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Quantitative Applications in the Social Sciences #64: Latent Class Analysis

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Quantitative Applications in the Social Sciences #64: Latent Class Analysis Cover

 

Synopses & Reviews

Synopsis:

Latent class analysis is a powerful tool for analyzing the structure of relationships among categorically scored variables. It enables researchers to explore the suitability of combining two or more categorical variables into typologies or scales. It also provides a method for testing hypotheses regarding the latent structure among categorical variables.

Synopsis:

This important method provides researchers with a powerful and flexible new technique for analyzing the structure of relationships among categorically scored variables. Frequently described as a "categorical data analogue to factor analysis," the method enables researchers to explore the suitability of combining two or more categorical variables into typologies or scales.

Product Details

ISBN:
9780803927520
Author:
Mccutcheon, Allan L.
Publisher:
Sage Publications (CA)
Editor:
McCutcheon, Allan L.
Author:
McCutcheon, Allan L.
Author:
McCutcheon
Author:
McCutcheon, Pam
Location:
Newbury Park, Calif. :
Subject:
Research
Subject:
Latent variables.
Subject:
Latent structure analysis.
Subject:
Probability & Statistics - Multivariate Analysis
Subject:
Mathematics - General
Edition Description:
Bibliography: p. 93-96.
Series:
Quantitative Applications in the Social Sciences
Series Volume:
64
Publication Date:
19870531
Binding:
TRADE PAPER
Language:
English
Illustrations:
Yes
Pages:
96
Dimensions:
850x550

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Related Subjects

History and Social Science » Sociology » Reference and Methodology
Science and Mathematics » Mathematics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics

Quantitative Applications in the Social Sciences #64: Latent Class Analysis New Trade Paper
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Product details 96 pages Sage Publications - English 9780803927520 Reviews:
"Synopsis" by , Latent class analysis is a powerful tool for analyzing the structure of relationships among categorically scored variables. It enables researchers to explore the suitability of combining two or more categorical variables into typologies or scales. It also provides a method for testing hypotheses regarding the latent structure among categorical variables.
"Synopsis" by , This important method provides researchers with a powerful and flexible new technique for analyzing the structure of relationships among categorically scored variables. Frequently described as a "categorical data analogue to factor analysis," the method enables researchers to explore the suitability of combining two or more categorical variables into typologies or scales.
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