Helen, on your particular problem, you might have a look at work on
dealing with noncompliance in experiments; here's one example:
http://gking.harvard.edu/files/abs/cluster-abs.shtml
for amelia, a reasonable strategy is to impute everything and then
revert imputations that are really structural missingness back to
missing. you don't want to use the imputed value when there can be no
value.
Gary
---
http://gking.harvard.edu
Helen Brown wrote:
Dear all,
I am using Amelia II to impute but I have a question regarding one of
my variables which seems to pose a problem for multiple imputation
unless I can find a better coding rule:
I want to control for **compliance with treatment*** (binary variable
1,0) but I am not sure how to deal with the following:
say patient1 is under T1 in 1990 and complies, then dummy for T1=1 and
dummy for compliance=1
say patient2 is under T1 in 1999 and does not comply, then dummy for
T1=1 and dummy for compliance=0
But, then, say patient1 is NOT under T1 in 1980 (T1=0)
what value should I assign to compliance in this case? Should I leave
it as a missing -no value- (it makes sense but I will lose many
observations). On the other hand, it doesnt' make sense to assign 1 or
0 to compliance if there was nothing to comply (or fail to comply)
with in the first place.
Moreover, if I leave the compliance value as missing in this case,
when I use Amelia II the missing value for compliance will be imputed
and I am not sure this would be correct given that in reality
compliance did not exist b/c there was no treatment to comply with.
Thanks in advance,
Regards,
Helen A. Brown
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