Latent Variable and Latent Structure Models

Herausgeber: Marcoulides, George A; Moustaki, Irini

• Gebundenes Buch

Produktbeschreibung

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 together two traditions: psychometrics and structural equation modeling. "Latent Variable and Latent Structure Models'" thought-provoking chapters from the leading researchers in the area will help to stimulate ideas for further research for many years to come. This volume will be of interest to researchers and practitioners from a wide variety of disciplines, including biology, business, economics, education, medicine, psychology, sociology, and other social and behavioral sciences. A working knowledge of basic multivariate statistics and measurement theory is assumed.

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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: Taylor & Francis Ltd (Sales)
• Seitenzahl: 292
• Erscheinungstermin: 1. März 2002
• Englisch
• Abmessung: 236mm x 161mm x 24mm
• Gewicht: 585g
• ISBN-13: 9780805840469
• ISBN-10: 080584046X
• Artikelnr.: 22115909

Inhaltsangabe

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.