RE: st: mi impute chained

[chong shiauyun <shiauyun416@hotmail.com>]

Hi, 

I am not sure if I should proceed to imputation or I need to change my dryrun model because in my dryrun, it seems to have some convergence problems. I am not sure how to check which sub-model that caused the convergence problem, even though I have specified -noisily-. The thing is that the iterations keep running something like:
Iteration 611: log likelihood = -12162.404  (not concave)
Iteration 612: log likelihood =   -12162.4  (not concave)
Iteration 613: log likelihood = -12162.397  (not concave)
Iteration 614: log likelihood = -12162.394  (not concave)
Iteration 615: log likelihood =  -12162.39  (not concave)
Iteration 616: log likelihood = -12162.387  (not concave)
Iteration 617: log likelihood = -12162.384  (not concave)
Iteration 618: log likelihood =  -12162.38  (not concave)

Shiau

----------------------------------------
> From: ymarchenko@stata.com
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: mi impute chained
> Date: Thu, 25 Oct 2012 07:21:35 -0500
>
> Chong Shiauyun <shiauyun416@hotmail.com> receives a "no observation" error
> when he runs the following imputation model using -mi impute chained-:
>
> > . mi impute chained (reg) birthweight (ologit, augment) ednmatpat
> > (logit, augment)sex (truncreg, ll(lVIQ) ul(uVIQ))verbiq,
> > add(20) rseed(11349730) burnin(50) chainonly dryrun report
>
> Shiau probably meant to omit the -dryrun- option in the above since
> -mi impute chained- does not perform any estimation when the -dryrun- option
> is specified.
>
> The -mi impute chained- command starts off by fitting univariate models on the
> observed data to obtain initial imputed values for each imputed variable. The
> "no observation" error typically occurs when one of such models contains no
> observations and is often caused by the existence of missing values in
> variables other than the imputed variables. In Shiau's case, the offending
> variables may be -lVIQ- and -uVIQ-.
>
> Shiau can use the -noisily- option of -mi impute chained- to identify the
> particular conditional model for which there are no observations and run this
> model manually on the observed data to determine the problem.
>
> Shiau can also send his data and do file to our technical support group at
> tech-support@stata.com to help him identify the problem.
>
>
> -- Yulia
> ymarchenko@stata.com
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