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$fit)) However, I can't seem to find a function equivalent to ilogit for a probit model, that I could use in this code: NEWCONC <- seq(0,0.6, length=25) NEWMORT <- predict(PROBIT, Conc=NEWCONC, se=TRUE) plot(data=DATA, Prop~Conc) lines(NEWCONC,###INVERSE PROBIT### (NEWMORT$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.
