compute_ICA_BinCont: Compute Individual Causal Association for a given D-vine...

In Surrogate: Evaluation of Surrogate Endpoints in Clinical Trials

Compute Individual Causal Association for a given D-vine copula model in the Binary-Continuous Setting

Description

The compute_ICA_BinCont() function computes the individual causal association for a fully identified D-vine copula model in the setting with a continuous surrogate endpoint and a binary true endpoint.

Usage

compute_ICA_BinCont(
  copula_par,
  rotation_par,
  copula_family1,
  copula_family2 = copula_family1,
  n_prec,
  q_S0,
  q_S1,
  marginal_sp_rho = TRUE,
  seed = 1
)

Arguments

copula_par	Parameter vector for the sequence of bivariate copulas that define the D-vine copula. The elements of copula_par correspond to (c_{12}, c_{23}, c_{34}, c_{13;2}, c_{24;3}, c_{14;23}).
rotation_par	Vector of rotation parameters for the sequence of bivariate copulas that define the D-vine copula. The elements of rotation_par correspond to (c_{12}, c_{23}, c_{34}, c_{13;2}, c_{24;3}, c_{14;23}).
copula_family1	Copula family of c_{12} and c_{34}. For the possible options, see loglik_copula_scale(). The elements of copula_family correspond to (c_{12}, c_{34}).
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}).
n_prec	Number of Monte Carlo samples for the computation of the mutual information.
q_S0	Quantile function for the distribution of S_0.
q_S1	Quantile function for the distribution of S_1.
marginal_sp_rho	(boolean) Compute the sample Spearman correlation matrix? Defaults to TRUE.
seed	Seed for Monte Carlo sampling. This seed does not affect the global environment.

Value

(numeric) A Named vector with the following elements:

• ICA

• Spearman's rho, \rho_s (\Delta S, \Delta T) (if asked)

• Kendall's tau, \tau (\Delta S, \Delta T) (if asked)

• Marginal association parameters in terms of Spearman's rho:

  (\rho_s(S_0, S_1), \rho_s(S_0, T_0), \rho_s(S_0, T_1), \rho_s(S_1, T_0), \rho_s(S_0, S_1), \rho_s(T_0, T_1)

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