hi--
I guess one thing to keep in mind is that if you want to interpret the
results of the random effects estimation (meaning the variance
components), you will have to impute under that model as well. Doing so
is kind of a nuisance (you could use the package pan). One alternative
is to impute a wide file (meaning y1,y2, x,z ....), but that's not very
useful if the problem is very difficult.
i'd be curious how you imputed under a random-effects specification?
regards,
michael
Kosuke Imai wrote:
Unfortunately, the mixed effects models do not work
with multiply
imputed data sets yet. This is certainly on our to-do list. Right
now, you would have to do this by hand - apply zelig(), setx(), and
sim() to each of the data sets and then combine sim results.
Kosuke
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On Tue, 29 Apr 2008, Didi Kuo wrote:
Dear Zelig List,
I am trying to do estimate a random effects logit model using
multiply imputed
data, but I get the following error message:
out<-zelig(cwarcons~rival_lag+weak10+civwar_nb+lref_totalnbl+lpopl
+
+lrgdp96l+polity2l+politysq+ethfrac+peace1+eeurop+lamerica+ssafrica+asia+
+
nafrme+lmtnest+elevdiff+Oil+instab+tag(1|ccode),data=mi(m1,m2,m3,m4,m5),
+ model="logit.mixed")
summary(out)
Error in apply(coef1, 1,
mean) : dim(X) must have a positive length
In addition: Warning messages:
1: In x$coef : $ operator is invalid for atomic vectors, returning NULL
2: In x$coef : $ operator is invalid for atomic vectors, returning NULL
3: In x$coef : $ operator is invalid for atomic vectors, returning NULL
4: In x$coef : $ operator is invalid for atomic vectors, returning NULL
5: In x$coef : $ operator is invalid for atomic vectors, returning NULL
Any ideas about how I might fix this?
Thanks,
Didi Kuo
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