Re: st: Is there an -mi drop- command?

[Richard Williams <richardwilliams.ndu@gmail.com>]

I'm glad to see there is a Stata command that does what Clyde wants. 
But, I still wonder about his last concern: "The most cogent 
objection I can think of to this proposal is that perhaps I shouldn't 
be using MI at all in these situations, or, perhaps, that my 
imputation models need some serious re-thinking when the imputations 
show this kind of irregularity." If you are getting imputations that 
give bizarre results is it ok to just drop them?


At 11:38 AM 4/9/2013, you wrote:
> I'm pretty sure the answer to this question is no: I've scoured the 
> MI manual and can't find it.
>
> Let me explain what I'm looking for and why I think such a command 
> would be useful.
>
> Working with a data set that has a great deal of missing 
> information, I sometimes end up over-generating imputations.  That 
> is, my initial estimate of the number of imputations I will need 
> ends up too high.  It would be nice to be able to tell Stata to 
> simply drop some of them, rather than having to start over and 
> generate a smaller number.  You might ask what the harm is in 
> keeping them all.  Well, the more imputations you have, the longer 
> each MI analysis takes, and if there are many analyses, the time 
> starts to add up.
>
> There is another reason I would like to see a command like 
> this.  When the data include difficult patterns of missingness, such 
> as pairs of variables V1 and V2 that are never both non-missing in 
> the same observation (so their imputations are entirely dependent on 
> yet other variables and there is no direct information about their 
> associations), my experience has been that the imputed data sets 
> sometimes contain imputed values that are widely outside the range 
> of the observed data, even by a few orders of magnitude.  MI 
> analyses that include these data sets sometimes produce results that 
> are clearly absurd.
>
> And there is a third situation.  When doing chained imputations, 
> there is the issue of the burn-in.  Again, we have to make an 
> initial guess and see what happens.  Sometimes, I will generate a 
> large number of imputations using a long burn-in because earlier 
> attempts with a shorter burn-in don't converge to stable 
> estimates.  Maybe I have 75 imputations after a burn-in of 30.  If I 
> study the convergence carefully, I may find that there are 3 or 4 
> imputations where convergence has not been achieved, but the rest 
> look OK.  It would be nice to be able to tell Stata to drop those 3 
> or 4--after all, 75 is just a round number and in most circumstances 
> 71 or 72 imputations will serve nearly as well.
>
> While the -mi estimate- command itself permits specification of a 
> numlist with the numbers of the imputations I want to use, having to 
> repeatedly specify this list is a nuisance.  It would be simpler to 
> be able to drop those imputations, re-save the data set, and then 
> move on to analysis.
>
> The most cogent objection I can think of to this proposal is that 
> perhaps I shouldn't be using MI at all in these situations, or, 
> perhaps, that my imputation models need some serious re-thinking 
> when the imputations show this kind of irregularity.
>
> Any thoughts?
>
> Clyde Schechter
> Dept. of Family & Social Medicine
> Albert Einstein College of Medicine
> Bronx, NY, USA
>
>
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-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
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