Estimation of the Proportion of Treatment Effect Explained by
Surrogate Outcome Information // 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.