Hello! This is my first post.

I am Stata beginner.





Using Program: Stata 13.0.

Method: GEE

Data: 5waves (unbalnaced)
Obs: 27,246


Situation:

1) My data has missing values (0.01%~2.96%)
2) I did Little’s MCAR test => result : not MCAR
3) So I did multiple imputations. => I made it.

mi set mlong
mi register imputed health1stclf i.caretran health1stclb i.edub i.genderb agerealb sposatb i.workb i.religionynb i.catime_w_binab lifehabitb i.yearf
mi impute mvn health1stclf i.caretran health1stclb i.edub i.genderb agerealb sposatb i.workb i.religionynb i.catime_w_binab lifehabitb i.yearf




Problem:

1) I tried to do QIC after multiple imputations to find good working correlation.

* DV: health1stclf

xi: qic health1stclf i.caretran health1stclb i.edub i.genderb agerealb sposatb i.workb i.religionynb i.catime_w_binab lifehabitb i.yearf, i(pid) j(time) family(gaussian) link(identity) corr(independent)

* I got error message


no; data are mi set
Use mi xtset to set or query these data; mi xtset has the same syntax as xtset.

Perhaps you did not type xtset. Some commands call xtset to obtain information about the settings. In that case, that
command is not appropriate for running directly on mi data. Use mi extract to select the data on which you want to run the
command, which is probably m=0.

r(119)



///////

2) So, I tried again in this way

mi estimate: qic health1stclf i.caretran health1stclb i.edub i.genderb agerealb sposatb i.workb i.religionynb i.catime_w_binab lifehabitb i.yearf, i(pid) j(time) family(gaussian) link(identity) corr(independent)


But I got an error message again.


mi estimate: command not supported
qic is not officially supported by mi estimate; see mi estimation for a list of Stata estimation commands that are
supported by mi estimate. You can use option cmdok to allow estimation anyway.
r(198);

/////////////////


Are there any ways to use QIC for multiple imputations-gee?

Or how can I find "goodness of fit" for working correlation for imputated dataset?



Many thanks for your advice.