Encyclopedia of Criminology and Criminal Justice

2014 Edition
| Editors: Gerben Bruinsma, David Weisburd

Propensity Score Matching

  • Ben Grunwald
  • John M. MacDonald
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-5690-2_46

Overview

Multivariate regression-based methods dominate the research literature in criminology for estimating the effects of causal variables. As many scholars have noted, however, regression suffers from a number of methodological and practical limitations (Berk 2004). On its own, regression provides a poor analytic framework for conceptualizing causal inference, offers limited tools to address nonlinear relationships, and encourages researchers to cherry-pick models in a manner that may bias the results of a study. Despite these issues, criminologists have failed to take full advantage of other approaches to observational research developed in the fields of statistics and biostatistics.

One alternative is propensity score matching (Rosenbaum and Rubin 1983), an analytic method closely associated with the Rubin Causal Model (RCM; Rubin 2008; Holland 1986). Though a number of criminological studies have used propensity score approaches (e.g., Haviland et al. 2007; MacDonald et al. 2007...

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Notes

Acknowledgements

The data used in this case study were originally collected as part of a grant funded by the National Institute on Drug Abuse (NIDA) (grant R01DA16722) to Andrew Morral at the RAND Corporation. The opinions expressed in this entry are those of the authors and do not represent the official positions of NIDA or the RAND Corporation.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of CriminologyUniversity of PennsylvaniaPhiladelphiaUSA