Vincent, As long as you are going to digest all those suggestions, let me offer one more:
If you want to avoid making an assumption about the functional form of the dose-response relationship (you don't even need to assume monotonicity!), and also avoid having to trust the asymptotic distributions of MLE's, a completely different approach is described in Stepwise Confidence Intervals without Mulitplicity Adjustment for Dose Response and Toxicity Studies Jason C. Hsu and Roger L. Berger June 99 issue of JASA In your case, this approach would involve a pairwise test for each positive dose population with the zero dose population (but without multiplicity adjustment, even though you are doing multiple tests!). So if you can pick a good test for comparing the means of two Poisson distributions (I'm sure there are plenty, though I'm not sure what I would recommend), then you can apply this method very easily. You lose the power of "pooling" that comes with the assumption of a functional relationship, but you may make up for this by getting more exact (not asymptotic) confidence bounds (and it's always comforting to make fewer assumptions). Just one more thing for you to stew on... Happy thinking, Jim Rogers > Hello to all: first and foremost: thank you for all this input. I only discovered about "R" last week (!) and I think I will dump my SAS license!!! > > > ;-) > > > This is a very dynamic listserve! > You "R" all great! Thank you! > > > I just hope some day I can help out a student the way you did today. > > > I will spend part of the weekend studying the different suggestions in detail. Again, I'm not a stats person, so I will need some time and good coffee to digest all this correctly. (I'm most worried about understanding the nonlin suggestion.) Early next week, I will post a "summary" of the suggestions and the path I chose to follow. (with proper syntax Professor Ripley, I promise) > > > ;-) > > > Have a nice weekend > > > Best regards, > > > Vincent Philion James A. Rogers, Ph.D. <[EMAIL PROTECTED]> Statistical Scientist Cantata Pharmaceuticals 300 Technology Square, 5th floor Cambridge, MA 02139 617.225.9009 x312 Fax 617.225.9010 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
