similar to: ANOVA for stratified cox regression

Dear List, I have tried a stratified Cox Regression, it is working fine, except for the "Anova"-Tests: Here the commands (should work out of the box): library(survival) d = colon[colon$etype==2, ] m = coxph(Surv(time, status) ~ strata(sex) + rx, data=d) summary(m) # Printout ok anova(m, test='Chisq') This is the output of the anova command: > Analysis of Deviance Table

Dear List, I am aware this is slightly off-topic, but I am sure there are people who already had the problem and who perhaps solved it. I am running long-lasting model fits using constrOptim command. At work there is a linux computer (Quad Core, debian) on which I already have compiled R and Atlas, in the hope that things will go faster on that machine. Atlas offers the possibility to be

Dear Tomas,Thank you.Regarding the "unnumbered" arguments, i.e. sprintf('%f %f', 1, 2, 3). This was the case I wanted to report, here a warning can be very useful.Regarding the "numbered" arguments, that is, sprintf('%$1f %$3f', 1, 2, 3). Here, omission of an argument might be intended, for example, in an application with support for multiple languages.

Dear Matthias, On 11/4/20 4:01 PM, matthias-gondan wrote: > Dear Tomas, > > Thank you. > > Regarding the "unnumbered" arguments, i.e. sprintf('%f %f', 1, 2, 3). > This was the case I wanted to report, here a warning can be very useful. > > Regarding the "numbered" arguments, that is, sprintf('%$1f %$3f', 1, > 2, 3). Here, omission

Dear Bill, All makes perfect sense (including the late evaluation). I actually discovered the problem by looking at old code which used your proposed solution. Still I find it strange (and, hnestly, I don?t like R?s behavior in this respect), and I am wondering why u is not being copied to L just before u is assigned a new value. Of course, this would require the R interpreter to track all these

Another way to avoid the problem is to not redefine variables that are arguments. E.g., > Su3 <- function(u=100, l=u, mu=0.53, sigma2=4.3^2, verbose) { if (verbose) { print(c(u, l, mu)) } uNormalized <- u/sqrt(sigma2) lNormalized <- l/sqrt(sigma2) muNormalized <- mu/sqrt(sigma2) c(uNormalized, lNormalized, muNormalized) } > Su3(verbose=TRUE)

Hello, One way of preventing that is to use ?force. Just put force(l) right after the commented out print and before you change 'u'. Hope this helps, Rui Barradas Citando Matthias Gondan <matthias-gondan at gmx.de>: > Dear R developers, > > sessionInfo() below > > Please have a look at the following two versions of the same function: > > 1. Intended

Dear R developers, The following command produces an interaction plot with lwd=2. interaction.plot(c(1, 2, 1, 2), c(1, 1, 2, 2), 1:4, lwd=2) In the legend, however, lwd seems to be 1, which does not seem to be intended behavior. Probably the lwd is not correctly forwarded to legend: from the interaction.plot source: legend(xleg, yleg, legend = ylabs, col = col, pch = if (type %in%

Dear R developers, I would like to have R choose the limits of the y-axis semi-automatically, e.g., zero should be included, but the maximum should be chosen depending on the data. Examples: plot(1:10, 1:10) # selects min and max automatically plot(1:10, 1:10, ylim=c(1, 10)) # manual definition plot(1:10, 1:10, ylim=c(0, Inf)) # this would be a nice feature, i.e. lower y limit = 0 defined

Dear R experts, For a fixed seed, the first random number produced by rnorm and runif has the same rank within the distribution, which I find useful. The following ranks differ, however. > set.seed(123) > runif(4) [1] *0.2875775* 0.7883051 *0.4089769* 0.8830174 > set.seed(123) > pnorm(rnorm(4)) [1] 0.2875775 0.4089769 0.9404673 0.5281055 I noticed that rnorm seems to

Dear R team, dear Prof. Therneau, library(survival) data(colon) ?colon gives me only a very rudimentary source (only a name). Is there a possibility to get a reference to the clinical trial these data are taken from? Many thanks in advance. With best wishes, Matthias Gondan --

Mathias, If it's any comfort, I appreciated the example; 'expected' behaviour maybe, but a very nice example for staff/student training! S Ellison > -----Original Message----- > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Matthias > Gondan > Sent: 02 September 2017 18:22 > To: r-help at r-project.org > Subject: [R] Strange lazy evaluation of

Dear Matthias, thanks for the suggestion, R-devel now warns on unused arguments by format (both numbered and un-numbered). It seems that the new warning is useful, often it finds cases when arguments were accidentally passed to sprintf but had been meant for a different function. R allows combining both numbered and un-numbered references in a single format, even though it may be better to

Dear R developers, sessionInfo() below Please have a look at the following two versions of the same function: 1. Intended behavior: > Su1 = function(u=100, l=u, mu=0.53, sigma2=4.3^2) + { + print(c(u, l, mu)) # here, l is set to u?s value + u = u/sqrt(sigma2) + l = l/sqrt(sigma2) + mu = mu/sqrt(sigma2) + print(c(u, l, mu)) + } > > Su1() [1] 100.00 100.00 0.53 [1]

Hello list, I have the following function which, as you can see, uses mean: meanratings <- round(apply(stack03[,c(102:121)],2,function(x) (tapply(x ,actcode, mean, na.rm=T))), digits=1) The above function yields the following output: q27a q27b q27c q27d q27e q27f q27g q27h q27i q27j q27k q27l q27m q27o q27p 1 7.8 8.1 7.7 7.9 7.9 NaN NaN 8.4 7.8 7.0 7.6 NaN NaN 7.1 6.0 2

Hello everyone, I am a new user of R. Does anybody know how hazard ratios are extracted for each factor level in a stratified Cox proportional hazard regression model? I have a cancer data set where the variable ?differentiation? is a factor with three levels: poor, intermediate and good. I would like to extract the hazard ratio for each grade level and relate it to another prognostic factor.

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Hello, I'm fitting poisson regression to mortality data and wish to stratify by age. Is there any way to perform this stratification and use the glm function in R? Thanks, Hannah Murdoch

Dear All, is there a stratified version of the Wilcoxon test (also known as van Elteren test) available in R? I could find it in the survdiff function of the survival package for censored data. I think, it should be possible to use this function creating a dummy censoring indicator and setting it to not censored, but may be there is a better way to perform the test. Thanks, Heinz T??chler

I was trying to do a bunch of planned contrast but ran into a snag. fit.contrast won't work with an Error term in aov. Ok, then I use lme. Only, now it seems there is no way to enter the interaction terms (something like "x1:x2"). I couldn't find a way to use the interaction term in the help. Is there an undocumented method or some other command for planned contrasts?