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Re: st: Missing indicator method for partially mising baseline measurements in randomized trials


From   Etan Lakam <etan.lakam@googlemail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Missing indicator method for partially mising baseline measurements in randomized trials
Date   Fri, 17 Jul 2009 18:13:50 +0100

More than helpful!
Thank you for this
Etan

On Fri, Jul 17, 2009 at 5:43 PM, Maarten buis<maartenbuis@yahoo.co.uk> wrote:
>
> --- On Fri, 17/7/09, Etan Lakam wrote:
>> I am analysis trial data from a randomized trial,
>> comparing the the body mass index (bmi2)  bewteen
>> the grousp at follow-up adjusting for the baseline
>> values of bmi (bmi1) Some of the values of bmi at
>> baseline are missing and I was advised to use the
>> missing indicator method to account for the
>> missing values of bmi at baseline, thus to have a
>> more efficient result. Being a movice in the field
>> of missing data, I don not have a clue on how to
>> do this is Stata.
>
> That is a good thing, because you should not do it.
> this is explained here:
> http://www.stata.com/statalist/archive/2007-12/msg00030.html
>
> If you really care about those observations and
> your missing data process satisfies the MAR
> assumption you could use -ice-. To install
> -ice- type in Stata -findit ice- and follow
> the links. (The MAR assumption means that the
> probability of being missing does not depend
> on the unobserved values, this assumption can
> thus only be made plausible through a
> theoretical argument and can never be
> emprically tested)
>
> Hope this helps,
> Maarten
>
> -----------------------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
> http://home.fsw.vu.nl/m.buis/
> -----------------------------------------
>
>
>
>
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