Hi Yao,
You could also have the results in a wide format:
res<-do.call(rbind,lapply(lapply(split(b,b$variable),function(x) t.test(x$value[x$O2=="13%"],x$value[x$O2=="21%"])),function(x) data.frame(mean13=x$estimate[1],mean21=x$estimate[2],p.value=x$p.value,CILow=x$conf.int[1],CIHigh=x$conf.int[2])))
res
# mean13 mean21 p.value CILow CIHigh
#EMW 14.35000 17.68000 0.09355374 -7.682686 1.022686
#EW.17.5 42.87000 45.97333 0.17464018 -9.265622 3.058955
#EW.INCU 49.61333 47.08333 0.43689727 -7.119234 12.179234
A.K.
----- Original Message -----
From: Yao He <yao.h.1988 at gmail.com>
To: arun <smartpink111 at yahoo.com>
Cc: R help <r-help at r-project.org>
Sent: Monday, January 7, 2013 10:57 AM
Subject: Re: [R] how to aggregate T-test result in an elegant way?
Hi,arun
Yes , I just want to do the t.test
I think maybe it is not necessary to generate a 3D array from the raw
data.frame by acast() at first
Thanks a lot
2013/1/7 arun <smartpink111 at yahoo.com>:
Hi Yao,
It's okay.
How did you generate the 3 D array?
Using ?acast()
I am not sure I understand your question "
if you meet a t-test task as I described , is that generate a
high-dimension array a good way ?"
Do you want to do the t-test in the melt dataset?
b<- read.table(text="
ID O2 variable value
1 TWF2H5 13% EW.INCU 49.38
2 TWF2H6 13% EW.INCU 48.02
3 TWF2H19 13% EW.INCU 51.44
280 TWF2H101 13% EW.17.5 42.26
281 TWF2H105 13% EW.17.5 43.52
282 TWF2H106 13% EW.17.5 42.83
472 TWF2N102 21% EW.17.5 45.97
473 TWF2N104 21% EW.17.5 43.32
474 TWF2N106 21% EW.17.5 48.63
689 TWF2N2 21% EMW 19.57
690 TWF2N6 21% EMW 18.07
691 TWF2N10 21% EMW 15.4
491 TWF2H5 13% EMW 15.61
492 TWF2H6 13% EMW 13.41
493 TWF2H19 13% EMW 14.03
199 TWF2N2 21% EW.INCU 48.69
200 TWF2N6 21% EW.INCU 50.52
201 TWF2N10 21% EW.INCU 42.04
",sep="",header=TRUE,stringsAsFactors=FALSE)
res<-lapply(lapply(split(b,b$variable),function(x) t.test(x$value[x$O2=="13%"],x$value[x$O2=="21%"])),function(x) data.frame(mean=x$estimate,p.value=x$p.value))
res1<-do.call(rbind,res)
row.names(res1)[grep("mean of x",row.names(res1))]<-gsub("(.*\\.).*$","\\113%",row.names(res1)[grep("mean of x",row.names(res1))])
row.names(res1)[grep("mean of y",row.names(res1))]<-gsub("(.*\\.).*$","\\121%",row.names(res1)[grep("mean of y",row.names(res1))])
res1
# mean p.value
#EMW.13% 14.35000 0.09355374
#EMW.21% 17.68000 0.09355374
#EW.17.5.13% 42.87000 0.17464018
#EW.17.5.21% 45.97333 0.17464018
#EW.INCU.13% 49.61333 0.43689727
#EW.INCU.21% 47.08333 0.43689727
A.K.
----- Original Message -----
From: Yao He <yao.h.1988 at gmail.com>
To: arun <smartpink111 at yahoo.com>
Cc: R help <r-help at r-project.org>
Sent: Monday, January 7, 2013 4:00 AM
Subject: Re: [R] how to aggregate T-test result in an elegant way?
Hi, arun
I'm so sorry for that isn't helpful.
One of question is that I don't know how to subset a small part as it
is a 3-dimension array so I just show the structure of that.
I tried dput() to a file , then what should I do for subsetting it?
Another question is :
My rawdata is a "melt" dataframe like that:
IID O2 variable value
1 TWF2H5 13% EW.INCU 49.38
2 TWF2H6 13% EW.INCU 48.02
3 TWF2H19 13% EW.INCU 51.44
280 TWF2H101 13% EW.17.5 42.26
281 TWF2H105 13% EW.17.5 43.52
282 TWF2H106 13% EW.17.5 42.83
472 TWF2N102 21% EW.17.5 45.97
473 TWF2N104 21% EW.17.5 43.32
474 TWF2N106 21% EW.17.5 48.63
689 TWF2N2 21% EMW 19.57
690 TWF2N6 21% EMW 18.07
691 TWF2N10 21% EMW 15.4
491 TWF2H5 13% EMW 15.61
492 TWF2H6 13% EMW 13.41
493 TWF2H19 13% EMW 14.03
199 TWF2N2 21% EW.INCU 48.69
200 TWF2N6 21% EW.INCU 50.52
201 TWF2N10 21% EW.INCU 42.04
if you meet a t-test task as I described , is that generate a
high-dimension array a good way ?
Thank you!
Yao He
2013/1/7 arun <smartpink111 at yahoo.com>:
HI,
I tried to create an example dataset (as you didn't provide the data).
set.seed(25)
a<-array(sample(1:50,60,replace=TRUE),dim=c(2,10,3))
dimnames(a)[[1]]<-c("13%","21%")
dimnames(a)[[2]]<-paste("TWF2H",101:110,sep="")
dimnames(a)[[3]]<-c("EW.INCU","EW.17.5","EMW")
str(a)
# int [1:2, 1:10, 1:3] 21 35 8 45 7 50 32 17 4 15 ...
#- attr(*, "dimnames")=List of 3
#..$ : chr [1:2] "13%" "21%"
.#.$ : chr [1:10] "TWF2H101" "TWF2H102" "TWF2H103" "TWF2H104" ...
#..$ : chr [1:3] "EW.INCU" "EW.17.5" "EMW"
res<-lapply(lapply(seq_len(dim(a)[3]),function(i) t.test(a[dimnames(a)[[1]][1],,i],a[dimnames(a)[[1]][2],,i])),function(x) data.frame(mean=x$estimate,p.value=x$p.value))
res1<-do.call(rbind,res)
row.names(res1)[grep("mean of x",row.names(res1))]<-gsub("(.*\\.).*$","\\113%",row.names(res1)[grep("mean of x",row.names(res1))])
row.names(res1)[grep("mean of y",row.names(res1))]<-gsub("(.*\\.).*$","\\121%",row.names(res1)[grep("mean of y",row.names(res1))])
res1
# mean p.value
#EW.INCU.13% 22.3 0.2754842
#EW.INCU.21% 29.3 0.2754842
#EW.17.5.13% 20.5 0.4705772
#EW.17.5.21% 16.0 0.4705772
#EMW.13% 23.9 0.9638679
#EMW.21% 24.2 0.9638679
A.K.
----- Original Message -----
From: Yao He <yao.h.1988 at gmail.com>
To: arun <smartpink111 at yahoo.com>
Cc: R help <r-help at r-project.org>
Sent: Sunday, January 6, 2013 11:21 PM
Subject: Re: [R] how to aggregate T-test result in an elegant way?
Thank you?it is really helpful everytime.
I didn't provide any example data because I thought it is just a
question of how to report t.test() result in R.
However,as you say,it is better to show more details for finding an elegant way
In fact I generate a 3-dimension array like that:
str(a)
num [1:2, 1:245, 1:3] 47.5 NA 48.9 NA 47.5 ...
- attr(*, "dimnames")=List of 3
..$ : chr [1:2] "13%" "21%"
..$ : chr [1:245] "TWF2H101" "TWF2H105" "TWF2H106" "TWF2H110" ...
..$ : chr [1:3] "EW.INCU" "EW.17.5" "EMW"
I want to do two sample mean t-test between 13% and 21% for each
variable "EW.INCU" "EW.17.5" "EMW".
So I try these codes:
variable<-dimnames(a)[[3]]
O2<-dimnames(a)[[1]]
for (i in variable) {
print(i)
print(O2[1])
print(O2[2])
print(t.test(a[O2[1],,i],a[O2[2],,i],na.rm=T))
}
I don't think it is an elegant way and I am inexperience to report raw result.
Could you give me more help?
Yao He
2013/1/7 arun <smartpink111 at yahoo.com>:
Hi,
You didn't provide any example data. So, I am not sure whether this helps.
set.seed(15)
dat1<-data.frame(A=sample(10:20,5,replace=TRUE),B=sample(18:28,5,replace=TRUE),C=sample(25:35,5,replace=TRUE),D=sample(20:30,5,replace=TRUE))
res<-lapply(lapply(seq_len(ncol(dat2)),function(i) t.test(dat2[,i],dat1[,1],paired=TRUE)),function(x) data.frame(meanDiff=x$estimate,p.value=x$p.value))# paired
names(res)<-paste("A",LETTERS[2:4],sep="")
res<- do.call(rbind,res)
res
# meanDiff p.value
#AB 9.4 0.021389577
#AC 15.0 0.002570261
#AD 10.6 0.003971604
#or
res1<-lapply(lapply(seq_len(ncol(dat2)),function(i) t.test(dat2[,i],dat1[,1],paired=FALSE)),function(x) data.frame(mean=x$estimate,p.value=x$p.value))
names(res1)<-paste("A",LETTERS[2:4],sep="")
res1<-do.call(rbind,res1)
row.names(res1)[grep("mean of y",row.names(res1))]<-gsub("(.*\\.).*","\\1A",row.names(res1)[grep("mean of y",row.names(res1))])
row.names(res1)[grep("mean of x",row.names(res1))]<-gsub("(\\w)(\\w)(\\.).*","\\1\\2\\3\\2",row.names(res1)[grep("mean of x",row.names(res1))])
res1
# mean p.value
#AB.B 25.2 1.299192e-03
#AB.A 15.8 1.299192e-03
#AC.C 30.8 5.145519e-05
#AC.A 15.8 5.145519e-05
#AD.D 26.4 1.381339e-03
#AD.A 15.8 1.381339e-03
A.K.
----- Original Message -----
From: Yao He <yao.h.1988 at gmail.com>
To: r-help at r-project.org
Cc:
Sent: Sunday, January 6, 2013 10:20 PM
Subject: [R] how to aggregate T-test result in an elegant way?
Dear all:
Plan 1:
I want to do serval t-test means for different variables in a loop ,
so I want to add all results to an object then dump() them to an
text. But I don't know how to append T-test result to the object?
I have already plot the barplot and I want to know an elegant way to
report raw result.
Can anybody give me some pieces of advice?
Yao He
?????????????????????????
Master candidate in 2rd year
Department of Animal genetics & breeding
Room 436,College of Animial Science&Technology,
China Agriculture University,Beijing,100193
E-mail: yao.h.1988 at gmail.com
??????????????????????????