Paper 812-2017: A General SAS® Macro to Implement Optimal N:1 Propensity Score Matching Within a Maximum Radius

A propensity score is the probability that an individual will be assigned to a condition or group, given a set of baseline covariates when the assignment is made. For example, the type of drug treatment given to a patient in a real-world setting might be non-randomly based on the patient's age, gender, geographic location, and socioeconomic status when the drug is prescribed. Propensity scores are used in many different types of observational studies to reduce selection bias. Subjects assigned to different groups are matched based on these propensity score probabilities, rather than matched based on the values of individual covariates. Although the underlying statistical theory behind the use of propensity scores is complex, implementing propensity score matching with SAS® is relatively straightforward. An output data set of each subject's propensity score can be generated with SAS using PROC LOGISTIC. And, a generalized SAS macro can generate optimized N:1 propensity score matching of subjects assigned to different groups using the radius method. Matching can be optimized either for the number of matches within the maximum allowable radius or by the closeness of the matches within the radius. This presentation provides the general PROC LOGISTIC syntax to generate propensity scores, provides an overview of different propensity score matching techniques, and discusses how to use the SAS macro for optimized propensity score matching using the radius method.