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Re: st: Multiple imputation for longitudinal data
From
Stas Kolenikov <[email protected]>
To
[email protected]
Subject
Re: st: Multiple imputation for longitudinal data
Date
Thu, 2 Dec 2010 17:39:53 -0600
You have monotone missing data, and you would most likely be better
off utilizing the methods for monotone missing data rather than
bluntly rely on multiple imputation. Check Little and Rubin's book on
missing data, chapter 7 (in the 2nd edition).
On Thu, Dec 2, 2010 at 5:11 PM, Eduardo Nunez <[email protected]> wrote:
> Dear Statalisters,
>
> I have Stata 11.1 (MP - Parallel Edition).
>
> I am interested in performing multiple imputation on a longitudinal
> data (on several variables with a percent of missing between 1-15%),
> were subjects are the cluster units with few observations in time.
> See below the data structure:
>
> xtdes, pattern(1000)
>
> pid: 1, 2, ..., 1438 n = 1432
> visit: 1, 2, ..., 12 T = 12
> Delta(visit) = 1 unit
> Span(visit) = 12 periods
> (pid*visit uniquely identifies each observation)
>
> Distribution of T_i: min 5% 25% 50% 75% 95% max
> 1 1 1 2 3 6 12
>
> Freq. Percent Cum. | Pattern
> ---------------------------+--------------
> 650 45.39 45.39 | 1...........
> 359 25.07 70.46 | 11..........
> 202 14.11 84.57 | 111.........
> 91 6.35 90.92 | 1111........
> 52 3.63 94.55 | 11111.......
> 44 3.07 97.63 | 111111......
> 11 0.77 98.39 | 1111111.....
> 9 0.63 99.02 | 11111111....
> 6 0.42 99.44 | 111111111...
> 4 0.28 99.72 | 1111111111..
> 3 0.21 99.93 | 11111111111.
> 1 0.07 100.00 | 111111111111
> ---------------------------+--------------
> 1432 100.00 | XXXXXXXXXXXX
>
> The article included in Stata FAQ ("How can I account for clustering
> when creating imputations with mi impute?") suggested using a
> "multivariate
> normal model to impute all clusters simultaneously" or strategy 3,
> although mentioned that is best suited to balanced repeated-measures
> data.
>
> Clearly, my data is not balanced. Moreover, the percent of data
> missing increased as patient follow-up gets far from baseline.
>
> Is there any other method suited for this type of longitudinal data?
> If not, how stringent is the limitation of not being balanced.
>
> Please, any help is welcome!
>
>
> Eduardo
> *
> * 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/
>
--
Stas Kolenikov, also found at http://stas.kolenikov.name
Small print: I use this email account for mailing lists only.
*
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