On Nov 19, 2013, at 10:59 AM, Calum wrote: > Hi there, > I hope someone can help me. > > I have a dataset of Concentration against Mortality, and I am trying to > compare the use of Logit and Probit models using this data. > > The issue I am having is trying to back transform the data from the probit > model, to plot it in normal space instead of log space. > I know this can be done with a logit model using the code below, where > ilogit is a function for the inverse logit: > > NEWCONC <- seq(0,0.6, length=25) > NEWMORT <- predict(LOGIT, Conc=NEWCONC, se=TRUE) > > plot(data=DATA, Prop~Conc) > lines(NEWCONC, ilogit(NEWMORT$fit)) > > However, I can't seem to find a function equivalent to ilogit for a probit > model, that I could use in this code: > > NEWCONC <- seq(0,0.6, length=25) > NEWMORT <- predict(PROBIT, Conc=NEWCONC, se=TRUE)
You should be looking at ?predict and paying particular attention to the 'type' argument. I think you want: type='response' > > plot(data=DATA, Prop~Conc) > lines(NEWCONC,###INVERSE PROBIT### (NEWMORT$fit)) > > > Any advice on this issue would be appreciated, > Thanks, > Calum > > > > -- > View this message in context: > http://r.789695.n4.nabble.com/Inverse-of-Probit-tp4680752.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. David Winsemius Alameda, CA, USA ______________________________________________ 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.
