similar to: Hazard function or cumulative Hazard function in R

Dear all, Is there a way to calculate the non-cumulative hazard (instantaneous hazard), which is the product of baseline hazard and exp{beta*covariate} ? I knew in survfit, we can get the estimator of cumulative baseline hazard, but how can we get the non-cumulative one? Thank you very much! Koshihaku -- View this message in context:

Dear R-users, I am checking the proportional hazard assumption of a cox model for a given covariate, let say Z1, after adjusting for other relavent covariates in the model. To this end, I fitted cox model stratified on the discrete values of Z1 and try to get beslow estimator for the baseline cumulative hazard function (H(t)) in each stratum. As far as i know, if the proportionality assumption

Hello: So i've fit a hazard function to a set of data using kmfit<-survfit(Surv(int, event)~factor(cohort)) this factor variable, "cohort" has four levels so naturally the strata variable has 4 values. I can use this data to estimate the hazard rate haz<-n.event/n.risk and calculate the cumulative hazard function by H<--log(haz) Now, I would like to plot this

Hi I am estimating the following coxph function with stratification and frailty?where each person had multiple events. m<-coxph(Surv(dtime1,status1)~gender+cage+uplf+strata(enum)+frailty(id),xmodel) ? > head(xmodel) id enum dtime status gender cage uplf 1 1008666 1 2259.1412037 1 MA 0.000 0 2 1008666 2 36.7495023 1 MA 2259.141 0 3 1008666

Hi, I am computing the Nelson-Aalen (NA) estimate of baseline cumulative hazard in two different ways using the "survival" package. I am expecting that they should be identical. However, they are not. Their difference is a monotonically increasing with time. This difference is probably not large to make any impact in the application, but is annoyingly non-trivial for me to just

Hi everyone. There's been several threads on baseline hazard in Cox model but I think they were all on cumulative baseline hazard, for instance http://tolstoy.newcastle.edu.au/R/help/01a/0464.html http://tolstoy.newcastle.edu.au/R/help/01a/0436.html "basehaz" in package survival seems to do a cumulative hazard. extract from the basehaz function: sfit <- survfit(fit) H

Dear all, I think the coxph and survfit.coxph can give the cumulative hazard of cox model. But is there any method to calculate the hazard Lambda(t)=lambda_0(t)*exp{beta*X(t)}? Any suggestion will be great help. Thank you very much! Koshihaku -- View this message in context: http://r.789695.n4.nabble.com/How-to-get-the-hazard-of-coxph-not-cumulative-hazard-tp3873516p3873516.html Sent from the R

Dear R-users, I computed a simple coxph model and plotted survival over time with associated confidence intervals for 2 covariate levels (males and females). M1 <- coxph(survobject~sex, data=surv) M1 survsex <- survfit(survobject~sex,data=surv) summary(survsex) plot(survsex, conf.int=T, col=c("black","red"), lty = c(1,2), lwd=c(1,2), xlab="Time",

I would like to simulate a stochastic process by specifying an intensity function, say lambda(t)=0.05 + 3 exp(鈭抰) I have the following code, but it has a number of problems. One issue I have is I do not know where the time variable is. I would appreciate your help with this code. library("survival") n <- 5000 lamc<-0.08 k1<-0.05 k2<-3 ld<-function(t){k1+k2}

Dear list, is there a function available which provides an estimate of the hazard function based on a cox proportional hazard model? I only found the cumulative hazard and the survival function as survfit options. Thanks for your help Peter

Dear All, I'm having just a little terminology problem, relating the language used in the Hosmer and Lemeshow text on Applied Survival Analysis to that of the help that comes with the survival package. I am trying to back out the values for the baseline hazard, h_o(t_i), for each event time or observation time. Now survfit(fit)$surv gives me the value of the survival function, S(t_i|X_i,B),

Hello everybody. First of all, I would like to present myself. I'm a french student in public health and I like statistics though I'm not that good in mathematics (but I try to catch up). I've discovered R recently while trying to find a statistical program in order to avoid rebooting my computer under windows when I need to do some statistical work. And here is my first question.

Hello , I am hoping for some advice regarding obtaining the values for the hazard function in a cox regression that I have undertaken. I have a model in the following form, analysed with the package survival (v. 2.34-1) and a log-log plot obtained using Design (v. 2.1-2). For two variables, the lines in the survival curves crossed. The statistician I been obtaining advice from (who does not

Dear all, I am trying to find a suitable R-function for parametric proportional hazard regressions. The package survival contains the coxph() function which performs a Cox regression which leaves the base hazard unspecified, i.e. it is a semi-parametric method. The package Design contains the function pphsm() which is good for parametric proportional hazard regressions when the underlying base

My question is, how to compute hazard function(H(t)) after building the coxph model. I even aware of the terminology that differs from hazard function(H(t)) and the hazard rate(h(t)). Here onward I wish to calculate both. Here what I have done in two different methods; ##########################################################################################

What is the best way to report the standard error when publishing Kaplan-Meier plots? In my field (Vascular Surgery), practitioners loosely refer to the "10% error" cutoff as the point at which to stop drawing the KM curve. I am interpreting this as the *standard error of the cumulative hazard*, although I'm having a difficult time finding some guidelines about this (perhaps I am

Hi, I would like to compare the hazard functions of two samples using the Cox proportional hazards model. For sample 1 I have individual time-to- event data. For sample 2 I don't have individual data, but grouped data that allows to obtain a hazard function. I am wondering if there is an R function that allows to obtain a hazard ratio of the two hazard funtions (under the

Dear R-users, I would like to fit a fully parametric proportional hazard model with a weibull baseline hazard and a logit link function. This is, the hazard function is: lambda_i (t) = lambda_0 (t) psi (x_i* beta) where lambda_0 is a weibull distribution and psi a logistic distribution. Does someone know a package and/or function on R to do this? Thanks. -- M.L. Avendaño [[alternative HTML

Dear Forum, I have a question about interaction estimate in the Cox model: why the hazard ratio of the interaction is not produced in the summary of the model? (Instead, the estimate of the coefficient is given in the print of the model.) # Example: modINT <-cph( Surv(T_BASE, T_FIN,STATUS)~ NYHA + ASINI + RFP + FE_REC + XX_PR*XX_DISF) print(modINT) coef se(coef) z

hi, LLVM, I found there is a flag DisableHazardRecognizer in TargetInstrImpl.cpp. I still don't understand how llvm detects data hazard in pre-RA-sched. pre-RA-sched is based on SDNode and all operands are vregs. Even you can calculate the operators of SDNodes, the data hazard in vreg are not same as physical register data hazard. Is it useful to optimize processor pipeline? thanks, --lx