On Jan 4, 2012, at 8:10 PM, Yoo Jinho wrote:
Dear all,
I have found some difference of the results between multinom()
function in
R and multinomial logistic regression in SPSS software.
The input data, model and parameters are below:
choles <- c(94, 158, 133, 164, 162, 182, 140, 157, 146, 182);
sbp <- c(105, 121, 128, 149, 132, 103, 97, 128, 114, 129);
case <- c(1, 3, 3, 2, 1, 2, 3, 1, 2, 2);
result <- multinom(case ~ choles + sbp + choles:sbp, abstol=1.0e-20,
reltol=1.0e-20, MaxNWts=10000);
However, the estimated coeffcients and standard errors of the
coefficeints
are different from the SPSS.
For instance,
the estimated coefficients of the variable "choles" are 0.1946555 and
0.6244513 from the above result, but the SPSS result are 0.213120 and
0.662575.
Standard errors are much more different.
Why these kind of discrepancies occur?
I was taught as a fundamental priciple that interpretation of
coefficients could not be done until you have both the data and the
internal coding. You have provided only half of those requirements. So
back to you.
--
David Winsemius, MD
West Hartford, CT
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