[R] post-hocs with multiple factors (anovas)?
Greg Trafton
trafton at itd.nrl.navy.mil
Fri Oct 11 18:11:20 CEST 2002
Hi, all. I'm working on post hoc comparisons on anovas with multiple
factors. the design is 1 repeated measure (session) and 1 between measure
(cond). my dependent measure is rl. here is the data I'm using (in a
data.frame):
mig <- data.frame(subj=factor(rep(subj,3)),
cond=factor(rep(cond,3)),
session=factor(c(rep(1,nsubj),rep(2,nsubj),rep(3,nsubj))),
rl)
> mig
subj cond session rl
1 401.1 NW 1 6.4081
2 402.1 NW 1 5.8861
3 500.1 NWC 1 5.3492
4 502.1 NWC 1 8.5302
5 601.1 NWR 1 2.7519
6 602.1 NWR 1 4.5404
7 603.1 NWR 1 4.3442
8 604.1 NWR 1 3.6722
9 401.1 NW 2 6.1492
10 402.1 NW 2 5.0506
11 500.1 NWC 2 6.5625
12 502.1 NWC 2 11.4430
13 601.1 NWR 2 2.8450
14 602.1 NWR 2 5.6558
15 603.1 NWR 2 3.3340
16 604.1 NWR 2 5.0548
17 401.1 NW 3 5.2717
18 402.1 NW 3 3.7337
19 500.1 NWC 3 3.6659
20 502.1 NWC 3 5.9463
21 601.1 NWR 3 2.3356
22 602.1 NWR 3 7.5458
23 603.1 NWR 3 5.0322
24 604.1 NWR 3 4.1381
summary(mgroup <- aov(rl ~ cond * session + Error(subj/(session)), data=mig))
I'm interested in posthoc comparisons between:
various levels of condition (I can get this with TukeyHSD,
pairwise.t.test, or multcomp)
various levels of session (ditto)
the full 6 comparisons (3 sessions by 2 conditions). that is, I want
to know if NW-session1 is diff from NW-session2, etc.
> tapply(mig$rl,IND=list(mig$cond, mig$session),FUN=mean)
1 2 3
NW 6.147100 5.59990 4.502700
NWC 6.939700 9.00275 4.806100
NWR 3.827175 4.22240 4.762925
Each of the earlier tests I've tried (TukeyHSD, pairwise.*, and
multcomp) all seem to do only one factor at a time.
Suggestions?
thanks!
greg
(I know my dataset is small, doesn't give appropriate omnibus stats to
run the post-hocs, but I'm currently in testing mode.)
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