Goodness-of-fit tests in the Cox proportional hazards model. Issue 12 (2nd December 2021)

• Record Type: Journal Article
• Authors: Cockeran, Marike; Meintanis, Simos George; Allison, James S.
• Is Part Of: Communications in statistics. Volume 50:Issue 12(2021)
• Page Start: 4132
• Page End: 4143
• Publication Date: 2021-12-02
• Subjects: Test for exponentiality -- Parametric bootstrap -- Survival model; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2019.1639738
• Languages: English
• ISSNs: 0361-0918

Abstract

Abstract: We consider a variety of tests for testing goodness-of-fit in a parametric Cox proportional hazards (PH) model and compare their performance. Aspects of the model under test include the baseline distribution and time-invariance of covariates. We also test for the PH model itself against a certain generalization. This is done through an extensive Monte Carlo study where we simulate the performance of the tests for these three paired hypotheses. The results show that the tests based on the empirical characteristic function and those based on the empirical Laplace transform have the best overall power performance. It is also found that the distributions of the considered test statistics do not depend on the specific functional form of the covariate function.