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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