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ERIC Number: EJ1122890
Record Type: Journal
Publication Date: 2017-Jan
Pages: 30
Abstractor: As Provided
ISSN: ISSN-0272-4316
Introduction to Latent Class Analysis with Applications
Porcu, Mariano; Giambona, Francesca
Journal of Early Adolescence, v37 n1 p129-158 Jan 2017
Latent class analysis (LCA) is a statistical method used to group individuals (cases, units) into classes (categories) of an unobserved (latent) variable on the basis of the responses made on a set of nominal, ordinal, or continuous observed variables. In this article, we introduce LCA in order to demonstrate its usefulness to early adolescence researchers. We provide an application of LCA to empirical data collected from a national survey carried out in 2010 in Italy to assess mathematics and reading skills of fifth-grade primary school pupils (10 years in age). The data were used to measure pupils' supplies of cultural capital by specifying a latent class model. This article aims to describe and interpret results of LCA, allowing users to replicate the analysis. All LCA examples included in the text are illustrated using the Latent GOLD package, and command files needed to reproduce all analyses with SAS and R are available as supplemental online appendix files along with the example data files.
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Publication Type: Journal Articles; Reports - Research
Education Level: Elementary Education; Grade 5; Intermediate Grades; Middle Schools
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Italy
Grant or Contract Numbers: N/A