Statistical and Substantive Checking in Growth Mixture Modeling: Comment on Bauer and Curran (2003).
University of California, Los Angeles
Indexed incrossrefpubmed
Abstract
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.
Citation impact
686
total citations
- FWCI
- 8.97
- Percentile
- 100%
- References
- 17
Citations per year
Authors
1Topics & keywords
Topics
Keywords
- Curran
- Latent growth modeling
- Dropout (neural networks)
- Equifinality
- Statistical model
- Class (philosophy)
- Mixture model
- Latent class model
UN Sustainable Development Goals
- Quality Education
No related works found for this paper.