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Biometrika 2000 87(3):706-710; doi:10.1093/biomet/87.3.706
© 2000 by Biometrika Trust
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The role of the propensity score in estimating dose-response functions

GW Imbens

Department of Economics, University of California at Los Angeles, Los Angeles, CA 90095, USA E-mail: imbens@econ.ucla.edu

Estimation of average treatment effects in observational studies often requires adjustment for differences in pre-treatment variables. If the number of pre-treatment variables is large, standard covariance adjustment methods are often inadequate. Rosenbaum & Rubin (1983) propose an alternative method for adjusting for pre-treatment variables for the binary treatment case based on the so-called propensity score. Here an extension of the propensity score methodology is proposed that allows for estimation of average casual effects with multi-valued treatments.

Key Words: causal inference; dose-response function; multivalued treatment; observational study; propensity score; unconfoundedness


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