delta.s.surv.estimate.new {hetsurrSurv} | R Documentation |
Calculates robust residual treatment effect accounting for surrogate marker information measured at a specified time and primary outcome information up to that specified time
Description
This function calculates the robust estimate of the residual treatment effect accounting for surrogate marker information measured at t_0
and primary outcome information up to t_0
i.e. the hypothetical treatment effect if both the surrogate marker distribution at t_0
and survival up to t_0
in the treatment group look like the surrogate marker distribution and survival up to t_0
in the control group. Ideally this function is only used as a helper function and is not directly called.
Usage
delta.s.surv.estimate.new(xone, xzero, deltaone, deltazero, sone, szero, t,
weight.perturb = NULL, landmark, extrapolate = FALSE, transform = FALSE,
approx = TRUE, warn.te = FALSE, warn.support = FALSE)
Arguments
xone |
numeric vector, the observed event times in the treatment group, X = min(T,C) where T is the time of the primary outcome and C is the censoring time. |
xzero |
numeric vector, the observed event times in the control group, X = min(T,C) where T is the time of the primary outcome and C is the censoring time. |
deltaone |
numeric vector, the event indicators for the treatment group, D = I(T<C) where T is the time of the primary outcome and C is the censoring time. |
deltazero |
numeric vector, the event indicators for the control group, D = I(T<C) where T is the time of the primary outcome and C is the censoring time. |
sone |
numeric vector; surrogate marker measurement at |
szero |
numeric vector; surrogate marker measurement at |
t |
the time of interest. |
weight.perturb |
weights used for perturbation resampling. |
landmark |
the landmark time |
extrapolate |
TRUE or FALSE; indicates whether the user wants to use extrapolation. |
transform |
TRUE or FALSE; indicates whether the user wants to use a transformation for the surrogate marker. |
approx |
TRUE or FALSE indicating whether an approximation should be used when calculating the probability of censoring; most relevant in settings where the survival time of interest for the primary outcome is greater than the last observed event but before the last censored case, default is TRUE. |
warn.te |
value passed from R.s.estimate function to control warnings; user does not need to specify. |
warn.support |
value passed from R.s.estimate function to control warnings; user does not need to specify. |
Details
Details are included in the documentation for R.s.surv.estimate.
Value
\hat{\Delta}_S(t,t_0)
, the robust residual treatment effect estimate accounting for surrogate marker information measured at t_0
and primary outcome information up to t_0
.
References
Parast, L., Cai, T., & Tian, L. (2017). Evaluating surrogate marker information using censored data. Statistics in Medicine, 36(11), 1767-1782.