similar to: Schoenfeld residuals for a null model coxph

hi sorry if this has been discussed before, but I'm wondering why the scaled Schoenfeld residuals do not follow the defining formula for obtaining them from the ordinary Schoenfeld residuals, but are instead offset by the estimated parameter values. e.g. library(survival) attach(ovarian) sv<-Surv(futime,fustat) f1<-coxph(sv~age+ecog.ps) f1

Dear all, I am struggling with calculation of Schoenfeld residuals of my Cox Ph models. Based on the formula as attached, I calculated the Schoenfeld residuals for both non tied and tied data, respectively. And then I validated my results with R using the same data sets. However, I found that my results for non-tied data was ok but the results for tied data were different from R's. How

Dear all, I use the Andersen plot to check for proportional hazards assumption for a factor (say x) in the Cox regression model and obtained a straight line that pass through the origin. However, the formal test done by the R-function cox.zph, which is based on the plot of Schonefeld residuals against time, indicates that proportional hazards assumption is violated. Further, a plot of the score

Dear All, Sorry to bother you again. I have a model: coxfita=coxph(Surv(rem.Remtime/365,rem.Rcens)~all.sex,data=nearma) and I'm trying to do a plot of Schoenfeld residuals using the code: plot(cox.zph(coxfita)) abline(h=0,lty=3) The error message I get is: Error in plot.window(...) : need finite 'ylim' values In addition: Warning messages: 1: In sqrt(x$var[i, i] * seval) : NaNs

Hi All, I have a left truncated, right censored cox model: coxph(Surv(start, stop, censor) ~ x + y, mydata) I would like to know how much of the observed variance (as a number between 0 and 1) is explained by each variable. How could I do that? Adding terms sequentially and then using anova(mod1, mod2) tells me whether I get a significant improvement of the fit, but does not tell me how much

Dear All, just a quick example: > x = 1:25 > x[12] = NA > x [1] 1 2 3 4 5 6 7 8 9 10 11 NA 13 14 15 16 17 18 19 20 21 22 23 24 25 > y = x[x<10] > y [1] 1 2 3 4 5 6 7 8 9 NA Is there any way of NOT getting NA for y = x[x<10]? Similarly > y = x[x<15] > y [1] 1 2 3 4 5 6 7 8 9 10 11 NA 13 14 How do I get rid of the NA (not post

Hi All, I'm having a problem with barplot: mydata [1,] 2 108 0 0 0 1 3 0 0 0 0 0 7 18 3 4 8 20 26 20 19 7 1 1 mycol = c(rep('yellow', 2), rep('white', 3), rep('orange',2), rep('white', 5), rep('orange',3), rep('red',9)) barplot(mydata, col = mycol) gives me an uniformly yellow barplot. How do I solve this? bw Federico

Hi All, is there a reasonably simple way of using a black and white chequer/checker board pattern as a colour: barplot(mydata, col = c('red', 'blue' 'checkerboard')) ? BW F -- Federico C. F. Calboli Neuroepidemiology and Ageing Research Imperial College, St. Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 75941602 Fax +44 (0)20 75943193 f.calboli

Hi, I am subsetting a matrix thus: test [,1] [,2] [,3] [1,] 1 7 13 [2,] 2 8 14 [3,] 3 9 15 [4,] 4 10 16 [5,] 5 11 17 [6,] 6 12 18 test[cbind(c(1,3,5), c(2,1,3))] [1] 7 3 17 This works fine, and is the equivalent of c(test[1,2], test[3,1], test[5,3]). cbind(c(1,3,5), c(2,1,3)) would obviously look like: [,1] [,2] [1,] 1 2 [2,]

Hi All, I am writing a function that reads a file in myfile = file('myfile.raw', 'rb') . . . . . close(myfile) No matter what, I get the warning Warning message: closing unused connection 3 (myfile.raw) Since the whole thing is in a function, I'd like to avoid unecessary noise for the user, and I'd like to kill the warning -- without having to mess with global options.

Hi, according to the help file rtags does not support VI(M) yet. Is there any known hack to ctags to get tags for R in VI(M)? BW F -- Federico C. F. Calboli Neuroepidemiology and Ageing Research Imperial College, St. Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 75941602 Fax +44 (0)20 75943193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com

Hi All, I have the following command: cat(rbind(table(gen$sex, gen$ddn2)[1,],round(table(gen$sex, gen$ddn2)[1,]/apply(table(gen$sex, gen$ddn2),2,sum) * 100)), sep = c(' (','%)\n'), file = '') 3 (20%) 17 (30%) 15 (31 i.e. it does NOT print the last separator, which is something that bugs me a bit, given that fact I'm trying to have some copy-paste ready stuff to put

Hi All, I have a parameter that is bimodal, and I want to get some sort of linear model done with it results = some.linear.function(bimodal.param ~ factor1 + some other stuff, mydata) I want to see if factor 1 matters (it has 3 levels, of of which can be taken as baseline), i.e: summary(results) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -2.108522

Dear All, a new version of MultiPhen (0.3) is available on CRAN, and will be available to a mirror near you soon. *Please upgrade* because this release is a bug fix release. A new version, with improvements in the output and more useful error messages is basically ready, but I will wait to release it until next week to add other possible improvements. For all asking for the related paper, Paul

Am 10.07.19 um 20:38 schrieb miguel medalha via samba: > >> How could I achieve that when my client from the LAN makes a request >> to xmpp.domain.tld, SAMBA4 direct that request to pfSense and respond >> with the IP assigned to it? > > In the smb.conf file of your DCs you insert the line: > > dns forwarder = [IP address of your pfSense machine] there is no

Dear List, After including cluster() option the coxreg (from eha package) produces results slightly different than that of coxph (from survival) in the following time-dependent treatment effect calculation (example is used just to make the point). Will appreciate any explaination / comment. cheers, Ehsan ############################ require(survival) require(eha) data(heart) # create weights

Hi everyone, I'm running a cox ph model on a dataset with a number of variables. Each variable has a different number of missing data, so that coxph() drops the individuals who are missing data at one or more variables. Because of this dropping (totally fine btw) I want to know how many events I am left with in the model. Is there a way of extracting them from the coxph() fit? or in any other

I am writing to get a better handle on a warning I am getting from a coxph analysis I am doing. I am analysing age of onset of dementia *after* the onset of parkinson disease. My data looks like: age.park age.dem age.death censor x1 x2 x3 x4 1 76 87 88 0 16 33 E3 E3 2 75 84 84 0 33 36 E3 E3 3 77 81 81 1 NA NA

Hello! Hmm, all of a sudden SWAT started to respond. Now when I try to access http://server:901/, I get: 500 Server Error chdir failed - the server is not configured correctly I created a tiny smb.conf in /opt/samba-3.0.0/lib/smb.conf which contains: root_s07nfs:/opt/samba-3.0.0/samba/bin/ > cat /opt/samba-3.0.0/lib/smb.conf [global] workgroup = EUROPE netbios name = S07NFS

Hallo! I lese gro?e Zeitreihen in R ein z.B. mit: > disc<-read.table("F:/R/DATA/discount_rate_usa.txt") disc hat dann folgende Struktur: > disc[1:5] V1 V2 1 01/03/1955 1.5 2 01/04/1955 1.5 3 01/05/1955 1.5 4 01/06/1955 1.5 5 01/07/1955 1.5 ich will das disc als Zeitreihe erkannt wird und will z.B 01/03/1955 in ein Datum verwandeln, aber es wird als