Dear R list,
again a newbie question here, so I wish I do not exasperated reader.
This is example of my data.frame
subject length consistency context acc frt
1 1 200 high scene_c 0.8181818 396.6642
2 2 200 high scene_c 1.0000000 595.7778
3 3 200 high scene_c 0.9090909 510.7315
4 4 200 high scene_c 0.9000000 503.4444
5 5 200 high scene_c 0.4000000 523.0000
6 6 200 high scene_c 1.0000000 811.5556
7 7 200 high scene_c 1.0000000 661.6402
8 8 200 high scene_c 1.0000000 395.2222
9 9 200 high scene_c 1.0000000 514.0909
10 10 200 high scene_c 0.9000000 654.6012
11 11 200 high scene_c 0.9000000 400.2222
12 12 200 high scene_c 0.8888889 631.1250
...
49 1 800 high scene_c 1.0000000 376.6667
50 2 800 high scene_c 1.0000000 606.2727
51 3 800 high scene_c 0.9000000 541.7778
52 4 800 high scene_c 1.0000000 483.7273
53 5 800 high scene_c 0.5555556 472.4087
...
My experimental plan contain only "within variables": length (200 or 800 ms)
consistency (high or low) and context(scene_c, scene_f, or scene_n) and so I
used aov(frt~length*consistency*context +
Error(subject/(length*consistency*context))) with one row per observation.
How I could obtain simply contrasts for each variables and for interaction?
Do I need using gmodels library with lme?
Thanks
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