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Statistical and Substantive Checking in Growth Mixture Modeling

Comment on Bauer and Curran (2003).

Bibliographic Data

ID23323675
AuthorsBengt Muthén (0000-0001-9308-6525, University of California, Los Angeles, corresponding author)
Year2003
Volume8
Issue3
Pages369-377
Publication date2003-09-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenuePsychological Methods (JOURNAL)
Journal identifiersISSN: 1082-989X • E-ISSN: 1939-1463
PublisherAmerican Psychological Association (APA) (PUBLISHER)
DOI10.1037/1082-989x.8.3.369
PMID14596497
OpenAlexW2094358882
LanguageEN
Citations received191
References cited7

This commentary discusses the D. J. Bauer and P. J. Curran (2003) investigation of growth mixture modeling. Single-class modeling of nonnormal outcomes is compared with modeling with multiple latent trajectory classes. New statistical tests of multiple-class models are discussed. Principles for substantive investigation of growth mixture model results are presented and illustrated by an example of high school dropout predicted by low mathematics achievement development in Grades 7-10.

Class (philosophy) · Curran · Dropout (neural networks) · Econometrics · Equifinality · Latent class model · Latent growth modeling · Machine learning · Mathematics education · Mixture model · Statistical analysis · Statistical model · Statistics · Structural equation modeling · Artificial Intelligence · Bayesian Methods and Mixture Models · Computer Science · Mathematics · Psychology · Statistical Methods and Bayesian Inference · Statistics Education and Methodologies

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Citations per year8,68
Citation span2004 - 2026 (23)
Citation velocitycurrent
Highly citedYes
Citation typesNeutral: 168

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