But that just gives me the prediction of Y for treatment A or B, not the ratio.
As I stated: # I am interested in the relationship: # Y(treatment =="B") / Y(treatment=="A") as a function of X, with a confidence interval! I can get the SE for either of them using predict.gam without a problem, but I don't know how to get the CI for the ratio! thanks, remko ------------------------------------------------- Remko Duursma Research Lecturer Hawkesbury Institute for the Environment University of Western Sydney Hawkesbury Campus, Richmond Mobile: +61 (0)422 096908 www.remkoduursma.com On Tue, Jun 28, 2011 at 2:09 PM, David Winsemius <dwinsem...@comcast.net> wrote: > > On Jun 27, 2011, at 10:45 PM, Remko Duursma wrote: > >> Dear R-helpers, >> >> I am trying to construct a confidence interval on a prediction of a >> gam fit. I have the Wood (2006) book, and section 5.2.7 seems relevant >> but I am not able to apply that to this, different, problem. >> >> Any help is appreciated! >> >> Basically I have a function Y = f(X) for two different treatments A >> and B. I am interested in the treatment ratios : Y(treatment = B) / >> Y(treatment = A) as a function of X, including a confidence interval >> for this treatment ratio (because we are testing this ratio against >> some value, across the range of X). >> >> The X values that Y is measured at differs between the treatments, but >> the ranges are similar. >> >> >> # Reproducible problem: >> X1 <- runif(20, 0.5, 4) >> X2 <- runif(20, 0.5, 4) >> >> Y1 <- 20*exp(-0.5*X1) + rnorm(20) >> Y2 <- 30*exp(-0.5*X2) + rnorm(20) >> >> # Look at data: >> plot(X1, Y1, pch=19, col="blue", ylim=c(0,max(Y1,Y2)), xlim=c(0,5)) >> points(X2, Y2, pch=19, col="red") >> >> # Full dataset >> dfr <- data.frame(X=c(X1,X2), Y=c(Y1,Y2), >> treatment=c(rep("A",20),rep("B",20))) >> >> # Fit gam >> # I use a gamma family here although it is not necessary: in the real >> problem it is, though. >> gfit <- gam(Y ~ treatment + s(X), data=dfr, family=Gamma(link=log)) >> >> # I am interested in the relationship: >> # Y(treatment =="B") / Y(treatment=="A") as a function of X, > > Can't you use predict.gam? > > plot(predict(gfit, newdata=data.frame(X=rep(seq(0.4, 4, by=0.1), 2), > treatment=c(rep("A",37),rep("B",37) ) ) )[1:37] ) > lines(predict(gfit3, newdata=data.frame(X=rep(seq(0.4, 4, by=0.1), 2), > treatment=c(rep("A",37),rep("B",37) ) ) )[-(1:37)]) > >> with a confidence interval! > > There is an se.fit argument to predict.gam(). > > > -- > > David Winsemius, MD > West Hartford, CT > > ______________________________________________ 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.