Bounty: 50
I have a dataset like this,
grouping1 grouping2 value
A Y 6.32
B Y 4.2
A X 2.3
A X 4.45
C Y 3.5
C X 1.67
B X 6.24
I wanted to see if there were differences on the values for the different grouping features.
So, I ran a 2-way ANOVA and I get p-values
for the values for: grouping1
, grouping2
and the interaction between grouping1
and grouping2
.
I get something like:
Variable p-value
Grouping1 .00001
Grouping2 .0003
Grouping1*Grouping2 .9
Meaning that there are differences in the groups but interaction effect is not significant.
Now, provided the assumptions are fulfilled I can make a tukey pairwise test to see which groups are different (I use statsmodels.stats.multicomp.pairwise_tukeyhsd). My question is,
Q1: Is it valid to run 3 pairwise tukey tests for,
- All the pairs of
grouping1
wheregrouping2
isX
- All the pairs of
grouping1
wheregrouping2
isY
- All the pairs of
grouping1
ignoringgrouping2
or only 1 and 2 are valid? My reasoning is that provided that the interactions are not significant, 3 is also valid.
Q2: Is doing 3 the same as running a one way ANOVA over the data ignoring grouping2, get a significant result and then run a tukey pairwise?
(I saw many questions about interpreting Tukey after 2-way anova, but none really answered this specific point).