similar to: Fleming-Harrington weighted log rank test

> 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 survivals functions can be tested by the Log-rank test and others, for example the Gehan-Breslow. The graham breslow work with the alpha values. But I don't know how is the Gehan-Breslow test with R. Somebody know a type function?.. or other suggestions? Any help will be really appreciated Jos? Bustos Marine Biologist Master Apllied Stat Program University of Concepci?n

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>

You are correct that the survreg routine only supports 'rho' of the Fleming-Harrington G-rho tests. This is a function of age -- I wrote the original code back when I was working with Tom (Fleming), and he was only using 1 parameter. Later he and David expanded the test to two parameters. This might be only the second request for the feature in the 30+ years since that date. Terry

> -----Original Message----- > From: Hal Finkel [mailto:hfinkel at anl.gov] > Sent: den 13 juli 2017 16:01 > To: Björn Pettersson A <bjorn.a.pettersson at ericsson.com>; David Chisnall > <David.Chisnall at cl.cam.ac.uk>; Dylan McKay <me at dylanmckay.io> > Cc: llvm-dev at lists.llvm.org; Carl Peto <carl.peto at me.com> > Subject: Re: [llvm-dev] RFC:

My experience of having the address space for functions (or function pointers) in the DataLayout i that when the .ll file is parsed we need to parse the DataLayout before any function declarations. That is needed because we want to attribute the functions with correct address space (according to DataLayout) when inserting them in the symbol table. An alternative would be to update address space

For adjusted survival curves I took the sample code from here: https://rpubs.com/daspringate/survival and adapted for my date, but got error. I would like to understand what is my mistake. Thanks! #ADAPTATION FOR MY DATA library(survival) library(survminer) df<-read.csv("F:/R/data/base.csv", header = TRUE, sep = ";") head(df) ID start stop censor sex age stage treatment 1

Cool. That explains a lot! Sorry if this is a total n00b question, but… how does the datalayout string get overridden? in llvm/lib/Target/AVR/AVRTargetMachine.cpp I can see the code that determines the default datalayout for AVR… static const char *AVRDataLayout = "e-P1-p:16:8-i8:8-i16:8-i32:8-i64:8-f32:8-f64:8-n8-a:8”; However in the LLVM iR below, the target datalayout was present and

Hello All, Below is some sample survival analysis code. I'd like to able to get the results from print(gehan.surv) into a matrix or data frame, so I can manipulate them and then create a table using odfWeave. Trouble is, I'm not quite sure how make such a conversion using the results from a print method. Is there some simple way of doing this? Thanks, Paul require(survival)

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

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,

Hello All, Learning to use the odfWeave package. I really like the package. It has good documentation, makes some very nice looking tables, and seems to have lots of options for customizing output. There are a few things I'd like to do that don't seem to be covered in the documentation though. So I'm not sure if they're possible or not. Here's a list of some things I'd

I’m not sure if it’s truly deterministic. It always gives the same results (so far) on my machine but I’m not sure that’s enough. My guess is it’s probably going to be deterministic on one machine but might well not be deterministic across environments. Like it might give varying results if cross compiled on different hosts, macOS vs intel Linux vs arm vs s390. (Obviously AVR is always a cross

Dear List, Does anybody no how to compare mean survival times for two (more) groups in R? What test statistics should I use? Thank you very much! Joe [[alternative HTML version deleted]]

Sorry for starting another topic, this is actually a reply to Segher's post on Sun Oct 22 on the 'mdct question' topic. I wasn't subscribed properly and so I didn't get email confirmation and thus can't add to that thread. So Segher, if the equation is indeed what you say it is, then replacing mdct_backward with this version should work, but it doesn't. Am I applying

Hi, Can someone tell me which MDCT and invMDCT equation uses? I implemented the invMDCT one given in eusipco.corrected.ps file (handed out by Monty way back) and it produces different time domain samples. I tried both the FFT method and the slow way directly from the equation and couldn't reproduce the results from the original code. This leads me to believe that the forward MDCT used in

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

That’s useful info, thanks. I think it will be useful for me to understand the connection, why this type of pointer is being emitted now. Do you have any suggestions where i can look to find the platform specific code that is making function pointers go into addrspace? Carl p.s. I am also working on passing the avr target flag to swift, but swift itself had (has?) limitations that make it

ExpeRts, I'm trying to compare three survival curves using the function "survdiff" in the survival package. Following is my code and corresponding error message. > survdiff(Surv(st_months, status) ~ strata(BOR), data=mydata) Error in survdiff(Surv(st_months, status) ~ strata(BOR), data = mydata) : No groups to test When I check the "strata" of the variable. I get .