[R] Re: HOWTO compare univariate binomial glm lrm models which are not nested
Jan.Verbesselt at biw.kuleuven.be
Sun Apr 17 16:02:32 CEST 2005
Thanks a lot for the input. I will take the considerations into account.
"2 or 3 completely pre-chosen models or you will invalidate inference and
estimates if you use these comparisons to build a final model"
The aim is not use the comparisons to build a final model but to select the
explanatory variable which explains most of the variance or has the best
predictive ability (p247 10.8 Harrell, 2001).
I'm comparing variables, which are all related to the remotely sensed water
content of vegetation, with binary fire occurrence data (1: fire / 0: no
fire). The aim is to select the water related variable which has the best
'performance' (Referring to literature about logistic regression used for
evaluation of fire danger indices).
e.g. a lrm model is lrm(firedata~waterrelated.variable)
Thanks a lot and best regards,
In addition to Brian's comment, AIC may be of use. You can't really use
c-index (ROC area) as it is not sensitive enough for comparing two
models. But whatever you use, the bad news is that you can't use the
results to compare more than 2 or 3 completely pre-chosen models or you
will invalidate inference and estimates if you use these comparisons to
build a final model.
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