``Propensity-Score Based Methods for Causal Inference in Observational Studies with Fixed Non-Binary Treatments.''



Propensity score methods have become a part of the standard toolkit for applied researchers who wish to ascertain causal effects from observational data. While they were originally developed for binary treatments, several researchers have proposed generalizations of the propensity score methodology for non-binary treatment regimes. Such extensions have widened the applicability of propensity score methods and are indeed becoming increasingly popular themselves. In this article, we closely examine the main methods that generalize propensity scores in this direction, namely, inverse propensity weighting (IPW), the propensity function (P-Function), and the generalized propensity score (GPS), along with recent extensions of the GPS that aim to improve its robustness. We compare the assumptions, theoretical properties, and empirical performance of these methods. On a theoretical level, the GPS and its extensions are advantageous in that they are designed to estimate the full dose response function rather than the average treatment effect that is estimated with the P-Function. IPW, on the other hand, is a very flexible methodology with a wide range of applications extending well beyond the current review. We compare GPS, recent methods that aim to improve its robustness, and IPW-based estimators with a new P-Function method, all of which estimate the dose response function. We illustrate our findings and proposals through simulation studies, including one based on an empirical application. While our proposed P-Function-based estimator preforms well, we generally advise caution in that all available methods can be biased by model misspecification and extrapolation. (Last Revised, December 2013)
You may also be interested in Imai, Kosuke and David A. van Dyk. (2004). ``Causal Inference With General Treatment Regimes: Generalizing the Propensity Score.'' Journal of the American Statistical Association, Vol. 99, No. 467 (September), pp. 854-866.

© Kosuke Imai
 Last modified: Mon Aug 26 16:23:46 EDT 2013