search for: coxreg

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(surviva...

Dear mailing list, I'm trying to run the sample program about coxreg in the eha package. But the command is not recognized. I tried the boot and also the survival library. Hope you can help me solve this little problem. Thank you. Jei ---------------------------------------------------------------- This message was sent using IMP, the Internet Messaging Progr...

...-------- check.parameters <- function(beta1, x, p) { # Check parameters and # determine variables to be tested # if(data.class(beta1) == "cph") x <- coxph.detail(beta1)$x if(is.null(x)) stop("Independent variables (x) not set") if(data.class(beta1) == "coxreg" || data.class( beta1) == "cph") beta1 <- beta1$coef if(!(data.class(beta1) == "numeric")) stop("Illegal parameter beta1 \n A vector of numeric coefficients or an object of class \"coxreg\" expected" ) m <- length(beta1) if(is.nu...

...x example missing link(s): key matxv survest key mgp.axis.labels win.slide gs.slide pphsm text html latex example missing link(s): print.pphsm print.cph text html latex missing link(s): print.cphfit print.coxreg print.cph.fit text html latex missing link(s): print.coxreg psm text html latex example missing link(s): survest summary.Design text html latex example missing link(s): confbar survp...

...is'. Its main focus is on proportional hazards modeling in survival analysis, and in that respect eha can be regarded as a complement and an extension to the 'survival' package. In fact eha requires survival. Eha contains three functions for proportional hazards analysis: 1. 'coxreg': Performs Cox regression, almost as 'coxph' in survival. There are two methods, 'efron' (default) and 'breslow', exactly as in coxph. There are two extensions, compared to coxph: (i) Sampling of survivors in risk sets (at event times), which can be useful with huge...

...14/15 May Aller?d, Denmark 16/17 May Basel, Switzerland Dr. Terry Therneau has worked in medical research statistics for over 15 years. He has written several papers on the use of residuals in the Cox model, and is the author of the survival routines found in S-PLUS, as well as the SAS routines COXREG and SURVTEST. Note: Due to his employer's policies and participation in "speaker's bureaus", and a recent decision to include the Insightful sponsored courses under that categorization, these are likely to be the last courses offered by Dr. Therneau through our sponsorship. Cour...

...is'. Its main focus is on proportional hazards modeling in survival analysis, and in that respect eha can be regarded as a complement and an extension to the 'survival' package. In fact eha requires survival. Eha contains three functions for proportional hazards analysis: 1. 'coxreg': Performs Cox regression, almost as 'coxph' in survival. There are two methods, 'efron' (default) and 'breslow', exactly as in coxph. There are two extensions, compared to coxph: (i) Sampling of survivors in risk sets (at event times), which can be useful with huge...

Hi out there Is there a way to get the estimated coefficients in a logistic / Cox regression without having to specify a 'formula' but by only giving the model matrix? Example for Cox regression: ## predictors n <- 50 q1 <- rnorm(n) q2 <- rgamma(n, 2, 2) Z <- cbind(q1, q2) ## response ttf <- rexp(n) tf <- round(runif(n)) ## compute estimates res <- coxph(Surv(ttf,

Hi. I am using Windows version of R 1.8.1. Being somewhat new to survival analysis, I am trying to compare cph (Design) with coxph (survival) for use with a survival data set. I was wondering why cph and coxph provide me with different confidence intervals for the hazard ratios for one of the variables. I was wondering if I am doing something wrong? Or if the two functions are calculating hazard

Dear all, How can I analyze a life table (e.g. for a cohort of insects) in R? I have 20 insects in 200 cages with two different treatments, whose survival is followed over time, such that, e.g., in one treatment, the number of animals surviving is c(20,18,16,12,10,8,4,0), while in the other treatment the survival is c(20,20,18,18,16,15,15,14) at 8 subsequent time intervals. I would very

For time scale that are truly discrete Cox proposed the "exact partial likelihood". I call that the "exact" method and SAS calls it the "discrete" method. What we compute is precisely the same, however they use a clever algorithm which is faster. To make things even more confusing, Prentice introduced an "exact marginal likelihood" which is not

Dear Prof Harrell and everyone, My PC: Window XP service pack 3 and service pack 2 R version 2.8.1 and 2.9 alpha For the last 3 days, after updating R, my two computers have been facing problems when running existing and runable R commands that involves with Design package I attempt to use 'survest', but I failed all the times with R (both 2.8.1 and 2.9 alpha) being shut down

...ified) Time Status Covariate (x) ------------------------- 4,00 1,00 ,00 3,00 1,00 1,00 1,00 1,00 1,00 1,00 ,00 1,00 2,00 1,00 1,00 2,00 1,00 ,00 3,00 ,00 ,00 The results in SPSS: -------------------- beta = 1,44 exp(beta) = 4,20 SE = 1,17 SPSS Syntax: -------------------- COXREG t /STATUS=s(1) /METHOD=ENTER x /CRITERIA=PIN(.05) POUT(.10) ITERATE(20) . The results in R: -------------------- beta = 1.46 exp(beta) = 4,32 SE = 1,17 R Syntax: -------------------- test1 <- list(time= c(4, 3,1,1,2,2,3), status=c(1,1,1,0,1,1,0),...

Dear R-users, I need to use the aftreg function in package 'eha' to estimate failure times for left truncated survival data. Apparently, survreg still cannot fit such models. Both functions should be fitting the accelerated failure time (Weibull) model. However, as G?ran Brostr?m points out in the help file for aftreg, the parameterisation is different giving rise to different

Hi, I am beginner with R and need firm guidance with my problem. I have seen some other threads discussing the subject of right censored data, but I am not sure whether or not this problem can be regarded as such. Data: I have a vector with laboratory test data (strength of wood specimens, example attached as txt-file). This data is the full sample. It is a common view that this kind of data

Dear List, How do I extract the approximate Wald test for the frailty (in the following example 17.89 value)? What about the P-values, other Chisq, DF, se(coef) and se2? How can they be extracted? ######################################################> kfitm1 Call: coxph(formula = Surv(time, status) ~ age + sex + disease + frailty(id, dist = "gauss"), data = kidney)