[R] Collapsing across trials

[Pedro Alcocer]

Hello,

My ultimate goal is a repeated measures (mixed model) ANOVA, however,
my present question is about how to reorganize my data into the format
that the ANOVA commands expect. In particular, how to collapse across
trials. (I am using the tutorial at
[http://personality-project.org/r/r.anova.html] for the mixed model
ANOVA)

The data I am using looks like this. A subject sees 10 trials per
condition and there are 2 conditions. I want the average of all the
reaction times (RTs) from a subject looking a one condition. I also
want to retain List in the final output.

Subj	List	Condition	RT
2	1	C		338
2	1	C		227
2	1	C		430
2	1	C		621
2	1	C		255
2	1	C		348
2	1	C		280
2	1	C		356
2	1	C		272
2	1	C		346
3	2	C		489
3	2	C		426
3	2	C		352
3	2	C		351
3	2	C		349
3	2	C		403
3	2	C		336
3	2	C		278
3	2	C		365
3	2	C		271
2	1	D		360
2	1	D		374
2	1	D		326
2	1	D		363
2	1	D		290
2	1	D		458
2	1	D		295
2	1	D		362
2	1	D		285
2	1	D		277
3	2	D		354
3	2	D		352
3	2	D		362
3	2	D		360
3	2	D		334
3	2	D		365
3	2	D		335
3	2	D		391
3	2	D		272
3	2	D		618

The result should look like this:
2	1	C		(AVG)
3	2	C		(AVG)
2	1	D		(AVG)
3	2	D		(AVG)

Where (AVG) is the average of the 10 trials.

The above is a simplified case. How can I do this with multiple RT
measurements per subject? In other words, the above, but with more
than one RT column per subject.

Resulting in:

Subj	List	Condition	RT1		RT2		RT3		RT4		RT5
2	1	C		(AVG1)	(AVG2)	(AVG2)	(AVG2)	(AVG2)
3	2	C		(AVG1)	(AVG2)	(AVG2)	(AVG2)	(AVG2)
2	1	D		(AVG1)	(AVG2)	(AVG2)	(AVG2)	(AVG2)
3	2	D		(AVG1)	(AVG2)	(AVG2)	(AVG2)	(AVG2)

I've come across the apply and aggregate functions in online
documentation, and I have the suspicion that they may be called for
here, but their application isn't clear to me. I am fairly new to R.

(I am using R 2.4.0 on Mac OS X.)

I'd appreciate any insights.

Pedro Alcocer
University of Florida