sample_deltas_BinCont: Sample individual casual treatment effects from given D-vine...

In Surrogate: Evaluation of Surrogate Endpoints in Clinical Trials

Sample individual casual treatment effects from given D-vine copula model in binary continuous setting

Description

Sample individual casual treatment effects from given D-vine copula model in binary continuous setting

Usage

sample_deltas_BinCont(
  copula_par,
  rotation_par,
  copula_family1,
  copula_family2 = copula_family1,
  n,
  q_S0 = NULL,
  q_S1 = NULL,
  q_T0 = NULL,
  q_T1 = NULL,
  marginal_sp_rho = TRUE,
  setting = "BinCont",
  composite = FALSE
)

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().
copula_family2	Copula family of the other bivariate copulas. For the possible options, see loglik_copula_scale().
n	Number of samples to be taken from the D-vine copula.
q_S0	Quantile function for the distribution of S_0.
q_S1	Quantile function for the distribution of S_1.
q_T0	Quantile function for the distribution of T_0. This should be NULL if T_0 is binary.
q_T1	Quantile function for the distribution of T_1. This should be NULL if T_1 is binary.
marginal_sp_rho	(boolean) Compute the sample Spearman correlation matrix? Defaults to TRUE.
setting	Should be one of the following two: "BinCont": for when S is continuous and T is binary. "SurvSurv": for when both S and T are time-to-event variables.
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.

Value

A list with two elements:

• Delta_dataframe: a dataframe containing the sampled individual causal treatment effects

• marginal_sp_rho_matrix: a matrix containing the marginal pairwise Spearman's rho parameters estimated from the sample. If marginal_sp_rho = FALSE, this matrix is not computed and NULL is returned for this element of the list.

Surrogate documentation built on Sept. 25, 2023, 5:07 p.m.