This chapter provides an overview of a group-based statistical methodology for analyzing developmental trajectories—the evolution of an outcome over age or time. A detailed account of the method’s statistical underpinnings and a full range of applications are provided in Nagin (2005).
This research has been supported by the National Science Foundation (NSF) (SES-99113700; SES-0647576) and the National Institute of Mental Health (RO1 MH65611-01A2).
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Notes
- 1.
Propensity score matching is a form of quasi-experimental analysis of non-experimental data developed by Rosenbaum and Rubin (1983). It is designed to balance observed differences between individuals experiencing and not experiencing some life event or receiving or not receiving a specified treatment. By balancing those observed covariates between the treated and untreated, they can be ruled out as potential confounders of the estimated treatment effect.
- 2.
I thank Steven Durlauf and Wayne Osgood for pointing out this important distinction.
- 3.
For example, when Moffitt (1993, 1997) uses the terms “life-course-persistent offenders” and “adolescence-limited offenders,” she is using these labels to describe two distinct clusters of developmental trajectories. Even if it were possible to pose a single distribution function that describes both clusters of individuals, this would not vitiate her theoretical conception of them as distinct groups.
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Nagin, D.S. (2009). Group-Based Modeling: An Overview. In: Krohn, M., Lizotte, A., Hall, G. (eds) Handbook on Crime and Deviance. Handbooks of Sociology and Social Research. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0245-0_4
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