similar to: choose the lines2

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)),])

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, 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, 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, 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, I guess you meant this: 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 2?????????????????????

Dear all, I would like to know if it is possible to fit in R a Cox ph model with time-dependent covariates and to account for hierarchical effects at the same time. Additionally, I'd like also to know if it would be possible to perform any feature selection on this model fit. I have a data set that is composed by multiple marker measurements (and hundreds of covariates) at different time

Hello, Hope that someone could help me plotting longitudinal data below: 7213 3333330001 0.8300 13.05.09 1 1 3333330001 0.8700 09.02.05 NULL 4797 3333330001 0.7700 21.03.07 NULL 2399 3333330001 0.7800 12.04.06 NULL 2400 3333330002 NULL 27.03.06 NULL 7230 3333330002 0.8200 14.05.09 0 2 3333330002 0.8400 09.02.05 NULL 4798 3333330002 0.8700 20.03.07 0 4799 3333330003 0.9000 20.03.07 13 2401

Hi R-users, I have a data set like this (first ten rows): id patient_id date code class eala ID1564262 1562 6.4.2006 12:00 5555 1 NA ID1564262 1562 6.4.2006 12:00 5555 1 NA ID1564264 1365 14.2.2006 14:35 5555 1 50 ID1564265 1342 7.4.2006 14:30 2222 2 50 ID1564266 1648 7.4.200614:30 2222 2 50 ID1564267 1263 10.2.2006 15:45 2222 2 10 ID1564267 1263 10.2.200615:45 3333 3 10 ID1564269 5646

I'm a bit of an amateur R programmer. I can do simple R scenarios but my handle on complex grammatical issues isn't steady. I have 12 CSV files that I've read into dataframes. Each has 8 columns and over 2000000 rows. Each dataframe has data associated by time component and a date component in the format of: X.DATE and then X.TIME X.DATE is in the format of MMDDYYYY and X.TIME is

Dear R People: I have two data frames, a.df and b.df as seen here: > a.df[1:10,] DATE GENDER PATIENT_ID AGE SYNDROME 1 4/16/2009 F 23686 45 RASH ON BODY 2 4/16/2009 F 13840 35 CANT URINATE 3 4/16/2009 M 12895 30 BLURRED VISION 4 4/16/2009 M 18375 33 UNABLE TO VOID 5 4/16/2009 M 2237 44

In response to those who asked for a better explanation of what the Vilno software does, here's a simple example that gives some idea of what it does. LABRESULTS is a dataset with multiple rows per patient , with lab sodium measurements. It has columns: PATIENT_ID, VISIT_NUM, and SODIUM. DEMO is a dataset with one row per patient, with demographic data. It has columns: PATIENT_ID, GENDER.

Does anyone have experience with will_paginate? I''m trying to use it with acts_as_ferret. routes.rb ... map.search ''/search'', :controller => ''notes'', :action => ''search'' notes.rb ... acts_as_ferret :fields => [ ''body'' ] notes_controller.rb ... def search if params[ :query ] @query = params[

For an Xray file system patients have folders and folders have studies. That is: patients folders studies id id id name patient_id folder_id ... label type ... ... The list of studies with their associated folder and patient might look like this: name folder_label study_type

I have 316 files. Each file represents a patient's breathing track (respiratory signal recorded for a variable number of cycles). All files have the same are made up of a header followed by a variable number of records. Each record contains 7 comma separated fields. The patient ID is recorder in the header which is stripped off when reading the file into a R data.frame. Since I need to keep

Dear All, Writing sooner than I thought I'd need to. I'm using R 2.4 on Mac OS X, with RODBC, PostgreSQL 8.1 and Actual's ODBC driver. I have all my data in Filemaker 8.5, but it is automatically exported into PostgreSQL for analysis as Filemaker's ODBC and JDBC access is awful, slow and has a tendency to crash. I have disability data where for each patient there is a survival

Hi, directory<- "/home/arunksa111/data.new" #first function filelist<-function(directory,number,list1){ setwd(directory) filelist1<-dir(directory) direct<-dir(directory,pattern = paste("MSMS_",number,"PepInfo.txt",sep=""), full.names = FALSE, recursive = TRUE) list1<-lapply(direct, function(x) read.table(x,header=TRUE, sep =