similar to: choose the lines2

Hi, May be this helps: 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)),])

Hi, Try this: final3New<-read.table(file="real_data_cecilia.txt",sep="\t") dim(final3New) #[1] 5369??? 5 #Inside the split within split, dummy==1 for the first row.? For lists that have many rows, I selected the row with dummy==0 (from the rest) using the #condition that the absolute difference between the dimensions of those rows and the first row dimension was minimum

Hi, Try this: dat1<- read.csv("dat7.csv",header=TRUE,stringsAsFactors=FALSE,sep="\t") dat.bru<- dat1[!is.na(dat1$evnmt_brutal),] fun1<- function(dat){??? ? ??? lst1<- split(dat,dat$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)),]) ???

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

Hi, I am not sure I understand your question correctly. dat1<- read.table(text=" id??????????? responsed_at???????????????? number_of_connection????????????????? scores 1????????????????? 12-01-2010?????????????????????????????????? 1????????????????????????????????????????????? 2 1????????????????? 15-02-2010??????????????????????????????????

Hi, One problem with your example dataset is that you have 11 list elements with the last one having different dimensions.? I think it was based on `summarized`. Then, the second problem I encountered for testing is that the dataset you provided doesn't fulfill the criteria. lst1<- list(structure(list......) #output of dput ? lst2<- lst1[1:10] #deleted the last list element

Hi, Your question is still not clear. May be this helps: dat2<- read.table(text=" patient_id????? t???????? scores 1????????????????????? 0??????????????? 1.6 1????????????????????? 1??????????????? 2.6 1????????????????????? 2???????????????? 2.2 1????????????????????? 3???????????????? 1.8 2????????????????????? 0????????????????? 2.3 2?????????????????????? 2???????????????? 2.5

Hi all, The C++11 (& C11) compare_exchange functions with explicit memory order allow you to specify two sets of semantics, one for when the exchange actually happens and one for when it fails. Unfortunately, at the moment the LLVM IR "cmpxchg" instruction only has one ordering, which means we get sub-optimal codegen. This probably affects all architectures which use