An Introduction to Latent Variable Mixture Modeling (Part 1): Overview and Cross-Sectional Latent Class and Latent Profile Analyses | Zendy

Kristoffer S. Berlin | Zendy; Natalie A. Williams | Zendy; Gilbert R. Parra | Zendy

Open Access

An Introduction to Latent Variable Mixture Modeling (Part 1): Overview and Cross-Sectional Latent Class and Latent Profile Analyses

Author(s) -

Kristoffer S. Berlin,

Natalie A. Williams,

Gilbert R. Parra

Publication year - 2013

Publication title -

journal of pediatric psychology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.054

H-Index - 121

eISSN - 1465-735X

pISSN - 0146-8693

DOI - 10.1093/jpepsy/jst084

Subject(s) - latent class model , latent variable , latent variable model , latent heat , probabilistic latent semantic analysis , structural equation modeling , mixture model , psychology , computer science , statistics , mathematics , artificial intelligence , physics , thermodynamics

Pediatric psychologists are often interested in finding patterns in heterogeneous cross-sectional data. Latent variable mixture modeling is an emerging person-centered statistical approach that models heterogeneity by classifying individuals into unobserved groupings (latent classes) with similar (more homogenous) patterns. The purpose of this article is to offer a nontechnical introduction to cross-sectional mixture modeling.

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