search for: selfprentice

...,] fit$phase2var<-(1-(nc/ntot))*t(db)%*%(db) fit$naive.var <- fit$naive.var+fit$phase2var fit$var<-fit$naive.var fit$coefficients <- fit$coef <- fit1$coefficients fit } The first fit1<-coxph() estimate the coefficient and second fit<-coxph() which seems a SelfPrentice method to estimate the variance. My question is why second coxph() estimate Prentice variance using SelfPrentice method. Should the jacknife variance of Prentice be implemented like: fit1 <- coxph(Surv(ent2,texit,cens)~X+cluster(id),eps=eps,x=TRUE) Th other question is unique id is not necessar...

Dear all, I have a couple of questions regarding the survival:::cch function. 1) I notice that Prentice and Self-Prentice functions are giving identical standard errors (not by chance but by programming design) while their estimates are different. My guess is they are both using the standard error form from Self and Prentice (1986). I see that standard errors for both methods are

...= 134 on 5 df, p=0 Score (logrank) test = 490 on 5 df, p=0, Robust = 165 p=0 (Note: the likelihood ratio and score tests assume independence of observations within a cluster, the Wald and robust score tests do not). > summary(fit.ccSP) Case-cohort analysis,x$method, SelfPrentice with subcohort of 668 from cohort of 4028 Call: cch(formula = Surv(edrel, rel) ~ stage + histol + age, data = ccoh.data, subcoh = ~subcohort, id = ~seqno, cohort.size = 4028, method = "SelfPren") Coefficients: Coef HR (95% CI) p stageII 0.736 2.088 1.491 2.925...

----- begin included message In case cohort study, we can fit proportional hazard regression model to case-cohort data. In R, the function is cch() in Survival package Now I am working on case cohort analysis with time dependent covariates using cch() of "Survival" R package. I wonder if cch() provide this utility or not? The cch() manual does not say if time dependent covariate is