Hello,
I'm having some problems reading data into Amelia. When I try to
read a Stata file (.dta), it tells me:
Error: Program was unable to read file contents
Please check instructions to make sure input is of correct type
When I try to read it in text format, it just shuts down/crashes (the
program, not the operating system).
I'm a Mac user, so I'm trying this on Virtual PC (though I've tried
it on a PC down the hall and had the same problems).
Any suggestions?
Thanks,
Strom
I am trying to use Amelia for Gauss (so that I can take advantage of the
functions not available in Amelia for Windows like rejection sampling).
I tried using the example in the Amelia document with the "wars" data
and this is the error message I received. I did look through the
amimput.src and did not see anything that could have led to the message.
Any suggestions on what the problem could be? Thanks.
Eric.
(gauss) new;
(gauss) library amelia;
(gauss) _AMepri=3;
(gauss) dbuf = amelia("wars");
_DXPRINT=0
^
C:\GAUSSL\SRC\AMIMPUT.SRC(100) : error G0156 : '_DXPRINT' : Illegal
redefinition of procedure
_DXASCHDR=1
^
C:\GAUSSL\SRC\AMIMPUT.SRC(101) : error G0156 : '_DXASCHDR' : Illegal
redefinition of procedure
_DXWKSHDR=1
^
C:\GAUSSL\SRC\AMIMPUT.SRC(102) : error G0156 : '_DXWKSHDR' : Illegal
redefinition of procedure
(gauss)
Eric A. Akunda
Doctoral Student (Marketing)
Kenan-Flagler Business School
University of North Carolina - Chapel Hill
CB # 3490 McColl
Chapel Hill, NC 27599-3490
Tel: 919-962-0783
Voice: 919-918-1222
Fax: 919-962-7186
Email: eric_akunda(a)unc.edu <mailto:eric_akunda@unc.edu>
Dear Prof. King,
I have recently begun using Amelia to do data imputation.
I attempted to use the time series cross-sectional function in Amelia
for Windows but could not. The reason is my data are observed monthly,
and the example in the Amelia document states how to perform imputation
for yearly data. What should I do to include monthly observations (in
either the windows/gauss version)?
My second question regards rejection sampling. I have examined the
imputed data and find that for the variable with the highest level of
missingness (60% missing), the imputations are rather unreasonable. I
intend to use rejection sampling by specifying a range from publicly
available data sources (I can get annual data for the variables from
some published sources). Since the imputed values "should" sum up to the
reported annual values, is there a way I can take this into account
(e.g. use the mean for the 12 months)?
Thank you very much for taking the time to answer my questions.
Eric A. Akunda
Doctoral Student (Marketing)
Kenan-Flagler Business School
University of North Carolina - Chapel Hill
CB # 3490 McColl
Chapel Hill, NC 27599-3490
Tel: 919-962-0783
Voice: 919-918-1222
Fax: 919-962-7186
Email: eric_akunda(a)unc.edu <mailto:eric_akunda@unc.edu>