sprocket <toelch <at> gmail.com> writes: > > > Hi, > > I am modeling a gen linear mixed model with binomial repeated measures > responses (y=cbind(correct/not correct)) of some individuals (id). > I have a 2X2 design (effort and costs) and another continuous independent > variable (scr). This will lead to something like this: > > mod.1<-lmer(y~effort+costs+scr+(1|id),family=binomial) > so far so good. In my experiment the probability to score a correct depends > also on a probability based on random choice. Short example: Individual 1 > has to choose 5 times before a correct can happen in the high effort > condition while in the low effort condition Ind 1 only has to choose 3 > times. So there is a different probability associated to the low and high > effort condition that an individual will choose correct. > How can I incorporate this into a model or does anybody know of paper where > a similar case has occurred? > > Ulf >
I think that you have to define a new factor that distinguishes the two levels of strong effort, say EffortLeve l( for lack of imagination on a Friday afternoon) and then from what you describe, the subjects are nested in this, i.e., some had a high effort of 5 and others of 3. Perhaps, the following would work then glmer(y ~ EffortLevel/(effort + costs + scr) + (1 | id), family = binomial) I think that if each observer has a unique id, that the nesting will be automatic for this variable, but you should verify that. -- Ken Knoblauch Inserm U846 Stem-cell and Brain Research Institute Department of Integrative Neurosciences 18 avenue du Doyen Lépine 69500 Bron France tel: +33 (0)4 72 91 34 77 fax: +33 (0)4 72 91 34 61 portable: +33 (0)6 84 10 64 10 http://www.sbri.fr/members/kenneth-knoblauch.html ______________________________________________ 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.
