Hi John, I think a solution is to 1. recode A and B as a single factor, AB, with four levels, 2. define each fixed effect as a function of AB minus the intercept (e.g. ed50 ~ as.factor(AB)-1). 3. extract the tTable as a data.frame with summary(model)$tTable.
I will be interested to see what other folks suggest. Cheers, Hank and then run the Probably not the best, nor the worst solution, might be to recode A and B On Jun 15, 2006, at 11:36 AM, John S. Walker wrote: > Gday, > > This is a repost since I only had one direct reply and I remain > mystified- This > may be stupidity on my part but it may not be so simple. > > > > > In brief, my problem is I'm not sure how to extract parameter > values/effect sizes from a nonlinear > regression model with a significant interaction term. > > My data sets are dose response curves (force and dose) for muscle that > also have two treatments applied > Treatment A (A- or A+) and Treatment B (B-/B+). A single muscle was > used for each experiment - a full dose response curve and one > treatment > from the matrix A*B (A-/B-, A+/B-, A-/B+ and A+,B+). There are 8 > replicates for each combination of treatments > We fit a dose response curve to each experiment with parameters upper, > ed50 and slope; we expect treatment A to change upper and ed50. We > want > to know if treatment B blocks the effect of treatment A and if so to > what degree. > This is similar to the Ludbrook example in Venables and Ripley, > however > they only had one treatment and I have two. > > my approach > > The dataframe is structured like this: > expt treatA treatB dose force. > 1 - - 0.1 20 > 1 - - 0.2 40 > ... > 4 + + 0.1 20 > 4 + > > I used a groupedData object: mydata=groupedData(force ~ dose | expt) > > I used an nlme obect to model the data as follows (pseudocode): > > myfit.nlme <- nlme(force ~ ss_tpl(dose, upper, ed50,slope), > fixed=list(ed50~factor(treatA)*factor(treatB))) > > > The function ss_tpl is a properly debugged and fully functional > selfstarting three parameter logistic function that I wrote- no > problem > here. In my analysis > I also included fixed terms for the other fit parameters; upper and > slope, but my main problem is with the > ed50 so that's all I've included here. > > Running an anova on the resulting object (anova(myfit.nlme) I found > the > A -/B- (control) to > be significantly different from zero, treatment A was significantly > different, treatment B had no significant > effect and there was a significant interaction between treatment A > and > treatment B. > > The interaction term is likely to be real. The treatments are on > sequential steps in a pathway and treatment B may be blocking the > effect of treatment A, i.e. treatment B alone has no effect because it > blocks a pathway that is not active, treatment A reduces force via > this > pathway and treament B therefore blocks the effect of treatment A when > used together. > > From what I understand, please correct me if I'm wrong, the parameter > estimates from summary(model.nlme) are not correct for main effects if > a significant interaction is present. For example in my data treatment > B alone has no signifcant effect in the anova but the interaction term > A:B is significant. I believe The summary estimate for B is the > estimate across all levels of A. What I want to do is pull out the > estimate for B when A is not present. I suppose I can do it manually > from the list of coefficients from nls or fit a oneway model with > treatment levels A, B, AB. But I was kind of hoping there was some > extractor function. > > The reason I need this is that the co-authors want to include a table > of parameter values with std errs or confidence intervals ala: > > Treat upper ed50 slope > A-/B- x x x <- shows value > for comparison to control studies > A+/B- x x x <-Shows A is working0 > A-/B+ x x x <- Shows B has no > effect alone > A+/B + x x x <-shows B > blocks A (not necessarily total) > > So back to my question,How do I extract estimates of the parameters > from my model object for a > specific combination of factors including the interaction term. > i.e. what is the ed50 (and std err) for A-/B-, A+/B-, A-/B+, A+/B > + ? > > > I think this is a fair question and one that many biomedical > scientists > would need. > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting- > guide.html Dr. M. Hank H. Stevens, Assistant Professor 338 Pearson Hall Botany Department Miami University Oxford, OH 45056 Office: (513) 529-4206 Lab: (513) 529-4262 FAX: (513) 529-4243 http://www.cas.muohio.edu/~stevenmh/ http://www.muohio.edu/ecology/ http://www.muohio.edu/botany/ "E Pluribus Unum" ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
