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Sage Publishing Latent Class and Discrete Latent Trait Models - Advanced Quantitative Techniques

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Description

This comprehensive guide by Ton Heinen examines the latent class model and its applications across social science research, offering detailed exploration of similarities and differences between latent class and latent trait models. The book serves as an essential resource for researchers seeking to understand how latent class analysis functions as a powerful instrument for data reduction, enabling flexible analysis of structural relationships between categorical variables whilst accounting for measurement error. Through careful examination of parameter estimation methods and model selection techniques, this volume extends the log-linear model framework to provide social scientists with practical tools for sophisticated quantitative analysis. Part of the Advanced Quantitative Techniques in the Social Sciences series from Sage Publications, it bridges theoretical foundations with applied methodology for professionals and academics working with complex categorical data.

Key Features

Explores the latent class model as a data reduction instrument used widely by social scientists for categorical variable analysis.

Compares latent class and latent trait models to clarify methodological distinctions and appropriate applications in research.

Covers parameter estimation techniques and model selection methods essential for implementing latent class analysis effectively.

Addresses measurement error correction through extension of log-linear model approaches in the latent class framework.

Part of the Advanced Quantitative Techniques in the Social Sciences series, providing structured learning for quantitative researchers.

Written by Ton Heinen and published by Sage Publications for academic and professional audiences in social science disciplines.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
11 June 1996
Listed Since
31 January 2007

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