Latent Class Analysis: A Guide to Best Practice

Latent class analysis (LCA) is a statistical procedure used to identify qualitatively different subgroups within populations who often share certain outward characteristics. The assumption underlying LCA is that membership in unobserved groups (or classes) can be explained by patterns of scores acro...

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Vydáno v:Journal of black psychology Ročník 46; číslo 4; s. 287 - 311
Hlavní autoři: Weller, Bridget E., Bowen, Natasha K., Faubert, Sarah J.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Los Angeles, CA SAGE Publications 01.05.2020
SAGE PUBLICATIONS, INC
Témata:
Best practice
Latent class analysis
ADHD
social determinants of health
National Survey of Children’s Health
latent class analysis
behavior problems
ISSN:0095-7984, 1552-4558
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Popis
Shrnutí:Latent class analysis (LCA) is a statistical procedure used to identify qualitatively different subgroups within populations who often share certain outward characteristics. The assumption underlying LCA is that membership in unobserved groups (or classes) can be explained by patterns of scores across survey questions, assessment indicators, or scales. The application of LCA is an active area of research and continues to evolve. As more researchers begin to apply the approach, detailed information on key considerations in conducting LCA is needed. In the present article, we describe LCA, review key elements to consider when conducting LCA, and provide an example of its application.
Bibliografie:ObjectType-Article-1
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ISSN:0095-7984
1552-4558
DOI:10.1177/0095798420930932