Dear all,
I'm currently in the process of analysing an imputed dataset but am having trouble performing correct regression models.
The current plugins used for ICE i think are up to date however I have specified them below just incase I have got the wrong ones.
which ice
c:\ado\stbplus\i\ice.ado
*! version 1.4.2 PR 03aug2007.
*! Based on _mvis2 version 1.0.2 PR 19jan2005.
*! v 1.0.0 PR 01Jun2001.
*! version 1.0.0 PR 20dec2004.
*! Based on artformatnos.ado v 1.0.0 PR 26Feb2004
*! version 1.0.0 PR 30may2006.
which mim
c:\ado\stbplus\m\mim.ado
*! mim.ado v1.1.0 (JCG, JBC, PR)
which mvpatterns
c:\ado\stbplus\m\mvpatterns.ado
*! 2.0.0 10jan2001 (STB-61: dm91)
once the dataset is imputed, i wish to regress 2 variables as follows
mim: regress active0_i chaq2_i
however the following error occurs:
invalid 'Settings'
Again if i run
mim regress active0_i chaq2_i
the following error occurs:
last estimates not found
I then tried using the micombine command:
micombine regress active2_i chaq2_i
another error "imputation identifier _j not found"
I have noticed that there is an _mj
so i create _j=_mj
and this seems to work with the following regression:
micombine regress active2_i chaq2_i
But i do not know if this is the correct way to analyse the dataset
additionally it does not work for
xi: micombine mlogit active2_i subtype_i
for which subtype_i was imputed as a categorical variable passively
any help would be appreciated, I have read through the UCLA guide on multiple imputation using ICE adn various other online resources but have yielded no results. And I keep hitting impassible brick walls
Regards
Sham
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