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Estimating the effect of medical treatments on subject responses is one ofthe crucial problems in medical research. Matched-pairs designs are commonlyimplemented in the field of medical research to eliminate confounding andimprove efficiency. In this article, new estimators of treatment effects forheterogeneous matched pairs data are proposed. Asymptotic properties of theproposed estimators are derived. Simulation studies show that the proposedestimators have some advantages over the famous Heckman's estimator and inverseprobability weighted (IPW) estimator. We apply the proposed methodologies to ablood lead level data set and an acute leukaemia data set.

Estimation of Treatment Effects for Heterogeneous Matched Pairs Data with Probit Models