[R] Binary logistic modelling: setting conditions (defining thresholds) in the fitted model (lrm)

From: Jan Verbesselt <Jan.Verbesselt_at_biw.kuleuven.be>
Date: Thu 12 Jan 2006 - 01:31:06 EST

Dear Rlist,

We are working with library(Design) & R 2.2.1// When using the following fitted model:

	knots  <- 5
	lrm.1        <- lrm(X8~rcs(X1,5),x=T,y=T)

X8 (binary 0/1 vector)
X1, X2 explantory variables

We would like to set the probability of X8=1 to zero when the X2 variable is smaller than a defined threshold, e.g. X2<50, because the X1 variable is not correct (contains more errors) anymore when X2<50.

How could we define this in the model smoothly without changing the values of the variables?

We keep in mind that setting thresholds in not a good solution because then information is lost. Therefore we also tested the following model. However, towards operational methods or techniques setting thresholds is simplifying relationships. Especially in this case were we saw that X1 could contain more errors when X2 < 50.

lrm.1 <- lrm(X8~rcs(X1,5)+ rcs(X2,5),x=T,y=T)

Thanks a lot for feedback & discussion,

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