On Mon, Jun 15, 2009 at 6:57 PM, Ben Amsel<benam...@gmail.com> wrote: > Hello R users, > > Given a linear (in the parameters) regression model where one predictor x > interacts with time and time*time (ie, a quadratic effect of time t): > y = b0 + b1(x) + b2(t) + b3(t^2) + b4(x*t) + b5(x*t^2) + e, > > I would like to construct 95% confidence bands (optimally, shaded) around > this function: > > *dy* = b1 + b4(t) + b5(t^2) > *dx* > > That is, the partial effect of x on y changing over time t > > Is this possible with predict() or perhaps another function? > > > Thank you very much > Ben
Hi Ben, Check out the 'Design' package, it has all kinds of convenience functions for plotting these type of things. install.packages('Design', dep=TRUE) ?ols Cheers, Dylan ______________________________________________ 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.