Latent Variable and Latent Structure Models

✍ Scribed by Marcoulides, George A.; Moustaki, Irini

Publisher: Taylor and Francis
Year: 2014
Tongue: English
Leaves: 296
Series: Quantitative Methodology Series
Category: Library

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✦ Synopsis

This edited volume features cutting-edge topics from the leading researchers in the areas of latent variable modeling. Content highlights include coverage of approaches dealing with missing values, semi-parametric estimation, robust analysis, hierarchical data, factor scores, multi-group analysis, and model testing. New methodological topics are illustrated with real applications. The material presented brings Read more...

Abstract:

Based on material presented at the 22nd Conference of the Society for Multivariate Analysis in the Behavioral Sciences (July 2000), these 12 papers describe original research and developments Read more...

✦ Table of Contents

Content: Contents: Preface. D.J. Bartholomew, Old and New Approaches to Latent Variable Modelling. I. Moustaki, C. O'Muircheartaigh, Locating "Don't Know," "No Answer" and Middle Alternatives on an Attitude Scale: A Latent Variable Approach. L.A. van der Ark, B.T. Hemker, K. Sijtsma, Hierarchically Related Nonparametric IRT Models, and Practical Data Analysis Methods. P. Tzamourani, M. Knott, Fully Semiparametric Estimation of the Two-Parameter Latent Trait Model for Binary Data. P. Rivera, A. Satorra, Analyzing Group Differences: A Comparison of SEM Approaches. R.D. Wiggins, A. Sacker, Strategies for Handling Missing Data in SEM: A User's Perspective. T. Raykov, S. Penev, Exploring Structural Equation Model Misspecifications Via Latent Individual Residuals. J-Q. Shi, S-Y. Lee, B-C. Wei, On Confidence Regions of SEM Models. P. Filzmoser, Robust Factor Analysis: Methods and Applications. M. Croon, Using Predicted Latent Scores in General Latent Structure Models. H. Goldstein, W. Browne, Multilevel Factor Analysis Modelling Using Markov Chain Monte Carlo Estimation. J-P. Fox, C.A.W. Glas, Modelling Measurement Error in Structural Multilevel Models.

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