Also: require(rms); ?plot.Predict Frank Greg Snow wrote > > Try the following: > > library(TeachingDemos) > ?TkPredict > fit.glm1 <- glm( Species=='virginica' ~ Sepal.Width+Sepal.Length, > data=iris, family=binomial) > TkPredict(fit.glm1) > > (you may need to install the TeachingDemos package first if you don't > already have it installed) > > You will now see a plot that shows the predicted probability compared > to one of the predictor variables, there are controls that you can > then change which variable is shown on the x axis and what the value > of the other variables are. Play with the controls to see the effects > of the different variables. You can now do the same thing with other > logistic regression models. This also works to show nonlinear > (polynomial, spline, etc.) fits of the variables and interactions. > There is a button that you can click that will show the command to > create the same plot in regular R graphics, and you can then use that > command (and change add=TRUE to overlay multiple ones) to create a > static plot showing the relationship. > > On Fri, Jul 6, 2012 at 2:30 PM, Abraham Mathew <abmathewks@> wrote: >> Ok, so let's say I have a logit equation outlined as Y= 2.5 + 3X1 + 2.3X2 >> + >> 4X3 + 3.6X4 + 2.2X5 >> >> So a one unit increase in X2 is associated with a 2.3 increase in Y, >> regardless of what the other >> predictor values are. So I guess instead of trying to plot of curve with >> all the predictors accounted >> for, I should plot each curve by itself. >> >> I'm still not sure how to do that with so many predictors. >> >> Any help would be appreciated. >> >> >> >> >> On Thu, Jul 5, 2012 at 4:23 PM, Bert Gunter <gunter.berton@> wrote: >> >>> You have an about 11-D response surface, not a curve! >>> >>> -- Bert >>> >>> On Thu, Jul 5, 2012 at 2:39 PM, Abraham Mathew <abmathewks@>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@ 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. >>>> >>> >>> >>> >>> -- >>> >>> Bert Gunter >>> Genentech Nonclinical Biostatistics >>> >>> Internal Contact Info: >>> Phone: 467-7374 >>> Website: >>> >>> http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm >>> >>> >>> >> >> >> -- >> *Abraham Mathew >> Statistical Analyst >> www.amathew.com >> 720-648-0108 >> @abmathewks* >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@ 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. > 538280@ > > ______________________________________________ > R-help@ 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. >
----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/Plotting-the-probability-curve-from-a-logit-model-with-10-predictors-tp4635563p4635846.html Sent from the R help mailing list archive at Nabble.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.