Model comparison is a crucial part of any statistical analysis. Due to recent computational advances, sophisticated techniques for Bayesian model comparison in survival analysis are becoming increasingly popular. There has been a recent surge in the statistical literature on Bayesian methods for model comparison, including articles by George and McCulloch (1993), Madigan and Raftery (1994), Ibrahim and Laud (1994), Laud and Ibrahim (1995), Kass and Raftery (1995), Chib (1995), Chib and Greenberg (1998), Raftery, Madigan, and Volinsky (1995), George, McCulloch, and Tsay (1996), Raftery, Madigan, and Hoeting (1997), Gelfand and Ghosh (1998), Clyde (1999), and Chen, Ibrahim, and Yiannoutsos (1999). Articles focusing on Bayesian approaches to model comparison in the context of survival analysis include Madigan and Raftery (1994), Raftery, Madigan, and Volinsky (1995), Sinha, Chen, and Ghosh (1999), Ibrahim, Chen, and Sinha (2001b), Ibrahim and Chen (1998), Ibrahim, Chen, and MacEachern (1999), Sahu, Dey, Aslanidou, and Sinha (1997), Aslanidou, Dey, and Sinha (1998), Chen, Harrington, and Ibrahim (1999), and Ibrahim, Chen, and Sinha (2001a).
KeywordsPosterior Probability Markov Chain Monte Carlo Bayesian Information Criterion Bayesian Model Average Markov Chain Monte Carlo Sample
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