Local full likelihood estimation for the proportional hazards model.
In this paper a new approach to local likelihood estimation for censored data is proposed. This method employs the full likelihood and alternates between estimating the baseline hazard and estimating the covariate effect. The proposed methodology incorporates multidimensional data via additive models. Some results regarding inference for the covariate effect are also presented.
Gentleman
R
R
Department of Statistics and Actuarial Science, University of Waterloo, Ontario, Canada.
Crowley
J
J
D000704:Analysis of Variance; D001699:Biometry; D006801:Humans; D016013:Likelihood Functions; D009101:Multiple Myeloma / Q000097:blood / Q000401:mortality; D016016:Proportional Hazards Models; D012709:Serum Albumin / Q000378:metabolism; D001613:beta 2-Microglobulin / Q000378:metabolism
D012709:Serum Albumin; D001613:beta 2-Microglobulin