I'm running stcox on multiply imputed data. I have used the same model and syntax on non-imputed data, and it works fine. But when I try to fit the model using mi estimate, I get the following error message:
Code:
mi estimate, hr: stcox i.HADS_A_gli c.PartAg_gli if Sex==0 HADS_A_gli: factor variables may not contain noninteger values an error occurred when mi estimate executed stcox on m=1 r(452);
The imputation output looks like this:
Code:
. mi impute mvn HADS_A_gli HADS_D_gli Sex PartAg_gli SmoStatPackYrs_gli_missing SES_gli physact_gli alcoh > ol_gli COPDcat_gli CVD_gli cancer_gli chrondisADL_gli diabetes_gli musc_skel_gli if (glicopd_HUNT==1 | > glicopd_HUNT==2), add(10) rseed (53421) note: variables Sex PartAg_gli COPDcat_gli CVD_gli cancer_gli chrondisADL_gli diabetes_gli musc_skel_gli contain no soft missing (.) values; imputing nothing Performing EM optimization: observed log likelihood = -6277.4486 at iteration 13 Performing MCMC data augmentation ... Multivariate imputation Imputations = 10 Multivariate normal regression added = 10 Imputed: m=1 through m=10 updated = 0 Prior: uniform Iterations = 1000 burn-in = 100 between = 100 ------------------------------------------------------------------ | Observations per m |---------------------------------------------- Variable | Complete Incomplete Imputed | Total -------------------+-----------------------------------+---------- HADS_A_gli | 1962 586 586 | 2548 HADS_D_gli | 2169 379 379 | 2548 Sex | 2548 0 0 | 2548 PartAg_gli | 2548 0 0 | 2548 SmoS~i_missing | 2434 114 114 | 2548 SES_gli | 2365 183 183 | 2548 physact_gli | 2532 16 16 | 2548 alcohol_gli | 2383 165 165 | 2548 COPDcat_gli | 2548 0 0 | 2548 CVD_gli | 2548 0 0 | 2548 cancer_gli | 2548 0 0 | 2548 chrondisADL_~i | 2548 0 0 | 2548 diabetes_gli | 2548 0 0 | 2548 musc_skel_gli | 2548 0 0 | 2548 ------------------------------------------------------------------ (complete + incomplete = total; imputed is the minimum across m of the number of filled-in observations.) . end of do-file
Sigrid
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