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

2013Journal of Pediatric Psychology引用 932

Psychometric Methodologies and TestingBayesian Methods and Mixture ModelsStatistical Methods and Bayesian Inference

Statistical Methods and Bayesian Inference Bayesian Methods and Mixture Models Psychometric Methodologies and Testing

作者

摘要

OBJECTIVE: 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. METHOD: An overview of latent variable mixture modeling is provided and 2 cross-sectional examples are reviewed and distinguished. RESULTS: Step-by-step pediatric psychology examples of latent class and latent profile analyses are provided using the Early Childhood Longitudinal Study-Kindergarten Class of 1998-1999 data file. CONCLUSIONS: Latent variable mixture modeling is a technique that is useful to pediatric psychologists who wish to find groupings of individuals who share similar data patterns to determine the extent to which these patterns may relate to variables of interest.

作者查看全部 (3)

Gilbert R. Parra

Natalie A. Williams

Kristoffer S. Berlin

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

详细信息

摘要

作者查看全部 (3)

相关技术查看全部 (3)

相关事件

相关文章