The current practice of latent growth curve modeling in the social and behavioral sciences: Observations and Recommendations
- PMID: 40917565
- PMCID: PMC12413013
- DOI: 10.1177/01650254241269723
The current practice of latent growth curve modeling in the social and behavioral sciences: Observations and Recommendations
Abstract
We examine recommendations for three key features of latent growth curve models in the structural equation modeling framework. As a basis for the discussion, we review current practice in the social and behavioral sciences literature as found in 441 reports published in the 19 months beginning in January 2019 and compare our findings to extant recommendations. We then provide suggestions for empirical researchers, reviewing the application of these very popular models, specifically focusing on comparison of alternative change models, time metric and interval features implemented, and the treatment of individually-varying time intervals.
Keywords: guidelines; latent curve models; longitudinal; review.
Conflict of interest statement
The authors report no conflicts of interest. This research was funded by the European Commission, Horizon2020 under grant agreement number: 732592-Lifebrain-H2020-SC1-2016-2017/H2020-SC1-2016-RTD and by NIH grant T32A039772, “Research training in drug abuse prevention: Closing the research-practice gap.”
Figures
References
-
- Baltes PB, & Nesselroade JR (1979). History and rationale of longitudinal research. In Nesselroade JR, & Baltes PB(Eds.), Longitudinal research in the study of behavior and development (pp. 1–39). Academic Press.
-
- Bauer DJ (2007). Observations on the use of growth mixture models in psychological research. Multivariate Behavioral Research, 42, 757–786. doi: 10.1080/00273170701710338 - DOI
Grants and funding
LinkOut - more resources
Full Text Sources
Research Materials