Re: [R] model.tables error from aov
In addition, your model statement is odd. Note that within-S factor Type is tested with both the type I and the type II residuals, whereas only the latter should be used. Try this model instead: aov.errs.ae - aov(TrainErrs ~ idio*Type + Error(Subject/ Type),data=learnDat.ae) or, for more clarity: aov.errs.ae - aov(TrainErrs ~ idio*Type + Error(Subject +Subject:Type),data=learnDat.ae), which explicitly denotes the two error strata. On 17-Dec-08, at 4:00 AM, r-help-requ...@r-project.org wrote: Your design seems to be unbalanced: multistatum aov is intended for balanced designs. My guess is that one idio subject has two Type=1 observations: in which case try removing one of them. On Tue, 16 Dec 2008, Harlan Harris wrote: Hi, I'm a new R user, coming from SPSS, and without a particularly strong stats background. I've got a data set that I'd like to do a mixed-design ANOVA with. No missing values. Here's the summary: summary(learnDat.ae) Type Subjectidio struct TrainErrs cond 0:20 11 : 3 idio :28 ae :58 Min. : 0.00 idioae :28 2:19 12 : 3 nonidio:30 fact: 0 1st Qu.: 6.25 idiofact : 0 3:19 14 : 3 Median :11.50 nonidioae:30 15 : 3 Mean :13.40 18 : 3 3rd Qu.:16.00 2 : 3 Max. :59.00 (Other):40 Note that the TrainErrs column is the only numeric column, and I forced everything else to be a factor. (Is that correct?) I then do the following: aov.errs.ae - aov(TrainErrs ~ (idio*Type) + Error(Subject/Type) + (idio), learnDat.ae) So, idio is between-subjects and Type is within-subjects. This is based on examples I've found elsewhere. summary(aov.errs.ae) This seems to work fine: Error: Subject Df Sum Sq Mean Sq F value Pr(F) idio 1179 1790.89 0.36 Type 1210 2101.05 0.32 Residuals 17 3401 200 Error: Subject:Type Df Sum Sq Mean Sq F value Pr(F) Type 2515 2582.44 0.103 idio:Type 2680 3403.22 0.053 . Residuals 34 3595 106 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 -- Please avoid sending me Word or PowerPoint attachments. See http://www.gnu.org/philosophy/no-word-attachments.html -Dr. John R. Vokey __ 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.
Re: [R] F values from a Repeated Measures aov
Two things: 1. the + Sex term is superfluous 2. the variable Subject needs to be a Factor, not a vector (as I suspect it currently is). That is, add: mydata.tab$Subject=as.factor(mydata.tab$Subject) in the preamble before the aov call, and all should be fine. On 29-Apr-08, at 4:00 AM, [EMAIL PROTECTED] wrote: Hi Folks, I have repeated measures for data on association time (under 2 acoustic condtions) in male and female frogs as they grow to adulthood (6 timepoints). Thus, two within-subject variables (Acoustic Condition: 2 levels, Timepoint: 6 levels) and one between-subject variable (Sex:male or female). I am pretty sure my distributions depart from normality but I would first like to simply run a RM anova on the data. My problem is that when I do this I generate different values of F for my main effects and interaction when I do the analysis in [R] and SPSS - so I don't know which one to believe. Here is my code in R: mydata.tab=read.delim(mydata.txt, header=T) #read in my data mydata.tab$Timepoint=as.factor(mydata.tab$Timepoint)#col headings are factors so df are correct mydata.tab$Acx.Cond=as.factor(mydata.tab$Acx.Cond) mydata.tab$Sex=as.factor(mydata.tab$Sex) aov.F=aov(Targ.Assoc.Time~(Timepoint*Acx.Cond*Sex) + Error(Subject/ (Timepoint*Acx.Cond))+(Sex), data=mydata.tab) #run aov where i look at the main effects of Timepoint, Acoustic Condition and Sex as well as all the interactions therein on the amount of time a frog spends associating with the target sound. Include anything to do with Subject in the error term. Does this look right for a Repeated Measures ANOVA, or am I missing something to make it RM and that explains the large discrepancies in my F-values between [R] and SPSS? As soon as I get this canonical aov code figured out I want to derive my p-values by bootstrapping my F distributions, but first I need those canonical F's. Thanks -Alex -- Alexander T Baugh Section of Integrative Biology Univ. of Texas at Austin C0930 Austin, TX 78712 http://darktropic.blogspot.com/ -- Please avoid sending me Word or PowerPoint attachments. See http://www.gnu.org/philosophy/no-word-attachments.html -Dr. John R. Vokey __ 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.
Re: [R] Journal for R
Yes. Try: Tutorials in Quantitative Methods for Psychology http://www.tqmp.org/ (I am on the Editorial Board). On 31-Mar-08, at 4:00 AM, [EMAIL PROTECTED] wrote: Hi the list I made up a new statistical procedure. I will publish it in a medical journal, but there will be only the way of using it, no calculation or algorithme detail. So is there a journal (I mean scientific journal) with selection commity to submit an article describing the detail of a package? Christophe -- Please avoid sending me Word or PowerPoint attachments. See http://www.gnu.org/philosophy/no-word-attachments.html -Dr. John R. Vokey __ 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.
