HI,
You can do this:
dat1<-
read.csv("dat7.csv",header=TRUE,stringsAsFactors=FALSE,sep="\t")
dat.bru<- dat1[!is.na(dat1$evnmt_brutal),]
fun2<- function(dat){?
????? lst1<- split(dat,dat$patient_id)
??? lst2<- lapply(lst1,function(x) x[cumsum(x$evnmt_brutal==0)>0,])
??? lst3<- lapply(lst2,function(x)
x[!(all(x$evnmt_brutal==1)|all(x$evnmt_brutal==0)),])
??? lst4<- lst3[lapply(lst3,nrow)!=0]
??? lst5<- lapply(seq_along(lst4),function(i){
????????????????????
do.call(rbind,lapply(which(lst4[[i]]$evnmt_brutal==1),function(x) {
??????????????????????????????????????? x1<-c(x-2,x-1,x)
??????????????????????????????????????? x2<-x1[!any(x1==0)]
??????????????????????????????????????? x3<-lst4[[i]][x2,]
???????????????????????????????????????
x4<-x3[!is.na(match(paste(x3$evnmt_brutal,collapse=""),"001")),]
??????????????????????????????????????? x4[!any(duplicated(x4$number))]
??????????????????????????????????????? }
??????????????????????????????????????? ))
??????????????????????????????????? })
?? lst6<-lst5[lapply(lst5,nrow)!=0]
?? names(lst6)<- unlist(lapply(lst6,function(x) unique(x$patient_id)))
?? Mean_01<-do.call(rbind,lapply(lst6,function(x)
cbind(Mean_Middle0=mean(x[seq(nrow(x))%%3==2,"basdai_d"]),Mean_1=mean(x[seq(nrow(x))%%3==0,"basdai_d"]))))
rownames(Mean_01)<- names(lst6)
? ?? lst7<-list(lst6,Mean_01)
?? lst7
?? #lapply(lst7,head,2)??
?? }?????????????????
fun2(dat.bru)
head(fun2(dat.bru)[[1]],3)
#$`2`
#??? X patient_id number responsed_at? t basdai_d evnmt_brutal
#13 13????????? 2???? 12?? 2011-07-05 12???? -1.0??????????? 0
#14 14????????? 2???? 13?? 2011-08-07 13????? 0.9??????????? 0
#15 15????????? 2???? 14?? 2011-09-11 14???? -0.8??????????? 1
#
#$`5`
?# ? X patient_id number responsed_at t basdai_d evnmt_brutal
#52 52????????? 5????? 8?? 2011-01-11 7???? -2.8??????????? 0
#53 53????????? 5????? 9?? 2011-02-13 8????? 0.0??????????? 0
#54 54????????? 5???? 10?? 2011-03-19 9???? -1.2??????????? 1
#
#$`6`
?# ? X patient_id number responsed_at? t basdai_d evnmt_brutal
#74 74????????? 6????? 9?? 2011-02-05? 8???? 0.80??????????? 0
#75 75????????? 6???? 10?? 2011-03-09? 9???? 0.15??????????? 0
#76 76????????? 6???? 11?? 2011-04-11 10??? -0.45??????????? 1
?head(fun2(dat.bru)[[2]],3)
# Mean_Middle0 Mean_1
#2???????? 0.90? -0.80
#5???????? 0.00? -1.20
#6???????? 0.15? -0.45
res1<- fun2(dat.bru)[[1]]
lapply(res1,function(x) tail(x,-1))[1:3]
#$`2`
?# ? X patient_id number responsed_at? t basdai_d evnmt_brutal
#14 14????????? 2???? 13?? 2011-08-07 13????? 0.9??????????? 0
#15 15????????? 2???? 14?? 2011-09-11 14???? -0.8??????????? 1
#
#$`5`
?# ? X patient_id number responsed_at t basdai_d evnmt_brutal
#53 53????????? 5????? 9?? 2011-02-13 8????? 0.0??????????? 0
#54 54????????? 5???? 10?? 2011-03-19 9???? -1.2??????????? 1
#
#$`6`
?# ? X patient_id number responsed_at? t basdai_d evnmt_brutal
#75 75????????? 6???? 10?? 2011-03-09? 9???? 0.15??????????? 0
#76 76????????? 6???? 11?? 2011-04-11 10??? -0.45??????????? 1
#or
res11<-do.call(rbind,lapply(res1,function(x) tail(x,-1)))
row.names(res11)<-1:nrow(res11)
A.K.
________________________________
From: GUANGUAN LUO <guanguanluo at gmail.com>
To: arun <smartpink111 at yahoo.com>
Sent: Tuesday, June 4, 2013 2:10 PM
Subject: choose the lines2
13 2 12 2011/7/5 12 -1 0
14 2 13 2011/8/7 13 0.9 0
15 2 14 2011/9/11 14 -0.8 1
52 5 8 2011/1/11 7 -2.8 0
53 5 9 2011/2/13 8 0 0
54 5 10 2011/3/19 9 -1.2 1
74 6 9 2011/2/5 8 0.8 0
75 6 10 2011/3/9 9 0.15 0
76 6 11 2011/4/11 10 -0.45 1
those are the result which i want, and then i want to choose like this
14 2 13 2011/8/7 13 0.9 0
15 2 14 2011/9/11 14 -0.8 1
53 5 9 2011/2/13 8 0 0
54 5 10 2011/3/19 9 -1.2 1
75 6 10 2011/3/9 9 0.15 0
76 6 11 2011/4/11 10 -0.45 1
so that i can calculate the mean of the lines with evnmt_brutal ==0 and compare
with the lines with evnmt_brutal==1
