Ho, D.E., Imai, K., King, G., and Stuart, E.A. (in press). MatchIt: Nonparametric preprocessing for parameteric causal inference. Forthcoming, Journal of Statistical Software.
Two-step process: does matching, then user does outcome analysis (integrated with Zelig package for R)
Wide array of estimation procedures and matching methods available: nearest neighbor, Mahalanobis, caliper, exact, full, optimal, subclassification
Sekhon, J. S. (in press). Matching: Multivariate and propensity score matching with balance optimization. Forthcoming, Journal of Statistical Software.
Uses automated procedure to select matches, based on univariate and multivariate balance diagnostics
Primarily 1:M matching (where M is a positive integer), allows matching with or without replacement, caliper, exact
Includes built-in effect and variance estimation procedures
Helmreich, J.E. and Pruzek, R.M. (2009). PSAgraphics: An R Package to Support Propensity Score Analysis. Journal of Statistical Software 29(6).
Available here.
From webpage: "A collection of functions that primarily produce graphics to aid in a Propensity Score Analysis (PSA). Functions include: cat.psa and box.psa to test balance within strata of categorical and
quantitative covariates, circ.psa for a representation of the estimated effect size by stratum, loess.psa that provides a graphic and loess based effect size estimate, and various balance functions
that provide measures of the balance achieved via a PSA in a categorical covariate."
Leuven, E. and Sianesi, B. (2003). psmatch2. Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing.
Abadie, A., Drukker, D., Herr, J. L., and Imbens, G. W. (2004). Implementing matching estimators for average treatment effects in Stata. The Stata Journal 4(3): 290-311.
Available here.
Primarily k:1 matching (with replacement)
Allows estimation of ATT or ATE, including robust variance estimators
Parsons, L. S. (2001). Reducing bias in a propensity score matched-pair sample using greedy matching techniques. In SAS SUGI 26, Paper 214-26.
Available here.
Parsons, L.S. (2005). Using SAS software to perform a case-control match on propensity score in an observational study. In SAS SUGI 30, Paper 225-25.
Available here.