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?
Best Answer
All I have to go by are the labels in your .csv file, but it looks to me like you set the problem up incorrectly in Prism. I transposed your data so each row in Prism is one matched sample. So the data entry looks like this:
Now the results (from GraphPad Prism 5.04) match the results you showed from R. The differences between means match, and the q values in Prism match the z values in R:
The problem is you had told Prism, essentially, that all the values collected at one time point were matched. By transposing, I am telling Prism that all the values from one sample (at multiple time points) were matched. If you choose one-way ANOVA in Prism, and specify repeated measures, it assumes that all values in one row are matched (not that all values in one column are matched).
Download the Prism file.