ESTIMATING CAUSAL EFFECTS OF TREATMENTS IN EXPERIMENTAL AND OBSERVATIONAL STUDIES

Abstract

A discussion of matching, randomization, random sampling, and other methods of controlling extraneous variation is presented. The objective is to specify the benefits of randomization in estimating causal effects of treatments. The basic conclusion is that randomization should be employed whenever possible, but the use of carefully controlled nonrandomized data to estimate causal effects is a reasonable and necessary procedure in many cases.