title: A Dirichlet process mixture model for survival outcome data: assessing nationwide kidney transplant centers.
abstract: Mortality rates are probably the most important indicator for the performance of kidney transplant centers. Motivated by the national evaluation of mortality rates at kidney transplant centers in the USA, we seek to categorize the transplant centers based on the mortality outcome. We describe a Dirichlet process model and a Dirichlet process mixture model with a half-cauchy prior for the estimation of the risk-adjusted effects of the transplant centers, with strategies for improving the model performance, interpretability, and classification ability. We derive statistical measures and create graphical tools to rate transplant centers and identify outlying groups of centers with exceptionally good or poor performance. The proposed method was evaluated through simulation and then applied to assess kidney transplant centers from a national organ failure registry.
authors.affiliation: Department of Biostatistics, University of Michigan, Ann Arbor, MI, U.S.A.
authors.forename: Lili
authors.initials: L
authors.lastname: Zhao
authors.forename: Jingchunzi
authors.initials: J
authors.lastname: Shi
authors.forename: Tempie H
authors.initials: TH
authors.lastname: Shearon
authors.forename: Yi
authors.initials: Y
authors.lastname: Li
mesh_terms: D001499:Bayes Theorem; D016000:Cluster Analysis; D003198:Computer Simulation; D006801:Humans; D016030:Kidney Transplantation / Q000401:mortality* / Q000592:standards; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D016016:Proportional Hazards Models; D011785:Quality Assurance, Health Care / Q000379:methods / Q000592:standards* / Q000706:statistics & numerical data; D019984:Quality Indicators, Health Care / Q000592:standards / Q000706:statistics & numerical data*; D012042:Registries; D012189:Retrospective Studies; D018709:Statistics, Nonparametric; D016019:Survival Analysis; D014481:United States / Q000453:epidemiology
keywords: Dirichlet process mixture; clustering; mixture model; stick-breaking process; survival data; transplant