How does one create multiple imputations?
Except in trivial settings, the probability distributions that one must draw from to produce proper MI’s tend to be complicated and intractable. Recently, however, a variety of new simulation methods have appeared in the statistical literature. These methods, known as Markov chain Monte Carlo (MCMC), have spawned a small revolution in Bayesian analysis and applied parametric modeling (Gilks, Richardson & Spiegelhalter, 1996). Schafer (1997) has adapted and implemented MCMC methods for the purpose of multiple imputation. In particular, he has written general-purpose MI software for incomplete multivariate data. They may be downloaded free of charge at our website.
