Hazard regression for interval-censored data with penalized spline.
This article introduces a new approach for estimating the hazard function for possibly interval- and right-censored survival data. We weakly parameterize the log-hazard function with a piecewise-linear spline and provide a smoothed estimate of the hazard function by maximizing the penalized likelihood through a mixed model-based approach. We also provide a method to estimate the amount of smoothing from the data. We illustrate our approach with two well-known interval-censored data sets. Extensive numerical studies are conducted to evaluate the efficacy of the new procedure.
Cai
Tianxi
T
Department of Biostatistics, Harvard University, Boston, Massachusetts 02115, USA. tcai@hsph.harvard.edu
Betensky
Rebecca A
RA
D001699:Biometry; D001943:Breast Neoplasms / Q000473:pathology / Q000628:therapy; D003627:Data Interpretation, Statistical; D005260:Female; D015658:HIV Infections / Q000150:complications / Q000635:transmission; D006467:Hemophilia A / Q000150:complications; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D016016:Proportional Hazards Models; D016019:Survival Analysis