Estimation of the Proportion of Treatment Effect Explained by Surrogate Outcome Information
Calculates censoring probability for weighting
Helper function
Estimates the treatment effect at time t, defined as the difference in...
Helper function
Calculates the residual treatment effect (the difference in restricted...
Calculates the residual treatment effect (the difference in restricted...
Calculates the residual treatment effect (the difference in restricted...
Helper function
Calculates the incremental value of the surrogate outcome information
Calculates kernel matrix
Helper function
Calculates the conditional probability of survival for control group v...
Calculates the proportion of the treatment effect (the difference in s...
Calculates the proportion of the treatment effect (the difference in r...
Calculates the proportion of the treatment effect (the difference in r...
Resampling for standard error estimation
Repeats a row
Weight function for resampling
Weight function
Estimates the proportion of treatment effect on a censored primary outcome that is explained by the treatment effect on a censored surrogate outcome/event. All methods are described in detail in Parast, et al (2020) "Assessing the Value of a Censored Surrogate Outcome" <doi:10.1007/s10985-019-09473-1> and Wang et al (2025) "Model-free Approach to Evaluate a Censored Intermediate Outcome as a Surrogate for Overall Survival" <doi:10.1002/sim.70268>. A tutorial for this package can be found at <https://www.laylaparast.com/surrogateoutcome>.