Publication Type
Journal Article
Version
publishedVersion
Publication Date
8-2026
Abstract
Despite the use of latent growth mixture modelling (LGMM) to study longitudinal changes, existing practices may inadvertently impede this very investigation. Although subgroup trajectories may theoretically differ in their structure (e.g., some subgroups being linear, some curvilinear), the current convention advocates overreliance on the baseline model to derive subsequent profile trajectories, which may obscure these structural differences. In this article, we provide a brief description of extant LGMM practices, after which we explicate the pitfalls of the current approach. Finally, we provide a principled approach for LGMM research moving forward. Specifically, we recommend specifying a set of theoretically plausible models that differ in the number of growth factors and selecting the most expansive model that demonstrates acceptable fit to the data.
Keywords
longitudinal change, latent growth mixture modelling, model fit
Discipline
Psychology | Statistics and Probability
Research Areas
Psychology
Areas of Excellence
Digital transformation
Publication
International Journal of Behavioral Development
First Page
1
Last Page
8
ISSN
0165-0254
Identifier
10.1177/01650254261471350
Publisher
Sage
Citation
CHIA, Jonathan L., WETTSTEIN, Markus, & HARTANTO, Andree.(2026). When the best-fit model is not best: The Glass Slipper Fallacy and latent growth mixture modelling. International Journal of Behavioral Development, , 1-8.
Available at: https://ink.library.smu.edu.sg/soss_research/4483
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1177/01650254261471350