April 23, 2015 . .
One of the major problems in observational research is estimating the true treatment effect. This is not hard when the selection and outcome processes are uncorrelated and all relevant variables are observed and properly controlled for. However, when the selection and outcome are correlated and it is not possible to remove this correlation on the basis of the observables, biased estimation results. The Heckman selection model affords one way of dealing with and minimizing this introduced bias. A parallel R based simulation of a Heckman style estimator compared to least squares and propensity scores highlights the potential utility of this framework.
statistics r methods heckman