilitation to control pain and improve activation levels for persistent pain following multilevel fusion can be challenging. This is a case report of a 68-year-old man who was referred for physiotherapy intervention 10 months after a multilevel spinal fusion for spinal stenosis. He reported high levels of persistent postoperative pain with minimal activity as a consequence of his pain following the surgery. The physiotherapy interventions consisted of three phases of rehabilitation starting with pool exercise that progressed to land-based walking. These were all combined with transcutaneous electrical nerve stimulation (TENS) that was used consistently for up to 8 hours per day. As outcome measures, daily pain levels and walking distances were charted once the pool programme was completed (in the third phase). Phase progression was determined by shuttle test results. The pain level was correlated with the distance walked using linear regression over a 5-day average. Over a 5-day moving average, the pain level reduced and walking distance increased. The chart of recorded pain level and walking distance showed a trend toward decreased pain with the increased distance walked. In a patient undergoing multilevel lumbar fusion, the combined use of TENS and a progressive walking programme (from pool to land) reduced pain and increased walking distance. This improvement was despite poor medication compliance and a reported high level of postsurgical pain.

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

PubMed

Roberts, Sarah C M

2012-07-01

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

Patient satisfaction with ambulatory care in Germany: effects of patient- and medical practice-related factors.

PubMed

Auras, Silke; Ostermann, Thomas; de Cruppé, Werner; Bitzer, Eva-Maria; Diel, Franziska; Geraedts, Max

2016-12-01

The study aimed to illustrate the effect of the patients' sex, age, self-rated health and medical practice specialization on patient satisfaction. Secondary analysis of patient survey data using multilevel analysis (generalized linear mixed model, medical practice as random effect) using a sequential modelling strategy. We examined the effects of the patients' sex, age, self-rated health and medical practice specialization on four patient satisfaction dimensions: medical practice organization, information, interaction, professional competence. The study was performed in 92 German medical practices providing ambulatory care in general medicine, internal medicine or gynaecology. In total, 9888 adult patients participated in a patient survey using the validated 'questionnaire on satisfaction with ambulatory care-quality from the patient perspective [ZAP]'. We calculated four models for each satisfaction dimension, revealing regression coefficients with 95% confidence intervals (CIs) for all independent variables, and using Wald Chi-Square statistic for each modelling step (model validity) and LR-Tests to compare the models of each step with the previous model. The patients' sex and age had a weak effect (maximum regression coefficient 1.09, CI 0.39; 1.80), and the patients' self-rated health had the strongest positive effect (maximum regression coefficient 7.66, CI 6.69; 8.63) on satisfaction ratings. The effect of medical practice specialization was heterogeneous. All factors studied, specifically the patients' self-rated health, affected patient satisfaction. Adjustment should always be considered because it improves the comparability of patient satisfaction in medical practices with atypically varying patient populations and increases the acceptance of comparisons. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

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…

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…

Individual and contextual socioeconomic determinants of knowledge of the ABC approach of preventing the sexual transmission of HIV in Nigeria: a multilevel analysis.

PubMed

Uthman, Olalekan A; Kayode, Gbenga A; Adekanmbi, Victor T

2013-12-01

Nigeria has the highest number of people living with HIV/AIDS in the world after India and South Africa. HIV/AIDS places a considerable burden on society's resources, and its prevention is a cost-beneficial solution to address these consequences. To the best of our knowledge, there has been no multilevel study performed to date that examined the separate and independent associations of individual and community socioeconomic status (SES) with HIV prevention knowledge in Nigeria. Multilevel linear regression models were applied to the 2008 Nigeria Demographic and Health Survey on 48871 respondents (Level 1) nested within 886 communities (Level 2) from 37 districts (Level 3). Approximately one-fifth (20%) of respondents were not aware of any of the Abstinence, Being faithful and Condom use (ABC) approach of preventing the sexual transmission of HIV. However, the likelihood of being aware of the ABC approach of preventing the sexual transmission of HIV increased with older age, male gender, greater education attainment, a higher wealth index, living in an urban area and being from least socioeconomically disadvantaged communities. There were significant community and district variations in respondents' knowledge of the ABC approach of preventing the sexual transmission of HIV. The present study provides evidence that both individual- and community-level SES factors are important predictors of knowledge of the ABC approach of preventing the sexual transmission of HIV in Nigeria. The findings underscore the need to implement public health prevention strategies not only at the individual level, but also at the community level.

Places, people and mental health: a multilevel analysis of economic inactivity.

PubMed

Fone, David; Dunstan, Frank; Williams, Gareth; Lloyd, Keith; Palmer, Stephen

2007-02-01

This paper investigates multilevel associations between the common mental disorders of anxiety, depression and economic inactivity measured at the level of the individual and the UK 2001 census ward. The data set comes from the Caerphilly Health & Social Needs study, in which a representative survey of adults aged 18-74 years was carried out to collect a wide range of information which included mental health status (using the Mental Health Inventory (MHI-5) scale of the Short Form-36 health status questionnaire), and socio-economic status (including employment status, social class, household income, housing tenure and property value). Ward level economic inactivity was measured using non-means tested benefits data from the Department of Work and Pensions (DWP) on long-term Incapacity Benefit and Severe Disablement Allowance. Estimates from multilevel linear regression models of 10,653 individuals nested within 36 census wards showed that individual mental health status was significantly associated with ward-level economic inactivity, after adjusting for individual-level variables, with a moderate effect size of -0.668 (standard error=0.258). There was a significant cross-level interaction between ward-level and individual economic inactivity from permanent sickness or disability, such that the effect of permanent sickness or disability on mental health was significantly greater for people living in wards with high levels of economic inactivity. This supports the hypothesis that living in a deprived neighbourhood has the most negative health effects on poorer individuals and is further evidence for a substantive effect of the place where you live on mental health.

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…

Family and School Influences on Adolescent Smoking Behaviour

ERIC Educational Resources Information Center

Wiium, Nora; Wold, Bente

2006-01-01

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

Beyond the United States and Japan: Testing Yamagishi's Emancipation Theory of Trust across 31 Nations

ERIC Educational Resources Information Center

Gheorghiu, Mirona A.; Vignoles, Vivian L.; Smith, Peter B.

2009-01-01

We examined the relationship between Individualism/Collectivism and generalized social trust across 31 European nations participating in the European Social Survey. Using multilevel regression analyses, the current study provides the first empirical investigation of the effects of cultural norms of Individualism/Collectivism on generalized social…

Influence of Misaligned Parents' Aspirations on Long-Term Student Academic Performance

ERIC Educational Resources Information Center

de Boer, Hester; van der Werf, Margaretha P. C.

2015-01-01

This article deals with the concept of misaligned parents' aspirations, its relationship with student background characteristics, and its effects on long-term student performance. It is defined as the difference between parents' educational ambitions for their child and the child's actual capacities. Multilevel regression analyses on a sample of…

Examining Relations between Mathematics Teachers' Instructional Vision and Knowledge and Change in Practice

ERIC Educational Resources Information Center

Munter, Charles; Correnti, Richard

2017-01-01

This article provides a longitudinal examination of how changes in more than 200 middle-grades mathematics teachers' instructional practices related to their (a) mathematical knowledge for teaching (MKT) and (b) instructional vision. Results of this multilevel regression analysis suggest that MKT and instructional vision are related to instruction…

Longitudinal cognitive biomarkers predicting symptom onset in presymptomatic frontotemporal dementia.

PubMed

Jiskoot, Lize C; Panman, Jessica L; van Asseldonk, Lauren; Franzen, Sanne; Meeter, Lieke H H; Donker Kaat, Laura; van der Ende, Emma L; Dopper, Elise G P; Timman, Reinier; van Minkelen, Rick; van Swieten, John C; van den Berg, Esther; Papma, Janne M

2018-06-01

We performed 4-year follow-up neuropsychological assessment to investigate cognitive decline and the prognostic abilities from presymptomatic to symptomatic familial frontotemporal dementia (FTD). Presymptomatic MAPT (n = 15) and GRN mutation carriers (n = 31), and healthy controls (n = 39) underwent neuropsychological assessment every 2 years. Eight mutation carriers (5 MAPT, 3 GRN) became symptomatic. We investigated cognitive decline with multilevel regression modeling; the prognostic performance was assessed with ROC analyses and stepwise logistic regression. MAPT converters declined on language, attention, executive function, social cognition, and memory, and GRN converters declined on attention and executive function (p < 0.05). Cognitive decline in ScreeLing phonology (p = 0.046) and letter fluency (p = 0.046) were predictive for conversion to non-fluent variant PPA, and decline on categorical fluency (p = 0.025) for an underlying MAPT mutation. Using longitudinal neuropsychological assessment, we detected a mutation-specific pattern of cognitive decline, potentially suggesting prognostic value of neuropsychological trajectories in conversion to symptomatic FTD.

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.

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

PubMed

Emmert, Martin; Meszmer, Nina; Sander, Uwe

2016-09-19

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

Associations between homocysteine metabolism related SNPs and carotid intima-media thickness: a Chinese sib pair study.

PubMed

Sun, Kexin; Song, Jing; Liu, Kuo; Fang, Kai; Wang, Ling; Wang, Xueyin; Li, Jing; Tang, Xun; Wu, Yiqun; Qin, Xueying; Wu, Tao; Gao, Pei; Chen, Dafang; Hu, Yonghua

2017-04-01

Carotid intima-media thickness (CIMT) is a good surrogate for atherosclerosis. Hyperhomocysteinemia is an independent risk factor for cardiovascular diseases. We aim to investigate the relationships between homocysteine (Hcy) related biochemical indexes and CIMT, the associations between Hcy related SNPs and CIMT, as well as the potential gene-gene interactions. The present study recruited full siblings (186 eligible families with 424 individuals) with no history of cardiovascular events from a rural area of Beijing. We examined CIMT, intima-media thickness for common carotid artery (CCA-IMT) and carotid bifurcation, tested plasma levels for Hcy, vitamin B6 (VB6), vitamin B12 (VB12) and folic acid (FA), and genotyped 9 SNPs on MTHFR, MTR, MTRR, BHMT, SHMT1, CBS genes. Associations between SNPs and biochemical indexes and CIMT indexes were analyzed using family-based association test analysis. We used multi-level mixed-effects regression model to verify SNP-CIMT associations and to explore the potential gene-gene interactions. VB6, VB12 and FA were negatively correlated with CIMT indexes (p < 0.05). rs2851391 T allele was associated with decreased plasma VB12 levels (p = 0.036). In FABT, CBS rs2851391 was significantly associated with CCA-IMT (p = 0.021) and CIMT (p = 0.019). In multi-level mixed-effects regression model, CBS rs2851391 was positively significantly associated with CCA-IMT (Coef = 0.032, se = 0.009, raw p < 0.001) after Bonferoni correction (corrected α = 0.0056). Gene-gene interactions were found between CBS rs2851391 and BHMT rs10037045 for CCA-IMT (p = 0.011), as well as between CBS rs2851391 and MTR rs1805087 for CCA-IMT (p = 0.007) and CIMT (p = 0.022). Significant associations are found between Hcy metabolism related genetic polymorphisms, biochemical indexes and CIMT indexes. There are complex interactions between genetic polymorphisms for CCA-IMT and CIMT.

Extended opening hours and patient experience of general practice in England: multilevel regression analysis of a national patient survey

PubMed Central

Cowling, Thomas E; Harris, Matthew; Majeed, Azeem

2017-01-01

Background The UK government plans to extend the opening hours of general practices in England. The ‘extended hours access scheme’ pays practices for providing appointments outside core times (08:00 to 18.30, Monday to Friday) for at least 30 min per 1000 registered patients each week. Objective To determine the association between extended hours access scheme participation and patient experience. Methods Retrospective analysis of a national cross-sectional survey completed by questionnaire (General Practice Patient Survey 2013–2014); 903 357 survey respondents aged ≥18 years old and registered to 8005 general practices formed the study population. Outcome measures were satisfaction with opening hours, experience of making an appointment and overall experience (on five-level interval scales from 0 to 100). Mean differences between scheme participation groups were estimated using multilevel random-effects regression, propensity score matching and instrumental variable analysis. Results Most patients were very (37.2%) or fairly satisfied (42.7%) with the opening hours of their general practices; results were similar for experience of making an appointment and overall experience. Most general practices participated in the extended hours access scheme (73.9%). Mean differences in outcome measures between scheme participants and non-participants were positive but small across estimation methods (mean differences ≤1.79). For example, scheme participation was associated with a 1.25 (95% CI 0.96 to 1.55) increase in satisfaction with opening hours using multilevel regression; this association was slightly greater when patients could not take time off work to see a general practitioner (2.08, 95% CI 1.53 to 2.63). Conclusions Participation in the extended hours access scheme has a limited association with three patient experience measures. This questions expected impacts of current plans to extend opening hours on patient experience. PMID:27343274

Extended opening hours and patient experience of general practice in England: multilevel regression analysis of a national patient survey.

PubMed

Cowling, Thomas E; Harris, Matthew; Majeed, Azeem

2017-05-01

The UK government plans to extend the opening hours of general practices in England. The 'extended hours access scheme' pays practices for providing appointments outside core times (08:00 to 18.30, Monday to Friday) for at least 30 min per 1000 registered patients each week. To determine the association between extended hours access scheme participation and patient experience. Retrospective analysis of a national cross-sectional survey completed by questionnaire (General Practice Patient Survey 2013-2014); 903 357 survey respondents aged ≥18 years old and registered to 8005 general practices formed the study population. Outcome measures were satisfaction with opening hours, experience of making an appointment and overall experience (on five-level interval scales from 0 to 100). Mean differences between scheme participation groups were estimated using multilevel random-effects regression, propensity score matching and instrumental variable analysis. Most patients were very (37.2%) or fairly satisfied (42.7%) with the opening hours of their general practices; results were similar for experience of making an appointment and overall experience. Most general practices participated in the extended hours access scheme (73.9%). Mean differences in outcome measures between scheme participants and non-participants were positive but small across estimation methods (mean differences ≤1.79). For example, scheme participation was associated with a 1.25 (95% CI 0.96 to 1.55) increase in satisfaction with opening hours using multilevel regression; this association was slightly greater when patients could not take time off work to see a general practitioner (2.08, 95% CI 1.53 to 2.63). Participation in the extended hours access scheme has a limited association with three patient experience measures. This questions expected impacts of current plans to extend opening hours on patient experience. 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/.

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

PubMed

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

2014-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

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

ERIC Educational Resources Information Center

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

2017-01-01

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

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

ERIC Educational Resources Information Center

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

2002-01-01

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

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

ERIC Educational Resources Information Center

Youngs, Howard; Piggot-Irvine, Eileen

2012-01-01

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

Multivariate functional response regression, with application to fluorescence spectroscopy in a cervical pre-cancer study.

PubMed

Zhu, Hongxiao; Morris, Jeffrey S; Wei, Fengrong; Cox, Dennis D

2017-07-01

Many scientific studies measure different types of high-dimensional signals or images from the same subject, producing multivariate functional data. These functional measurements carry different types of information about the scientific process, and a joint analysis that integrates information across them may provide new insights into the underlying mechanism for the phenomenon under study. Motivated by fluorescence spectroscopy data in a cervical pre-cancer study, a multivariate functional response regression model is proposed, which treats multivariate functional observations as responses and a common set of covariates as predictors. This novel modeling framework simultaneously accounts for correlations between functional variables and potential multi-level structures in data that are induced by experimental design. The model is fitted by performing a two-stage linear transformation-a basis expansion to each functional variable followed by principal component analysis for the concatenated basis coefficients. This transformation effectively reduces the intra-and inter-function correlations and facilitates fast and convenient calculation. A fully Bayesian approach is adopted to sample the model parameters in the transformed space, and posterior inference is performed after inverse-transforming the regression coefficients back to the original data domain. The proposed approach produces functional tests that flag local regions on the functional effects, while controlling the overall experiment-wise error rate or false discovery rate. It also enables functional discriminant analysis through posterior predictive calculation. Analysis of the fluorescence spectroscopy data reveals local regions with differential expressions across the pre-cancer and normal samples. These regions may serve as biomarkers for prognosis and disease assessment.

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

PubMed

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

2012-07-01

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

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

An Airline-Based Multilevel Analysis of Airfare Elasticity for Passenger Demand

NASA Technical Reports Server (NTRS)

Castelli, Lorenzo; Ukovich, Walter; Pesenti, Raffaele

2003-01-01

Price elasticity of passenger demand for a specific airline is estimated. The main drivers affecting passenger demand for air transportation are identified. First, an Ordinary Least Squares regression analysis is performed. Then, a multilevel analysis-based methodology to investigate the pattern of variation of price elasticity of demand among the various routes of the airline under study is proposed. The experienced daily passenger demands on each fare-class are grouped for each considered route. 9 routes were studied for the months of February and May in years from 1999 to 2002, and two fare-classes were defined (business and economy). The analysis has revealed that the airfare elasticity of passenger demand significantly varies among the different routes of the airline.

Highly-Efficient and Modular Medium-Voltage Converters

DTIC Science & Technology

2015-09-28

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

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

ERIC Educational Resources Information Center

Karakolidis, Anastasios; Pitsia, Vasiliki; Emvalotis, Anastassios

2016-01-01

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

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

ERIC Educational Resources Information Center

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

2014-01-01

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

Using Multilevel Modeling in Counseling Research

ERIC Educational Resources Information Center

Lynch, Martin F.

2012-01-01

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

Multilevel Modeling: Overview and Applications to Research in Counseling Psychology

ERIC Educational Resources Information Center

Kahn, Jeffrey H.

2011-01-01

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

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

ERIC Educational Resources Information Center

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

2016-01-01

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

Multilevel Cognitive Diagnosis Models for Assessing Changes in Latent Attributes

ERIC Educational Resources Information Center

Huang, Hung-Yu

2017-01-01

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

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

ERIC Educational Resources Information Center

Goldstein, Harvey; Bonnet, Gerard; Rocher, Thierry

2007-01-01

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

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

ERIC Educational Resources Information Center

Schweig, Jonathan

2014-01-01

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

The relationship between aircraft noise exposure and day-use visitor survey responses in backcountry areas of national parks.

PubMed

Rapoza, Amanda; Sudderth, Erika; Lewis, Kristin

2015-10-01

To evaluate the relationship between aircraft noise exposure and the quality of national park visitor experience, more than 4600 visitor surveys were collected at seven backcountry sites in four U.S. national parks simultaneously with calibrated sound level measurements. Multilevel logistic regression was used to estimate parameters describing the relationship among visitor responses, aircraft noise dose metrics, and mediator variables. For the regression models, survey responses were converted to three dichotomous variables, representing visitors who did or did not experience slightly or more, moderately or more, or very or more annoyance or interference with natural quiet from aircraft noise. Models with the most predictive power included noise dose metrics of sound exposure level, percent time aircraft were audible, and percentage energy due to helicopters and fixed-wing propeller aircraft. These models also included mediator variables: visitor ratings of the "importance of calmness, peace and tranquility," visitor group composition (adults or both adults and children), first visit to the site, previously taken an air tour, and participation in bird-watching or interpretive talks. The results complement and extend previous research conducted in frontcountry areas and will inform evaluations of air tour noise effects on visitors to national parks and remote wilderness sites.

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

English Phonological Awareness in Bilinguals: A Cross-Linguistic Study of Tamil, Malay and Chinese English-Language Learners

ERIC Educational Resources Information Center

Dixon, L. Quentin; Chuang, Hui-Kai; Quiroz, Blanca

2012-01-01

To test the lexical restructuring hypothesis among bilingual English-language learners, English phonological awareness (PA), English vocabulary and ethnic language vocabulary (Mandarin Chinese, Malay or Tamil) were assessed among 284 kindergarteners (168 Chinese, 71 Malays and 45 Tamils) in Singapore. A multi-level regression analysis showed that…

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

ERIC Educational Resources Information Center

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

2010-01-01

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

Couples at Risk Following the Death of Their Child: Predictors of Grief versus Depression

ERIC Educational Resources Information Center

Wijngaards-de Meij, Leoniek; Stroebe, Margaret; Schut, Henk; Stroebe, Wolfgang; van den Bout, Jan; van der Heijden, Peter; Dijkstra, Iris

2005-01-01

This longitudinal study examined the relative impact of major variables for predicting adjustment (in terms of both grief and depression) among bereaved parents following the death of their child. Couples (N = 219) participated 6, 13, and 20 months postloss. Use of multilevel regression analyses enabled assessment of the impact of several…

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

ERIC Educational Resources Information Center

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

2007-01-01

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

Evaluating the Effect of a Television Public Service Announcement about Epilepsy

ERIC Educational Resources Information Center

Martiniuk, Alexandra L. C.; Secco, Mary; Yake, Laura; Speechley, Kathy N.

2010-01-01

Public service announcements (PSAs) are non-commercial advertisements aiming to improve knowledge, attitudes and/or behavior. No evaluations of epilepsy PSAs exist. This study sought to evaluate a televised PSA showing first aid for a seizure. A multilevel regression analysis was used to determine the effect of the PSA on epilepsy knowledge and…

Exploring Person Fit with an Approach Based on Multilevel Logistic Regression

ERIC Educational Resources Information Center

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

2015-01-01

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

The importance of contextual, relational and cognitive factors for novice nurses' emotional state and affective commitment to the profession. A multilevel study.

PubMed

Hoeve, Yvonne Ten; Brouwer, Jasperina; Roodbol, Petrie F; Kunnen, Saskia

2018-05-13

This study explored the effects of contextual, relational and cognitive factors derived from novice nurses' work experiences on emotions and affective commitment to the profession. With an increasing demand for well-trained nurses, it is imperative to investigate which work-related factors most affect their commitment to develop effective strategies to improve work conditions, work satisfaction and emotional attachment. A repeated-measures within subjects design. From September 2013 - September 2014 eighteen novice nurses described work-related experiences in unstructured diaries and scored their emotional state and affective commitment on a scale. The themes that emerged from the 18 diaries (with 580 diary entries) were quantified as contextual, relational and cognitive factors. Contextual factors refer to complexity of care and existential events; relational factors to experiences with patients, support from colleagues, supervisors and physicians; cognitive factors to nurses' perceived competence. The first multilevel regression analysis, based on the 18 diaries with 580 entries, showed that complexity of care, lack of support and lack of competence were negatively related to novice nurses' affective commitment, whereas received support was positively related. The next multilevel regression analyses showed that all contextual, relational and cognitive factors were either related to negative or positive emotions. To retain novice nurses in the profession, it is important to provide support and feedback. This enables novice nurses to deal with the complexity of care and feelings of incompetence and to develop a professional commitment. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

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...

African-American women's Upward Economic Mobility and Small for Gestational Age Births: A Population-Based Study.

PubMed

Collins, James W; Mariani, Allison; Rankin, Kristin

2018-03-01

Background The relationship between African-American women's upward economic mobility and small for gestational age (weight for gestational < 10th percentile, SGA) rates is incompletely understood. Objective To ascertain the extent to which African-American women's upward economic mobility from early-life impoverishment is coupled with reduced SGA rates. Methods Stratified and multilevel logistic regression analyses were completed on the Illinois transgenerational dataset of African-American infants (1989-1991) and their Chicago-born mothers (1956-1976) with linked U.S. census income information. Results Impoverished-born (defined as lowest quartile of neighborhood income distribution) African-American women (n = 4891) who remained impoverished by the time of delivery had a SGA rate of 19.7%. Individuals who achieved low (n = 5827), modest (n = 2254), or high (n = 732) upward economic mobility by adulthood had lower SGA rates of 17.2, 14.8, and 13.7%, respectively; RR = 0.9 (0.8-0.9), 0.8 (0.7-0.8), and 0.7 (0.6-0.8), respectively. In adjusted (controlling for traditional individual-level risk factors) multilevel regression models, there was a decreasing linear trend in SGA rates with increasing levels of upward economic mobility; the adjusted RR of SGA birth for impoverished-born African-American women who experienced low, modest, of high (compared to no) upward mobility equaled 0.95 (0.91, 0.99), 0.90 (0.83, 0.98), and 0.86 (0.75, 0.98), respectively, p < 0.05. Conclusions African-American women's upward economic mobility from early-life residence in poor urban communities is associated with lower SGA rates independent of adulthood risk status.

Suburban migration and the birth outcome of Chicago-born white and African-American women: the merit of the healthy migrant theory?

PubMed

Collins, James W; Rankin, Kristin M; Janowiak, Christine M

2013-11-01

The healthy migrant theory posits that women who migrate before pregnancy are intrinsically healthier and therefore have better birth outcomes than those who don't move. Objective. To determine whether migration to the suburbs is associated with lower rates of preterm (<37 weeks) birth among Chicago-born White and African-American mothers. We performed stratified and multilevel logistic regression analyses on an Illinois transgenerational dataset of non-Latino White and African-American infants (1989-1991) and their mothers (1956-1976) with appended US census income information. Forty percent of Chicago-born White mothers (N = 45,135) migrated to Suburban Cook County and 30 % migrated to the more geographically distant collar counties. In contrast, 10 % of Chicago-born African-American mothers (N = 41,221) migrated to Suburban Cook and only two percent migrated to the collar counties. Chicago-born White and African-American migrant mothers to Suburban Cook County had lower preterm birth rates than their non-migrant counterparts; RR = 0.8 (0.8-0.9) and 0.8 (0.7-0.8), respectively. When neighborhood income was singularly taken into account, the protective association of suburban migration and preterm birth disappeared among Chicago-born Whites. In race-specific multilevel multivariate regression models which included neighborhood income, the adjusted odds ratio of preterm birth, low birth weight, and small for gestational-age for Chicago-born White and African-American migrant (compared to non-migrant) mothers approximated unity. Neighborhood income underlies the protective association of suburban migration and birth outcome among Chicago-born White and African-American mothers. These findings do not support the healthy migrant hypothesis of reproductive outcome.

Caregiver satisfaction with paediatric HIV treatment and care in Nigeria and equity implications for children living with HIV.

PubMed

Chamla, Dick; Asadu, Chukwuemeka; Adejuyigbe, Ebun; Davies, Abiola; Ugochukwu, Ebele; Umar, Lawal; Oluwafunke, Ilesanmi; Hassan-Hanga, Fatimah; Onubogu, Chinyere; Tunde-Oremodu, Immaculata; Madubuike, Chinelo; Umeadi, Esther; Epundu, Obed; Omosun, Adenike; Anigilaje, Emmanuel; Adeyinka, Daniel

2016-03-01

Caregiver satisfaction has the potential to promote equity for children living with HIV, by influencing health-seeking behaviour. We measured dimensions of caregiver satisfaction with paediatric HIV treatment in Nigeria, and discuss its implications for equity by conducting facility-based exit interviews for caregivers of children receiving antiretroviral therapy in 20 purposively selected facilities within 5 geopolitical zones. Descriptive analysis and factor analysis were performed. Due to the hierarchical nature of the data, multilevel regression modelling was performed to investigate relationships between satisfaction factors and socio-demographic variables. Of 1550 caregivers interviewed, 63% (95% CI: 60.6-65.4) reported being very satisfied overall; however, satisfaction varied in some dimensions: only 55.6% (53.1-58.1) of caregivers could talk privately with health workers, 56.9% (54.4-59.3) reported that queues to see health workers were too long, and 89.9% (88.4-91.4) said that some health workers did not treat patients living with HIV with sufficient respect. Based on factor analysis, two underlying factors, labelled Availability and Attitude, were identified. In multilevel regression, the satisfaction with availability of services correlated with formal employment status (p < .01), whereas caregivers receiving care in private facilities were less likely satisfied with both availability (p < .01) and attitude of health workers (p < .05). State and facility levels influenced attitudes of the health workers (p < .01), but not availability of services. We conclude that high levels of overall satisfaction among caregivers masked dissatisfaction with some aspects of services. The two underlying satisfaction factors are part of access typology critical for closing equity gaps in access to HIV treatment between adults and children, and across socio-economic groups.

Caregiver satisfaction with paediatric HIV treatment and care in Nigeria and equity implications for children living with HIV

PubMed Central

Chamla, Dick; Asadu, Chukwuemeka; Adejuyigbe, Ebun; Davies, Abiola; Ugochukwu, Ebele; Umar, Lawal; Oluwafunke, Ilesanmi; Hassan-Hanga, Fatimah; Onubogu, Chinyere; Tunde-Oremodu, Immaculata; Madubuike, Chinelo; Umeadi, Esther; Epundu, Obed; Omosun, Adenike; Anigilaje, Emmanuel; Adeyinka, Daniel

2016-01-01

ABSTRACT Caregiver satisfaction has the potential to promote equity for children living with HIV, by influencing health-seeking behaviour. We measured dimensions of caregiver satisfaction with paediatric HIV treatment in Nigeria, and discuss its implications for equity by conducting facility-based exit interviews for caregivers of children receiving antiretroviral therapy in 20 purposively selected facilities within 5 geopolitical zones. Descriptive analysis and factor analysis were performed. Due to the hierarchical nature of the data, multilevel regression modelling was performed to investigate relationships between satisfaction factors and socio-demographic variables. Of 1550 caregivers interviewed, 63% (95% CI: 60.6–65.4) reported being very satisfied overall; however, satisfaction varied in some dimensions: only 55.6% (53.1–58.1) of caregivers could talk privately with health workers, 56.9% (54.4–59.3) reported that queues to see health workers were too long, and 89.9% (88.4–91.4) said that some health workers did not treat patients living with HIV with sufficient respect. Based on factor analysis, two underlying factors, labelled Availability and Attitude, were identified. In multilevel regression, the satisfaction with availability of services correlated with formal employment status (p < .01), whereas caregivers receiving care in private facilities were less likely satisfied with both availability (p < .01) and attitude of health workers (p < .05). State and facility levels influenced attitudes of the health workers (p < .01), but not availability of services. We conclude that high levels of overall satisfaction among caregivers masked dissatisfaction with some aspects of services. The two underlying satisfaction factors are part of access typology critical for closing equity gaps in access to HIV treatment between adults and children, and across socio-economic groups. PMID:27392010

Are environmental influences on physical activity distinct for urban, suburban, and rural schools? A multilevel study among secondary school students in Ontario, Canada.

PubMed

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

2013-05-01

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. Multilevel linear regression analyses were used to examine the environment- and student-level characteristics associated with time spent in PA among grades 9 to 12 students attending 76 secondary schools in Ontario, Canada, as part of the SHAPES-Ontario study. This approach was first conducted with the full data set testing for interactions between environment-level factors and school location. Then, school-location specific regression models were run separately. Statistically significant between-school variation was identified among students attending urban (σ(2) μ0  = 8959.63 [372.46]), suburban (σ(2) μ0  = 8918.75 [186.20]), and rural (σ(2) μ0  = 9403.17 [203.69]) schools, where school-level differences accounted for 4.0%, 2.0%, and 2.1% of the variability in students' time spent in PA, respectively. Students attending an urban or suburban school that provided another room for PA or was located within close proximity to a shopping mall or fast food outlet spent more time in PA. Students' time spent in PA varies by school location and some features of the school environment have a different impact on students' time spent in PA by school location. Developing a better understanding of the environment-level characteristics associated with students' time spent in PA by school location may help public health and planning experts to tailor school programs and policies to the needs of students in different locations. © 2013, American School Health Association.

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

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

Quantitative analysis of organizational culture in occupational health research: a theory-based validation in 30 workplaces of the organizational culture profile instrument

PubMed Central

2013-01-01

Background This study advances a measurement approach for the study of organizational culture in population-based occupational health research, and tests how different organizational culture types are associated with psychological distress, depression, emotional exhaustion, and well-being. Methods Data were collected over a sample of 1,164 employees nested in 30 workplaces. Employees completed the 26-item OCP instrument. Psychological distress was measured with the General Health Questionnaire (12-item); depression with the Beck Depression Inventory (21-item); and emotional exhaustion with five items from the Maslach Burnout Inventory general survey. Exploratory factor analysis evaluated the dimensionality of the OCP scale. Multilevel regression models estimated workplace-level variations, and the contribution of organizational culture factors to mental health and well-being after controlling for gender, age, and living with a partner. Results Exploratory factor analysis of OCP items revealed four factors explaining about 75% of the variance, and supported the structure of the Competing Values Framework. Factors were labeled Group, Hierarchical, Rational and Developmental. Cronbach’s alphas were high (0.82-0.89). Multilevel regression analysis suggested that the four culture types varied significantly between workplaces, and correlated with mental health and well-being outcomes. The Group culture type best distinguished between workplaces and had the strongest associations with the outcomes. Conclusions This study provides strong support for the use of the OCP scale for measuring organizational culture in population-based occupational health research in a way that is consistent with the Competing Values Framework. The Group organizational culture needs to be considered as a relevant factor in occupational health studies. PMID:23642223

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

PubMed

Ohlsson, Henrik; Merlo, Juan

2009-08-01

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

Child maltreatment and educational attainment in young adulthood: results from the Ontario Child Health Study.

PubMed

Tanaka, Masako; Georgiades, Katholiki; Boyle, Michael H; MacMillan, Harriet L

2015-01-01

There is increasing evidence for the adverse effects of child maltreatment on academic performance; however, most of these studies used selective samples and did not account for potential confounding or mediating factors. We examined the relationship between child physical abuse (PA; severe and non-severe) and sexual abuse (SA) and educational attainment (years of education, failure to graduate from high school) with a Canadian community sample. We used data from the Ontario Child Health Study (N = 1,893), a province-wide longitudinal survey. Potential confounding variables (family socio-demographic and parental capacity) and child-level characteristics were assessed in 1983, and child abuse was determined in 2000-2001 based on retrospective self-report. Results showed that PA and SA were associated with several factors indicative of social disadvantage in childhood. Multilevel regression analyses for years of education revealed a significant estimate for severe PA based on the unadjusted model (-0.60 years, 95% CI = [-0.45, -0.76]); estimates for non-severe PA (0.05 years, CI = [-0.15, 0.26]) and SA (-0.25 years, CI = [-0.09, -0.42]) were not significant. In the adjusted full model, the only association to reach significance was between severe PA and reduced years of education (-0.31 years, CI = [-0.18, -0.44]). Multilevel regression analyses for failure to graduate from high school showed significant unadjusted estimates for severe PA (OR = 1.77, 95% CI = [1.21, 2.58]) and non-severe PA (OR = 1.61, CI = [1.01, 2.57]); SA was not associated with this outcome (OR = 1.40, CI = [0.94, 2.07]). In the adjusted full models, there were no significant associations between child abuse variables and failure to graduate. The magnitude of effect of PA on both outcomes was reduced largely by child individual characteristics. These findings generally support earlier research, indicating the adverse effects of child maltreatment on educational attainment. Of particular note, severe PA was associated with reduced years of education after accounting for a comprehensive set of potential confounding variables and child characteristics. © The Author(s) 2014.

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

PubMed Central

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

2014-01-01

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

Exercise Effects for Children With Autism Spectrum Disorder: Metabolic Health, Autistic Traits, and Quality of Life.

PubMed

Toscano, Chrystiane V A; Carvalho, Humberto M; Ferreira, José P

2018-02-01

This study examined the effects of a 48-week exercise-based intervention on the metabolic profile, autism traits, and perceived quality of life in children with autism spectrum disorder (ASD). We randomly allocated 64 children with ASD (aged 6-12 years) to experimental ( n = 46) and control groups ( n = 18) and used multilevel regression modeling to examine responses to receiving or not receiving the intervention. The experimental group showed beneficial effects on metabolic indicators (high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and total cholesterol), autism traits, and parent-perceived quality of life. Our results provide support for exercise and physical activity, including basic coordination and strength exercises, as important therapeutic interventions for children with ASD.

Influence of health providers on pediatrics' immunization rate.

PubMed

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

2012-12-01

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

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2016-11-01

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

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.

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

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.

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…

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…

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

PubMed Central

Roberts, Sarah C.M.

2014-01-01

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

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.

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

Social cohesion matters in health.

PubMed

Chuang, Ying-Chih; Chuang, Kun-Yang; Yang, Tzu-Hsuan

2013-10-28

The concept of social cohesion has invoked debate due to the vagueness of its definition and the limitations of current measurements. This paper attempts to examine the concept of social cohesion, develop measurements, and investigate the relationship between social cohesion and individual health. This study used a multilevel study design. The individual-level samples from 29 high-income countries were obtained from the 2000 World Value Survey (WVS) and the 2002 European Value Survey. National-level social cohesion statistics were obtained from Organization of Economic Cooperation and Development datasets, World Development Indicators, and Asian Development Bank key indicators for the year 2000, and from aggregating responses from the WVS. In total 47,923 individuals were included in this study. The factor analysis was applied to identify dimensions of social cohesion, which were used as entities in the cluster analysis to generate a regime typology of social cohesion. Then, multilevel regression models were applied to assess the influences of social cohesion on an individual's self-rated health. Factor analysis identified five dimensions of social cohesion: social equality, social inclusion, social development, social capital, and social diversity. Then, the cluster analysis revealed five regimes of social cohesion. A multi-level analysis showed that respondents in countries with higher social inclusion, social capital, and social diversity were more likely to report good health above and beyond individual-level characteristics. This study is an innovative effort to incorporate different aspects of social cohesion. This study suggests that social cohesion was associated with individual self-rated after controlling individual characteristics. To achieve further advancement in population health, developed countries should consider policies that would foster a society with a high level of social inclusion, social capital, and social diversity. Future research could focus on identifying possible pathways by which social cohesion influences various health outcomes.

No effect of unemployment on intimate partner-related femicide during the financial crisis: a longitudinal ecological study in Spain.

PubMed

Torrubiano-Domínguez, J; Vives-Cases, C; San-Sebastián, M; Sanz-Barbero, B; Goicolea, I; Álvarez-Dardet, C

2015-09-30

Spain's financial crisis has been characterized by an increase in unemployment. This increase could have produced an increase in deaths of women due to intimate partner-related femicides (IPF). This study aims to determine whether the increase in unemployment among both sexes in different regions in Spain is related to an increase in the rates of IPF during the current financial crisis period. An ecological longitudinal study was carried out in Spain's 17 regions. Two study periods were defined: pre-crisis period (2005-2007) and crisis period (2008-2013). IPF rates adjusted by age and unemployment rates for men and women were calculated. We fitted multilevel linear regression models in which observations at level 1 were nested within regions according to a repeated measurements design. Rates of unemployment have progressively increased in Spain, rising above 20 % from 2008 to 2013 in some regions. IPF rates decreased in some regions during crisis period with respect to pre-crisis period. The multilevel analysis does not support the existence of a significant relationship between the increase in unemployment in men and women and the decrease in IPF since 2008. The increase in unemployment in men and women in Spain does not appear to have an effect on IPF. The results of the multilevel analysis discard the hypothesis that the increase in the rates of unemployment in women and men are related to an increase in IPF rates. The decline in IPF since 2008 might be interpreted as the result of exposure to other factors such as the lower frequency of divorces in recent years or the medium term effects of the integral protection measures of the law on gender violence that began in 2005.

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

PubMed

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

2015-07-01

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

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.

Dental Care Utilization for Examination and Regional Deprivation

PubMed Central

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

2015-01-01

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

Political democracy, economic liberalization, and macro-sociological models of intergenerational mobility.

PubMed

Gugushvili, Alexi

2017-08-01

Building on the previously investigated macro-sociological models which analyze the consequences of economic development, income inequality, and international migration on social mobility, this article studies the specific contextual covariates of intergenerational reproduction of occupational status in post-communist societies. It is theorized that social mobility is higher in societies with democratic political regimes and less liberalized economies. The outlined hypotheses are tested by using micro- and macro-level datasets for 21 post-communist societies which are fitted into multilevel mixed-effects linear regressions. The derived findings suggest that factors specific to transition societies, conventional macro-level variables, and the legacy of the Soviet Union explain variation in intergenerational social mobility, but the results vary depending which birth cohorts survey participants belong to and whether or not they stem from advantaged or disadvantaged social origins. These findings are robust to various alternative data, sample, and method specifications. Copyright © 2017 Elsevier Inc. All rights reserved.

Brief Report: Decentralizing ART Supply for Stable HIV Patients to Community-Based Distribution Centers: Program Outcomes From an Urban Context in Kinshasa, DRC.

PubMed

Vogt, Florian; Kalenga, Lucien; Lukela, Jean; Salumu, Freddy; Diallo, Ibrahim; Nico, Elena; Lampart, Emmanuel; Van den Bergh, Rafael; Shah, Safieh; Ogundahunsi, Olumide; Zachariah, Rony; Van Griensven, Johan

2017-03-01

Facility-based antiretroviral therapy (ART) provision for stable patients with HIV congests health services in resource-limited countries. We assessed outcomes and risk factors for attrition after decentralization to community-based ART refill centers among 2603 patients with HIV in Kinshasa, Democratic Republic of Congo, using a multilevel Poisson regression model. Death, loss to follow-up, and transfer out were 0.3%, 9.0%, and 0.7%, respectively, at 24 months. Overall attrition was 5.66/100 person-years. Patients with >3 years on ART, >500 cluster of differentiation type-4 count, body mass index >18.5, and receiving nevirapine but not stavudine showed reduced attrition. ART refill centers are a promising task-shifting model in low-prevalence urban settings with high levels of stigma and poor ART coverage.

Social Influence and Individual Risk Factors of HIV Unsafe Sex among Female Entertainment Workers in China

PubMed Central

Yang, Xiushi; Xia, Guomei; Li, Xiaoming; Latkin, Carl; Celentano, David

2010-01-01

Female entertainment workers in China are at increased sexual risk of HIV, but causes of their unprotected sex remain poorly understood. We develop a model that integrates information-motivation-behavioral skills (IMB) with social influences and test the model in a venue-based sample of 732 female entertainment workers in Shanghai. Most IMB and social influence measures are statistically significant in bivariate relationships to condom use; only HIV prevention motivation and behavioral self-efficacy remain significant in the multiple regressions. Self-efficacy in condom use is the most proximate correlate, mediating the relationship between information and motivation and condom use. Both peer and venue supports are important, but their influences over condom use are indirect and mediated through prevention motivation and/or self-efficacy. Behavioral intervention is urgently needed and should take a multi-level approach, emphasizing behavioral skills training and promoting a supportive social/working environment. PMID:20166789

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.

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

PubMed

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

2018-01-01

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

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

PubMed

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

2018-06-01

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

Assessment of work intensification by managers and psychological distressed and non-distressed employees: a multilevel comparison.

PubMed

Bamberger, Simon Grandjean; Larsen, Anelia; Vinding, Anker Lund; Nielsen, Peter; Fonager, Kirsten; Nielsen, René Nesgaard; Ryom, Pia; Omland, Øyvind

2015-01-01

Work intensification is a popular management strategy to increase productivity, but at the possible expense of employee mental stress. This study examines associations between ratings of work intensification and psychological distress, and the level of agreement between compared employee-rated and manager-rated work intensification. Multi-source survey data were collected from 3,064 employees and 573 company managers from the private sector in 2010. Multilevel regression models were used to compare different work intensification ratings across psychological distress strata. Distressed employees rated higher degree of total work intensification compared to non-distressed employees, and on three out of five sub ratings there were an increased prevalence of work intensification in the case group. In general, there was poor agreement between employee and company work intensification rating. Neither manager-rated work intensification nor employee/manager discrepancy in work intensification ratings was associated with psychological distress. Distressed employees had a higher total score of employee/manager agreed work intensification, and a higher prevalence of increased demands of labour productivity. This study demonstrates higher ratings of employee/manager agreed work intensification in distressed employees compared to non-distressed employees, challenging previous findings of reporting bias in distressed employees' assessment of work environment.

Assessment of work intensification by managers and psychological distressed and non-distressed employees: a multilevel comparison

PubMed Central

BAMBERGER, Simon Grandjean; LARSEN, Anelia; VINDING, Anker Lund; NIELSEN, Peter; FONAGER, Kirsten; NIELSEN, René Nesgaard; RYOM, Pia; OMLAND, Øyvind

2015-01-01

Work intensification is a popular management strategy to increase productivity, but at the possible expense of employee mental stress. This study examines associations between ratings of work intensification and psychological distress, and the level of agreement between compared employee-rated and manager-rated work intensification. Multi-source survey data were collected from 3,064 employees and 573 company managers from the private sector in 2010. Multilevel regression models were used to compare different work intensification ratings across psychological distress strata. Distressed employees rated higher degree of total work intensification compared to non-distressed employees, and on three out of five sub ratings there were an increased prevalence of work intensification in the case group. In general, there was poor agreement between employee and company work intensification rating. Neither manager-rated work intensification nor employee/manager discrepancy in work intensification ratings was associated with psychological distress. Distressed employees had a higher total score of employee/manager agreed work intensification, and a higher prevalence of increased demands of labour productivity. This study demonstrates higher ratings of employee/manager agreed work intensification in distressed employees compared to non-distressed employees, challenging previous findings of reporting bias in distressed employees’ assessment of work environment. PMID:25752252

School Leadership and Cyberbullying—A Multilevel Analysis

PubMed Central

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

2017-01-01

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

School Leadership and Cyberbullying-A Multilevel Analysis.

PubMed

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

2017-10-15

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

Inequalities in mortality by socioeconomic factors and Roma ethnicity in the two biggest cities in Slovakia: a multilevel analysis.

PubMed

Rosicova, Katarina; Reijneveld, Sijmen A; Madarasova Geckova, Andrea; Stewart, Roy E; Rosic, Martin; Groothoff, Johan W; van Dijk, Jitse P

2015-11-05

The socioeconomic and ethnic composition of urban neighbourhoods may affect mortality, but evidence on Central European cities is lacking. The aim of this study was to assess the associations between socioeconomic and ethnic neighbourhood indicators and the mortality of individuals aged 20-64 years old in the two biggest cities of the Slovak Republic. We obtained data on the characteristics of neighbourhoods and districts (educational level, unemployment, income and share of Roma) and on individual mortality of residents aged 20-64 years old, for the two largest cities in the Slovak Republic (Bratislava and Kosice) in the period 2003-2005. We performed multilevel Poisson regression analyses adjusted for age and gender on the individual (mortality), neighbourhood (education level and share of Roma in population) and district levels (unemployment and income). The proportions of Roma and of low-educated residents were associated with mortality at the neighbourhood level in both cities. Mutually adjusted, only the association with the proportion of Roma remained in the model (risk ratio 1.02; 95 % confidence interval 1.01-1.04). The area indicators - high education, income and unemployment - were not associated with mortality. The proportion of Roma is associated with early mortality in the two biggest cities in the Slovak Republic.

Insular pathways to health care in the city: a multilevel analysis of access to hospital care in urban Kerala, India.

PubMed

Levesque, Jean-Frédéric; Haddad, Slim; Narayana, Delampady; Fournier, Pierre

2007-07-01

To identify individual and urban unit characteristics associated with access to inpatient care in public and private sectors in urban Kerala, and to discuss policy implications of inequalities in access. We analysed the NSSO survey (1995-1996) for urban Kerala with regard to source and trajectories of hospitalization. Multinomial multilevel regression models were built for 695 cases nested in 24 urban units. Private sector accounts for 62% of hospitalizations. Only 31% of hospitalizations are in free wards and 20% of public hospitalizations involve payment. Hospitalization pathways suggest a segmentation of public and private health markets. Members of poor and casual worker households have lower propensity of hospitalization in paying public wards or private hospitals. There were important variations between cities, with higher odds of private hospitalization in towns with fewer hospital beds overall and in districts with high private-public bed ratios. Cities from districts with better economic indicators and dominance of private services have higher proportion of private hospitalizations. The private sector is the predominant source of inpatient care in urban Kerala. The public sector has an important role in providing access to care for the poor. Investing in the quality of public services is essential to ensure equity in access.

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

PubMed

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

2011-01-01

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

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

PubMed

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

2018-03-30

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

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

PubMed

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

2014-08-06

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

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

PubMed

Cornell, Dewey; Huang, Francis

2016-11-01

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

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

PubMed Central

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

2014-01-01

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

Do doctors' attachment styles and emotional intelligence influence patients' emotional expressions in primary care consultations? An exploratory study using multilevel analysis.

PubMed

Cherry, M Gemma; Fletcher, Ian; Berridge, Damon; O'Sullivan, Helen

2018-04-01

To investigate whether and how doctors' attachment styles and emotional intelligence (EI) might influence patients' emotional expressions in general practice consultations. Video recordings of 26 junior doctors consulting with 173 patients were coded using the Verona Coding Definition of Emotional Sequences (VR-CoDES). Doctors' attachment style was scored across two dimensions, avoidance and anxiety, using the Experiences in Close Relationships: Short Form questionnaire. EI was assessed with the Mayer-Salovey-Caruso Emotional Intelligence Test. Multilevel Poisson regressions modelled the probability of patients' expressing emotional distress, considering doctors' attachment styles and EI and demographic and contextual factors. Both attachment styles and EI were significantly associated with frequency of patients' cues, with patient- and doctor-level explanatory variables accounting for 42% of the variance in patients' cues. The relative contribution of attachment styles and EI varied depending on whether patients' presenting complaints were physical or psychosocial in nature. Doctors' attachment styles and levels of EI are associated with patients' emotional expressions in primary care consultations. Further research is needed to investigate how these two variables interact and influence provider responses and patient outcomes. Understanding how doctors' psychological characteristics influence PPC may help to optimise undergraduate and postgraduate medical education. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

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

2015-01-01

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

Investigating the relationship between costs and outcomes for English mental health providers: a bi-variate multi-level regression analysis.

PubMed

Moran, Valerie; Jacobs, Rowena

2018-06-01

Provider payment systems for mental health care that incentivize cost control and quality improvement have been a policy focus in a number of countries. In England, a new prospective provider payment system is being introduced to mental health that should encourage providers to control costs and improve outcomes. The aim of this research is to investigate the relationship between costs and outcomes to ascertain whether there is a trade-off between controlling costs and improving outcomes. The main data source is the Mental Health Minimum Data Set (MHMDS) for the years 2011/12 and 2012/13. Costs are calculated using NHS reference cost data while outcomes are measured using the Health of the Nation Outcome Scales (HoNOS). We estimate a bivariate multi-level model with costs and outcomes simultaneously. We calculate the correlation and plot the pairwise relationship between residual costs and outcomes at the provider level. After controlling for a range of demographic, need, social, and treatment variables, residual variation in costs and outcomes remains at the provider level. The correlation between residual costs and outcomes is negative, but very small, suggesting that cost-containment efforts by providers should not undermine outcome-improving efforts under the new payment system.

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

PubMed

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

2015-07-01

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

Micro-epidemiology and spatial heterogeneity of P. vivax parasitaemia in riverine communities of the Peruvian Amazon: A multilevel analysis.

PubMed

Carrasco-Escobar, Gabriel; Gamboa, Dionicia; Castro, Marcia C; Bangdiwala, Shrikant I; Rodriguez, Hugo; Contreras-Mancilla, Juan; Alava, Freddy; Speybroeck, Niko; Lescano, Andres G; Vinetz, Joseph M; Rosas-Aguirre, Angel; Llanos-Cuentas, Alejandro

2017-08-14

Malaria has steadily increased in the Peruvian Amazon over the last five years. This study aimed to determine the parasite prevalence and micro-geographical heterogeneity of Plasmodium vivax parasitaemia in communities of the Peruvian Amazon. Four cross-sectional active case detection surveys were conducted between May and July 2015 in four riverine communities in Mazan district. Analysis of 2785 samples of 820 individuals nested within 154 households for Plasmodium parasitaemia was carried out using light microscopy and qPCR. The spatio-temporal distribution of Plasmodium parasitaemia, dominated by P. vivax, was shown to cluster at both household and community levels. Of enrolled individuals, 47% had at least one P. vivax parasitaemia and 10% P. falciparum, by qPCR, both of which were predominantly sub-microscopic and asymptomatic. Spatial analysis detected significant clustering in three communities. Our findings showed that communities at small-to-moderate spatial scales differed in P. vivax parasite prevalence, and multilevel Poisson regression models showed that such differences were influenced by factors such as age, education, and location of households within high-risk clusters, as well as factors linked to a local micro-geographic context, such as travel and occupation. Complex transmission patterns were found to be related to human mobility among communities in the same micro-basin.

Data Assimilation and Propagation of Uncertainty in Multiscale Cardiovascular Simulation

NASA Astrophysics Data System (ADS)

Schiavazzi, Daniele; Marsden, Alison

2015-11-01

Cardiovascular modeling is the application of computational tools to predict hemodynamics. State-of-the-art techniques couple a 3D incompressible Navier-Stokes solver with a boundary circulation model and can predict local and peripheral hemodynamics, analyze the post-operative performance of surgical designs and complement clinical data collection minimizing invasive and risky measurement practices. The ability of these tools to make useful predictions is directly related to their accuracy in representing measured physiologies. Tuning of model parameters is therefore a topic of paramount importance and should include clinical data uncertainty, revealing how this uncertainty will affect the predictions. We propose a fully Bayesian, multi-level approach to data assimilation of uncertain clinical data in multiscale circulation models. To reduce the computational cost, we use a stable, condensed approximation of the 3D model build by linear sparse regression of the pressure/flow rate relationship at the outlets. Finally, we consider the problem of non-invasively propagating the uncertainty in model parameters to the resulting hemodynamics and compare Monte Carlo simulation with Stochastic Collocation approaches based on Polynomial or Multi-resolution Chaos expansions.

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

ERIC Educational Resources Information Center

Djonko-Moore, Cara M.

2016-01-01

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

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

ERIC Educational Resources Information Center

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

2007-01-01

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

The Contribution of Organized Youth Sport to Antisocial and Prosocial Behavior in Adolescent Athletes

ERIC Educational Resources Information Center

Rutten, Esther A.; Stams, Geert Jan J. M.; Biesta, Gert J. J.; Schuengel, Carlo; Dirks, Evelien; Hoeksma, Jan B.

2007-01-01

In this study, we investigated the contribution of organized youth sport to antisocial and prosocial behavior in adolescent athletes. The sample consisted of N = 260 male and female soccer players and competitive swimmers, 12 to 18 years of age. Multilevel regression analysis revealed that 8% of the variance in antisocial behavior and 7% of the…

The Performance of Multilevel Growth Curve Models under an Autoregressive Moving Average Process

ERIC Educational Resources Information Center

Murphy, Daniel L.; Pituch, Keenan A.

2009-01-01

The authors examined the robustness of multilevel linear growth curve modeling to misspecification of an autoregressive moving average process. As previous research has shown (J. Ferron, R. Dailey, & Q. Yi, 2002; O. Kwok, S. G. West, & S. B. Green, 2007; S. Sivo, X. Fan, & L. Witta, 2005), estimates of the fixed effects were unbiased, and Type I…

Estimation of Contextual Effects through Nonlinear Multilevel Latent Variable Modeling with a Metropolis-Hastings Robbins-Monro Algorithm

ERIC Educational Resources Information Center

Yang, Ji Seung; Cai, Li

2014-01-01

The main purpose of this study is to improve estimation efficiency in obtaining maximum marginal likelihood estimates of contextual effects in the framework of nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM). Results indicate that the MH-RM algorithm can produce estimates and standard…

Explaining Variance and Identifying Predictors of Children's Communication via a Multilevel Model of Single-Case Design Research: Brief Report

ERIC Educational Resources Information Center

Ottley, Jennifer Riggie; Ferron, John M.; Hanline, Mary Frances

2016-01-01

The purpose of this study was to explain the variability in data collected from a single-case design study and to identify predictors of communicative outcomes for children with developmental delays or disabilities (n = 4). Using SAS® University Edition, we fit multilevel models with time nested within children. Children's level of baseline…

Exploring the Association between Transformational Leadership and Teacher's Self-Efficacy in Greek Education System: A Multilevel SEM Model

ERIC Educational Resources Information Center

Gkolia, Aikaterini; Koustelios, Athanasios; Belias, Dimitrios

2018-01-01

The main aim of this study is to examine the effect of principals' transformational leadership on teachers' self-efficacy across 77 different Greek elementary and secondary schools based on a centralized education system. For the investigation of the above effect multilevel Structural Equation Modelling analysis was conducted, recognizing the…

Taiwanese Students' Science Learning Self-Efficacy and Teacher and Student Science Hardiness: A Multilevel Model Approach

ERIC Educational Resources Information Center

Wang, Ya-Ling; Tsai, Chin-Chung

2016-01-01

This study aimed to investigate the factors accounting for science learning self-efficacy (the specific beliefs that people have in their ability to complete tasks in science learning) from both the teacher and the student levels. We thus propose a multilevel model to delineate its relationships with teacher and student science hardiness (i.e.,…

Modeling of Academic Achievement of Primary School Students in Ethiopia Using Bayesian Multilevel Approach

ERIC Educational Resources Information Center

Sebro, Negusse Yohannes; Goshu, Ayele Taye

2017-01-01

This study aims to explore Bayesian multilevel modeling to investigate variations of average academic achievement of grade eight school students. A sample of 636 students is randomly selected from 26 private and government schools by a two-stage stratified sampling design. Bayesian method is used to estimate the fixed and random effects. Input and…

Preschool Classroom Behavioral Context and School Readiness Outcomes for Low-Income Children: A Multilevel Examination of Child- and Classroom-Level Influences

ERIC Educational Resources Information Center

Bulotsky-Shearer, Rebecca J.; Dominguez, Ximena; Bell, Elizabeth R.

2012-01-01

Guided by an ecological theoretical model, the authors used a series of multilevel models to examine associations among children's individual problem behavior, the classroom behavioral context, and school readiness outcomes for a cohort of low-income children (N = 3,861) enrolled in 229 urban Head Start classrooms. Associations were examined…

A method of Modelling and Simulating the Back-to-Back Modular Multilevel Converter HVDC Transmission System

NASA Astrophysics Data System (ADS)

Wang, Lei; Fan, Youping; Zhang, Dai; Ge, Mengxin; Zou, Xianbin; Li, Jingjiao

2017-09-01

This paper proposes a method to simulate a back-to-back modular multilevel converter (MMC) HVDC transmission system. In this paper we utilize an equivalent networks to simulate the dynamic power system. Moreover, to account for the performance of converter station, core components of model of the converter station gives a basic model of simulation. The proposed method is applied to an equivalent real power system.

Multilevel selection analysis of a microbial social trait

PubMed Central

de Vargas Roditi, Laura; Boyle, Kerry E; Xavier, Joao B

2013-01-01

The study of microbial communities often leads to arguments for the evolution of cooperation due to group benefits. However, multilevel selection models caution against the uncritical assumption that group benefits will lead to the evolution of cooperation. We analyze a microbial social trait to precisely define the conditions favoring cooperation. We combine the multilevel partition of the Price equation with a laboratory model system: swarming in Pseudomonas aeruginosa. We parameterize a population dynamics model using competition experiments where we manipulate expression, and therefore the cost-to-benefit ratio of swarming cooperation. Our analysis shows that multilevel selection can favor costly swarming cooperation because it causes population expansion. However, due to high costs and diminishing returns constitutive cooperation can only be favored by natural selection when relatedness is high. Regulated expression of cooperative genes is a more robust strategy because it provides the benefits of swarming expansion without the high cost or the diminishing returns. Our analysis supports the key prediction that strong group selection does not necessarily mean that microbial cooperation will always emerge. PMID:23959025

Spatial Random Effects Survival Models to Assess Geographical Inequalities in Dengue Fever Using Bayesian Approach: a Case Study

NASA Astrophysics Data System (ADS)

Astuti Thamrin, Sri; Taufik, Irfan

2018-03-01

Dengue haemorrhagic fever (DHF) is an infectious disease caused by dengue virus. The increasing number of people with DHF disease correlates with the neighbourhood, for example sub-districts, and the characteristics of the sub-districts are formed from individuals who are domiciled in the sub-districts. Data containing individuals and sub-districts is a hierarchical data structure, called multilevel analysis. Frequently encountered response variable of the data is the time until an event occurs. Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in DHF survival. Using a case study approach, we report on the implications of using multilevel with spatial survival models to study geographical inequalities in all cause survival.

Regional variations in mortality rates in England and Wales: an analysis using multi-level modelling.

PubMed

Langford, I H; Bentham, G

1996-03-01

Mortality rates in England and Wales display a persistent regional pattern indicating generally poorer health in the North and West. Some of this is simply a reflection of regional differences in the extent of social deprivation which is known to exert a profound influence on health. Part of the pattern may also be the result of regional differences in urbanization which also affect mortality rates. However, there may be important regional differences over and above these compositional effects. This study attempts to establish the magnitude of such independent regional differences in mortality rates by using the techniques of multi-level modelling. Standardized mortality rates (SMRs) for males and females under 65 for 1989-91 in local authority districts are grouped into categories using the ACORN classification scheme. The Townsend Index is included as a measure of social deprivation. Using a cross-classified multi-level model, it is shown that region accounts for approximately four times more variation in SMRs than is explained by the ACORN classification. Analysis of diagnostic residuals show a clear North-South divide in excess mortality when both regional and socio-economic classification of districts are modelled simultaneously, a possibility allowed for by the use of a multi-level model.

Modeling spatial effects of PM{sub 2.5} on term low birth weight in Los Angeles County

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

Coker, Eric, E-mail: cokerer@onid.orst.edu; Ghosh, Jokay; Jerrett, Michael

Air pollution epidemiological studies suggest that elevated exposure to fine particulate matter (PM{sub 2.5}) is associated with higher prevalence of term low birth weight (TLBW). Previous studies have generally assumed the exposure–response of PM{sub 2.5} on TLBW to be the same throughout a large geographical area. Health effects related to PM{sub 2.5} exposures, however, may not be uniformly distributed spatially, creating a need for studies that explicitly investigate the spatial distribution of the exposure–response relationship between individual-level exposure to PM{sub 2.5} and TLBW. Here, we examine the overall and spatially varying exposure–response relationship between PM{sub 2.5} and TLBW throughout urbanmore » Los Angeles (LA) County, California. We estimated PM{sub 2.5} from a combination of land use regression (LUR), aerosol optical depth from remote sensing, and atmospheric modeling techniques. Exposures were assigned to LA County individual pregnancies identified from electronic birth certificates between the years 1995-2006 (N=1,359,284) provided by the California Department of Public Health. We used a single pollutant multivariate logistic regression model, with multilevel spatially structured and unstructured random effects set in a Bayesian framework to estimate global and spatially varying pollutant effects on TLBW at the census tract level. Overall, increased PM{sub 2.5} level was associated with higher prevalence of TLBW county-wide. The spatial random effects model, however, demonstrated that the exposure–response for PM{sub 2.5} and TLBW was not uniform across urban LA County. Rather, the magnitude and certainty of the exposure–response estimates for PM{sub 2.5} on log odds of TLBW were greatest in the urban core of Central and Southern LA County census tracts. These results suggest that the effects may be spatially patterned, and that simply estimating global pollutant effects obscures disparities suggested by spatial patterns of effects. Studies that incorporate spatial multilevel modeling with random coefficients allow us to identify areas where air pollutant effects on adverse birth outcomes may be most severe and policies to further reduce air pollution might be most effective. - Highlights: • We model the spatial dependency of PM{sub 2.5} effects on term low birth weight (TLBW). • PM{sub 2.5} effects on TLBW are shown to vary spatially across urban LA County. • Modeling spatial dependency of PM{sub 2.5} health effects may identify effect 'hotspots'. • Birth outcomes studies should consider the spatial dependency of PM{sub 2.5} effects.« less

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.

Dropout revisited: patient- and therapist-initiated discontinuation of psychotherapy as a function of organizational instability.

PubMed

Werbart, Andrzej; Andersson, Håkan; Sandell, Rolf

2014-01-01

To explore the association between the stability or instability of services' organizational structure and patient- and therapist-initiated discontinuation of therapy in routine mental health. Three groups, comprising altogether 750 cases in routine mental health care in eight different clinics, were included: cases with patient-initiated discontinuation, therapist-initiated discontinuation, and patients remaining in treatment. Multilevel multinomial regression was used to estimate three models: An initial, unconditional intercept-only model, another one including patient variables, and a final model with significant patient and therapist variables including the organizational stability of the therapists' clinic. High between-therapist variability was noted. Odds ratios and significance tests indicated a strong association of organizational instability with patient-initiated premature termination in particular. The question of how organizational factors influence the treatment results needs further research. Future studies have to be designed in ways that permit clinically meaningful subdivision of the patients' and the therapists' decisions for premature termination.

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.

Anthropometry and blood pressure changes in a Caribbean adolescent population of African ancestry: an evaluation of longitudinal data using a multilevel mixed regression approach.

PubMed

Nichols, S; Cadogan, F

2012-10-01

The aim of this study was to determine the effect of growth pattern on blood pressure changes in an adolescent population of African ancestry based on longitudinal data and to compare this with estimates derived from cross-sectional data. Participants had measurements of weight, height, blood pressure and percentage body fat taken annually using standardized procedures. Annual blood pressure and anthropometry velocities as well as one- and three-year interval gender specific tracking coefficients were computed. We investigated whether changes in blood pressure could be explained by measures of growth using a multilevel mixed regression approach. The results showed that systolic blood pressure (SBP) increased by 1.27 and 3.09 mmHg per year among females and males, respectively. Similarly, diastolic blood pressure (DBP) increased by 1.16 and 1.92 mmHg per year among females and males, respectively. Multilevel analyses suggested that weight, body mass index, percentage body fat and height were the strongest anthropometric determinants of blood pressure change in this population. The results also suggest that there are gender differences in the relative importance of these anthropometric measures with height playing a minor role in predicting blood pressure changes among adolescent females. With the exception of DBP at 18 years among females, there were no significant differences between mean blood pressure generated from cross-sectional and longitudinal data by age in both males and females. Anthropometric measures are important covariates of age-related blood pressure changes and cross-sectional data may provide a more cost-effective and useful proxy for generating age-related blood pressure estimates in this population.

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.…

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

PubMed

Dahlin, Johanna; Härkönen, Juho

2013-12-01

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

A closed-loop multi-level model of glucose homeostasis

PubMed Central

Uluseker, Cansu; Simoni, Giulia; Dauriz, Marco; Matone, Alice

2018-01-01

Background The pathophysiologic processes underlying the regulation of glucose homeostasis are considerably complex at both cellular and systemic level. A comprehensive and structured specification for the several layers of abstraction of glucose metabolism is often elusive, an issue currently solvable with the hierarchical description provided by multi-level models. In this study we propose a multi-level closed-loop model of whole-body glucose homeostasis, coupled with the molecular specifications of the insulin signaling cascade in adipocytes, under the experimental conditions of normal glucose regulation and type 2 diabetes. Methodology/Principal findings The ordinary differential equations of the model, describing the dynamics of glucose and key regulatory hormones and their reciprocal interactions among gut, liver, muscle and adipose tissue, were designed for being embedded in a modular, hierarchical structure. The closed-loop model structure allowed self-sustained simulations to represent an ideal in silico subject that adjusts its own metabolism to the fasting and feeding states, depending on the hormonal context and invariant to circadian fluctuations. The cellular level of the model provided a seamless dynamic description of the molecular mechanisms downstream the insulin receptor in the adipocytes by accounting for variations in the surrounding metabolic context. Conclusions/Significance The combination of a multi-level and closed-loop modeling approach provided a fair dynamic description of the core determinants of glucose homeostasis at both cellular and systemic scales. This model architecture is intrinsically open to incorporate supplementary layers of specifications describing further individual components influencing glucose metabolism. PMID:29420588

A collision dynamics model of a multi-level train

DOT National Transportation Integrated Search

2006-11-05

In train collisions, multi-level rail passenger vehicles can deform in modes that are different from the behavior of single level cars. The deformation in single level cars usually occurs at the front end during a collision. In one particular inciden...

[Effect of Adolescents' Abuse Experience on Suicidal Ideation: Focused on Moderated Mediation Effect of Self-esteem on Depression and Anxiety].

PubMed

Kim, Ji Young; Lee, Kyunghee

2015-10-01

The purpose of this study was to examine the moderating mediation effect of self-esteem on the relations among adolescents' abuse experiences, depression and anxiety, and suicidal ideation. The participants were selected using secondary data from a population in the 2012 Korea Welfare Panel Survey (KOWEPS). Data were analyzed using SPSS 15.0 and SPSS Macro, and bootstrapping and hierarchical regression analysis were performed to analyze multilevel models. First, analysis of the mediating effect of the adolescents' abuse showed that there was significant mediating influence between suicidal ideation and depression and anxiety. Second, hierarchical regression analysis showed that self-esteem had significant mediation effect on depression and anxiety in adolescents' suicidal ideation. Third, SPSS Macro showed that self-esteem also significantly moderated the mediating effect of adolescents' abuse experiences on suicidal ideation through depression and anxiety. The study results suggest that in future research on adolescent's abuse experience, the risk of suicide in depression and anxiety scores should be selected through evaluation of each individual's self-esteem scale. Coping strategies with immediate early intervention should be suggested.

Are There Racial-Ethnic Disparities in Time to Pressure Ulcer Development and Pressure Ulcer Treatment in Older Adults After Nursing Home Admission?

PubMed Central

Bliss, Donna Z.; Gurvich, Olga; Savik, Kay; Eberly, Lynn E.; Harms, Susan; Mueller, Christine; Wyman, Jean F.; Garrard, Judith; Virnig, Beth

2017-01-01

Objective The objective of this study was to assess whether there are racial and ethnic disparities in the time to development of a pressure ulcer and number of pressure ulcer treatments in individuals aged 65 and older after nursing home admission. Method Multi-level predictors of time to a pressure ulcer from three national surveys were analyzed using Cox proportional hazards regression for White Non-Hispanic residents. Using the Peters–Belson method to assess for disparities, estimates from the regression models were applied to American Indians/Alaskan Natives, Asians/ Pacific Islanders, Blacks, and Hispanics separately resulting in estimates of expected outcomes as if they were White Non-Hispanic, and were then compared with their observed outcomes. Results More Blacks developed pressure ulcers sooner than expected. No disparities in time to a pressure ulcer disadvantaging other racial/ethnic groups were found. There were no disparities in pressure ulcer treatment for any group. Discussion Reducing disparities in pressure ulcer development offers a strategy to improve the quality of nursing home care. PMID:25260648

Are there racial-ethnic disparities in time to pressure ulcer development and pressure ulcer treatment in older adults after nursing home admission?

PubMed

Bliss, Donna Z; Gurvich, Olga; Savik, Kay; Eberly, Lynn E; Harms, Susan; Mueller, Christine; Wyman, Jean F; Garrard, Judith; Virnig, Beth

2015-06-01

The objective of this study was to assess whether there are racial and ethnic disparities in the time to development of a pressure ulcer and number of pressure ulcer treatments in individuals aged 65 and older after nursing home admission. Multi-level predictors of time to a pressure ulcer from three national surveys were analyzed using Cox proportional hazards regression for White Non-Hispanic residents. Using the Peters-Belson method to assess for disparities, estimates from the regression models were applied to American Indians/Alaskan Natives, Asians/Pacific Islanders, Blacks, and Hispanics separately resulting in estimates of expected outcomes as if they were White Non-Hispanic, and were then compared with their observed outcomes. More Blacks developed pressure ulcers sooner than expected. No disparities in time to a pressure ulcer disadvantaging other racial/ethnic groups were found. There were no disparities in pressure ulcer treatment for any group. Reducing disparities in pressure ulcer development offers a strategy to improve the quality of nursing home care. © The Author(s) 2014.

The Code of the Street and Violent Versus Property Crime Victimization.

PubMed

McNeeley, Susan; Wilcox, Pamela

2015-01-01

Previous research has shown that individuals who adopt values in line with the code of the street are more likely to experience violent victimization (e.g., Stewart, Schreck, & Simons, 2006). This study extends this literature by examining the relationship between the street code and multiple types of violent and property victimization. This research investigates the relationship between street code-related values and 4 types of victimization (assault, breaking and entering, theft, and vandalism) using Poisson-based multilevel regression models. Belief in the street code was associated with higher risk of experiencing assault, breaking and entering, and vandalism, whereas theft victimization was not related to the street code. The results suggest that the code of the street influences victimization broadly--beyond violence--by increasing behavior that provokes retaliation from others in various forms.

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

PubMed

Yu, Chuan; Li, Xiao-song

2008-11-01

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

The Association between Adolescent Life Satisfaction, Family Structure, Family Affluence and Gender Differences in Parent-Child Communication

ERIC Educational Resources Information Center

Levin, Kate Ann; Dallago, Lorenza; Currie, Candace

2012-01-01

The study sought to examine young people's life satisfaction in the context of the family environment, using data from the 2006 HBSC: WHO-collaborative Study in Scotland (N = 5,126). Multilevel linear regression analyses were carried out for 11-, 13- and 15-year old boys and girls, with outcome measure ridit-transformed life satisfaction. The…

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

PubMed

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

2016-11-04

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

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

PubMed

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

2017-09-01

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

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

PubMed Central

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

2016-01-01

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

Sex moderates associations between perceptions of the physical and social environments and physical activity in youth.

PubMed

Moore, Justin B; Beets, Michael W; Kaczynski, Andrew T; Besenyi, Gina M; Morris, Sara F; Kolbe, Mary Bea

2014-01-01

To determine if the sex of the child moderates the relationships between perceptions of the physical/social environments and moderate to vigorous physical activity (MVPA) in youth. Cross-sectional. North Carolina. A final sample of 711 children, 8 to 17 years of age, was available for analysis. Self-reported presence of environmental factors previously identified to be associated with physical activity in youth was collected via survey. Daily MVPA was assessed via accelerometry for a minimum of 4 days. Multilevel linear regression models were employed, adjusted for clustering at the county and individual level. MVPA was first regressed onto sex and environmental perception items while controlling for grade and race. The interaction term between sex and environmental perception was then added to the model. A significant positive association was observed in the first models between MVPA and two items related to parent permission to (1) walk and (2) ride a bike in the neighborhood. These effects were fully moderated by sex, with males indicating "yes" on these items exhibiting 6.87 and 5.21 more minutes of MVPA (respectively) than males indicating "no." Environmental perceptions appear to be related to MVPA, but this relationship is present only in males. Future research should be conducted to identify modifiable social and physical characteristics that are associated with MVPA in females.

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.

Enhancing prediction power of chemometric models through manipulation of the fed spectrophotometric data: A comparative study

NASA Astrophysics Data System (ADS)

Saad, Ahmed S.; Hamdy, Abdallah M.; Salama, Fathy M.; Abdelkawy, Mohamed

2016-10-01

Effect of data manipulation in preprocessing step proceeding construction of chemometric models was assessed. The same set of UV spectral data was used for construction of PLS and PCR models directly and after mathematically manipulation as per well known first and second derivatives of the absorption spectra, ratio spectra and first and second derivatives of the ratio spectra spectrophotometric methods, meanwhile the optimal working wavelength ranges were carefully selected for each model and the models were constructed. Unexpectedly, number of latent variables used for models' construction varied among the different methods. The prediction power of the different models was compared using a validation set of 8 mixtures prepared as per the multilevel multifactor design and results were statistically compared using two-way ANOVA test. Root mean squares error of prediction (RMSEP) was used for further comparison of the predictability among different constructed models. Although no significant difference was found between results obtained using Partial Least Squares (PLS) and Principal Component Regression (PCR) models, however, discrepancies among results was found to be attributed to the variation in the discrimination power of adopted spectrophotometric methods on spectral data.

Mindfulness, Physical Activity and Avoidance of Secondhand Smoke: A Study of College Students in Shanghai.

PubMed

Gao, Yu; Shi, Lu

2015-08-21

To better understand the documented link between mindfulness and longevity, we examine the association between mindfulness and conscious avoidance of secondhand smoke (SHS), as well as the association between mindfulness and physical activity. In Shanghai University of Finance and Economics (SUFE) we surveyed a convenience sample of 1516 college freshmen. We measured mindfulness, weekly physical activity, and conscious avoidance of secondhand smoke, along with demographic and behavioral covariates. We used a multilevel logistic regression to test the association between mindfulness and conscious avoidance of secondhand smoke, and used a Tobit regression model to test the association between mindfulness and metabolic equivalent hours per week. In both models the home province of the student respondent was used as the cluster variable, and demographic and behavioral covariates, such as age, gender, smoking history, household registration status (urban vs. rural), the perceived smog frequency in their home towns, and the asthma diagnosis. The logistic regression of consciously avoiding SHS shows that a higher level of mindfulness was associated with an increase in the odds ratio of conscious SHS avoidance (logged odds: 0.22, standard error: 0.07, p < 0.01). The Tobit regression shows that a higher level of mindfulness was associated with more metabolic equivalent hours per week (Tobit coefficient: 4.09, standard error: 1.13, p < 0.001). This study is an innovative attempt to study the behavioral issue of secondhand smoke from the perspective of the potential victim, rather than the active smoker. The observed associational patterns here are consistent with previous findings that mindfulness is associated with healthier behaviors in obesity prevention and substance use. Research designs with interventions are needed to test the causal link between mindfulness and these healthy behaviors.

Mindfulness, Physical Activity and Avoidance of Secondhand Smoke: A Study of College Students in Shanghai

PubMed Central

Gao, Yu; Shi, Lu

2015-01-01

Introduction: To better understand the documented link between mindfulness and longevity, we examine the association between mindfulness and conscious avoidance of secondhand smoke (SHS), as well as the association between mindfulness and physical activity. Method: In Shanghai University of Finance and Economics (SUFE) we surveyed a convenience sample of 1516 college freshmen. We measured mindfulness, weekly physical activity, and conscious avoidance of secondhand smoke, along with demographic and behavioral covariates. We used a multilevel logistic regression to test the association between mindfulness and conscious avoidance of secondhand smoke, and used a Tobit regression model to test the association between mindfulness and metabolic equivalent hours per week. In both models the home province of the student respondent was used as the cluster variable, and demographic and behavioral covariates, such as age, gender, smoking history, household registration status (urban vs. rural), the perceived smog frequency in their home towns, and the asthma diagnosis. Results: The logistic regression of consciously avoiding SHS shows that a higher level of mindfulness was associated with an increase in the odds ratio of conscious SHS avoidance (logged odds: 0.22, standard error: 0.07, p < 0.01). The Tobit regression shows that a higher level of mindfulness was associated with more metabolic equivalent hours per week (Tobit coefficient: 4.09, standard error: 1.13, p < 0.001). Discussion: This study is an innovative attempt to study the behavioral issue of secondhand smoke from the perspective of the potential victim, rather than the active smoker. The observed associational patterns here are consistent with previous findings that mindfulness is associated with healthier behaviors in obesity prevention and substance use. Research designs with interventions are needed to test the causal link between mindfulness and these healthy behaviors. PMID:26308029

Religion and the Unmaking of Prejudice toward Muslims: Evidence from a Large National Sample

PubMed Central

Shaver, John H.; Troughton, Geoffrey; Sibley, Chris G.; Bulbulia, Joseph A.

2016-01-01

In the West, anti-Muslim sentiments are widespread. It has been theorized that inter-religious tensions fuel anti-Muslim prejudice, yet previous attempts to isolate sectarian motives have been inconclusive. Factors contributing to ambiguous results are: (1) failures to assess and adjust for multi-level denomination effects; (2) inattention to demographic covariates; (3) inadequate methods for comparing anti-Muslim prejudice relative to other minority group prejudices; and (4) ad hoc theories for the mechanisms that underpin prejudice and tolerance. Here we investigate anti-Muslim prejudice using a large national sample of non-Muslim New Zealanders (N = 13,955) who responded to the 2013 New Zealand Attitudes and Values Study. We address previous shortcomings by: (1) building Bayesian multivariate, multi-level regression models with denominations modeled as random effects; (2) including high-resolution demographic information that adjusts for factors known to influence prejudice; (3) simultaneously evaluating the relative strength of anti-Muslim prejudice by comparing it to anti-Arab prejudice and anti-immigrant prejudice within the same statistical model; and (4) testing predictions derived from the Evolutionary Lag Theory of religious prejudice and tolerance. This theory predicts that in countries such as New Zealand, with historically low levels of conflict, religion will tend to increase tolerance generally, and extend to minority religious groups. Results show that anti-Muslim and anti-Arab sentiments are confounded, widespread, and substantially higher than anti-immigrant sentiments. In support of the theory, the intensity of religious commitments was associated with a general increase in tolerance toward minority groups, including a poorly tolerated religious minority group: Muslims. Results clarify religion’s power to enhance tolerance in peaceful societies that are nevertheless afflicted by prejudice. PMID:26959976

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.

Selection of optimal complexity for ENSO-EMR model by minimum description length principle

NASA Astrophysics Data System (ADS)

Loskutov, E. M.; Mukhin, D.; Mukhina, A.; Gavrilov, A.; Kondrashov, D. A.; Feigin, A. M.

2012-12-01

One of the main problems arising in modeling of data taken from natural system is finding a phase space suitable for construction of the evolution operator model. Since we usually deal with strongly high-dimensional behavior, we are forced to construct a model working in some projection of system phase space corresponding to time scales of interest. Selection of optimal projection is non-trivial problem since there are many ways to reconstruct phase variables from given time series, especially in the case of a spatio-temporal data field. Actually, finding optimal projection is significant part of model selection, because, on the one hand, the transformation of data to some phase variables vector can be considered as a required component of the model. On the other hand, such an optimization of a phase space makes sense only in relation to the parametrization of the model we use, i.e. representation of evolution operator, so we should find an optimal structure of the model together with phase variables vector. In this paper we propose to use principle of minimal description length (Molkov et al., 2009) for selection models of optimal complexity. The proposed method is applied to optimization of Empirical Model Reduction (EMR) of ENSO phenomenon (Kravtsov et al. 2005, Kondrashov et. al., 2005). This model operates within a subset of leading EOFs constructed from spatio-temporal field of SST in Equatorial Pacific, and has a form of multi-level stochastic differential equations (SDE) with polynomial parameterization of the right-hand side. Optimal values for both the number of EOF, the order of polynomial and number of levels are estimated from the Equatorial Pacific SST dataset. References: Ya. Molkov, D. Mukhin, E. Loskutov, G. Fidelin and A. Feigin, Using the minimum description length principle for global reconstruction of dynamic systems from noisy time series, Phys. Rev. E, Vol. 80, P 046207, 2009 Kravtsov S, Kondrashov D, Ghil M, 2005: Multilevel regression modeling of nonlinear processes: Derivation and applications to climatic variability. J. Climate, 18 (21): 4404-4424. D. Kondrashov, S. Kravtsov, A. W. Robertson and M. Ghil, 2005. A hierarchy of data-based ENSO models. J. Climate, 18, 4425-4444.

Television viewing and forms of bullying among adolescents from eight countries.

PubMed

Kuntsche, Emmanuel; Pickett, William; Overpeck, Mary; Craig, Wendy; Boyce, William; de Matos, Margarida Gaspar

2006-12-01

Based on theories suggesting that frequent television viewers act and react in hostile, malicious, malevolent, or verbally aggressive ways rather than being physically violent, the present study investigates relationships between television viewing and different forms of bullying. Multilevel regression models were estimated based on cross-sectional data from 31,177 adolescents aged 11, 13, and 15 years from Canada, Estonia, Israel, Latvia, Macedonia, Poland, Portugal, and the United States who participated in the 2001-2002 Health Behavior in School-aged Children Survey. Although all different forms of bullying were associated with television viewing in bivariate analyses, only the verbal forms (i.e. "calling mean names" and "spreading rumors") remained significant in multiple regression models. These relationships were observed consistently in all eight participating countries. However, the association between television viewing and physical forms of bullying such as kicking, pushing, or shoving around, varied across countries. In most weekend TV viewing cultures, frequent television viewers were prone to kick or push another student in addition to verbal forms of bullying, which was not the case in weekday viewing cultures. These results demonstrate the importance of limiting adolescents' time engaged in unsupervised television watching, and the need to motivate adolescents to engage in joint family activities or organized after-school activities.