A SAS Procedure Based on Mixture Models for Estimating Developmental Trajectories

Bobby L. Jones, Daniel S. Nagin and Kathryn Roeder
Additional contact information
Bobby L. Jones: Carnegie Mellon University
Daniel S. Nagin: Carnegie Mellon University
Kathryn Roeder: Carnegie Mellon University

Sociological Methods & Research, 2001, vol. 29, issue 3, 374-393

Abstract: This article introduces a new SAS procedure written by the authors that analyzes longitudinal data (developmental trajectories) by fitting a mixture model. The TRAJ procedure fits semiparametric (discrete) mixtures of censored normal, Poisson, zero-inflated Poisson, and Bernoulli distributions to longitudinal data. Applications to psychometric scale data, offense counts, and a dichotomous prevalence measure in violence research are illustrated. In addition, the use of the Bayesian information criterion to address the problem of model selection, including the estimation of the number of components in the mixture, is demonstrated.

Date: 2001
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0049124101029003005 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:somere:v:29:y:2001:i:3:p:374-393

DOI: 10.1177/0049124101029003005

Access Statistics for this article

More articles in Sociological Methods & Research
Bibliographic data for series maintained by SAGE Publications ().