similar to: logrank test

hie how do you compute the logrank test using R what commands do you use my data looks something like just an example treatmentgrp strata censoringTime survivalTime censoring act.surv.time [1,] 2 2 42.89005 1847.3358 1 42.89005 [2,] 1 1 74.40379 440.3467 1 74.40379 [3,] 2 2

in R when carring out the log rank test is the censored variable denoted by 1 or 0 or its of no consequence. thanks --------------------------------- always stay connected to friends. [[alternative HTML version deleted]]

hie is it possible to get the code for the logrank test l just need the chisquared value. thanks --------------------------------- [[alternative HTML version deleted]]

How can I get the Log - Rank p value to be output? The chi square value can be output, so I was thinking if I can also have the degrees of freedom output I could generate the p value, but can't see how to find df either. > (survtest <- survdiff(Surv(time, cens) ~ group, data = surv,rho=0)) Call: survdiff(formula = Surv(time, cens) ~ group, data = surv, rho = 0) N Observed

l'm trying to find the "survdiff" package/function but it seems i cant get it how do l instal it if its not there thanks --------------------------------- [[alternative HTML version deleted]]

R Folk: Please forgive what I'm sure is a fairly na?ve question; I hope it's clear. A colleague and I have been doing a really simple one-off survival analysis, but this is an area with which we are not very familiar, we just happen to have gathered some data that needs this type of analysis. We've done quite a bit of reading, but answers escape us, even though the question below

Hello! I want to compare two Kaplan-Meier-Curves by using the Logrank-Test: logrank(Surv(time[b], status[b]) ~ group[b]) This way I only get the value of the test-statistic, but not the p-value. Does anybody know how I can get the p-value? Thanks in advance! Verena Hoffmann

hie 1...i'm trying to carryout a relibility testusing cronbach's alpha what fuctin do i use. 2.. this is more of a statistical question.if the alpha value for all the variables is negative what does it mean. and if the alpha value is negative for all tyha variables but is greater than 0.7 for some sections of the variables what does that mean thanks in advance

Hi all, Using: R version 2.8.1 Patched (2009-03-07 r48068) on OSX (10.5.6) with survival version: Version: 2.35-3 Date: 2009-02-10 I get the following using the first example in ?summary.survfit: > summary( survfit( Surv(futime, fustat)~1, data=ovarian)) Call: survfit(formula = Surv(futime, fustat) ~ 1, data = ovarian) time n.risk n.event survival

Hola Estoy tratando de correr un survival analysis usando un Cox regression model. Tengo una duda respecto a la organizacion del script. Tengo una variable que es -tamano del individuo- y quiero ver si hay diferencia en sobrevivencia respecto a tamano. Como diseno de campo los tamanos fueron ubicados de forma aleatoria en bloques al azar. Cuado planteo el script tengo algo como:

R 2.8.1 Windows XP I am trying to plot the results of a coxph using plot(survfit()). The plot should, I believe, show two lines one for survival in each of two treatment (Drug) groups, however my plot shows only one line. What am I doing wrong? My code is reproduced below, my figure is attached to this EMail message. John > #Create simple survival object >

Hi, Is it normal to get intercept in the list of covariates in the output of survreg function with standard error, z, p.value etc? Does it mean that intercept was fitted with the covariates? Does Value column represent coefficients or some thing else? Regards, ------------------------------------------------- tmp = survreg(Surv(futime, fustat) ~ ecog.ps + rx, ovarian,

Hello, As I am quitte an ignorant user of R, excuse me for any wrongfull usage of all the terms. My question relates to the statistics behind the survdiff function in the package survival. My textbook knowledge of the logrank test tells me that if I want to compare two survival curves, I have to take the sum of the factors: (O-E)^2/E of both groups, which will give me the Chisq. If I calculate

hie l would like to create about ten strata l have tried using sample(c(1,2),1,replace=TRUE) but all l get is a vector of 1 and 2 if i change it to sample(c(1,10),1,replace=TRUE) it gives me a vector of 1 and 10 how do l go about it --------------------------------- [[alternative HTML version deleted]]

Dear R users, I am trying to use "muhaz" and "plot.muhaz" functions in "muhaz" package to estimate and plot hazard funciton. However function "muhaz" always gives error message "Error in Surv(times, delta) : object "times" not found". I could not even run their sample codes in the user's manual as follows: data(ovarian)

i would like to add a variable to an existing matrix by manipulating 2 previous variables eg for the data m treat strata censti survTime [1,] 1 2 284.684074 690.4961005 [2,] 1 1 172.764515 32.3990335 [3,] 1 1 2393.195400 24.6145279 [4,] 2 1 30.364771 8.0272267 [5,] 1 1 523.182282 554.7659501 l

Hello, I am having some trouble with the 'censoring-adjusted C-index' by Uno et al, in the package survAUC. The relevant function is UnoC. The question has to do with what happens when I specify a time point t for the upper limit of the time range under consideration (we want to avoid using the right-end tail of the KM curve). Copying from the example in the help file: TR <-

Dear all, I am using R 3.4.3 on Windows 10. I am preparing some teaching materials and I'm having trouble matching the by-hand version with the R code. I have fitted a Cox model - let's use the ovarian data as an example: library(survival) data(ovarian) ova_mod <- coxph(Surv(futime,fustat)~age+rx,data=ovarian) If I want to make predict survival for a new set of individuals at 100

Dear All: I have some questions about the output of coxph. Below is the input and output: ---------------------------------------- > coxph(formula = Surv(futime, fustat) ~ age + rx + ecog.ps, data = + ovarian, x = TRUE) Call: coxph(formula = Surv(futime, fustat) ~ age + rx + ecog.ps, data = ovarian, x = TRUE) coef exp(coef) se(coef) z p age 0.147 1.158

Hi, I'm using natural cubic splines from splines::ns() in survival regression (regressing inter-arrival times of patients to a queue on queue size). The queue size fluctuates between 3600 and 3900. I would like to be able to run predict.survreg() for sizes <3600 and >3900 by assuming that the rate for <3600 is the same as for 3600 and that for >4000 it's the same as for