ANOVA and Post-hoc estimates using data including multiple imputations

Dear all,

once more, multiple imputation is the bane of my existence
I hope somebody can help me with what started out as a small little calculation. I couldn't find much info on the web and the one I found were all looking at multi-factor designs and/or repeated measures, which is not what I am trying to do and I didn't get how I could apply that to my problem. Whats more, the imputations in my data set make it very hard to adapt anything to my problem, since most commands do not work. I am using Stata 13.

My main problem is: I am simply trying to simpy compare five group means for a 4 point scale.
But since the data had a significant amount of missing data, I decided to use multiple imputations (m=5) to handle the data. I was easily able to get a table combining the means of each group over all imputations using

Now I want to know if the difference in the means are signifcant and which groups differ from others. Normally I would simply use the anova or oneway command with post-hoc tests and be done with it. The Problem is stata does not allow the anova or oneway. command with the mi: estimate

After some digging I found kind of a work around, by using the mixed command with effect coding (following the advise from the articel Ginkel and Kroonenberg, 2014).
This is the Syntax I used:

[ATTACH=CONFIG]temp_4680_1460724578994_452[/ATTACH]

So fare so good. But as far as I understood, the results from this analysis only show me which groups differ signifcantly from the grand mean, but not which groups differ signficantly from each other, as I would get from post-hoc tests. Unfortunately Ginkel and Kroonenberg do not adress post-hoc tests.

In addition I discovered that I can force Stata to run the anova command anyway, by using the cmdok option. However, the result look more like the ones from the mixed model. So basically I end up with the same Information.

[ATTACH=CONFIG]temp_4681_1460724681192_402[/ATTACH]

I tried to use the contrast postestimation command to get a post-hoc like result. But, once again, that doesn't work with mi:estimate. If I try to force it to run, using the cmdok option again, I get an error message.

Does somebody know a way around it? I simply need a measure to see if the groups differ in order to report it.

I would gladly appreciate any help or suggestions.

Thanks in advance.

P.S: Sorry for the Long post. I hope it makes any sence at all.