Performance evaluation of propensity score methods for estimating average treatment effects with multi-level treatments.

ABSTRACT: The propensity score (PS) method is widely used to estimate the average treatment effect (TE) in observational studies. However, it is generally confined to the binary treatment assignment. In an extension to the settings of a multi-level treatment, Imbens proposed a generalized propensity score which is the conditional probability of receiving a particular level of the treatment given pre-treatment variables. The average TE can then be estimated by conditioning solely on the generalized PS under the assumption of weak unconfounded-ness. In the present work, we adopted this approach and conducted extensive simulations to evaluate the performance of several methods using the generalized PS, including subclassification, matching, inverse probability of treatment weighting (IPTW), and covaria

SUBMITTER: Nian H 

PROVIDER: S-EPMC6609155 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature