  Propensity score matching is a tool for causal inference in non-randomized
studies that allows for conditioning on large sets of covariates. The use of
propensity scores in the social sciences is currently experiencing a tremendous
increase; however it is far from a commonly used tool. One impediment towards a
more wide-spread use of propensity score methods is the reliance on specialized
software, because many social scientists still use SPSS as their main analysis
tool. The current paper presents an implementation of various propensity score
matching methods in SPSS. Specifically the presented SPSS custom dialog allows
researchers to specify propensity score methods using the familiar
point-and-click interface. The software allows estimation of the propensity
score using logistic regression and specifying nearest-neighbor matching with
many options, e.g., calipers, region of common support, matching with and
without replacement, and matching one to many units. Detailed balance
statistics and graphs are produced by the program.
