similar to: weighed Fleming-Harrington log rank test

Thank you Terry. Right now I can use comp() from survMisc package to do the 2-parameter version of F-H weighting. I think both SAS and stata offer the 2-parameter version, so just?thought it would be nice if survdiff() can have that option given it's standard package in R.? Thanks! John On Friday, February 16, 2018, 7:08:46 AM PST, Therneau, Terry M., Ph.D. <therneau at mayo.edu>

> 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. >>

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

The data set in R is wrong. I've found mistakes on 2 lines in a quick look. I don't know if the data is incorrect in the Appendix of Fleming and Harrington as well (someone seems to have borrowed my copy), which is where the data set appears to have been taken from, given all the "-9" codes in it. (Note, Tom Fleming originally got the data from me, so I'm fairly

I read through Harrington and Fleming (1982) but it is beyond my statistical comprehension. I have survival data for insects that have a very finite expiration date. I'm trying to test for differences in survival distributions between different groups. I understand that the medical field is most often dealing with censored data and that survival analysis, at least in the package survival,

Hi, When I run the following Cox proportional hazards model on the Mayo clinic's PBC data set (given in the "survival" package), the regression coefficients do not agree with the results presented in Table 4.6.3 (p. 195) of Fleming & Harrington's book. library(survival) data(pbc) ans.cox <- coxph(Surv(time, status) ~ log(bili) + log(alb) + age + log(protime) +

We have around 30+ users using one computer (Win2kTS) So I guess that means one smbd process is handling all 30 users' requests? You can watch the smbd process for this machine max out the CPU at times Is there anyway of getting multiple smbd processes per client/computer that connects Thanks, Paul -------------- next part -------------- A non-text attachment was scrubbed... Name:

Hi there, Can anyone please help me because I am going to get crazy with the pbc data set. I just want to apply simple cox regression in the data set. I am a beginner in R but I don't think I am doing anything wrong. I have the book of Fleming and Harrington 1990. I perform cox regression by typing: out<- coxph(Surv(times/365,status)~log(bili)+log(proth)+edema+log(albumin)+age) out

hie Im trying to calculate the power of the logrank test for different values of rho .I was just wandering whether the following programme would do it. any suggestions are welcome s=50 number=1 count1=0;count2=0;count3=0;count4=0;count5=0;count6=0;count7=0;count7=0; count8=0;count9=0 while(s!=0){ n=20 n1=n/2

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi all, I wanted to let everyone know that going forward, Matt Fleming will be doing at least some of the releases and prereleases for Syslinux. Other than who pushes the button, there should be little or no change in how the builds are done, where they are kept and so on. Thanks Matt! -hpa -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.12

Hello R gurus, I want to calculate the Spearman rho between two ranked lists. I am getting results with cor.test that differ in comparison to my own spearman function: > my.spearman function(l1, l2) { if(length(l1) != length(l2)) stop("lists must have same length") r1 <- rank(l1) r2 <- rank(l2) dsq <- sapply(r1-r2,function(x) x^2) 1 - ((6 * sum(dsq))

It's amazing what you can learn in a few days... Having just found out that Queen Elizabeth has a great sense of humor, it has now emerged that Kevin Fleming - a man who (both with and without his moustache) has been an amazing contributor and influencer in the Asterisk project is set to move on to a new challenge outside the project - but still within the realms of Open Source. Kevin has

The combination of survreg + gamma frailty = invalid model, i.e., the example that you quote. I did not realize that this had been added to the survreg help file until very recently. I will try to fix the oversight. Other, more detailed documentation states that Gaussian frailty + AIC is the only valid random effects choice for survreg. Details: frailty(x) with no optional

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

hie when i use plot.survfit to plot more than one graph why I only see the last graph how do i see the other graphs.for example n=20 n1=n/2 n2=n/4 a11=4;a12=4 ;a21=4 ;a22=4 t1<-array(1,c(n1)) t2<-array(2,c(n1)) treatgrp=matrix(c(t1,t2))

David's answers were correct. You are looking deep into the code when there is no reason to to so. 1. h(t|(X=x,Z=z)) = exp(Beta0 + XZBeta1) Most statisticians will tell you that this is an unwise model. The reason is that if you replace X with "X+1" the fit changes, which is almost never desirable. What if someone coded your dummy variable as 1/0 instead of 0/1 -- wouldn't

Thanks for sharing the questions and responses! Is it possible to appreciate how much the coefficients matter in one or the other model? Say, using Biau's example, using coxph, as.factor(grade2 == "high")TRUE gives hazard ratio 1.27 (rounded). As clinician I can grasp this HR as 27% relative increase. I can relate with other published results. With survreg the Weibull model gives a

> I was wondering why survreg (in survival package) can not handle > three-way interactions. I have an AFT ..... You have given us no data to diagnose your problem. What do you mean by "cannot handle" -- does the package print a message "no 3 way interactions", gives wrong answers, your laptop catches on fire when you run it, ....? Also, make sure you read

Dear all, I'm struggling with predicting "expected time until death" for a coxph and survreg model. I have two datasets. Dataset 1 includes a certain number of people for which I know a vector of covariates (age, gender, etc.) and their event times (i.e., I know whether they have died and when if death occurred prior to the end of the observation period). Dataset 2 includes another