I'd recommend having a look at the lrm function in the Design package. Looking at the examples should show you how you can product this type of plot using some of the other components of this package.
On 26/11/06, Aimin Yan <[EMAIL PROTECTED]> wrote: > I am trying to fit a logistic regression model for this data set. > Firstly, I want to plot P(Y=1) vs As and P(Y=1) vs Aa. > Does any body know how to do these in R. > Thanks, > Aimin > > > p5 <- read.csv("http://www.public.iastate.edu/~aiminy/data/p_5_2.csv") > > str(p5) > 'data.frame': 1030 obs. of 6 variables: > $ P : Factor w/ 5 levels "821p","8ABP",..: 1 1 1 1 1 1 1 1 1 1 ... > $ Aa : Factor w/ 19 levels "ALA","ARG","ASN",..: 12 16 7 18 11 10 19 19 > 19 1 ... > $ As : num 126.9 64.1 82.7 7.6 42.0 ... > $ Ms : num 92.4 50.7 75.3 17.2 57.7 ... > $ Cur: num -0.1320 -0.0977 -0.0182 0.2368 0.1306 ... > $ Y : int 0 0 1 1 0 0 1 0 1 1 ... > > ______________________________________________ > R-help@stat.math.ethz.ch 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. > -- ================================= David Barron Said Business School University of Oxford Park End Street Oxford OX1 1HP ______________________________________________ R-help@stat.math.ethz.ch 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.