[R] t-test across columns

[arun]

Hi,
Not sure about the format for the 2nd part.
df1<- ##data

library(plyr)
df2<-ddply(df1,.(name,cat),summarize, cbind(t.test(val,df1$val)$statistic,t.test(val,df1$val)$p.value))
 df3<-cbind(df2[,1:2],data.frame(df2[,3]))
 colnames(df3)[3:4]<- c("t-val","p.val")
library(reshape2)
df3m<-  melt(df3,id.var=c("name","cat"))
xtabs(value~name+cat+variable,data=df3m)
, , variable = t-val

      cat
name      p178266580    p178269196    p178316310    p191287337    p195158904
  12.2 -1.1697701975 -5.2812696387 -1.2740973341  2.1926665883  0.1529759080
  15.9 -2.5063901671  0.0000000000 -0.2169806106  1.5455008954 -1.6574358795
      cat
name      p196921846    p197427158    p238921966
  12.2  0.2260409495 -0.3320635130  3.3659689025
  15.9  6.6278680348  0.0000000000  0.0000000000

, , variable = p.val

      cat
name      p178266580    p178269196    p178316310    p191287337    p195158904
  12.2  0.3092408498  0.0003382099  0.3762474897  0.0419925673  0.8812900356
  15.9  0.0147796276  0.0000000000  0.8365830321  0.1822041450  0.1096087365
      cat
name      p196921846    p197427158    p238921966
  12.2  0.8226135494  0.7435688987  0.0071990164
  15.9  0.0005489640  0.0000000000  0.0000000000

#or
res<-dcast(df3m,name~cat+variable,value.var="value")
row.names(res)<- res[,1]
 res1<- res[,-1]
res1
     p178266580_t-val p178266580_p.val p178269196_t-val p178269196_p.val
12.2         -1.16977       0.30924085         -5.28127     0.0003382099
15.9         -2.50639       0.01477963               NA               NA
     p178316310_t-val p178316310_p.val p191287337_t-val p191287337_p.val
12.2       -1.2740973        0.3762475         2.192667       0.04199257
15.9       -0.2169806        0.8365830         1.545501       0.18220414
     p195158904_t-val p195158904_p.val p196921846_t-val p196921846_p.val
12.2        0.1529759        0.8812900        0.2260409      0.822613549
15.9       -1.6574359        0.1096087        6.6278680      0.000548964
     p197427158_t-val p197427158_p.val p238921966_t-val p238921966_p.val
12.2       -0.3320635        0.7435689         3.365969      0.007199016
15.9               NA               NA               NA               NA

A.K.


----- Original Message -----
From: Nico Met <nicomet80 at gmail.com>
To: R help <r-help at r-project.org>
Cc: 
Sent: Monday, July 15, 2013 11:50 AM
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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