I have the following questions on the EM and multiple imputation. 1. Assuming my response is fully observed and I have missingness in my continuous covariates, is there a way to compute fitted values after using the EM algorithm to get estimates for the parameters?
2. I recently read a paper by Ibrahim, Lipsitz and Chen (1999) in Biometrics, where they used the Monte Carlo EM to maximise the likelihood when there were missing continuous covariates, is this similar to the use of data augmentation after EM (as used by Schafer)? Infact the paper by Wei and Tanner (JASA, 1990), proposing the Monte Carlo EM states that the imputations in the E-step are called multiple imputations by Rubin. Thanks. Vumani Dlamini Central Statistical Office Ministry of Economic Planning Swaziland _________________________________________________________________ STOP MORE SPAM with the new MSN 8 and get 2 months FREE* http://join.msn.com/?page=features/junkmail
