This class of objects is returned by the function penPHcure when is called with the argument pen.type = "none". Objects of this class have methods for the functions summary and predict.
a numeric vector with the estimated regression coefficients in the cure (incidence) component.
a numeric vector with the true estimated regression coefficients in the survival (latency) component.
a numeric vector with the estimated cumulative baseline hazard function at the unique event times (reported in the "names" attribute).
the value of the log-likelihood for the estimated model.
an integer to indicate if the Expectation-Maximization (EM) algorithm converged. The possible values are: 1 if it converged, -1 if it exceeded the maximum number of iterations or -2 if it stopped due to non-finite elements in the regression coefficients.
the maximum number of iteration before the convergence of the Expectation-Maximization (EM) algorithm.
the sample size (number of individuals).
the number of unique failure times.
logical value: TRUE in case of tied event times.
the proportion of censored individuals.
character string indicating the method used to transform the covariates included in the incidence (cure) component from time-varying to time-invariant. See penPHcure for more details.
a formula object with all variables involved in the latency (survival) component of the model.
a formula object with all variables involved in the incidence (survival) component of the model.
[optional] a list with elements named bs, betas and nboot. The elements bs and betas are matrices containing on each row the estimated regression coefficients in the incidence and latency components, respectively, for each of the nboot bootstrap resamples. This object is returned only if the function penPHcure was called with the argument inference = TRUE.
object of class call, with all the specified arguments.