Smoothing spline-based score tests for proportional hazards models.
We propose "score-type" tests for the proportional hazards assumption and for covariate effects in the Cox model using the natural smoothing spline representation of the corresponding nonparametric functions of time or covariate. The tests are based on the penalized partial likelihood and are derived by viewing the inverse of the smoothing parameter as a variance component and testing an equivalent null hypothesis that the variance component is zero. We show that the tests have a size close to the nominal level and good power against general alternatives, and we apply them to data from a cancer clinical trial.
Lin
Jiang
J
GlaxoSmithKline, P.O. Box 13398, Research Triangle Park, North Carolina 27709, USA.
Zhang
Daowen
D
Davidian
Marie
M
D000704:Analysis of Variance; D001699:Biometry / Q000379:methods*; D001943:Breast Neoplasms / Q000188:drug therapy / Q000378:metabolism; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D008593:Menopause; D016016:Proportional Hazards Models; D011960:Receptors, Estrogen / Q000378:metabolism
D011960:Receptors, Estrogen