fit_copula_model_BinCont: Fit copula model for binary true endpoint and continuous...

In Surrogate: Evaluation of Surrogate Endpoints in Clinical Trials

Fit copula model for binary true endpoint and continuous surrogate endpoint

Description

The function fit_copula_model_BinCont() fits the copula model for a continuous surrogate endpoint and binary true endpoint. Because the bivariate distributions of the surrogate-true endpoint pairs are functionally independent across treatment groups, a bivariate distribution is fitted in each treatment group separately.

Usage

fit_copula_model_BinCont(
  data,
  copula_family,
  marginal_surrogate,
  marginal_surrogate_estimator = NULL,
  twostep = FALSE,
  fitted_model = NULL,
  maxit = 500,
  method = "BFGS"
)

Arguments

data	A data frame in the correct format (See details).
copula_family	One of the following parametric copula families: "clayton", "frank", "gaussian", or "gumbel".
marginal_surrogate	Marginal distribution for the surrogate. For all available options, see ?Surrogate::cdf_fun.
marginal_surrogate_estimator	Not yet implemented
twostep	(boolean) if TRUE, the two step estimator implemented in twostep_BinCont() is used for estimation.
fitted_model	Fitted model from which initial values are extracted. If NULL (default), standard initial values are used. This option intended for when a model is repeatedly fitted, e.g., in a bootstrap.
maxit	Maximum number of iterations for the numeric optimization, defaults to 500.
method	Optimization algorithm for maximizing the objective function. For all options, see ?maxLik::maxLik. Defaults to "BFGRS".

Value

WIP

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