indexing for Wilcoxon test (take 2)

Wed, Nov 14, 2012 11:00 AM

Hello,

Thanks for the data example.
Try the following.

sp <- split(dat, dat$trial)
control <- sp[[1]]
lapply(sp[-1], function(x) wilcox.test(control[["removed"]], 
x[["removed"]]))

Hope this helps,

Rui Barradas

Em 14-11-2012 18:01, 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

structure(list(id = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L), trial = c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L), sex = c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), removed = c(2.65,
1.41, 2.24, 0, 2.65, 3.87, 2.24, 2.65, 4.36, 2.24, 2.45, 2.45,
2.45, 2.24, 2.45, 2.65, 5.48, 2.65, 2.83, 1.73, 2.45, 2.24, 2.45,
3.46, 1.41, 1.73, 2.45, 1, 2.83, 1.73, 2.83, 3, 3.74, 2.24, 2.24,
1.41, 2.83, 2.45, 3.16, 3.61, 3.61, 3.16, 2.65, 2.65, 3.74, 2,
5.39, 5.48, 4.69, 3.46, 2.45, 5.39, 3.74, 1.73, 3.74, 3.32, 4.24,
0, 3, 1, 3, 2, 3.16, 3.46, 3.16, 1, 2.83, 1.41, 5.48, 2.45, 3.46,
2.45, 3.16, 1, 2.65, 3, 1.73, 3.61, 4.12, 2.24), eaten = c(2,
1, 1, 0, 2.24, 1, 0, 1.41, 2.45, 2, 1.73, 2, 2, 1, 1, 1.73, 2.83,
2, 2.45, 1.41, 2.45, 1, 1.41, 2.65, 1, 1.73, 2.24, 1, 1.73, 1.73,
2.24, 1.73, 2.83, 2, 1.73, 1, 2.24, 1, 2, 2, 2.45, 2.24, 2.45,
1.73, 2.24, 1.41, 1.73, 2.45, 2, 2, 2.24, 1.73, 2.45, 1.73, 1,
2.45, 2, 0, 1.73, 1, 2.24, 1.41, 2, 2.45, 1.73, 1, 2, 1.41, 1.73,
1.41, 2.24, 2.24, 1.41, 1, 2, 1, 1.73, 1.41, 2, 2.24), scatter = c(1.41,
0, 1.73, 0, 0, 2.83, 0, 2.24, 3, 1, 1.41, 0, 1.41, 1.41, 1.41,
2, 0, 1.73, 1, 0, 0, 1.73, 0, 2.24, 0, 0, 0, 0, 1.41, 0, 0, 2.45,
2, 1, 1.41, 1, 1.73, 2, 1, 2.45, 1, 1.73, 1, 1.41, 1.41, 1.41,
1.41, 3.61, 1, 2.83, 1, 0, 1, 0, 1, 2.24, 1.73, 0, 2.45, 0, 0,
1.41, 0, 2.45, 0, 0, 2, 0, 0, 1.73, 0, 1, 1, 0, 1, 1.41, 0, 2.45,
1, 0), larder = c(1, 1, 1, 0, 1.41, 2.45, 2.24, 0, 2, 0, 1, 1.41,
0, 1.41, 1.73, 0, 4.69, 0, 1, 1, 0, 1, 2, 0, 1, 0, 1, 0, 1.73,
0, 1.73, 0, 1.41, 0, 0, 0, 0, 1, 2.24, 1.73, 2.45, 1.41, 0, 1.41,
2.65, 0, 4.9, 3.32, 4.12, 0, 0, 5.1, 2.65, 0, 3.46, 0, 3.32,
0, 0, 0, 2, 0, 2.45, 0, 2.65, 0, 0, 0, 5.2, 1, 2.65, 0, 2.65,
0, 1.41, 2.45, 0, 2.24, 3.46, 0), total = c(1.73, 1, 2, 0, 1.41,
3.74, 2.24, 2.24, 3.61, 1, 1.73, 1.41, 1.41, 2, 2.24, 2, 4.69,
1.73, 1.41, 1, 0, 2, 2, 2.24, 1, 0, 1, 0, 2.24, 0, 1.73, 2.45,
2.45, 1, 1.41, 1, 1.73, 2.24, 2.45, 3, 2.65, 2.24, 1, 2, 3, 1.41,
5.1, 4.9, 4.24, 2.83, 1, 5.1, 2.83, 0, 3.61, 2.24, 3.74, 0, 2.45,
0, 2, 1.41, 2.45, 2.45, 2.65, 0, 2, 0, 5.2, 2, 2.65, 1, 2.83,
0, 1.73, 2.83, 0, 3.32, 3.61, 0)), .Names = c("id", "trial",
"sex", "removed", "eaten", "scatter", "larder", "total"), class =
"data.frame", row.names = c(NA,
-80L))

(Obrigado Rui!)

indexing for Wilcoxon test (take 2)

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