ERIC Number: EJ1028225
Record Type: Journal
Publication Date: 2014
Abstractor: As Provided
Reference Count: 36
Multilevel Latent Class Analysis: Parametric and Nonparametric Models
Finch, W. Holmes; French, Brian F.
Journal of Experimental Education, v82 n3 p307-333 2014
Latent class analysis is an analytic technique often used in educational and psychological research to identify meaningful groups of individuals within a larger heterogeneous population based on a set of variables. This technique is flexible, encompassing not only a static set of variables but also longitudinal data in the form of growth mixture modeling, as well as the application to complex multilevel sampling designs. The goal of this study was to investigate--through a Monte Carlo simulation study--the performance of several methods for parameterizing multilevel latent class analysis. Of particular interest was the comparison of several such models to adequately fit Level 1 (individual) data, given a correct specification of the number of latent classes at both levels (Level 1 and Level 2). Results include the parameter estimation accuracy as well as the quality of classification at Level 1.
Descriptors: Nonparametric Statistics, Multivariate Analysis, Monte Carlo Methods, Computation, Accuracy, Classification, Identification
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Authoring Institution: N/A