Look at the Predict.Plot and TkPredict functions in the TeachingDemos package. These will not plot all 11 dimensions at once, but will plot 2 of the dimensions conditioned on the others. You can then change the conditioning to see relationships.
These use base rather than ggplot graphics. On Thu, Jul 5, 2012 at 3:39 PM, Abraham Mathew <abmathe...@gmail.com> wrote: > 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* > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -- Gregory (Greg) L. Snow Ph.D. 538...@gmail.com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
