Nonlongitudinal Estimation of Growth Curve Parameters: The Cohort Growth Model

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.

Keywords:

• growth curve models
• cross-sectional research designs
• simulation study
• delinquency behavior

Notes

¹ Between 2011 and 2016, the study was embedded as Project A2 within the Collaborative Research Center 882 “From Heterogeneties to Inequalities” at the Faculty of Sociology, Bielefeld University, Germany.

² Although the survey should provide the broadest possible basis for a panel dataset, the sampling process included a stratification towards lower-track schools to obtain sufficient numbers of delinquent behaviors. Due to different state law regulations in Nuremberg the sample was drawn to include only students of lower track schools, while in Dortmund all types of secondary schools participated in the survey.

Additional information

Funding

This work was supported by the Deutsche Forschungsgemeinschaft. The empirical data set ‘Chances and Risks in the Life Course’ was supported by the German Research Foundation (DFG) under grant number INST 215/399.