compute_ICA: 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 setting of choice.

Description

The compute_ICA() function computes the individual causal association for a fully identified D-vine copula model. See details for the default definition of the ICA in each setting.

Usage

compute_ICA(endpoint_types, ...)

Arguments

endpoint_types	(character) vector with two elements indicating the endpoint types: "continuous" or "ordinal".
...	Arguments to pass onto compute_ICA_ContCont(), compute_ICA_OrdCont(), or compute_ICA_OrdOrd()

Value

(numeric) A Named vector with the following elements:

• ICA

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

• Marginal association parameters in terms of Spearman's rho (if asked):

  \rho_{s}(T_0, S_0), \rho_{s}(T_0, S_1), \rho_{s}(T_0, T_1), \rho_{s}(S_0, S_1), \rho_{s}(S_0, T_1), \rho_{s}(S_1, T_1)

Surrogate documentation built on April 11, 2025, 6:09 p.m.