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

[Jan Verbesselt]

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,
Jan




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