fit_copula_model_BinCont: 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"
)

Value

WIP

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".