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 mor
Ah, that was it. I had a bad row in there that I had forgotten to remove.
Thank you very much for the prompt (and correct!) response.
-Harlan
On Tue, Dec 16, 2008 at 3:58 PM, Prof Brian Ripley wrote:
> Your design seems to be unbalanced: multistatum aov is intended for
> balanced designs. My g
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 particu
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 TrainErrscond
0:20
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