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...ata$histol <- factor(ccoh.data$histol,labels=c("FH","UH")) ## tumour stage ccoh.data$stage <- factor(ccoh.data$stage,labels=c("I","II","III","IV")) ccoh.data$age <- ccoh.data$age/12 # Age in years cch(Surv(edrel, rel) ~ stage + histol + age, data =ccoh.data, subcoh = ~subcohort, id=~seqno, cohort.size=4028) cch(Surv(edrel, rel) ~ stage + histol + age, data =ccoh.data, subcoh = ~subcohort, id=~seqno, cohort.size=4028, method="SelfPren") 2) I also notice that Lin-Ying beta estimates a...

...) is same, but the lower and upper CI and P-value are a little different. Can we exactly use coxph() to repeat cch() using with appropriate configuration in coxph()? Is SAS a better way(PHREG,CASECOH.SAS) to implement time-dependent case-cohort? > summary(fit2.ccP) Call: coxph(formula = Surv(edrel, rel) ~ stage + histol + age + offset(-100 * (1 - subcohort)) + cluster(seqno), data = ccoh.data) n= 1154 coef exp(coef) se(coef) robust se z p stageII 0.7363 2.09 0.1213 0.1699 4.33 1.5e-05 stageIII 0.5976 1.82 0.1233 0.1753 3.41 6.5e-04 stageIV 1.3...

----- 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

Jin Wang had an error. My original note specified a variable that was 1 for subjects NOT in the subcohort, so the correct coxph call is coxph(Surv(edrel, rel) ~ stage + histol + age + offset(-100*(subcohort==0)) + cluster(seqno), data =ccoh.data) This gives the same coefficients as the cch example, along with the infinitesimal jackknife or "robust" variance estimate. Terry Therneau