[R] F values from a Repeated Measures aov

Alex Baugh alex.baugh at gmail.com
Mon Apr 28 23:58:30 CEST 2008

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



> 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.


Alexander T Baugh
Section of Integrative Biology
Univ. of Texas at Austin C0930
Austin, TX 78712

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