Alternatives to randomized experiments

Randomized experiments are preferred for making inferences about causality when they can be implemented and their assumptions are met. Yet assumptions can fail (e.g., attrition, treatment noncompliance) or randomization may be unethical or infeasible. I describe alternative design and statistical approaches that permit testing causal hypotheses and present current empirical evidence related to alternative designs. Alternative designs permit a wider range of research questions to be answered and permit more direct generalization of causal effects; however, when using such designs, estimates of the magnitude of the causal effect may be more uncertain.