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Re: st: R: imputation of missing dates


From   Yulia Blomstedt <sungurik@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: R: imputation of missing dates
Date   Fri, 6 May 2011 16:44:15 +0200

Thank you Maarten,

matching is probably the best way to solve it. Can STATA do that for
me? The database is built on 177 thousand individuals, so there is no
way I could it manually.
/Yulia

On Fri, May 6, 2011 at 3:14 PM, maarten buis
<maartenlbuis@googlemail.com> wrote:
> The fact that the probability of participating depends on education
> and age is not a problem as long as you include it in your imputation
> model. This is what (the rather confusing) term Missing At Random
> means, missingness is random _after_ controlling for observed
> variables. However, it sounds to me like you want something that is
> logically impossible: to find a date at which an exam took place when
> no exam took place. Remember that the whole machinery of imputation is
> based on the idea that the value exists but was not observed, in your
> case the value did not exist in the first place.
>
> You might try matching. That will try to find for each examer a
> non-examer that is as similar as possible on a set of observed
> explanatory variables. The real problem is that people who choose not
> to participate tend to do that for a reason, e.g. they did not choose
> to participate because they already knew they would perform badly. If
> such reasons are also strong predictors of the dependent variable
> (which is often the case) and they are not measured (which is also
> often case), then matching will not help you.
>
> Hope this is not too depressing,
> Maarten
>
> On Fri, May 6, 2011 at 2:27 PM, Yulia Blomstedt <sungurik@gmail.com> wrote:
>> Thank you Carlo.
>> I've been going through the literature but have not yet been able to
>> come up with  mi syntax that would work for me.
>>
>> Answering your questions:
>> 1) The examination was voluntary. 60% of the invited individuals have
>> participated. Others have not due to various reasons
>> 2) Our earlier study showed that non-participants differ in their
>> education level (higher) and age (younger) from the participants, but
>> not in other characteristics.
>> This of course raises a concern of whether mi is applicable at all,
>> since its assumption is that the missing data are missing at random.
>>
>> If mi is not applicable, what other method could I use to create the
>> EXAMDATE for non-participants?
>>
>> /Yulia
>> *
>> *   For searches and help try:
>> *   http://www.stata.com/help.cgi?search
>> *   http://www.stata.com/support/statalist/faq
>> *   http://www.ats.ucla.edu/stat/stata/
>>
>
>
>
> --
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
>
> http://www.maartenbuis.nl
> --------------------------
>
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>



-- 
Yulia Blomstedt, PhD

Epidemiology and Public Health Sciences,
Dept of Public Health and Clinical Medicine,
Umeå University,
SE-901 85 Umeå
Sweden

tel: +46 (0)90 785 10 79
fax: +46 (0)90 13 89 77

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/


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