I have a logit model with about 10 predictors and I am trying to plot the
probability curve for the model.
Y=1 = 1 / 1+e^-z where z=B0 + B1X1 + ... + BnXi
If the model had only one predictor, I know to do something like below.
mod1 = glm(factor(won) ~ as.numeric(bid), data=mydat,
family=binomial(link="logit"))
all.x <- expand.grid(won=unique(won), bid=unique(bid))
y.hat.new <- predict(mod1, newdata=all.x, type="response")
plot(bid<-000:250,predict(mod1,newdata=data.frame(bid<-c(000:250)),type="response"),
lwd=5, col="blue", type="l")
I'm not sure how to proceed when I have 10 or so predictors in the logit
model. Do I simply expand the
expand.grid() function to include all the variables?
So my question is how do I form a plot of a logit probability curve when I
have 10 predictors?
would be nice to do this in ggplot2.
Thanks!
--
*Abraham Mathew
Statistical Analyst
www.amathew.com
720-648-0108
@abmathewks*
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