Hi folks, I originally tried R-SIG-Mixed-Models for this one (https://stat.ethz.ch/pipermail/r-sig-mixed-models/2010q3/004170.html), but I think that the final steps to a solution aren't mixed-model specific, so I thought I'd ask my final questions here.
I used gamm4 to fit a generalized additive mixed model to data from a AxBxC design, where A is a random effect (human participants in an experiment), B is a 2-level factor predictor variable, and C is a continuous variable that is likely non-linear. I tell gamm4 to fit a smooth across C to each level of B independently, and I can use predict.gam(...,se.fit=T) to obtain predictions from the fitted model as well as the standard error for the prediction. I'd like to visualize the BxC interaction to see if smoothing C within each level of B was really necessary, and if so, where it is (along the C dimension) that B affects the smooth. It's easy enough to obtain the predicted B1-B2 difference function, but I'm stuck on how to convey the uncertainty of this function (e.g. computing the confidence interval of the difference at each value of C). One thought is that predict.gam(...,se.fit=T) returns SE values, so if I could find out the N on which these SE values are computed, I could compute the difference CI as sqrt( ( (SD_B1)^2 + (SD_B2)^2 ) / N ) * qt( .975, df=N-1 ) However, I can't seem to figure out what value of N was used to compute the SEs that predict.gam(...,se.fit=T) produces. Can anyone point me to where I might find N? Further, is N-1 the proper df for the call to qt()? Finally, with a smooth function and 95% confidence intervals computed at each of a large number of points, don't I run into a problem of an inflated Type I error rate? Or does the fact that each point is not independent from those next to it make this an inappropriate concern? Cheers, Mike -- Mike Lawrence Graduate Student Department of Psychology Dalhousie University Looking to arrange a meeting? Check my public calendar: http://tr.im/mikes_public_calendar ~ Certainty is folly... I think. ~ ______________________________________________ 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.