Multivariate Multiple Membership Random Effects Models

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Multivariate Multiple-membership Random Effects Models

Author : Sunyoung Park (Ph. D. in educational psychology)
Publisher :
ISBN 13 :
Total Pages : 340 pages
Book Rating : 4.:/5 (15 download)

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Book Synopsis Multivariate Multiple-membership Random Effects Models by : Sunyoung Park (Ph. D. in educational psychology)

Download or read book Multivariate Multiple-membership Random Effects Models written by Sunyoung Park (Ph. D. in educational psychology) and published by . This book was released on 2018 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: The current dissertation, composed of two studies, focused on the models that handle several data structure complexities simultaneously. The first study introduced and evaluated Markov Chain Monte Carlo (MCMC) estimation of the multivariate multiple-membership random effects model (MV-MMREM) for handling multiple-membership data in scenarios with multiple, related outcomes. The second study assessed performance of the deviance information criterion (DIC) for selecting the best-fitting model to help support a researcher's choices about whether to add fixed effects to the MV-MMREM effects model. While a recent study introduced the idea of the MV-MMREM, no research has directly assessed its estimation nor demonstrated its use with real data. Therefore, real multiple-membership dataset were used that includes multiple related outcomes to demonstrate interpretation of MV-MMREM parameters. In addition, a simulation study was conducted to assess estimation of the MV-MMREM under a number of design conditions including the proportion of multiple membership individuals, the number of clusters, the sample size per cluster, the degree of correlation among pairs of outcomes, the true intra-class correlation coefficient, type of missingness, and proportion of missingness. Additionally, the robustness of results were assessed for multivariate multiple-membership data when analyzed using multivariate, hierarchical linear model that ignores the multiple-membership structure (MV-HLM) and when instead using multiple, univariate MMREMs (one for each outcome). The results were assessed using relative parameter bias (RPB), relative standard error bias (RSEB), and coverage rates. In the second study, another real dataset were analyzed with the resulting DIC values compared to demonstrate how it is used to support selection of the best-fitting model. In the associated simulation study, the same set of design conditions as in the first study (but not considered missingness and considered the magnitude of coefficients of predictor variables) were manipulated. The DIC was used to choose between three different conditional MV-MMREMs that differ in their fixed effects parameter specification. We assessed and compared correct model identification rates based on the DIC with inferences and based on the statistical significance of the parameters being added in the set of nested models.

Multivariate Generalized Linear Mixed Models Using R

Author : Damon Mark Berridge
Publisher : CRC Press
ISBN 13 : 1439813272
Total Pages : 284 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Multivariate Generalized Linear Mixed Models Using R by : Damon Mark Berridge

Download or read book Multivariate Generalized Linear Mixed Models Using R written by Damon Mark Berridge and published by CRC Press. This book was released on 2011-04-25 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from panel and related studies via the Sabre software package in R.A Un

Multilevel Modeling

Author : Douglas A. Luke
Publisher : SAGE Publications
ISBN 13 : 1544310315
Total Pages : 129 pages
Book Rating : 4.5/5 (443 download)

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Book Synopsis Multilevel Modeling by : Douglas A. Luke

Download or read book Multilevel Modeling written by Douglas A. Luke and published by SAGE Publications. This book was released on 2019-12-13 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilevel Modeling is a concise, practical guide to building models for multilevel and longitudinal data. Author Douglas A. Luke begins by providing a rationale for multilevel models; outlines the basic approach to estimating and evaluating a two-level model; discusses the major extensions to mixed-effects models; and provides advice for where to go for instruction in more advanced techniques. Rich with examples, the Second Edition expands coverage of longitudinal methods, diagnostic procedures, models of counts (Poisson), power analysis, cross-classified models, and adds a new section added on presenting modeling results. A website for the book includes the data and the statistical code (both R and Stata) used for all of the presented analyses.

Multilevel Modeling Using R

Author : W. Holmes Finch
Publisher : CRC Press
ISBN 13 : 1466515864
Total Pages : 225 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Multilevel Modeling Using R by : W. Holmes Finch

Download or read book Multilevel Modeling Using R written by W. Holmes Finch and published by CRC Press. This book was released on 2016-03-09 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilevel Modelling using R provides a helpful guide to conducting multilevel data modeling using the R software environment. After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single level and multilevel data. The book concludes with Bayesian fitting of multilevel models. Complete data sets for the book can be found on the book's website www.mlminr.com/

Multilevel Analysis

Author : Tom A B Snijders
Publisher : SAGE
ISBN 13 : 144625433X
Total Pages : 369 pages
Book Rating : 4.4/5 (462 download)

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Book Synopsis Multilevel Analysis by : Tom A B Snijders

Download or read book Multilevel Analysis written by Tom A B Snijders and published by SAGE. This book was released on 2011-10-30 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Second Edition of this classic text introduces the main methods, techniques and issues involved in carrying out multilevel modeling and analysis. Snijders and Bosker′s book is an applied, authoritative and accessible introduction to the topic, providing readers with a clear conceptual and practical understanding of all the main issues involved in designing multilevel studies and conducting multilevel analysis. This book provides step-by-step coverage of: • multilevel theories • ecological fallacies • the hierarchical linear model • testing and model specification • heteroscedasticity • study designs • longitudinal data • multivariate multilevel models • discrete dependent variables There are also new chapters on: • missing data • multilevel modeling and survey weights • Bayesian and MCMC estimation and latent-class models. This book has been comprehensively revised and updated since the last edition, and now discusses modeling using HLM, MLwiN, SAS, Stata including GLLAMM, R, SPSS, Mplus, WinBugs, Latent Gold, and SuperMix. This is a must-have text for any student, teacher or researcher with an interest in conducting or understanding multilevel analysis. Tom A.B. Snijders is Professor of Statistics in the Social Sciences at the University of Oxford and Professor of Statistics and Methodology at the University of Groningen. Roel J. Bosker is Professor of Education and Director of GION, Groningen Institute for Educational Research, at the University of Groningen.

Applied Mixed Model Analysis

Author : Jos W. R. Twisk
Publisher : Cambridge University Press
ISBN 13 : 1108480578
Total Pages : 249 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Applied Mixed Model Analysis by : Jos W. R. Twisk

Download or read book Applied Mixed Model Analysis written by Jos W. R. Twisk and published by Cambridge University Press. This book was released on 2019-04-18 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing interpretation of results, this hands-on guide explains why, when, and how to use mixed models with your data.

Egocentric Network Analysis

Author : Brea L. Perry
Publisher : Structural Analysis in the Soc
ISBN 13 : 110713143X
Total Pages : 371 pages
Book Rating : 4.1/5 (71 download)

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Book Synopsis Egocentric Network Analysis by : Brea L. Perry

Download or read book Egocentric Network Analysis written by Brea L. Perry and published by Structural Analysis in the Soc. This book was released on 2018-03-22 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: An in-depth, comprehensive and practical guide to egocentric network analysis, focusing on fundamental theoretical, research design, and analytic issues.

Multilevel Models

Author : Jichuan Wang
Publisher : Walter de Gruyter
ISBN 13 : 3110267705
Total Pages : 275 pages
Book Rating : 4.1/5 (12 download)

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Book Synopsis Multilevel Models by : Jichuan Wang

Download or read book Multilevel Models written by Jichuan Wang and published by Walter de Gruyter. This book was released on 2011-12-23 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in multilevel statistical models for social science and public health studies has been aroused dramatically since the mid-1980s. New multilevel modeling techniques are giving researchers tools for analyzing data that have a hierarchical or clustered structure. Multilevel models are now applied to a wide range of studies in sociology, population studies, education studies, psychology, economics, epidemiology, and public health. This book covers a broad range of topics about multilevel modeling. The goal of the authors is to help students and researchers who are interested in analysis of multilevel data to understand the basic concepts, theoretical frameworks and application methods of multilevel modeling. The book is written in non-mathematical terms, focusing on the methods and application of various multilevel models, using the internationally widely used statistical software, the Statistics Analysis System (SAS®). Examples are drawn from analysis of real-world research data. The authors focus on twolevel models in this book because it is most frequently encountered situation in real research. These models can be readily expanded to models with three or more levels when applicable. A wide range of linear and non-linear multilevel models are introduced and demonstrated.

Multilevel Analysis

Author : Tom A. B. Snijders
Publisher : SAGE
ISBN 13 : 9780761958901
Total Pages : 282 pages
Book Rating : 4.9/5 (589 download)

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Book Synopsis Multilevel Analysis by : Tom A. B. Snijders

Download or read book Multilevel Analysis written by Tom A. B. Snijders and published by SAGE. This book was released on 1999 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilevel analysis covers all the main methods, techniques and issues for carrying out multilevel modeling and analysis. The approach is applied, and less mathematical than many other textbooks.

Mixed Effects Models for Complex Data

Author : Lang Wu
Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)

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Book Synopsis Mixed Effects Models for Complex Data by : Lang Wu

Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.

The Multivariate One-way Classification Model with Random Effects

Author : James Robert Schott
Publisher :
ISBN 13 :
Total Pages : 220 pages
Book Rating : 4.:/5 (87 download)

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Book Synopsis The Multivariate One-way Classification Model with Random Effects by : James Robert Schott

Download or read book The Multivariate One-way Classification Model with Random Effects written by James Robert Schott and published by . This book was released on 1981 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: A well-known model in univariate statistical analysis is the one-way random effects model. In this paper we investigate the multivariate generalization of this model, that is, the multivariate one-way random effects model. Two specific situations, regarding the structure of the variance-covariance matrix of the random error vectors, are considered. In the first and most general case, it is only assumed that this variance-covariance matrix is symmetric and positive definite. In the second case, it is assumed, in addition, that the variance-covariance matrix is a scalar multiple of the identity matrix. Maximum likelihood estimates are obtained and the likelihood ratio test for a hypothesis test on the rank of the variance-covariance matrix of the random effect vectors is derived. Properties of the likelihood ratio test are investigated for the general case, while for the second case an alternative test is developed and its properties are investigated. In each case a sequential procedure for determining the rank of the variance-covariance matrix of the random effect vectors is presented.

Multilevel Modeling

Author : Steven P. Reise
Publisher : Psychology Press
ISBN 13 : 1135655359
Total Pages : 332 pages
Book Rating : 4.1/5 (356 download)

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Book Synopsis Multilevel Modeling by : Steven P. Reise

Download or read book Multilevel Modeling written by Steven P. Reise and published by Psychology Press. This book was released on 2003-01-30 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book illustrates the current work of leading multilevel modeling (MLM) researchers from around the world. The book's goal is to critically examine the real problems that occur when trying to use MLMs in applied research, such as power, experimental design, and model violations. This presentation of cutting-edge work and statistical innovations in multilevel modeling includes topics such as growth modeling, repeated measures analysis, nonlinear modeling, outlier detection, and meta analysis. This volume will be beneficial for researchers with advanced statistical training and extensive experience in applying multilevel models, especially in the areas of education; clinical intervention; social, developmental and health psychology, and other behavioral sciences; or as a supplement for an introductory graduate-level course.

Hierarchical Linear Models

Author : Stephen W. Raudenbush
Publisher : SAGE
ISBN 13 : 9780761919049
Total Pages : 520 pages
Book Rating : 4.9/5 (19 download)

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Book Synopsis Hierarchical Linear Models by : Stephen W. Raudenbush

Download or read book Hierarchical Linear Models written by Stephen W. Raudenbush and published by SAGE. This book was released on 2002 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: New edition of a text in which Raudenbush (U. of Michigan) and Bryk (sociology, U. of Chicago) provide examples, explanations, and illustrations of the theory and use of hierarchical linear models (HLM). New material in Part I (Logic) includes information on multivariate growth models and other topics.

Handbook of Advanced Multilevel Analysis

Author : Joop Hox
Publisher : Routledge
ISBN 13 : 1136951261
Total Pages : 698 pages
Book Rating : 4.1/5 (369 download)

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Book Synopsis Handbook of Advanced Multilevel Analysis by : Joop Hox

Download or read book Handbook of Advanced Multilevel Analysis written by Joop Hox and published by Routledge. This book was released on 2011-01-11 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new handbook is the definitive resource on advanced topics related to multilevel analysis. The editors assembled the top minds in the field to address the latest applications of multilevel modeling as well as the specific difficulties and methodological problems that are becoming more common as more complicated models are developed. Each chapter features examples that use actual datasets. These datasets, as well as the code to run the models, are available on the book’s website http://www.hlm-online.com . Each chapter includes an introduction that sets the stage for the material to come and a conclusion. Divided into five sections, the first provides a broad introduction to the field that serves as a framework for understanding the latter chapters. Part 2 focuses on multilevel latent variable modeling including item response theory and mixture modeling. Section 3 addresses models used for longitudinal data including growth curve and structural equation modeling. Special estimation problems are examined in section 4 including the difficulties involved in estimating survival analysis, Bayesian estimation, bootstrapping, multiple imputation, and complicated models, including generalized linear models, optimal design in multilevel models, and more. The book’s concluding section focuses on statistical design issues encountered when doing multilevel modeling including nested designs, analyzing cross-classified models, and dyadic data analysis. Intended for methodologists, statisticians, and researchers in a variety of fields including psychology, education, and the social and health sciences, this handbook also serves as an excellent text for graduate and PhD level courses in multilevel modeling. A basic knowledge of multilevel modeling is assumed.

Random Effect and Latent Variable Model Selection

Author : David Dunson
Publisher : Springer Science & Business Media
ISBN 13 : 0387767215
Total Pages : 174 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Random Effect and Latent Variable Model Selection by : David Dunson

Download or read book Random Effect and Latent Variable Model Selection written by David Dunson and published by Springer Science & Business Media. This book was released on 2010-03-18 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Random Effect and Latent Variable Model Selection In recent years, there has been a dramatic increase in the collection of multivariate and correlated data in a wide variety of ?elds. For example, it is now standard pr- tice to routinely collect many response variables on each individual in a study. The different variables may correspond to repeated measurements over time, to a battery of surrogates for one or more latent traits, or to multiple types of outcomes having an unknown dependence structure. Hierarchical models that incorporate subje- speci?c parameters are one of the most widely-used tools for analyzing multivariate and correlated data. Such subject-speci?c parameters are commonly referred to as random effects, latent variables or frailties. There are two modeling frameworks that have been particularly widely used as hierarchical generalizations of linear regression models. The ?rst is the linear mixed effects model (Laird and Ware , 1982) and the second is the structural equation model (Bollen , 1989). Linear mixed effects (LME) models extend linear regr- sion to incorporate two components, with the ?rst corresponding to ?xed effects describing the impact of predictors on the mean and the second to random effects characterizing the impact on the covariance. LMEs have also been increasingly used for function estimation. In implementing LME analyses, model selection problems are unavoidable. For example, there may be interest in comparing models with and without a predictor in the ?xed and/or random effects component.

The Impact of Weights' Specifications with the Multiple Membership Random Effects Model

Author : Jennifer Lynn Galindo
Publisher :
ISBN 13 :
Total Pages : 268 pages
Book Rating : 4.:/5 (92 download)

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Book Synopsis The Impact of Weights' Specifications with the Multiple Membership Random Effects Model by : Jennifer Lynn Galindo

Download or read book The Impact of Weights' Specifications with the Multiple Membership Random Effects Model written by Jennifer Lynn Galindo and published by . This book was released on 2015 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of the simulation was to assess the impact of weight pattern assignment when using the multiple membership random effects model (MMREM). In contrast with most previous methodological research using the MMREM, mobility was not randomly assigned; rather the likelihood of student mobility was generated as a function of the student predictor. Two true weights patterns were used to generate the data (random equal and random unequal). For each set of generated data, the true correct weights and two incorrect fixed weight patterns (fixed equal and fixed unequal) that are similar to those used in practice by applied researchers were used to estimate the model. Several design factors were manipulated including the percent mobility, the ICC, and the true generating values of the level one and level two mobility predictors. To assess parameter recovery, relative parameter bias was calculated for the fixed effects and random effects variance components. Standard error (SE) bias was also calculated for the standard errors estimated for each fixed effect. Substantial relative parameter bias differences between weight patterns used were observed for the level two school mobility predictor across conditions as well as the level two random effects variance component, in some conditions. Substantial SE bias differences between weight patterns used were also found for the school mobility predictor in some conditions. Substantial SE and parameter bias was found for some parameters for which it was not anticipated. The results, discussion, future directions for research, and implications for applied researchers are discussed.

Multilevel Modeling of Categorical Outcomes Using IBM SPSS

Author : Ronald H Heck
Publisher : Routledge
ISBN 13 : 1136672346
Total Pages : 449 pages
Book Rating : 4.1/5 (366 download)

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Book Synopsis Multilevel Modeling of Categorical Outcomes Using IBM SPSS by : Ronald H Heck

Download or read book Multilevel Modeling of Categorical Outcomes Using IBM SPSS written by Ronald H Heck and published by Routledge. This book was released on 2013-05-07 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first workbook that introduces the multilevel approach to modeling with categorical outcomes using IBM SPSS Version 20. Readers learn how to develop, estimate, and interpret multilevel models with categorical outcomes. The authors walk readers through data management, diagnostic tools, model conceptualization, and model specification issues related to single-level and multilevel models with categorical outcomes. Screen shots clearly demonstrate techniques and navigation of the program. Modeling syntax is provided in the appendix. Examples of various types of categorical outcomes demonstrate how to set up each model and interpret the output. Extended examples illustrate the logic of model development, interpretation of output, the context of the research questions, and the steps around which the analyses are structured. Readers can replicate examples in each chapter by using the corresponding data and syntax files available at www.psypress.com/9781848729568. The book opens with a review of multilevel with categorical outcomes, followed by a chapter on IBM SPSS data management techniques to facilitate working with multilevel and longitudinal data sets. Chapters 3 and 4 detail the basics of the single-level and multilevel generalized linear model for various types of categorical outcomes. These chapters review underlying concepts to assist with trouble-shooting common programming and modeling problems. Next population-average and unit-specific longitudinal models for investigating individual or organizational developmental processes are developed. Chapter 6 focuses on single- and multilevel models using multinomial and ordinal data followed by a chapter on models for count data. The book concludes with additional trouble shooting techniques and tips for expanding on the modeling techniques introduced. Ideal as a supplement for graduate level courses and/or professional workshops on multilevel, longitudinal, latent variable modeling, multivariate statistics, and/or advanced quantitative techniques taught in psychology, business, education, health, and sociology, this practical workbook also appeals to researchers in these fields. An excellent follow up to the authors’ highly successful Multilevel and Longitudinal Modeling with IBM SPSS and Introduction to Multilevel Modeling Techniques, 2nd Edition, this book can also be used with any multilevel and/or longitudinal book or as a stand-alone text introducing multilevel modeling with categorical outcomes.