Re: st: stratification and model checking after imputation

[Kimberly Forde <kimberlyaforde1@yahoo.com>]

Dear Statalisters,

I am conducting an analysis in a large database and not surprisingly there are a number of missing variables.  Body mass index is important to my study and unfortuantely is missing in about 20% of records.  I have chosen to impute this data using the mi commands (STATA 11). After imputing this data, I have encountered 2 distinct problems:

1. I am having difficulty running stratified analyses because "by" statements cannot be used with the mi command.  I was thinking that perhaps I could use an interaction term and then use a lincom command to obtain the actual estimates thereafter.  Are there other ways to circumvent the limitations of the mi commands with stratified analyses?

2. Is there any way to do model checking for survival analyses after the data has been imputed using "mi"?  In the complete case analyses, I was about to compare AICs and also use visual inspection of log-log plots to determine if proportional hazards assumptions were being met.  I have not been able to do so after imputation.  Does anyone know of a way to get around this issue? Would you suggest using the best model obtained from the complete case analysis and then using the same covariates to construct a final model after imputation?

Any assistance you may have to offer would be greatly appreciated!!!!!

Thanks,
Kim  


      

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