Hi there,
I am new to MI and was wondering if I could obtain some help.
At the moment, I am performing MI on a dataset of size n= 200. This appears to work fine. However, part of my project is to break up the data set into male (n=92) and female (n=108). When I try and run the same MI for the male and female data sets using the Ameila package, I get the following errors
For the male data set, the error message:
"The resulting variance matrix was not invertible. Please check your data for highly collinear variables.
Warning message:
In amelia.prep(data = data, m = m, idvars = idvars, empri = empri, :
You have a small number of observations, relative to the number, of variables in the imputation model. Consider removing some variables,"
and for the female data set:
"The resulting variance matrix was not invertible. Please check your data for highly collinear variables."
As a result, if I want to perform m = 50 imputations, R will only provide me with 40 or so.
Have others had similar problems? If so how have you overcome them. If not, what can you suggest I do?
Regards,
Ian
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Hi all,
I'm using AmeliaView, via the Tcl/tk interface in Linux. Everything
seems to be working correctly,except that I want more than 5 output
datasets, there are only five data sets in the directory. There are
no error messages or anything, so I'm not quite sure what may cause
this. Any ideas or suggestions?
Thanks.
best,
-Nathan
----------
Nathan A. Paxton
Ph.D. Candidate
Dept. of Government, Harvard University
Resident Tutor
John Winthrop House, Harvard University
napaxton AT fas DOT harvard DOT edu
http://www.fas.harvard.edu/~napaxton
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Hi,
I am performing MI on a dataset in R and then performing my analysis in Mplus. I have a nominal variable in my data set (with say three levels) but to perform the analysis in Mplus, I have to tranform the varible into two ordinal variables: one for level 2 and one for 3 which are both compared with the reference level. My question is what are peolpe out there doing when dealing with a similar situation? Should I be performing the MI on the nominal or ordinal variables?
Regards,
Ian
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