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Jul 27, 2012 at 9:25 comment added Ruben Thanks for the reference, can't find a PDF, but I'll look it up in the lib. I meant that: Initially I did complete-cases analysis and because I definitely had information on a vital covariate only from that assessment, I didn't bother to look for the other predictors in the other assessments. I did that now and now have 440 fewer (dataset of ~1800) missings on the central predictor, but still ~600 missings on the covariate. I can predict up to 38% of the variance in that oft-missing covariate using the other variables in the model and FIML seems a good approach, even when NMAR... Reading up..
Jul 27, 2012 at 3:52 comment added Tim I'm not entirely sure what you mean by "I often have data on the central predictor from another source". However, as regards the missing data assumptions, in problems that I model I generally always assume that the data is MAR as I tend not to have sufficient data to do anything else, so it sounds like you have data that will permit you to do something outside of my experience. I'd suggest you have a flick through Little, Roderick J. A. and Donald B. Rubin (1987), Statistical Analysis with Missing Data. Brisbane: John Wiley & Sons. It is not so new, but I always find it really useful.
Jul 26, 2012 at 21:20 history bounty ended Ruben
Jul 26, 2012 at 21:20 vote accept Ruben
Jul 26, 2012 at 21:20 comment added Ruben You helped me a lot, especially with the part about conditional variance, thanks. I thought about it some more, and read up on FIML and remembered all that MAR/MCAR jazz. I may have a follow-up question regarding NMAR vs. MAR as a FIML assumption, but that's for another post.
Jul 25, 2012 at 11:58 comment added Ruben Thanks for clearing that up. You're correct in saying that the conditional variance matters more, I just read this remark "restricted variance may have caused us to underestimate the relationship" too often. Actually, I often have data on the central predictor from another source, more often a vital covariate is missing. Would I follow the same procedure? I can actually in some cases model the reason for missing data (ie. dad dead, unknown, didn't show).
Jul 25, 2012 at 5:11 history answered Tim CC BY-SA 3.0