Title: Perturbation-based model tests with application to the Clayton model
Authors: Wenqing He - University of Western Ontario (Canada) [presenting]
Abstract: The perturbation resampling method can be employed to estimate the covariance matrix of an estimator when the estimator is obtained through minimizing a U-process. This perturbation resampling is proposed to establish general tests for the detection of model misspecification or for model checking. The proposed tests enjoy the simplicity and a theoretical justification. We apply the proposed method to modify previous tests for the assessment of Clayton models in multivariate survival analysis, where the asymptotic variance is intractable. The proposed tests present a promising performance in the simulation studies and have simpler procedures than the nonparametric bootstrap which can also be applied to approximate the covariance matrix. A colon cancer study further illustrates the proposed methods.