Treatments of Missing Data: A Monte Carlo Comparison of RBHDI, Iterative Stochastic Regression Imputation, and Expectation-Maximization.

Describes a Monte Carlo investigation of four methods for treating incomplete data: (1) resemblance based hot-deck imputation (RBHDI); (2) iterated stochastic regression imputation; (3) structured model expectation maximization; and (4) saturated model expectation maximization. Results favored the expectation maximization methods. (SLD)