ICA_given_model_constructor: Constructor for the function that returns that ICA as a...

In Surrogate: Evaluation of Surrogate Endpoints in Clinical Trials

Constructor for the function that returns that ICA as a function of the identifiable parameters

Description

ICA_given_model_constructor() returns a function fixes the unidentifiable parameters at user-specified values and takes the identifiable parameters as argument.

Usage

ICA_given_model_constructor(
  fitted_model,
  copula_par_unid,
  copula_family2,
  rotation_par_unid,
  n_prec,
  measure = "ICA",
  mutinfo_estimator,
  composite,
  seed,
  restr_time = +Inf
)

Arguments

fitted_model	Returned value from fit_model_SurvSurv(). This object contains the estimated identifiable part of the joint distribution for the potential outcomes.
copula_par_unid	Parameter vector for the sequence of unidentifiable bivariate copulas that define the D-vine copula. The elements of copula_par correspond to (c_{23}, c_{13;2}, c_{24;3}, c_{14;23}).
copula_family2	Copula family of the other bivariate copulas. For the possible options, see loglik_copula_scale(). The elements of copula_family2 correspond to (c_{23}, c_{13;2}, c_{24;3}, c_{14;23}).
rotation_par_unid	Vector of rotation parameters for the sequence of unidentifiable bivariate copulas that define the D-vine copula. The elements of rotation_par correspond to (c_{23}, c_{13;2}, c_{24;3}, c_{14;23}).
n_prec	Number of Monte Carlo samples for the computation of the mutual information.
measure	Compute intervals for which measure of surrogacy? Defaults to "ICA". See first column names of sens_results for other possibilities.
mutinfo_estimator	Function that estimates the mutual information between the first two arguments which are numeric vectors. Defaults to FNN::mutinfo() with default arguments. @param plot_deltas (logical) Plot the sampled individual treatment effects?
composite	(boolean) If composite is TRUE, then the surrogate endpoint is a composite of both a "pure" surrogate endpoint and the true endpoint, e.g., progression-free survival is the minimum of time-to-progression and time-to-death.
seed	Seed for Monte Carlo sampling. This seed does not affect the global environment.
restr_time	Restriction time for the potential outcomes. Defaults to +Inf which means no restriction. Otherwise, the sampled potential outcomes are replace by pmin(S0, restr_time) (and similarly for the other potential outcomes).

Value

A function that computes the ICA as a function of the identifiable parameters. In this computation, the unidentifiable parameters are fixed at the values supplied as arguments to ICA_given_model_constructor()

Surrogate documentation built on June 22, 2024, 9:16 a.m.