You should have better response posting to the r-sig-mixed-models list (repeated measures are mixed effects models).
-- Bert On Sun, Dec 2, 2012 at 12:18 PM, Giuseppe Pagnoni <gpagn...@gmail.com>wrote: > Dear all, > > I am having quite a hard time in trying to figure out how to correctly > spell out a model in R (a repeated-measures anova with a > within-subject covariate, I guess). Even though I have read in the > posting guide that statistical advice may or may not get an answer on > this list, I decided to try it anyway, hoping not to incur in > somebody's ire for misusing the tool. > > For the sake of clarity, I will explain the problem. > > We conducted an experiment measuring average response times in a > cognitive task. The task has two types of stimuli (stim1, stim2) and > was performed in a 6-run session, where subjects performed the task > under condition A on odd-numbered runs and under condition B on > even-numbered runs. Thus, the temporal sequence of the runs was the > following: > > - run 1: cond A > - run 2: cond B > - run 3: cond A > - run 4: cond B > - run 5: cond A > - run 6: cond B > > where for each run and for each subject, an average RT was collected > for stim1 and for stim2. > > After collecting and plotting the data, an approximately linear > decrease in RT from run1 to run6 was apparent in most subjects > (practice effect: subjects become better and faster with time). > > Now, I am struggling with how to properly specify a model to perform > the group analysis by taking into account this confounding practice > effect, so that the real effects of interest (the main effect of > condition, and the interaction of condition and stimulus type) can be > better assessed. > > I used a dataframe in long format, with `subj', `rt' (response time), > `stim' (stim1, stim2), `cond' (A, B), and `run' (1 to 6) as columns, > where `run' is coded as an integer so that it can be used for modeling > a linear trend. The R command I tried is: > > rt.aov <- aov(rt ~ run + stim * cond + Error(subj /(run + stim * > cond)), data=rt.df) > > but I am not at all sure that the error term is correctly specified. > > Furthermore, we have also collected data on an additional batch of > subjects that performed the task in the 6-run session but with the > order of conditions A and B reversed (A on even-numbered runs and B on > odd-numbered runs); now, if we wanted to analyze the data from the two > groups of subjects together, by including a between-subjects group > factor (groupAB, groupBA), would the model specification become > something like the following? > > rt.aov <- aov(rt ~ run + group * stim * cond + Error(subj /(run + > stim * cond)), data=rt.df) > > Perhaps should lme() be used instead (and with which formula?)? > > Many thanks in advance to anybody who'd be so kind to offer their > advice or tip on this. I have scoured the web and some textbooks for > a few days now, but to little avail. > > very best > > giuseppe > > > -- > Giuseppe Pagnoni > Dip. Scienze Biomediche, Metaboliche e Neuroscienze > Sezione Fisiologia e Neuroscienze > Univ. di Modena e Reggio Emilia > Via Campi 287 > I-41125 Modena, Italy > Tel: +39-059-205-5742 > Fax: +39-059-205-5363 > > ______________________________________________ > 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. > -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm [[alternative HTML version deleted]] ______________________________________________ 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.
