similar to: Adjusted survival curves

For adjusted survival curves I took the sample code from here: https://rpubs.com/daspringate/survival and adapted for my date, but ... have a QUESTION. library(survival) library(survminer) df<-read.csv("base.csv", header = TRUE, sep = ";") head(df) ID start stop censor sex age stage treatment 1 1 0 66 0 2 1 3 1 2 2 0 18 0 1 2 4 2 3 3 0 43 1 2 3 3 1 4 4 0 47 1 2 3 NA 2 5 5

Adjusted survival curves (Thanks to sample code: https://rpubs.com/daspringate/survival ) Thanks to Moderator/Admin's Great Work! For a successful solution I used advice that could be understood: 1. Peter Dalgaard: The code does not work, because the covariates are not factors. 2. Jeff Newmiller: "Change the columns into factors before you give them to the coxph function, e.g.

Adjusted survival curves. (Sample code here: https://rpubs.com/daspringate/survival ) Deep gratitude?to Moderator/Admin! At?David Winsemius prompt, more elegant working code:Thanks, Ted :) library(survival) library(survminer) df<-read.csv("F:/R/data/edgr-orig.csv", header = TRUE, sep = ";") df2 <- df df2[,c('treatment', 'age', 'sex',

Hi all,? The survdiff() from survival package has an argument "rho" that implements Fleming-Harrington weighted long rank test.? But according to several sources including "survminer" package (https://cran.r-project.org/web/packages/survminer/vignettes/Specifiying_weights_in_log-rank_comparisons.html), Fleming-Harrington weighted log-rank test should have 2 parameters

Hi. I am using Windows version of R 1.8.1. Being somewhat new to survival analysis, I am trying to compare cph (Design) with coxph (survival) for use with a survival data set. I was wondering why cph and coxph provide me with different confidence intervals for the hazard ratios for one of the variables. I was wondering if I am doing something wrong? Or if the two functions are calculating hazard

> On Feb 13, 2018, at 4:02 PM, array chip via R-help <r-help at r-project.org> wrote: > > Hi all, > > The survdiff() from survival package has an argument "rho" that implements Fleming-Harrington weighted long rank test. > > But according to several sources including "survminer" package

> On Feb 14, 2018, at 5:26 PM, David Winsemius <dwinsemius at comcast.net> wrote: > >> >> On Feb 13, 2018, at 4:02 PM, array chip via R-help <r-help at r-project.org> wrote: >> >> Hi all, >> >> The survdiff() from survival package has an argument "rho" that implements Fleming-Harrington weighted long rank test. >>

I'm trying to fit a Cox proportional hazards model to some hospital admission data. About 25% of the patients have had at least one admission, and of these, 40% have had two admissions within the 12 month period of the study. Each patients has had one of 4 treatments, and one of the treatment groups has had no admissions for the period. I used:

hello: my data looks like: time1  time2   event  catagoria 2004    2006        1            C 2004    2005        0            C 2005    2010        1            E 2007    2009        1            C 2006    2007        0            E 2008    2010        0            C 2008    2010        1            E ... and the census interval is 1 year I have tried  this

Hi r users, I have two data sets (X1, X2). For example, time1<-c( 0, 8, 15, 22, 43, 64, 85, 106, 127, 148, 169, 190 ,211 ) outpue1<-c(171 ,164 ,150 ,141 ,109 , 73 , 47 ,26 ,15 ,12 ,6 ,2 ,1 ) X1<-cbind(time1,outpue1) time2<-c( 0 ,8 ,15 , 22 ,43 , 64 ,85 ,106 ,148) output2<-c( 5 ,5 ,4 ,5 ,5 ,4 ,1 ,2 , 1 ) X2<-cbind(time2,output2) I want to

Greetings listeRs - Given a data frame such as times time1 time2 time3 time4 1 70.408543 48.92378 7.399605 95.93050 2 17.231940 27.48530 82.962916 10.20619 3 20.279220 10.33575 66.209290 30.71846 4 NA 53.31993 12.398237 35.65782 5 9.295965 NA 48.929201 NA 6 63.966518 42.16304 1.777342 NA one can use "transform" to

Dear all, I have data from 1970 to 1990 for people above age 50. Now I want to calculate survival curves by age starting at age 50 using the Kaplan Meier Estimator. The problem I have is that there are already people in 1970 who are older than 50 years. I guess this is called delayed entry or left truncation (?). I thought the code would be: roland <- survfit(Surv(time=age.enter,

Hi, I would like to merge two data frames. It is just that I want the merging to be done with some kind of a fuzzy criterion. Let me explain. My first data frame looks like this : ID1 time1 dt 1 2008-01-02 13:11 10 2 2008-01-02 14:20 20 3

Dear List, I have (for example) 50 observations collected from 50 experimental sites and want to look at changes of 50 observations as function of time in a graph. I found that I could do that using R-code below: time2 <- 1:25 y1=rnorm(25, mean=0, sd=1) y2=rnorm(25, mean=0, sd=1) ... y50=rnorm(25, mean=2, sd=1) plot(time2, y1, type='b', xlim=range(0,30), ylim=range(y1, y2),

Hola Javier, Muchas gracias por responder tan rápido! Yo trabajo en Mac OS X 10.9.4. Versión 0.98.953 de RStudio. Versión 3.0.2 (2013-09-25) de R. ## Este es el script que estoy trabajando. Se trata de una rutina para automatizar el cálculo de la duración del evento. setwd("/Users/angelacamargosanabria/Documents/ANGELITA/1-DOC/1-TESIS/4-PAPERS/1-Mamiferos/DATOS/Bases") BASE <-

Hello all, I've 2 strings that representing the start and end values of a date and time. For example, time1 <- c("21/04/2005","23/05/2005","11/04/2005") time2 <- c("15/07/2009", "03/06/2008", "15/10/2005") as.difftime(time1,time2) Time differences in secs [1] NA NA NA attr(,"tzone") [1] "" How can i

Hola Pedro. El INE cambió los ficheros de microdatos no hace mucho, aquí dejo como se haría ahora, (utilizando MicroDatosEs). Lo que cambia es la función para recodificar. http://rpubs.com/joscani/unemplrate El 15/10/14 a las #4, Carlos Ortega escribió: > Hola Pedro, > > Acabo de recordar que hace poco José Luis Cañadas (participa en esta lista) > publicó un enlace suyo a un

To Whomever is Interested, I have spent several days searching the web, help files, the R wiki and the archives of this mailing list for a solution to this problem, but nonetheless I apologize in advance if I have missed something obvious. The problem is this; I have a 5-column data frame with about 4.2 million rows, and want to create a new (and hopefully much smaller) data frame that

Could of requests: 1) Is there any example or writeup on the difficulties of extending reference classes across packages? Just so I can fully understand the issues. 2) In what sorts of situations does the performance of reference classes cause problems? Sure, it's an order of magnitude slower than constructing a simple environment, but those timings are in microseconds, so one would need a

Hello, Below is the code for a basic bar graph. I was seeking advice regarding the following: (a) For each time period there are values from 16 people. How I can change the colour value so that each person has a different colour, which recurs across each of the three graphs/tie epriods? (b) I have seen much more sophisticated examples using lattice (e.g each person has a separate