similar to: anova tables in survreg (PR#9806)

Hi, I would like to fit parametric survival models to time-to-event data that are left truncated. I have checked the help page for survreg and looked in the R-help archive, and it appears that the R function survreg from the survival library (version 2.16) should allow me to take account of left truncation. However, when I try the command

Add GS base to the HVM VCPU context returned by xc_vcpu_getcontext() Signed-off-by: Aravindh Puthiyaparambil <aravindh@virtuata.com> diff -r e62ab14d44af -r babbb3e0f4d3 xen/arch/x86/domctl.c --- a/xen/arch/x86/domctl.c Fri Apr 20 11:36:02 2012 -0700 +++ b/xen/arch/x86/domctl.c Fri Apr 20 17:55:49 2012 -0700 @@ -1592,6 +1592,12 @@ void arch_get_info_guest(struct vcpu *v,

Hi all, For loads and stores i want to extract information about the number of indices accessed. For instance: struct S {int X, int *Y}; __global__ void kernel(int *A, int **B, struct S) {   int x = A[..][..]; // -> L: A[..][..]   int y = *B[2];   // -> L: B[0][2]   int z = S.y[..];  // -> L: S.1[..]   // etc.. } I am performing some preprocessing on IR to: 1. Move constant

Hello list, I have a linear regression ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14) trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69) group <- gl(2,10,20, labels=c("Ctl","Trt")) weight <- c(ctl, trt) reg <- lm(weight ~ group) sreg <- summary(reg) and I would like to dump exactly what I see on the console with

Hello, some months ago i wrote to the mailing list asking some questions about register pairing, i've been experimenting several things with the help i got back then. Some background first: this issue is for a backend for an 8bit microcontroller with only 8bit regs, however it has a few 16bit instructions that only work with fixed register pairs, so it doesnt allow all combinations of regs.

Hello everybody, does anybody know how the function plot.survfit exactly works? I'd like to plot the log of the cummulative hazard against the log time by using plot.survfit(...fun="cloglog") which does not work correctly. The scales are wrong and there is an error message about infinit numbers. It must have something to do with the censored data, doesn't it? #Example:

Dear R-Helpers: I have tried everything I can think of and hope not to appear too foolish when my error is pointed out to me. I have some real data (18 points) that look linear on a log-log plot so I used them for a comparison of lm() and survreg. There are no suspensions. survreg.df <- data.frame(Cycles=c(2009000, 577000, 145000, 376000, 37000, 979000, 17420000, 71065000, 46397000,

https://bugzilla.netfilter.org/show_bug.cgi?id=979 --- Comment #3 from Alvaro <alvaroneay at gmail.com> --- (In reply to porjo38 from comment #0) > The output of nft_rule_snprintf_json() includes a JSON array called 'expr'. > I would like to suggest that each type be split into its own object where > the 'type' value becomes the key name. So for example, rather than

Hey all, I am trying to use the survreg function in R to estimate the mean and standard deviation to come up with the MLE of alpha and lambda for the weibull distribution. I am doing the following: times<-c(10,13,18,19,23,30,36,38,54,56,59,75,93,97,104,107,107,107) censor<-c(1,0,0,1,0,1,1,0,0,0,1,1,1,1,0,1,0,0) survreg(Surv(times,censor),dist='weibull') and I get the following

Can anybody give me a neat example of interval censored data analysis codes in R? Given that suvreg(Surv(c(1,1,NA,3),c(2,NA,2,3),type="interval2")~1) works why does survreg(Surv(data[,1],data[,2],type="interval2")~1) not work where data is : T.1 T.2 Status 1 0.0000000 0.62873036 1 2 0.0000000 2.07039068 1 3 0.0000000

Hi all, Sorry if this has been answered already, but I couldn't find it in the archives or general internet. Is it possible to implement the gompertz distribution as survreg.distribution to use with survreg of the survival library? I haven't found anything and recent attempts from my side weren't succefull so far. I know that other packages like 'eha' and

Does anyone know if the survreg function in the survival package can fit numerical covariates ? When I fit a survival model of the form survreg( Surv(time,censored) ~ x ) then x is always treated as a factor even if it is numeric (and even if I try to force it to be numeric using as.numeric(x). Thus, in the particular example I am analysing, a simple numerical covariate becomes a factor

Full_Name: Dave Ramsey Version: 1.8.0 OS: win2000 Submission from: (NULL) (202.27.240.6) there is a bug in extractAIC.survreg in library MASS. A survreg model object has no component called "residuals". Hence n <- length(fit$residuals) returns 0 resulting in errors workaround: replace n <- length(fit$residuals) with n <- length(residuals(fit)) ### sorry: error

Hi,Just a quick one, does anyone know the command for accessing the standard errors from a survreg object? I can access the coefficients by model$coefficients, but I cant seem to find a command to access the errors. Any help would be greatly appreciated.Regards,Andre [[alternative HTML version deleted]]

Hello, I'm working with some left censored survival data using accelerated failure time models. I am interested in fitting different distributions to the data but seem to be getting the same results from the model fit using survreg regardless of the assumed distribution. These two codes seem to provide the same results: aft.gaussian <-

Dear R-list I have been trying to make survreg fit a normal regression model with left truncated data, but unfortunately I am not able to figure out how to do it. The following survreg-call seems to work just fine when the observations are right censored: library(survival) n<-100000 #censored observations x<-rnorm(n) y<-rnorm(n,mean=x) d<-data.frame(x,y) d$ym<-pmin(y,0.5)

Hello, I?m trying to do some analysis using survreg function. I need to implement there my own distribution with density: lambda*exp(-lambda*y), where y = a1/(1+exp(-a2*x)). a1, a2 are unknown parameters and x >0. I need to get estimates of a1 and a2 (and lambda of course) I?m really not good at programming. Is there any way how to implement this distribution to survreg without

I have a question, I generated some data and tried survreg to analyze them, but here, I want to get the covariance matrix of the coefficients. I know how to get corr from survreg, say, summary(f,corr=T), but how to get covariance matrix of the coefficient ? can I put them in a matrix and output ? thanks below is what I did <mailto:r-help@stat.math.ethz.ch> n=100; beta=1.0

Dear R Listers- I am attempting to analyse the survival of seeds in cages (exclosures) that differ in their permeability to rainforest mammals. Because I did not observe the moment of seed disappearance, my data is interval censored. This limits my options for analysis (as I understand it) to survreg, in the survival package. Because I repeated the experiment in 8 sites, I have a random

dear r experts: It seems my message got spam filtered, another try: i would appreciate advice on how to get the p-value from the object 'sr' created with the function survreg() as given below. vlad sr<-survreg(s~groups, dist="gaussian") Coefficients: (Intercept) groups -0.02138485 0.03868351 Scale= 0.01789372 Loglik(model)= 31.1 Loglik(intercept only)= 25.4