[R] t-test across columns

[David Carlson]

This may be close to what you want:

> t.val <- by(x, x$cat, function(y) if (min(table(y$name)>1)) {
+      t.test(val~name, y)})
> t.out <- do.call(rbind, sapply(t.val, function(y) c(y$statistic, 
+       p.value=y$p.value)))
> t.out
                    t      p.value
p178266580 -0.1156475 0.9144054453
p178316310 -1.0874356 0.4143944591
p191287337 -0.6776053 0.5315717871
p195158904  1.1522850 0.2769290728
p196921846 -4.2342996 0.0003925339

But I'm not sure what you mean about columns for each cat unless you
want the frequencies: 

> freq.out <- xtabs(~cat+name, x)
> freq.out <- freq.out[apply(freq.out, 1, function(y) min(y) > 1),]
> freq.out
            name
cat          12.2 15.9
  p178266580    4   11
  p178316310    2    3
  p191287337    3    5
  p195158904    8    7
  p196921846   26    5
> results <- cbind(freq.out, t.out)
> results
           12.2 15.9          t      p.value
p178266580    4   11 -0.1156475 0.9144054453
p178316310    2    3 -1.0874356 0.4143944591
p191287337    3    5 -0.6776053 0.5315717871
p195158904    8    7  1.1522850 0.2769290728
p196921846   26    5 -4.2342996 0.0003925339

-------------------------------------
David L Carlson
Associate Professor of Anthropology
Texas A&M University
College Station, TX 77840-4352



-----Original Message-----
From: r-help-bounces at r-project.org
[mailto:r-help-bounces at r-project.org] On Behalf Of Nico Met
Sent: Monday, July 15, 2013 10:50 AM
To: R help
Subject: [R] t-test across columns

Dear all,

I would like to do t-test across two columns "name" with different
"cat"
with overall mean ("val").

(Removing if there is a single observation)

And finally, make a matrix with t-value and p-value associated with
a name
(in rows) and cat (in columns)

dput(x)
structure(list(name = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 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, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("12.2", "15.9"
), class = "factor"), cat = structure(c(2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L, 1L, 1L, 3L, 1L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 8L, 8L,
8L, 8L, 8L, 8L, 8L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L), .Label =
c("p178266580",
"p178269196", "p178316310", "p191287337", "p195158904",
"p196921846",
"p197427158", "p238921966"), class = "factor"), val = c(148.90772,
184.253375, 183.974866666667, 191.868125, 173.30515, 187.876975,
177.453775, 184.799525, 212.39065, 205.504525, 186.152025,
194.337075,
193.2703, 204.71665, 211.4452, 202.609175, 203.72918, 193.7261,
196.1186, 202.79556, 203.48818, 191.13744, 205.23315, 198.66842,
196.81032, 200.90512, 206.13564, 205.372225, 196.22835, 211.04686,
219.977133333333, 224.7602, 231.6596, 211.105816666667, 215.44474,
210.83514, 228.173125, 224.09034, 212.96026, 239.0085, 213.5407,
227.12115, 209.24888, 232.8964, 232.22146, 228.1643, 236.43082,
232.20792, 238.49192, 224.64014, 233.75898, 207.06138, 215.3649,
211.14802, 201.86854, 200.52278, 199.05752, 194.90904, 214.44334,
249.357266666667, 239.98525, 234.508483333333, 243.865083333333,
233.595816666667, 248.1219, 225.289416666667, 248.220883333333,
193.69566, 198.43578, 205.06055, 208.525975, 198.28692, 206.88496,
201.60162, 205.7943, 210.5117, 196.69886, 193.58288, 198.86094,
201.81676, 225.8266, 205.879725, 218.370475, 214.006125, 198.74038,
206.00314, 198.37446, 225.5357, 216.721025, 226.543925, 158.1011,
158.15674, 166.07518, 179.942225, 158.16046, 165.0685, 159.56146
)), .Names = c("name", "cat", "val"), class = "data.frame",
row.names = c(
NA,
97L))

Thanks

Nico

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