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 r...
Calculates the proportion of the treatment effect (the difference in r...
tools:::Rd_package_title("SurrogateOutcome")
Repeats a row
Provides functions to estimate 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, Tian, Cai (2020) "Assessing the Value of a Censored Surrogate Outcome" <doi:10.1007/s10985-019-09473-1>. The main functions are (1) R.q.event() which calculates the proportion of the treatment effect (the difference in restricted mean survival time at time t) explained by surrogate outcome information observed up to a selected landmark time, (2) R.t.estimate() which calculates the proportion of the treatment effect explained by primary outcome information only observed up to a selected landmark time, and (3) IV.event() which calculates the incremental value of the surrogate outcome information.