similar to: weighed Fleming-Harrington log rank test

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

> 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

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,

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

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

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:

    Dear R users.  I am trying to program the comp() routine in package survMisc.                                                                                                             I am reading the data below with d=read.table( "C:\\. . .",fill=TRUE,header=TRUE) Then I load the packages 'survival' and 'survMisc', library(survival), library(survMisc)  and I run

I am not sure if this is the right place for that kind of questions, but I wondered that the recommended package survival did not pass R's check procedure without warnings: 1) unbalanced braces: * Rd files with unbalanced braces: * man/Surv.Rd * man/cluster.Rd * man/cox.zph.Rd * man/coxph.Rd * man/coxph.detail.Rd * man/date.ddmmmyy.Rd * man/lines.survfit.Rd *

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

dear all, I would like to know whether survdiff and survReg function in the survival package work for left-truncated and right-censored data. If not, what other functions can i use to make comparison between two survival curves with LTRC data. thanks for any help given sing yee

Meant to respond to this but forgot. I didn't write a new terms() function -- I added an attribute to the terms() (a vector of the names of the constructed model matrix), thus preserving the information at the point when it was available. I do agree that it would be preferable to have an upstream fix ... On Thu, Mar 8, 2018 at 9:39 AM, Therneau, Terry M., Ph.D. via R-devel <r-devel

I believe this has to do terms() making "term.labels" (hence the dimnames of "factors") with deparse(), so that the backquotes are included for non-syntactic names. The backquotes are not in the column names of the input data.frame (nor model frame) so you get a mismatch when subscripting the data.frame or model.frame with elements of terms()$term.labels. I think you can

my program given below can some one make it presentable. I trying to simulate survival data and calculate the power. I think i could have done better. s=10 number=0 count1=0;count2=0;count3=0;count4=0;count5=0;count6=0;count7=0;count8=0; count9=0; count11=0;count22=0;count33=0;count44=0;count55=0;count66=0;count77=0; count88=0;count99=0; while(s!=0){ n=100 n1=n/2 n2=n/4

Hello R users: I wonder if any function are available for multiple log-rank tests with adjusted P-values. I found survdiff( ) only give pooled tests but without pairwise ones. Thanks a lot ! best wishes zhang zihong [[alternative HTML version deleted]]

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 .

>>>>> Ben Bolker <bbolker at gmail.com> >>>>> on Thu, 8 Mar 2018 09:42:40 -0500 writes: > Meant to respond to this but forgot. > I didn't write a new terms() function -- I added an attribute to the > terms() (a vector of the names > of the constructed model matrix), thus preserving the information at > the point when

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) +

Thanks to Bill Dunlap for the clarification. On follow-up it turns out that this will be an issue for many if not most of the routines in the survival package: a lot of them look at the terms structure and make use of the dimnames of attr(terms, 'factors'), which also keeps the unneeded backquotes. Others use the term.labels attribute. To dodge this I will need to create a