title: Inferences on the association parameter in copula models for bivariate survival data.
abstract: We investigate two-stage parametric and two-stage semi-parametric estimation procedures for the association parameter in copula models for bivariate survival data where censoring in either or both components is allowed. We derive asymptotic properties of the estimators and compare their performance by simulations. Both parametric and semi-parametric estimators of the association parameter are efficient at independence, and the parameter estimates in the margins have high efficiency and are robust to misspecification of dependency structures. In addition, we propose a consistent variance estimator for the semi-parametric estimator of the association parameter. We apply the proposed methods to an AIDS data set for illustration.
authors.affiliation: National Heart, Lung, and Blood Institute, Bethesda, Maryland 20892-7938, USA.
authors.forename: J H
authors.initials: JH
authors.lastname: Shih
authors.forename: T A
authors.initials: TA
authors.lastname: Louis
mesh_terms: D017088:AIDS-Related Opportunistic Infections / Q000401:mortality; D000163:Acquired Immunodeficiency Syndrome / Q000401:mortality; D001699:Biometry / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D016019:Survival Analysis