[R] repeated measures help; disagreement with SPSS

[Greg Trafton]

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.)
-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-
r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "info", "help", or "[un]subscribe"
(in the "body", not the subject !)  To: r-help-request at stat.math.ethz.ch
_._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._