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用于风险和生存回归贝叶斯分析的广义共轭先验。

Generalized conjugate priors for Bayesian analysis of risk and survival regressions.

作者信息

Greenland Sander

机构信息

Department of Epidemiology, UCLA School of Public Health, 22333 Swenson Drive, Topanga, California 90290, USA.

出版信息

Biometrics. 2003 Mar;59(1):92-9. doi: 10.1111/1541-0420.00011.

DOI:10.1111/1541-0420.00011
PMID:12762445
Abstract

Conjugate priors for Bayesian analyses of relative risks can be quite restrictive, because their shape depends on their location. By introducing a separate location parameter, however, these priors generalize to allow modeling of a broad range of prior opinions, while still preserving the computational simplicity of conjugate analyses. The present article illustrates the resulting generalized conjugate analyses using examples from case-control studies of the association of residential wire codes and magnetic fields with childhood leukemia.

摘要

用于相对风险贝叶斯分析的共轭先验可能具有很大的局限性,因为它们的形状取决于其位置。然而,通过引入一个单独的位置参数,这些先验得以推广,从而能够对广泛的先验观点进行建模,同时仍保留共轭分析的计算简便性。本文通过住宅电线编码和磁场与儿童白血病关联的病例对照研究中的实例,阐述由此产生的广义共轭分析。

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