Description Usage Arguments Value Author(s) Examples
View source: R/Functions_SurrogateTest.R
This function calculates the treatment effect in the survival setting i.e. the difference in survival at time t between the treatment group and the control group. The inverse probability of censoring weighted estimate of survival within each treatment group is used; there is an option to use the Kaplan-Meier estimate instead. This function is generally not expected to be used directly by the user, it is called by the recover.B function.
1 | delta.estimate(xone, xzero, deltaone, deltazero, t, weight = NULL, KM = FALSE)
|
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. |
t |
the time of interest. |
weight |
a n_1+n_0 by x matrix of weights where n_1 = sample size in the treatment group and n_0 = sample size in the control group, default is null; generally not supplied by user, only used by other functions. |
KM |
true or false, indicating whether the Kaplan-Meier estimate of survival should be used instead of the inverse probability of censoring weighted estimate |
the difference in survival at time t (treatment group minus control group)
Layla Parast
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