This paper utilizes recent simulation techniques in a two-stage estimation method which is applicable for a wide range of statistical models in the presence of missing data. The first stage of the method provides a way to estimate (and simulate from) the joint distribution of missing variables when the missing variables are continuous, binary, or ordered discrete. The second stage uses the first-stage estimates to “integrate” out the effects of the missing variables and obtain model estimates. The implementation of the method in this paper allows theoretically important, partially missing wage and school characteristic variables-which are not necessarily independently determined-to be included in a proportional hazard model of teacher attrition.