twostep_BinCont: Fit binary-continuous copula submodel with two-step estimator

In Surrogate: Evaluation of Surrogate Endpoints in Clinical Trials

Fit binary-continuous copula submodel with two-step estimator

Description

The twostep_BinCont() function fits the copula (sub)model fir a continuous surrogate and binary true endpoint with a two-step estimator. In the first step, the marginal distribution parameters are estimated through maximum likelihood. In the second step, the copula parameter is estimate while holding the marginal distribution parameters fixed.

Usage

twostep_BinCont(
  X,
  Y,
  copula_family,
  marginal_surrogate,
  marginal_surrogate_estimator = NULL,
  method = "BFGS"
)

Arguments

X	(numeric) Continuous surrogate variable
Y	(integer) Binary true endpoint variable (T_k \, \in \, \{0, 1\})
copula_family	Copula family, one of the following: "clayton" "frank" "gumbel" "gaussian" The parameterization of the respective copula families can be found in the help files of the dedicated functions named copula_loglik_copula_scale().
marginal_surrogate	Marginal distribution for the surrogate. For all available options, see ?Surrogate::cdf_fun.
marginal_surrogate_estimator	Not yet implemented
method	Optimization algorithm for maximizing the objective function. For all options, see ?maxLik::maxLik. Defaults to "BFGRS".

Value

A list with three elements:

• ml_fit: object of class maxLik::maxLik that contains the estimated copula model.

• marginal_S_dist: object of class fitdistrplus::fitdist that represents the marginal surrogate distribution.

• copula_family: string that indicates the copula family

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