[EMAIL PROTECTED] wrote:
Dear R-helpers,
I tried to create a 3D surface showing the interaction between two
continuous explanatory variables; the response variable is binary (0/1).
The model is:
model<-glm(incidence~sun*trees,binomial)
then I used "wireframe" to create a 3D plot:
xyz<-expand.grid(sun=seq(30,180,1),trees=seq(0,4000,10))
xyz$incidence<-as.vector(predict(model,xyz))
wireframe(incidence~sun*trees,xyz,scales=list(arrows=FALSE))
which gives me a 3D plot, but the scaling of the y-axis is wrong. the range
is not from 0 to 1.
so my question: is there a way to plot these kind of models, with binary
response variables?
thanks for your help, Heike
library(Design)
d <- datadist(mydata); options(datadist='d')
f <- lrm(incidence ~ sun*trees) # lrm is for binary or ordinal response
plot(f, sun=NA, trees=NA)
# add method='image' or 'contour' to get other types of graphs
plot(f, sun=NA, trees=NA, fun='plogis') # probability scale
--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
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