I can't get the same results in R as in GraphPad Prism for repeated measures anova.
The experiment was a stimulation time course, so I have as DV=response and as factor "time" within groups, also I add a factor sample for each experiment
data <- read.csv("http://dl.dropbox.com/u/4828275/datos.csv")
options(contrasts=c("contr.sum","contr.poly"))
## Convert variables to factor
data <- within(data, {
sample <- factor(sample)
time <- factor(time)
})
aov <- aov(response~time+sample, data=data)
summary(glht(aov, linfct=mcp(time="Dunnett")))
Simultaneous Tests for General Linear Hypotheses
Multiple Comparisons of Means: Dunnett Contrasts
Fit: lme.formula(fixed = response ~ time, data = data, random = ~1 |
sample)
Linear Hypotheses:
Estimate Std. Error z value Pr(>|z|)
2 - 0 == 0 1.1789 2.0800 0.567 1
5 - 0 == 0 1.2966 2.0800 0.623 1
10 - 0 == 0 1.0555 2.0800 0.507 1
15 - 0 == 0 0.4317 2.0800 0.208 1
30 - 0 == 0 0.2148 2.0800 0.103 1
(Adjusted p values reported -- bonferroni method)
For repeated measures I have this code
aov.repeated <- ezANOVA(
data
, dv = .(response)
, wid = .(time)
, within = .(sample)
, type = 1
, return_aov = TRUE
)$aov
The GraphPad Prism results for the same data was
Table Analyzed Data 1
Repeated Measures ANOVA
P value 0.0415
P value summary *
Are means signif. different? (P < 0.05) Yes
Number of groups 6
F 2.863
R square 0.4172
Was the pairing significantly effective?
R square 0.1980
F 2.119
P value 0.1162
P value summary ns
Is there significant matching? (P < 0.05) No
ANOVA Table SS df MS
Treatment (between columns) 130.6 5 26.12
Individual (between rows) 77.30 4 19.32
Residual (random) 182.4 20 9.121
Total 390.3 29
Dunnett's Multiple Comparison Test Mean Diff. q Significant? P < 0.05? Summary 95% CI of diff
0 vs 2 -2.861 1.498 No ns -8.085 to 2.362
0 vs 5 -5.777 3.024 Yes * -11.00 to -0.5531
0 vs 10 -6.009 3.146 Yes * -11.23 to -0.7855
0 vs 15 -4.621 2.419 No ns -9.844 to 0.6029
0 vs 30 -2.581 1.351 No ns -7.805 to 2.642
How can I get the same results as above in R? Is there a way to get Dunnett's Multiple Comparison Test in aov.repeated?

