[amelia] Is this possible to impute

Dear Amelia Developers I have the following situation. Lets take two independently collected samples from the same population (drawn with the same sampling technique, with low chance of overlap and data collected around the same time). Sample 1 has variables A and C-E. Sample 2 has variables B-E. Both samples have 500 observations. I merge the datasets so I get a dataset with 1000 observations with variables A through E (where A-E are continuous normal). A and C-E is observed for the first 500 cases and B-E for case 501-1000. I can assume that data is missing completely at random. My imputation model would include all variables (from A-E) and in my analysis model I want to regress A on B for example (correlate A with B). I just talked to Craig Enders and he verified that this imputation will not work with Proc MI or NORM as the maximum likelihood model is not identified due to no cases where A and B are observed at the same time. But I know Amelia uses a different procedure. Is it possible to run this in Amelia and get unbiased results? Thanks Levi - Amelia mailing list served by Harvard-MIT Data Center [Un]Subscribe/View Archive: http://lists.gking.harvard.edu/?info=amelia More info about Amelia: http://gking.harvard.edu/amelia