Dear Dave, I think you want this model.
lme(value~condition:diff - 1,random=~1|subject) Note that I removed the replicate ID from the model. Include it in the model makes only sense if you can expect a similar replication effects the first/second/thirth time that a subject performs your test. HTH, Thierry ---------------------------------------------------------------------------- ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek team Biometrie & Kwaliteitszorg Gaverstraat 4 9500 Geraardsbergen Belgium Research Institute for Nature and Forest team Biometrics & Quality Assurance Gaverstraat 4 9500 Geraardsbergen Belgium tel. + 32 54/436 185 thierry.onkel...@inbo.be www.inbo.be To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey > -----Oorspronkelijk bericht----- > Van: r-help-boun...@r-project.org > [mailto:r-help-boun...@r-project.org] Namens Dave Deriso > Verzonden: donderdag 20 mei 2010 9:27 > Aan: David Atkins > CC: r-help@r-project.org > Onderwerp: Re: [R] Mixed Effects Model on Within-Subjects Design > > Hi Dave, > > Thank you for your helpful advice. I will take a look at the > multicomp package. > > I was wondering where the lme() function outputs the > interaction between condition*difficulty? > > Below is the output to the code I had originally sent. Which > one of these is condition*difficulty? > > Fixed effects: value ~ condition * diff > Value Std.Error DF t-value p-value > (Intercept) 300109.95 9506.690 688 31.568289 0.0000 > condition2 27717.65 9071.048 688 3.055617 0.0023 > condition3 -23718.72 9071.048 688 -2.614772 0.0091 > diff50 56767.55 9071.048 688 6.258103 0.0000 > diff75 120031.80 9071.048 688 13.232408 0.0000 > condition2:diff50 -45481.21 12828.399 688 -3.545354 0.0004 > condition3:diff50 7333.37 12828.399 688 0.571651 0.5677 > condition2:diff75 -38765.77 12828.399 688 -3.021871 0.0026 > condition3:diff75 12919.59 12828.399 688 1.007109 0.3142 > > Also, why are diff25 and condition1 missing from the output?? > > Thanks again for your generous help!!! > > Best, > Dave Deriso > > > On Wed, May 19, 2010 at 10:08 PM, David Atkins > <datk...@u.washington.edu> wrote: > > > > Dave-- > > > > Given that you want all comparisons among all means in your > design, you won't get that directly in a call to lme (or lmer > in lme4 package). Take a look at multcomp package and its > vignettes, where I think you'll find what you're looking for. > > > > cheers, Dave > > > > -- > > Dave Atkins, PhD > > Research Associate Professor > > Department of Psychiatry and Behavioral Science University of > > Washington datk...@u.washington.edu > > > > Center for the Study of Health and Risk Behaviors (CSHRB) > 1100 NE 45th > > Street, Suite 300 Seattle, WA 98105 > > 206-616-3879 > > http://depts.washington.edu/cshrb/ > > (Mon-Wed) > > > > Center for Healthcare Improvement, for Addictions, Mental Illness, > > Medically Vulnerable Populations (CHAMMP) > > 325 9th Avenue, 2HH-15 > > Box 359911 > > Seattle, WA 98104? > > 206-897-4210 > > http://www.chammp.org > > (Thurs) > > > > Dear R Experts, > > > > I am attempting to run a mixed effects model on a within-subjects > > repeated measures design, but I am unsure if I am doing it > properly. I > > was hoping that someone would be able to offer some guidance. > > > > There are 5 independent variables (subject, condition, difficulty, > > repetition) and 1 dependent measure (value). Condition and > difficulty > > are fixed effects and have 3 levels each (1,2,3 and 25,50,75 > > respectively), while subject and repetition are random > effects. Three > > repeated measurements > > (repetitions) were taken for each condition x difficulty > pair for each > > subject, making this an entirely within-subject design. > > > > > > > > I would like an output that compares the significance of > the 3 levels > > of difficulty for each condition, as well as the overall > interaction > > of condition*difficulty. The ideal output would look like this: > > > > condition1:diff25 vs. condition1:diff50 p_value = .... > > condition1:diff25 vs. condition1:diff75 p_value = .... > > condition1:diff50 vs. condition1:diff75 p_value = .... > > > > condition2:diff25 vs. condition1:diff50 p_value = .... > > condition2:diff25 vs. condition1:diff75 p_value = .... > > condition2:diff50 vs. condition1:diff75 p_value = .... > > > > condition3:diff25 vs. condition1:diff50 p_value = .... > > condition3:diff25 vs. condition1:diff75 p_value = .... > > condition3:diff50 vs. condition1:diff75 p_value = .... > > > > condition*diff p_value = .... > > > > > > > > Here is my code: > > > > #get the data > > study.data > =read.csv("http://files.davidderiso.com/example_data.csv";, > > header=T) > > attach(study.data) > > subject = factor(subject) > > condition = factor(condition) > > diff = factor(diff) > > rep = factor(rep) > > > > #visualize whats happening > > interaction.plot(diff, condition, value, ylim=c(240000, > > 450000),ylab="value", xlab="difficulty", trace.label="condition") > > > > #compute the significance > > library(nlme) > > study.lme = lme(value~condition*diff,random=~1|subject/rep) > > summary(study.lme) > > > > > > > > Thank you so much for your generous help!!! > > > > Best, > > Dave Deriso > > UCSD Psychology > > > > [[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. > > ______________________________________________ > 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. > Druk dit bericht a.u.b. niet onnodig af. 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