Dear List,
I am trying to assess the prediction accuracy of an ordinal model fit with
LRM in the Design package. I used predict.lrm to predict on an independent
dataset and am now attempting to assess the accuracy of these predictions.
>From what I have read, the AUC is good for this because it is threshold
independent. I obtained the AUC for the fit model output from the c score (c
= 0.78). For the predicted values and independent data, for each level of
the response I used the ROCR functions to get the AUC (i.e., probability y
>= class1, y >= class2, y >= class3 etc) and plotted the ROC curves for
each. The AUC values are all higher (AUC = 0.80 - 0.93) for the predicted
values than what I got from the fit model in lrm.
I am not sure whether I have misinterpreted the use of the AUC for ordinal
models or whether the prediction results are actually better than the model
results.
Any help / clarification appreciated,
Colin
Colin Robertson
University of Victoria
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