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A Bayesian Approach To Ordinal Outcomes For Neurosurgical Clinical Research., Sally Wood
A Bayesian Approach To Ordinal Outcomes For Neurosurgical Clinical Research., Sally Wood
Sally Wood
The objective of this study is to demonstrate a Bayesian approach for the statistical analysis of neurosurgical data where the investigators have used an ordinal scale for the outcome. A Bayesian approach that uses data augmentation and Gibbs sampling to perform ordinal probit regression is demonstrated in a neurosurgical context. The statistical approach is applied to a regression analysis to examine the relationship between female gender and the outcome of severe traumatic brain injury measured with the Glascow Outcome Scale. The approach is applied to a hierarchical meta-analysis to examine the relationship between age and the outcome from subarachnoid haemorrhage …
Priors For A Bayesian Analysis Of Extreme Values, Sally Wood, Julian Wang
Priors For A Bayesian Analysis Of Extreme Values, Sally Wood, Julian Wang
Sally Wood
This article proposes a new prior specification for a Bayesian analysis of the k largest order statistics model. We show that using Jeffreys priors for the end-point and shape parameters of the k largest order statistics model leads to biased estimates of the shape parameter for small to medium sample sizes and to the posterior mode of the end-point being equal to the most extreme observed value. We propose a conjugate prior for the shape parameter and a prior for the end-point which removes the posterior mode at the most extreme observed value while remaining uninformative for values of the …