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A SAS Procedure Based on Mixture Models for Estimating Developmental Trajectories

Author

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  • BOBBY L. JONES

    (Carnegie Mellon University)

  • DANIEL S. NAGIN

    (Carnegie Mellon University)

  • KATHRYN ROEDER

    (Carnegie Mellon University)

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.

Suggested Citation

  • Bobby L. Jones & Daniel S. Nagin & Kathryn Roeder, 2001. "A SAS Procedure Based on Mixture Models for Estimating Developmental Trajectories," Sociological Methods & Research, , vol. 29(3), pages 374-393, February.
    • Handle: RePEc:sae:somere:v:29:y:2001:i:3:p:374-393
    DOI: 10.1177/0049124101029003005
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    1. Bengt Muthén, 1989. "Latent variable modeling in heterogeneous populations," Psychometrika, Springer;The Psychometric Society, vol. 54(4), pages 557-585, September.
    2. William Meredith & John Tisak, 1990. "Latent curve analysis," Psychometrika, Springer;The Psychometric Society, vol. 55(1), pages 107-122, March.
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    1. Min Hua Jen & Ron Johnston & Kelvyn Jones & Richard Harris & Axel Gandy, 2010. "International Variations In Life Expectancy: A Spatio‐Temporal Analysis," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 101(1), pages 73-90, February.
    2. Sridharan, Sanjeev & Jones, Bobby & Caudill, Barry & Nakaima, April, 2016. "Steps towards incorporating heterogeneities into program theory: A case study of a data-driven approach," Evaluation and Program Planning, Elsevier, vol. 58(C), pages 88-97.
    3. Michael S. Pollard & Harold D. Green & David P. Kennedy & Myong-Hyun Go & Joan S. Tucker, 2013. "Adolescent Friendship Networks and Trajectories of Binge Drinking," Working Papers WR-998, RAND Corporation.
    4. Daniel McNeish & Jeffrey R. Harring, 2017. "The Effect of Model Misspecification on Growth Mixture Model Class Enumeration," Journal of Classification, Springer;The Classification Society, vol. 34(2), pages 223-248, July.
    5. Silvia Montagna & Surya T. Tokdar & Brian Neelon & David B. Dunson, 2012. "Bayesian Latent Factor Regression for Functional and Longitudinal Data," Biometrics, The International Biometric Society, vol. 68(4), pages 1064-1073, December.
    6. Jennings, Wesley G. & Loeber, Rolf & Ahonen, Lia & Piquero, Alex R. & Farrington, David P., 2018. "An examination of developmental patterns of chronic offending from self-report records and official data: Evidence from the Pittsburgh Girls Study (PGS)," Journal of Criminal Justice, Elsevier, vol. 55(C), pages 71-79.
    7. Patrick Sturgis & Louise Sullivan, 2008. "Exploring social mobility with latent trajectory groups," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 65-88, January.
    8. Frank Rijmen & Edward H. Ip & Stephen Rapp & Edward G. Shaw, 2008. "Qualitative longitudinal analysis of symptoms in patients with primary and metastatic brain tumours," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(3), pages 739-753, June.
    9. Karlamangla, Arun S. & Singer, Burton H. & Williams, David R. & Schwartz, Joseph E. & Matthews, Karen A. & Kiefe, Catarina I. & Seeman, Teresa E., 2005. "Impact of socioeconomic status on longitudinal accumulation of cardiovascular risk in young adults: the CARDIA Study (USA)," Social Science & Medicine, Elsevier, vol. 60(5), pages 999-1015, March.
    10. LEBIHAN, Laetitia & MAO TAKONGMO, Charles Olivier, 2018. "Mathematics Trajectories and Risk Factors During Childhood," MPRA Paper 88612, University Library of Munich, Germany.
    11. Dirlam, Jonathan & Zheng, Hui, 2017. "Job satisfaction developmental trajectories and health: A life course perspective," Social Science & Medicine, Elsevier, vol. 178(C), pages 95-103.
    12. McDonough, Peggy & Sacker, Amanda & Wiggins, Richard D., 2005. "Time on my side? Life course trajectories of poverty and health," Social Science & Medicine, Elsevier, vol. 61(8), pages 1795-1808, October.
    13. Corrado, Raymond R. & McCuish, Evan C. & Hart, Stephen D. & DeLisi, Matt, 2015. "The role of psychopathic traits and developmental risk factors on offending trajectories from early adolescence to adulthood: A prospective study of incarcerated youth," Journal of Criminal Justice, Elsevier, vol. 43(4), pages 357-368.
    14. Dmytro Babik & Rahul Singh & Xia Zhao & Eric W. Ford, 2017. "What you think and what I think: Studying intersubjectivity in knowledge artifacts evaluation," Information Systems Frontiers, Springer, vol. 19(1), pages 31-56, February.
    15. Simon Larose & Stéphane Duchesne & David Litalien & Anne-Sophie Denault & Michel Boivin, 2019. "Adjustment Trajectories During the College Transition: Types, Personal and Family Antecedents, and Academic Outcomes," Research in Higher Education, Springer;Association for Institutional Research, vol. 60(5), pages 684-710, August.
    16. Norris, Fran H. & Tracy, Melissa & Galea, Sandro, 2009. "Looking for resilience: Understanding the longitudinal trajectories of responses to stress," Social Science & Medicine, Elsevier, vol. 68(12), pages 2190-2198, June.
    17. McCuish, Evan C. & Corrado, Raymond R. & Hart, Stephen D. & DeLisi, Matt, 2015. "The role of symptoms of psychopathy in persistent violence over the criminal career into full adulthood," Journal of Criminal Justice, Elsevier, vol. 43(4), pages 345-356.

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