title: A regression survival model for testing the proportional hazards hypothesis.
abstract: A semi-parametric generalization of the proportional hazards regression model is defined, whereby the hazard functions can cross for different values of the covariates. In the two-sample comparison, it includes in particular the case of two Weibull distributions differing in scale and shape parameters. A global test of the proportional hazards assumption is proposed against such defined alternatives. Its power in the two-sample case is compared to that of previously described tests by using simulation experiments. Survival data of patients with breast carcinoma, including several prognostic factors, are presented as an illustration.
authors.affiliation: Centre Hospitalier Régional Universitaire, Paris, France.
authors.forename: C
authors.initials: C
authors.lastname: Quantin
authors.forename: T
authors.initials: T
authors.lastname: Moreau
authors.forename: B
authors.initials: B
authors.lastname: Asselain
authors.forename: J
authors.initials: J
authors.lastname: Maccario
authors.forename: J
authors.initials: J
authors.lastname: Lellouch
mesh_terms: D000970:Antineoplastic Agents / Q000627:therapeutic use; D001699:Biometry; D001943:Breast Neoplasms / Q000188:drug therapy / Q000201:enzymology / Q000401:mortality; D005260:Female; D006801:Humans; D007770:L-Lactate Dehydrogenase / Q000378:metabolism; D015233:Models, Statistical; D016016:Proportional Hazards Models; D012044:Regression Analysis; D016019:Survival Analysis
chemical_list: D000970:Antineoplastic Agents; D007770:L-Lactate Dehydrogenase