RE: Missing Gender (Categorical values)

From: "diane r mould" Subject:RE: [NMusers] Missing Gender (Categorical values) Date: Wed, 31 Jul 2002 19:24:54 -0400 Dear Alan I would have to agree with Lewis' summary - that if you have some reason to believe that sex is an important covariate or if there is reason to believe that the missingness of sex is informative (non ignorable) then you have reason to undertake some form of multiple imputation to attempt to account for that covariate. However, if you are just in the process of identification of covariates, then you would be better off taking less intensive measures than imputation. Therefore, I would ask for more more input from you on that issue before launching into some discussion on how to do that and whether the results are reasonable. is this covariate part of your hunt for covariates? is there some reason to think that the missingness is not ignorable? The work that was published in CPT did not have to estimate sex based on imputation, but we did have to estimate performance status, which is also a discrete covariate and therefore has some of the same issues associated with imputation. Unlike sex, which is correlated with other covariates such as weight or creatinine clearance, we did not see correlations for performance status that would help predict it (other than the response) although we were also not missing as much data as you seem to be. Therefore, I expect that your imputation model for sex would probably be more reliable than ours was for performance status. So if you do need to use some form of imputation then I think it would be do-able. Please let me know your thoughts Best Regards Diane