Hi everyone, I've been asked to run a number of Wilcoxon tests on some behavioral data (below is a sample). They want me to compare each trial to the first trial, considered the control trial. I know I can use brackets to index and select, for example, trial 1 vs. trial 4 (not exactly sure how to set that up either) but it would save me a ton of time if there was a way to do all the comparisons at once - but for one response variable (e.g., removed) at a time. Thanks so much! Jeff id trial sex removed eaten scatter larder total 1 1 1 2.65 2 1.41 1 1.73 2 1 1 1.41 1 0 1 1 3 1 1 2.24 1 1.73 1 2 4 1 1 0 0 0 0 0 5 1 1 2.65 2.24 0 1.41 1.41 6 1 1 3.87 1 2.83 2.45 3.74 7 1 1 2.24 0 0 2.24 2.24 8 1 1 2.65 1.41 2.24 0 2.24 1 2 1 4.36 2.45 3 2 3.61 2 2 1 2.24 2 1 0 1 3 2 1 2.45 1.73 1.41 1 1.73 4 2 1 2.45 2 0 1.41 1.41 5 2 1 2.45 2 1.41 0 1.41 6 2 1 2.24 1 1.41 1.41 2 7 2 1 2.45 1 1.41 1.73 2.24 8 2 1 2.65 1.73 2 0 2 1 3 1 5.48 2.83 0 4.69 4.69 2 3 1 2.65 2 1.73 0 1.73 3 3 1 2.83 2.45 1 1 1.41 4 3 1 1.73 1.41 0 1 1 5 3 1 2.45 2.45 0 0 0 6 3 1 2.24 1 1.73 1 2 7 3 1 2.45 1.41 0 2 2 8 3 1 3.46 2.65 2.24 0 2.24 1 4 1 1.41 1 0 1 1 2 4 1 1.73 1.73 0 0 0 3 4 1 2.45 2.24 0 1 1 4 4 1 1 1 0 0 0 5 4 1 2.83 1.73 1.41 1.73 2.24 6 4 1 1.73 1.73 0 0 0 7 4 1 2.83 2.24 0 1.73 1.73 8 4 1 3 1.73 2.45 0 2.45 1 5 1 3.74 2.83 2 1.41 2.45 2 5 1 2.24 2 1 0 1 3 5 1 2.24 1.73 1.41 0 1.41 4 5 1 1.41 1 1 0 1 5 5 1 2.83 2.24 1.73 0 1.73 6 5 1 2.45 1 2 1 2.24 7 5 1 3.16 2 1 2.24 2.45 8 5 1 3.61 2 2.45 1.73 3 1 6 1 3.61 2.45 1 2.45 2.65 2 6 1 3.16 2.24 1.73 1.41 2.24 3 6 1 2.65 2.45 1 0 1 4 6 1 2.65 1.73 1.41 1.41 2 5 6 1 3.74 2.24 1.41 2.65 3 6 6 1 2 1.41 1.41 0 1.41 7 6 1 5.39 1.73 1.41 4.9 5.1 8 6 1 5.48 2.45 3.61 3.32 4.9 1 7 1 4.69 2 1 4.12 4.24 2 7 1 3.46 2 2.83 0 2.83 3 7 1 2.45 2.24 1 0 1 4 7 1 5.39 1.73 0 5.1 5.1 5 7 1 3.74 2.45 1 2.65 2.83 6 7 1 1.73 1.73 0 0 0 7 7 1 3.74 1 1 3.46 3.61 8 7 1 3.32 2.45 2.24 0 2.24 1 8 1 4.24 2 1.73 3.32 3.74 2 8 1 0 0 0 0 0 3 8 1 3 1.73 2.45 0 2.45 4 8 1 1 1 0 0 0 5 8 1 3 2.24 0 2 2 6 8 1 2 1.41 1.41 0 1.41 7 8 1 3.16 2 0 2.45 2.45 8 8 1 3.46 2.45 2.45 0 2.45 1 9 1 3.16 1.73 0 2.65 2.65 2 9 1 1 1 0 0 0 3 9 1 2.83 2 2 0 2 4 9 1 1.41 1.41 0 0 0 5 9 1 5.48 1.73 0 5.2 5.2 6 9 1 2.45 1.41 1.73 1 2 7 9 1 3.46 2.24 0 2.65 2.65 8 9 1 2.45 2.24 1 0 1 1 10 1 3.16 1.41 1 2.65 2.83 2 10 1 1 1 0 0 0 3 10 1 2.65 2 1 1.41 1.73 4 10 1 3 1 1.41 2.45 2.83 5 10 1 1.73 1.73 0 0 0 6 10 1 3.61 1.41 2.45 2.24 3.32 7 10 1 4.12 2 1 3.46 3.61 8 10 1 2.24 2.24 0 0 0 -- ******************************************************** Jeffrey A. Stratford, PhD Department of Biology and Health Sciences Wilkes University, PA 18766 USA 570-332-2942 http://web.wilkes.edu/jeffrey.stratford/ ******************************************************** [[alternative HTML version deleted]]
Hello, Use ?dput to post data, like this it's unreadable. For instance, dput(Mydata) # paste the output of this in a post. Hope this helps, Rui Barradas Em 14-11-2012 15:58, Jeffrey Stratford escreveu:> Hi everyone, > > I've been asked to run a number of Wilcoxon tests on some behavioral data > (below is a sample). They want me to compare each trial to the first > trial, considered the control trial. I know I can use brackets to index and > select, for example, trial 1 vs. trial 4 (not exactly sure how to set that > up either) but it would save me a ton of time if there was a way to do all > the comparisons at once - but for one response variable (e.g., removed) at > a time. > > Thanks so much! > > Jeff > > id trial sex removed eaten scatter larder total 1 1 1 2.65 2 1.41 1 1.73 > 2 1 1 1.41 1 0 1 1 3 1 1 2.24 1 1.73 1 2 4 1 1 0 0 0 0 0 5 1 1 2.65 2.24 > 0 1.41 1.41 6 1 1 3.87 1 2.83 2.45 3.74 7 1 1 2.24 0 0 2.24 2.24 8 1 1 > 2.65 1.41 2.24 0 2.24 1 2 1 4.36 2.45 3 2 3.61 2 2 1 2.24 2 1 0 1 3 2 1 > 2.45 1.73 1.41 1 1.73 4 2 1 2.45 2 0 1.41 1.41 5 2 1 2.45 2 1.41 0 1.41 6 > 2 1 2.24 1 1.41 1.41 2 7 2 1 2.45 1 1.41 1.73 2.24 8 2 1 2.65 1.73 2 0 2 > 1 3 1 5.48 2.83 0 4.69 4.69 2 3 1 2.65 2 1.73 0 1.73 3 3 1 2.83 2.45 1 1 > 1.41 4 3 1 1.73 1.41 0 1 1 5 3 1 2.45 2.45 0 0 0 6 3 1 2.24 1 1.73 1 2 7 > 3 1 2.45 1.41 0 2 2 8 3 1 3.46 2.65 2.24 0 2.24 1 4 1 1.41 1 0 1 1 2 4 1 > 1.73 1.73 0 0 0 3 4 1 2.45 2.24 0 1 1 4 4 1 1 1 0 0 0 5 4 1 2.83 1.73 > 1.41 1.73 2.24 6 4 1 1.73 1.73 0 0 0 7 4 1 2.83 2.24 0 1.73 1.73 8 4 1 3 > 1.73 2.45 0 2.45 1 5 1 3.74 2.83 2 1.41 2.45 2 5 1 2.24 2 1 0 1 3 5 1 > 2.24 1.73 1.41 0 1.41 4 5 1 1.41 1 1 0 1 5 5 1 2.83 2.24 1.73 0 1.73 6 5 > 1 2.45 1 2 1 2.24 7 5 1 3.16 2 1 2.24 2.45 8 5 1 3.61 2 2.45 1.73 3 1 6 1 > 3.61 2.45 1 2.45 2.65 2 6 1 3.16 2.24 1.73 1.41 2.24 3 6 1 2.65 2.45 1 0 1 > 4 6 1 2.65 1.73 1.41 1.41 2 5 6 1 3.74 2.24 1.41 2.65 3 6 6 1 2 1.41 1.41 > 0 1.41 7 6 1 5.39 1.73 1.41 4.9 5.1 8 6 1 5.48 2.45 3.61 3.32 4.9 1 7 1 > 4.69 2 1 4.12 4.24 2 7 1 3.46 2 2.83 0 2.83 3 7 1 2.45 2.24 1 0 1 4 7 1 > 5.39 1.73 0 5.1 5.1 5 7 1 3.74 2.45 1 2.65 2.83 6 7 1 1.73 1.73 0 0 0 7 7 > 1 3.74 1 1 3.46 3.61 8 7 1 3.32 2.45 2.24 0 2.24 1 8 1 4.24 2 1.73 3.32 > 3.74 2 8 1 0 0 0 0 0 3 8 1 3 1.73 2.45 0 2.45 4 8 1 1 1 0 0 0 5 8 1 3 > 2.24 0 2 2 6 8 1 2 1.41 1.41 0 1.41 7 8 1 3.16 2 0 2.45 2.45 8 8 1 3.46 > 2.45 2.45 0 2.45 1 9 1 3.16 1.73 0 2.65 2.65 2 9 1 1 1 0 0 0 3 9 1 2.83 2 > 2 0 2 4 9 1 1.41 1.41 0 0 0 5 9 1 5.48 1.73 0 5.2 5.2 6 9 1 2.45 1.41 > 1.73 1 2 7 9 1 3.46 2.24 0 2.65 2.65 8 9 1 2.45 2.24 1 0 1 1 10 1 3.16 > 1.41 1 2.65 2.83 2 10 1 1 1 0 0 0 3 10 1 2.65 2 1 1.41 1.73 4 10 1 3 1 > 1.41 2.45 2.83 5 10 1 1.73 1.73 0 0 0 6 10 1 3.61 1.41 2.45 2.24 3.32 7 > 10 1 4.12 2 1 3.46 3.61 8 10 1 2.24 2.24 0 0 0 >