[R] Design: predict.lrm does not recognise lrm.fit object

From: Roy Sanderson <R.A.Sanderson_at_newcastle.ac.uk>
Date: Tue 12 Jul 2005 - 21:10:43 EST


I'm using logistic regression from the Design library (lrm), then fastbw to undertake a backward selection and create a reduced model, before trying to make predictions against an independent set of data using predict.lrm with the reduced model. I wouldn't normally use this method, but I'm contrasting the results with an AIC/MMI approach. The script contains:

# Determine full logistic regression

lrm_logist = lrm(PresAbs ~ Size + X2ndpc + soil + AAR + tjan.jun, data=training)
# Backward selection of variables in model
lrm_stp = fastbw(lrm_logist, rule="p", sls=0.05)
# Fit reduced model

lrm_reduced = lrm.fit(training[,lrm_stp$parms.kept[-1]], training$PresAbs)
# Predict using parameters from reduced model against a new dataset
predict(lrm_reduced, testing, type="fitted.ind")

It is the last command that fails, reporting the error: Error in getOldDesign(fit): fit was not created with a Design library fitting function.

On further investigation, the class of the object from lrm.fit is only "lrm", whereas predict.lrm seems to be expecting objects with the class "lrm", "Design", "glm", judging from the examples on the predict.lrm help page. Many of the attributes differ also. Does anyone know a simple work-around for this problem?

Many thanks

R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Tue Jul 12 20:34:03 2005

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