RE: [R] Re: HOWTO compare univariate binomial glm lrm models which are not nested

From: Jan Verbesselt <Jan.Verbesselt_at_biw.kuleuven.be>
Date: Mon 18 Apr 2005 - 00:02:32 EST


Dear all,

Thanks a lot for the input. I will take the considerations into account.

Referring to;
"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,
Jan

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"

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.

Frank
"


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