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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 Variable and Latent Structure Models

This edited volume features cutting-edge topics from the leading researchers in the areas of latent variable modeling. Content highlights;

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Latent Variable and Latent Structure Models

This edited volume features cutting-edge topics from the leading researchers in the areas of latent variable modeling. Content highlights;

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Current Topics in the Theory and Application of Latent Variable Models

This book presents recent developments in the theory and application of latent variable models (LVMs) by some of the most prominent;

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Current Topics in the Theory and Application of Latent Variable Models

This book presents recent developments in the theory and application of latent variable models (LVMs) by some of the most prominent;

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Handbook of Latent Variable and Related Models

This Handbook covers latent variable models, which are a flexible class of models for modeling multivariate data to explore relationships;

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Latent Variable Models and Factor Analysis

Latent Variable Models and Factor Analysis provides a comprehensive and unified approach to factor analysis and latent variable modeling;

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Advances in Latent Class Analysis

What is latent class analysis? If you asked that question thirty or forty years ago you would have gotten a different answer than you would;

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Confirmatory Factor Analysi For Aplie Re

using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities and differences between CFA and;

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Latent Variable Models

Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces latent variable models by utilizing;

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Latent Variable Models

Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces latent variable models by utilizing;

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An Introduction to Latent Variable Growth Curve Modeling: Concepts, Issues, and Application, Second Edition

This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents;

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An Introduction to Latent Variable Growth Curve Modeling

This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents;

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Latent Variable Analysis and Signal Separation

This book constitutes the proceedings of the 12th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICS 2015;

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Generalized Linear Models

This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective;

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Latent Variable Modeling with R

This book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized;

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Latent Variable Modeling with R

This book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized;

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A Primer of Multivariate Statistics

Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable;

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A Primer of Multivariate Statistics

Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable;

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Innovative Psychometric Modeling and Methods

, Chapters 3 and 5 illustrate the usage of generalized linear mixed effect models and item tree models to analyze eye-tracking data. Chapter 8;

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Latent Variable Analysis and Signal Separation

This book constitutes the proceedings of the 13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017;

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Advances in Latent Variable Mixture Models

The current volume, Advances in Latent Variable Mixture Models, contains chapters by all of the speakers who participated in the 2006 CILVR;

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Latent Variable Modeling Using R

This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the;

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Latent Variable Modeling Using R

This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the;

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Advances in Latent Variable Mixture Models

The current volume, Advances in Latent Variable Mixture Models, contains chapters by all of the speakers who participated in the 2006 CILVR;

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Innovative Psychometric Modeling and Methods (hc)

, Chapters 3 and 5 illustrate the usage of generalized linear mixed effect models and item tree models to analyze eye-tracking data. Chapter 8;

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Cross-Cultural Analysis

national data sets such as the latest European Social Survey. With an emphasis on the generalized latent variable approach, internationally;

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