Generalized conjugate priors for Bayesian analysis of risk and survival regressions.
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.
Greenland
Sander
S
Department of Epidemiology, UCLA School of Public Health, 22333 Swenson Drive, Topanga, California 90290, USA. lesdomes@ucla.edu
D001499:Bayes Theorem; D016022:Case-Control Studies; D002648:Child; D003627:Data Interpretation, Statistical; D004574:Electromagnetic Fields / Q000009:adverse effects; D006801:Humans; D007938:Leukemia / Q000453:epidemiology / Q000209:etiology; D016015:Logistic Models; D016016:Proportional Hazards Models; D012306:Risk; D016019:Survival Analysis