Hello everyone,
I did a Quade Test as a non-parametric alternative of the one-factorial repeated measures ANOVA, as my data are not normally distributed. My experimental design includes one factor having 3 levels (t1, t2, t3). All 28 subjects are confronted with all levels (t1, t2, t3) making it to a repeated measure design. I did the Quade Test and following post hoc tests using R and the following code:
This test yielded the following results:
Quade test:
Quade F = 4.8, num df = 2, denom df = 54, p-value = 0.012
From this it can be deduced that there is a significant difference between at least 2 groups as F(2,54) = 4.8, p-value<.05.
To find out which of the three groups (t1, t2, t3) differ from each other, I conducted posthoc tests.
This test yielded the following results:
Pairwise comparisons using posthoc-Quade test with TDist approximation:
t1-t2: .04,
t2-t3: .02,
t1-t3: 1.0
(P-value adjustment method: Bonferroni)
The posthoc test makes it clear that there is a difference between groups t1 and t2 as well as groups t2 and t3.
The question is: How do I calculate the effect size for the Quade Test given the values I have computed above?
Thanks for any help!
Annika
I did a Quade Test as a non-parametric alternative of the one-factorial repeated measures ANOVA, as my data are not normally distributed. My experimental design includes one factor having 3 levels (t1, t2, t3). All 28 subjects are confronted with all levels (t1, t2, t3) making it to a repeated measure design. I did the Quade Test and following post hoc tests using R and the following code:
Code:
library(PMCMR)
quade.test(dependentVar~independentVar|subject, data = data)Quade test:
Quade F = 4.8, num df = 2, denom df = 54, p-value = 0.012
From this it can be deduced that there is a significant difference between at least 2 groups as F(2,54) = 4.8, p-value<.05.
To find out which of the three groups (t1, t2, t3) differ from each other, I conducted posthoc tests.
Code:
posthoc.quade.test(y=data$dependentVar, groups=data$independentVar, blocks=data$subject, p.adjust.method = "bonferroni")Pairwise comparisons using posthoc-Quade test with TDist approximation:
t1-t2: .04,
t2-t3: .02,
t1-t3: 1.0
(P-value adjustment method: Bonferroni)
The posthoc test makes it clear that there is a difference between groups t1 and t2 as well as groups t2 and t3.
The question is: How do I calculate the effect size for the Quade Test given the values I have computed above?
Thanks for any help!
Annika