B is the specification for time-varying covariates. Otherwise, your model will think that each row is one independent observation that either had an event or was censored at "time" or "total_time." HTH, Daniel
javier palacios wrote:
Dear R-community, which of the following two formats is correct? Are both correct? Please, consider this example: data table: Data S sta time TDC1 total_time A 1 0 1 48.50 1 B 0 0 1 65.96 2 B 1 1 2 65.08 2 C 0 0 1 0.00 2 C 1 1 2 0.00 2 D 0 0 1 72.74 2 D 1 1 2 72.52 2 E 0 0 1 61.84 2 E 0 1 2 60.56 2 F 0 0 1 35.04 4 F 0 1 2 36.97 4 F 0 2 3 37.92 4 F 1 3 4 39.01 4 time - time to event sta - starting time TDC - time dependent covariates total_time - total time at risk option A coxph(Surv(time,S) ~ time_dependent_covariates, data=data.frame(Data)) option B coxph(Surv(sta,time,S) ~ time_dependent_covariates, data=data.frame(Data)) option C coxph(Surv(total_time,S) ~ time_dependent_covariates, data=data.frame(Data)) How can time at risk be visualized in the coxph output? Best regards, Javier
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