##### Anova for (simple) within-subject designs.
##### Source: http://blog.gribblelab.org/2009/03/09/repeated-measures-anova-using-r/
##### (This is a use of "ANOVA with repeated measures")
##### working with the following data:

###
## The data, unfortunately, has to be in a DIFFERENT FORMAT than for 
##   paired-t and so on.  Paired-t tests wanted one row per subject
##   with a column of the outcome for each treatment.
##   But ANOVA wants one row per outcome.  
## Here's some example data structured properly for ANOVA-within-subjects:

> dv <- c(1,3,4,2,2,3,2,5,6,3,4,4,3,5,6)
> subject <- factor(c("s1","s1","s1","s2","s2","s2","s3","s3","s3",
+ "s4","s4","s4","s5","s5","s5"))
> myfactor <- factor(c("f1","f2","f3","f1","f2","f3","f1","f2","f3",
+ "f1","f2","f3","f1","f2","f3"))
> mydata <- data.frame(dv, subject, myfactor)

## So your data will look like this:

dv (ie, dependent variable)	subject		myfactor (ie, treatment)
1				s1		f1
3				s1		f2
4				s1		f3
2				s2		f1
2				s2		f2
3				s2		f3
...

## Now you're ready to run the test:
> am1 <- aov(dv ~ myfactor + Error(subject/myfactor), data=mydata)
> summary(am1)

## You get:

Error: subject
          Df Sum Sq Mean Sq F value Pr(>F)
Residuals  4   12.4     3.1
Error: subject:myfactor
          Df  Sum Sq Mean Sq F value   Pr(>F)
myfactor   2 14.9333  7.4667  13.576 0.002683 **
Residuals  8  4.4000  0.5500
---
Signif. codes:  0 Ô***Õ 0.001 Ô**Õ 0.01 Ô*Õ 0.05 Ô.Õ 0.1 Ô Õ 1