25 Apr
2011
25 Apr
'11
11:58 p.m.
Hi Class,
We are trying to set priors when using Amelia for imputation, but it
keeps return errors like "The resulting variance matrix was not invertible.
Please check your data for highly collinear variables"
The priors look something like:
pr<-matrix(NA,6,5)
for (i in 1:6){
pr[i,1]<-i+48
pr[i,2]<-47
pr[i,3]<-1.81
pr[i,4]<-2.01
pr[i,5]<-0.9
}
Amelia runs without any problem if we don't set priors. Does anybody know
what the problem might be?
Many thanks,
Yue
On Sun, Apr 24, 2011 at 9:36 PM, Leslie Finger <lfinger(a)fas.harvard.edu>wrote;wrote:
Dear Class,
My partner and I are clustering the standard errors in new way (that we
think
makes more sense in theory than what the authors were doing), but now,
while
some clustered standard errors are very slightly bigger than the lm output,
some standard errors are actually smaller (in the same regression). Does
anybody have any intuition about what this might mean?
-Leslie and Adela
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