st: Multiple imputation in panel data when subjects die

[mf8@york.ac.uk]

Dear Statalist

I have a panel data set with some missing values which I would like to 
impute using Stata's mi command. However, over time, subjects in my panel 
die.

An example of the type of pattern I observe is:

Subject 1: M M M O O O D D D D D D

Subject 2: O O O O O M O O O O O D 

Where M is 'missing', O is 'observed' and D is 'dead'. 

In the exchange between Yulia Marchenko and Jibonayan Raychaudhuri 
(http://www.stata.com/statalist/archive/2009-08/msg00388.html), Paul 
Allison's (2001, page 74) approach to dealing with missing values in 
longitudinal data is outlined, namely, if the data set is in "long" form, 
reshape it to "wide" form so that there is one record for each subject 
(with distinct variables for measurements on the imputation variable at 
different points in time) and then perform the imputation, before reshaping 
back to "long" form.

Because, over time, my subjects die, I have some missing values ("."s) 
which need to be imputed, because they are "true missing values" (the "M"s 
above), and also missing values which should not be imputed (the "D"s).

My proposed solution is to replace all missing values owing to the subject 
having died (the "D"s) with another Stata coding for a missing value (e.g. 
".a"), so that only the true missing values (the remaining "."s) are 
imputed by mi.

Taking this approach, and using the reshaping approach suggested by Allison 
and Yulia outlined above, Stata successfully imputes missing values for the 
"."s and not the ".a"s, which I think is great.

My question is this: does my approach make sense, that is, does it 
represent a "principled" approach to mi for panel data in the presence of 
deaths, in the spirit of Allison (2001) and Yulia?

With thanks, in advance, for any help anyone can give me. 

Martin Forster

REF: Allison, P. 2001, Missing Data. Sage University Papers Series on 
Quantitative Applications in the Social Sciences.

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