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Latent Markov Models for Longitudinal Data

Drawing on the authors' extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data;

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Latent Markov Models for Longitudinal Data

Drawing on the authors' extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data;

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An Introduction to Latent Class Analysis

latent classes, a latent class model approach for analyzing learning structures, the latent Markov analysis for longitudinal data, and path;

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Measurement Error in Longitudinal Data

Markov chains, and equivalence/DIF testing. Finally, the use of vignettes in the context of longitudinal data and estimation methods for;

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Modern Methods for Business Research

by latent growth curve methods and structures, and configural models of longitudinal categorical data.;

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Latent Class and Latent Transition Analysis

for theoretical, technical, and practical issues in cross-sectional and longitudinal data. Plentiful examples enable the reader to acquire a;

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Modern Methods for Business Research

by latent growth curve methods and structures, and configural models of longitudinal categorical data.;

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The EM Algorithm and Related Statistical Models

data problems. The text covers current topics including statistical models with latent variables, as well as neural network models, and Markov;

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Longitudinal Data Analysis Using Structural Equation Models

When determining the most appropriate method for analyzing longitudinal data, you must first consider what research question you want to;

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Generalized Latent Variable Modeling

This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models;

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Latent Curve Models

An effective technique for data analysis in the social sciences The recent explosion in longitudinal data in the social sciences highlights;

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Structural Equation Modeling

, evaluation, and modification. Chapters cover: Confirmatory Factor Analysis (CFA); Structural Equation Models (SEM); SEM for Longitudinal Data; Multi;

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Longitudinal Structural Equation Modeling with Mplus

- and multiple-indicator data. The book discusses measurement equivalence testing, intensive longitudinal data modeling, and missing data;

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Longitudinal Multivariate Psychology

time-dependent changes in population averages. As longitudinal data have recently become much more prevalent in psychology and the social;

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Longitudinal Multivariate Psychology

time-dependent changes in population averages. As longitudinal data have recently become much more prevalent in psychology and the social;

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Longitudinal Structural Equation Modeling

This comprehensive resource reviews structural equation modeling (SEM) strategies for longitudinal data to help readers see which modeling;

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Longitudinal Structural Equation Modeling

This comprehensive resource reviews structural equation modeling (SEM) strategies for longitudinal data to help readers see which modeling;

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Hidden Markov Models for Time Series

HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process New case studies on animal;

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Hidden Markov Models for Time Series

sets online New to the second edition A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi;

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Data Analysis with Mplus

A practical introduction to using Mplus for the analysis of multivariate data, this volume provides step-by-step guidance, complete with;

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Longitudinal Research with Latent Variables

longitudinal data. It is especially in the ?eld of longitudinal research and analysis, including panel research, that progress has been made in recent;

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Longitudinal Research with Latent Variables

longitudinal data. It is especially in the ?eld of longitudinal research and analysis, including panel research, that progress has been made in recent;

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Semi-Markov Models

Featuring previously unpublished results, Semi-Markov Models: Control of Restorable Systems with Latent Failures describes;

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Multivariate Applications in Substance Use Research

; explores methods for analyzing longitudinal data for individuals nested within groups, such as families, classrooms, and treatment groups;

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Multivariate Applications in Substance Use Research

; explores methods for analyzing longitudinal data for individuals nested within groups, such as families, classrooms, and treatment groups;

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Advances in Latent Variable Mixture Models

latent variable mixture models before the volume moves to more specific constellations of topics. Part I, Multilevel and Longitudinal Systems;

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Latent Variable Models and Factor Analysis

numerical examples. Nature and interpretation of a latent variable is also introduced along with related techniques for investigating dependency;

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