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 <nicome...@gmail.com>
To: R help <r-help@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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