Hello,

I am wondering if you can use multiple imputation for chained equation (MICE) to just perform a single imputed dataset in Stata. I think the command I am using for analysis is not compatible with multiple imputation (the commmand I am using is gllamm, a user generated command for multilevel models). So, is it reasonable to run just one imputation in MICE (see code below) and then run my analysis how I normally would (i.e., not using the mi estimate command)? I choose MICE for imputation because I have multiple variable types that need to be imputed (binary, continuous, and ordinal/categorical) and it seemed to be the correct imputation option to choose given my variety of variable types.

I am open to other single imputation suggestions is anyone has them.

Code:
mi set mlong;
xi: mi register imputed Lr2_number_adults_ LSize_Cat_ Lr_Do_you_own_;

xi: mi register regular Garden_Active_ i.Year Garden_ID LSite_Visit_Curr_or_Prior_ LSold_GID_ LPickups_ LUR_Curr_Yr_or_Prior_ LSOD_Curr_or_Prior_ LKGD_Curr_Or_Prior_ LCommunity_Garden_ LMarket_Garden_ LYr_Act_Prior_ LSoil_Test_Curr_or_Prior_ i.r_L_classes i.r_L_volunteer_3_max i.r_L_social_2_max;
xi: mi impute chained (logit) Lr_Do_you_own_ (regress) Lr2_number_adults_ (ologit) LSize_Cat_ = Garden_Active_ i.Year Garden_ID LCommunity_Garden_ LMarket_Garden_ LSite_Visit_Curr_or_Prior_ LSold_GID_ LPickups_ LUR_Curr_Yr_or_Prior_ LSOD_Curr_or_Prior_ LKGD_Curr_Or_Prior_ LYr_Act_Prior_ LSoil_Test_Curr_or_Prior_ i.r_L_classes i.r_L_volunteer_3_max i.r_L_social_2_max, add(1);

Many thanks,
Alyssa