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 [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.