multcompare contradicts friedman test
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I used a friedman test on a (24,2) matrix, MatForAnova, whose columns represented the factor (2 levels) of interest and whose rows represented the other factor present in the experiment (3 levels, 8 observations per level). I did
[P_friedman1,TABLE,STATS_friedman1] = friedman(MatForAnova,8,'off');
which yielded:
P_friedman1 = 2.1921e-005
TABLE =
'Source' 'SS' 'df' 'MS' 'Chi-sq' 'Prob>Chi-sq'
'Columns' [408.3333] [ 1] [408.3333] [18.0147] [2.1921e-005]
'Interaction' [ 28.6667] [ 2] [ 14.3333] [] []
'Error' [ 583] [42] [ 13.8810] [] []
'Total' [ 1020] [47] [] [] []
STATS_friedman1 =
source: 'friedman'
n: 3
meanranks: [5.5833 11.4167]
sigma: 4.7610
I then did
multcompare(STATS_friedman1)
which yielded
ans = 1.0000 2.0000 -13.4522 -5.8333 1.7856
The two columns overlapped in the graph that multcompare generates: only blue and gray, no red different groups. Meaning that the two columns were not seen as different by multcompare, despite the low pval=2.1921e-005 as seen in the table. What is wrong with this picture? Help. Neurobiologically yours, E
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