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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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Latent Variable and Latent Structure Models

-group analysis, and model testing. New methodological topics are illustrated with real applications. The material presented brings together two;

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Latent Variable and Latent Structure Models

-group analysis, and model testing. New methodological topics are illustrated with real applications. The material presented brings together two;

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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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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 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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Latent Markov Models for Longitudinal Data

focuses on the formulation of latent Markov models and the practical use of these models. Numerous examples illustrate how latent Markov models;

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Latent Markov Models for Longitudinal Data

focuses on the formulation of latent Markov models and the practical use of these models. Numerous examples illustrate how latent Markov models;

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Latent Variable Models

communicating about latent variable models. The informal writing style and the numerous illustrative examples make the book accessible to readers;

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Latent Variable Models

communicating about latent variable models. The informal writing style and the numerous illustrative examples make the book accessible to readers;

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Generalized Latent Variable Modeling

latent variable modeling, the authors clearly explain and contrast a wide range of estimation and prediction methods from biostatistics;

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Handbook of Latent Variable and Related Models

among observed and latent variables.- Covers a wide class of important models- Models and statistical methods described;

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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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Latent Variable Modeling with R

of the data using R, the relevant theory, the assumptions underlying the model, and other statistical details to help readers better understand;

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Latent Variable Modeling with R

of the data using R, the relevant theory, the assumptions underlying the model, and other statistical details to help readers better understand;

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

then special topics such as missing data models, LGM power and Monte Carlo estimation, and latent growth interaction models. The model;

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Statistical Factor Analysis And Related Methods

Statistical Factor Analysis and Related Methods Theory and Applications In bridging the gap between the mathematical and statistical theory;

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Advances in Latent Class Analysis

spanning several decades helped the method to expand and reach its current potential. The current volume in the Center for Integrated Latent;

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Structural Equation Models

development in its proper historical context-essential to understanding the application, strengths and weaknesses of each particular method. This book;

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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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Latent Curve Models

its emphasis on modeling and the use of numerous examples, this is an excellent book for graduate courses in latent trajectory models as well;

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An Introduction to Latent Class Analysis

This book provides methods and applications of latent class analysis, and the following topics are taken up in the focus of discussion;

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Capture-Recapture Methods for the Social and Medical Sciences

which allow the application of these methods. It has contributions from more than 40 researchers, and is divided into eight parts, including;

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Capture-Recapture Methods for the Social and Medical Sciences

which allow the application of these methods. It has contributions from more than 40 researchers, and is divided into eight parts, including;

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Modern Methods for Business Research

generalizability theory, latent trait and latent class models, and multi-faceted Rasch modeling. The chapters on decision analysis feature applied location;

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