Advances in Latent Variable Mixture Models

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Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models

mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, a wide range of estimation and prediction methods from biostatistics, psychometrics, econometrics

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Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis

This book introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. This approach helps less mathematically inclined students grasp

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Measurement Error and Latent Variables in Econometrics, Volume 37 (Advanced Textbooks in Economics)

models (SEMs), a very general and important class of models, with the LISREL model as its best-known representation, encompassing almost all linear equation systems with latent variables

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A Primer on Experiments with Mixtures

the leverage of certain design points Models containing ratios of the components, Cox's mixture polynomials, and the fitting of a slack variable model A review of least squares and the analysis of variance

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Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences

, and practical issues in categorical latent variable modeling for both cross-sectional and longitudinal data.

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An Introduction to Latent Variable Growth Curve Modeling: Concepts, Issues, and Applications, Second Edition (Quantitative Methodology Series)

This volume presents Latent Variable Growth Curve Modeling for analyzing repeated measures. It is likely that most readers have already mastered many of LGM's underpinnings, in as much as repeated

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Latent Curve Models: A Structural Equation Perspective (Wiley Series in Probability and Statistics)

of research and findings and, at the same time, provide original results. The book analyzes LCMs from the perspective of structural equation models (SEMs) with latent variables. While the authors discuss simple

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Intermediate Probability: A Computational Approach

, and convergence concepts, to more advanced ones which are usually not addressed at this mathematical level, or have never previously appeared in textbook form. The author adopts a computational approach throughout

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Structural Equation Modeling: A Second Course

: Extensions. Evaluating Between-Group Differences in Latent Variable Means, Marilyn S. Thompson & Samuel B. Green. Using Latent Growth Models to Evaluate Longitudinal Change, Gregory R. Hancock & Frank

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Statistical Methods for the Evaluation of Educational Services and Quality of Products (Contributions to Statistics)

factors, e.g. the satisfaction, calling for the use of latent variables models; the simultaneous presence of components of pleasure and components of uncertainty in the explication of the judgments

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