首页 | 本学科首页   官方微博 | 高级检索  
     


Bayesian Binomial Regression: Predicting Survival at a Trauma Center
Authors:Edward J. Bedrick  Ronald Christensen  Wesley Johnson
Affiliation:1. Department of Statistics , University of New Mexico , Albuquerque , NM , 87131;2. Division of Statistics , University of California at Davis , Davis , CA , 95616 , USA
Abstract:
Standard methods for analyzing binomial regression data rely on asymptotic inferences. Bayesian methods can be performed using simple computations, and they apply for any sample size. We provide a relatively complete discussion of Bayesian inferences for binomial regression with emphasis on inferences for the probability of “success.” Furthermore, we illustrate diagnostic tools, perform model selection among nonnested models, and examine the sensitivity of the Bayesian methods.
Keywords:Bayesian analysis  Importance sampling  Kullback–Leibler divergence  Logistic regression  Model selection  Prediction  Probit analysis  Regression diagnostics.
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号