Displaying 4 results from an estimated 4 matches for "lst7".
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lst
2013 Jun 08
0
data
...)
???????? lst5<- lst4[lapply(lst4,length)>0]
??? ?lst6<- lapply(lst5,function(x) {
??? ??? ??? ??? ??? lst<- lapply(x,function(y){
??? ??? ??? ??? ??? ??? ? y[!all(y$dummy==1),]
??? ??? ??? ??? ??? ??? ?? })
??? ??? ??? ??? ??? lst[lapply(lst,nrow)>0]
??? ??? ??? ??? ??? })
???????? lst7<- lapply(lst6,function(x){
??? ??? ??? ??? ??? lst<- lapply(x,function(y) {
??? ??? ??? ??? ??? ??? x1<- y[1,]
??? ??? ??? ??? ??? ??? x2<- y[-1,]
??? ??? ??? ??? ??? ??? x3<- subset(x2,dummy==0)
??? ??? ??? ??? ??? ??? x4<- x3[which.min(abs(x1$dimension-x3$dimension)),]
??? ??? ?...
2013 Jun 04
0
choose the lines2
...!=0]
?? names(lst6)<- unlist(lapply(lst6,function(x) unique(x$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)
#$`2`
#??? X patient_id number responsed_at? t basdai_d evnmt_brutal
#13 13????????? 2???? 12?? 2011-07-05 12???? -1.0??????????? 0
#14 14????????? 2???? 13?? 2011-08-07 13????...
2013 Jun 04
0
choose the lines2
...??? ??? ??? ??? ??? ??? ??? ??? ))
??? ??? ??? ??? ??? ??? ??? ??? ??? })
?? lst6<-lst5[lapply(lst5,nrow)!=0]
?? names(lst6)<- unlist(lapply(lst6,function(x) unique(x$patient_id)))
?? Mean0bet_01<- do.call(rbind,lapply(lst6,function(x) mean(x[seq(nrow(x))%%3==2,"basdai_d"])))
?? lst7<-list(lst6,Mean0bet_01)
?? lst7
?? #lapply(lst7,head,2)???
?? }?? ??? ??? ??? ???
fun2(dat.bru)
##output from first 2 patients
#[[1]]
#[[1]]$`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??...
2013 Jun 07
4
matched samples, dataframe, panel data
I R-helpers
#I have a data panel of thousands of firms, by year and industry and
#one dummy variable that separates the firms in two categories: 1 if the firm have an auditor; 0 if not
#and another variable the represents the firm dimension (total assets in thousand of euros)
#I need to create two separated samples with the same number os firms where
#one firm in the first have a corresponding