Colin Robertson wrote:> Dear List,
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> I would like to calculate the Goodman-Kruskal gamma for the predicted
> classes obtained from an ordinal regression model using lrm in the Design
> package. I couldn't find a way to get gamma for predicted values in
Design
> so have found previous positings suggesting to use :
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> Rcorr.cens(x, S outx = TRUE) in the Hmisc package
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> My question is, will this work for predicted vs observed factors? I.e. x
> predicted class and S = observed class? Or is there a better way to obtain
> this? I used the maximum individual probability for each observation to
> determine the predicted class.
Rank correlation measures are for correlating a continuous or ordinal
prediction with a response (continuous, ordinal, or binary). So you
should be able to do something like rcorr.cens(predict(fit),
as.numeric(Y), outx=TRUE). Note that rcorr is all lower case. This
assumes that the levels of Y are in order, as does lrm.
Note that the new version of lrm has a method for getting predicted mean
scores from an ordinal lrm.
Frank
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> Any help appreciated,
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> Thanks
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> Colin
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> Colin Robertson
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> Dept of Geography
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> University of Victoria
--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University