[R] repeated measures help; disagreement with SPSS
Greg Trafton
trafton at itd.nrl.navy.mil
Tue Oct 8 21:50:55 CEST 2002
Hi, all.
I have a simple design I'm comparing to output from SPSS.
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
I'm interested in the main effect of cond, session, and the
interaction between the two.
and here is what I get:
> 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
(the means are correct, duh ;-)
> summary(aov(rl ~ cond * session + Error(subj), data=mig))
Error: subj
Df Sum Sq Mean Sq F value Pr(>F)
cond 2 28.305 14.153 1.9916 0.2311
Residuals 5 35.531 7.106
Error: Within
Df Sum Sq Mean Sq F value Pr(>F)
session 2 4.4502 2.2251 2.9868 0.09616 .
cond:session 4 17.7335 4.4334 5.9509 0.01024 *
Residuals 10 7.4499 0.7450
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
(the cond effect is consistent with SPSS)
> summary(aov(rl ~ cond * session + Error(subj/(session)), data=mig))
Error: subj
Df Sum Sq Mean Sq F value Pr(>F)
cond 2 28.305 14.153 1.9916 0.2311
Residuals 5 35.531 7.106
Error: subj:session
Df Sum Sq Mean Sq F value Pr(>F)
session 2 4.4502 2.2251 2.9868 0.09616 .
cond:session 4 17.7335 4.4334 5.9509 0.01024 *
Residuals 10 7.4499 0.7450
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
(I ran this one this way b/c of a similar example from Baron's "Notes
for psychology experiments. Unfortunately, neither the session nor
the interaction cond:session are the same as SPSS's output, though the
degrees of freedom are correct in both, of course).
I'm certainly able to believe that SPSS is wrong and R is right, but
thought I'd check with this list to make sure I'm not doing something
completely stupid...
(this is only a partial dataset; I'm using it just to test for now)
thanks!
greg
(I'm drawing heavily on "Notes on the use of R for psychology
experiments and questionnaires" by Jonathan Baron.)
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