Latent Class and Discrete Latent Trait Models: Similarities and Differences (Advanced Quantitative Techniques in the Social Sciences)

Dr. Ton Heinen

ISBN 10: 0803974337 / ISBN 13: 9780803974333

Published by Sage Publications, Inc, 1996

About this Item

209 pages. 9.50x6.50x0.75 inches. In Stock.

Seller Inventory # x-0803974337

Bibliographic Details

• Title: Latent Class and Discrete Latent Trait Models: Similarities and Differences (Advanced Quantitative Techniques in the Social Sciences)
• Publisher: Sage Publications, Inc
• Publication Date: 1996
• Language: English
• ISBN 10: 0803974337
• ISBN 13: 9780803974333
• Binding: Hardcover
• Condition: Brand New
• Weight: 0.57 kilograms

About this title

Synopsis

The standard latent class model. It has been popular among social scientists as an instrument for data reduction, as a flexible tool for analyzing structural relationships between categorical variables, and as a natural extension of the log-linear model in order to take measurement error into account. What, however, are the similarities and differences between the latent class model and latent trait models? Through a careful examination of these issues, author Ton Heinen explores such topics as how to estimate the parameters of latent class analysis models as well as the methods for model selection and ways to examine the correspondence between discrete latent trait models and certain restricted latent class models. In addition, he reviews log-linear models, latent trait models, and a number of restricted latent class models in detail as well as for the estimation of parameters for these models. Readers who would like to see how the estimation of the parameters in latent trait models plays a role in the correspondence between latent class and latent trait models will find Latent Class and Discrete Latent Trait Models a fascinating read.

Review

"Although there are differences between latent class and latent trait models, the author of this very readable book delineates the similarities between these modeling approaches." 

Source: Journal of Mathematical Psychology