Displaying 3 results from an estimated 3 matches for "aovres".
2006 Jan 18
1
Within-Subjects ANOVA & comparisons of individual means
...=F)
> con
[,1] [,2] [,3] [,4] [,5]
[1,] 1 0 0 0 0
[2,] -1 1 0 0 0
[3,] 0 -1 1 0 0
[4,] 0 0 -1 1 0
[5,] 0 0 0 -1 1
[6,] 0 0 0 0 -1
> contrasts(d$interval)=con
and then I'm doing the ANOVA
> aovRes = aov(dv~interval+Error(subject/interval), data=d)
> summary(aovRes)
Error: subject
Df Sum Sq Mean Sq F value Pr(>F)
Residuals 6 2.48531 0.41422
Error: subject:interval
Df Sum Sq Mean Sq F value Pr(>F)
interval 5 13.8174 2.7635 8.7178 3.417e-05 ***
Resid...
2006 Jan 22
0
Error in 1:object$rank : NA/NaN argument
...ow=F)
> con
[,1] [,2] [,3] [,4] [,5]
[1,] 1 0 0 0 0
[2,] -1 1 0 0 0
[3,] 0 -1 1 0 0
[4,] 0 0 -1 1 0
[5,] 0 0 0 -1 1
[6,] 0 0 0 0 -1
> contrasts(d$interval)=con
and then I'm doing the ANOVA
> aovRes = aov(dv~interval+Error(subject/interval), data=d)
> summary(aovRes)
Error: subject
Df Sum Sq Mean Sq F value Pr(>F)
Residuals 6 2.48531 0.41422
Error: subject:interval
Df Sum Sq Mean Sq F value Pr(>F)
interval 5 13.8174 2.7635 8.7178 3.417e-05 ***
Resi...
2006 Jan 18
3
linear contrasts with anova
I have some doubts about the validity of my procedure to estimeate linear contrasts ina a factorial design.
For sake of semplicity, let's imagine a one way ANOVA with three levels. I am interested to test the significance of the difference between the first and third level (called here contrast C1) and between the first and the seconda level (called here contrast C2). I used the following