Nonlongitudinal Estimation of Growth Curve Parameters: The Cohort Growth Model. Issue 3 (4th May 2019)

• Record Type: Journal Article
• Authors: Fischer, Kevin A.; Klein, Andreas G.; Reinecke, Jost
• Is Part Of: Structural equation modeling. Volume 26:Issue 3(2019)
• Page Start: 402
• Page End: 417
• Publication Date: 2019-05-04
• Subjects: growth curve models -- cross-sectional research designs -- simulation study -- delinquency behavior; Multivariate analysis -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 519.535
• DOI: 10.1080/10705511.2018.1533834
• Languages: English
• ISSNs: 1070-5511

Abstract

Abstract : The cohort growth model (CGM) is a method for estimating the parameters of a latent growth model (LGM) based on cross-sectional data. The CGM models the interindividual differences in the growth rate, and it models how subjects' growth rate is related to their initial status. We derive model identification for the CGM and illustrate, in a simulation study, that the CGM provides unbiased parameter estimates in most simulation conditions. Based on empirical data we compare the estimates of the CGM with the estimates of the LGM. The results were comparable for both models. Although the estimates of the (co)-variances were different, the estimates of both models led to similar conclusions on the developmental change. Finally, we discuss the advantages and limitations of the CGM, and we provide recommendations for its use in empirical research.