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ERIC Number: EJ911283
Record Type: Journal
Publication Date: 2011
Pages: 20
Abstractor: As Provided
Reference Count: 21
ISSN: ISSN-1070-5511
Conducting Confirmatory Latent Class Analysis Using M"plus"
Finch, W. Holmes; Bronk, Kendall Cotton
Structural Equation Modeling: A Multidisciplinary Journal, v18 n1 p132-151 2011
Latent class analysis (LCA) is an increasingly popular tool that researchers can use to identify latent groups in the population underlying a sample of responses to categorical observed variables. LCA is most commonly used in an exploratory fashion whereby no parameters are specified a priori. Although this exploratory approach is reasonable when very little prior research has been conducted in the area under study, it can be very limiting when much is already known about the variables and population. Confirmatory latent class analysis (CLCA) provides researchers with a tool for modeling and testing specific hypotheses about response patterns in the observed variables. CLCA is based on placing specific constraints on the parameters to reflect these hypotheses. The popular and easy-to-use latent variable modeling software package M"plus" can be used to conduct a variety of CLCA types using these parameter constraints. This article focuses on the basic principles underlying the use of CLCA, and the M"plus" programming code necessary for carrying it out. (Contains 7 tables.)
Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A