SAS now has the PSMATCH procedure which should be your starting point, if you have SAS 9.4 TS1M5+.    This link has fully worked examples about half way down.  https://support.sas.com/rnd/app/stat/procedures/psmatch.html PSMATCH Procedure The PSMATCH procedure provides a variety of tools for performing propensity score analysis. The PSMATCH procedure reduces the effects of confounding in nonrandomized trials or observational studies where the subjects are not randomly assigned to the treatment and control groups. The PSMATCH procedure computes propensity scores, which estimate the probability that a subject is assigned to treatment given a set of pretreatment (baseline) covariates. The following methods for using the propensity scores to adjust the data for valid estimation of treatment effect are available: Inverse probability of treatment weighting and weighting by the odds. Stratification of observations that have similar propensity scores. In a subsequent outcome analysis, the treatment effect can be estimated within each stratum, and the estimates can be combined across strata to compute an average treatment effect. Matching treated unit with one or more control units that have a similar value of the propensity score. Methods of matching include: fixed ratio matching variable ratio matching full matching Provides various plots for assessing balance. Included plots are: cloud plots, which are scatter plots in which the points are jittered to prevent overplotting box plots for continuous variables bar charts for classification variables a standardized differences plot that summarizes differences between the treated and control groups The PSMATCH procedures saves propensity scores and weights in an output data set that contains a sample that has been adjusted either by weighting, stratification, or matching. If the sample is stratified, you can save the strata identification in the output data set. If the sample is matched, you can save the matching identification in the output data set. ... View more