BACKGROUND
Measuring disease and injury burden in populations requires a composite metric that captures both premature mortality and the prevalence and severity of ill-health. The 1990 Global Burden… (More)
Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables Nicholas G. Polson a , James G. Scott b & Jesse Windle c a Statistics and Econometrics , University of Chicago Booth School… (More)
We study the classic problem of choosing a prior distribution for a location parameter β = (β1, . . . , βp) as p grows large. First, we study the standard “global-local shrinkage” approach, based on… (More)
BACKGROUND
Child sexual abuse is considered a modifiable risk factor for mental disorders across the life course. However the long-term consequences of other forms of child maltreatment have not yet… (More)
There has been increased interest of late in the Bayesian approach to multiple testing (often called the multiple comparisons problem), motivated by the need to analyze DNA microarray data in which… (More)
BACKGROUND
The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and… (More)
This paper presents a general, fully Bayesian framework for sparse supervised-learning problems based on the horseshoe prior. The horseshoe prior is a member of the family of multivariate scale… (More)
This paper argues that the half-Cauchy distribution should replace the inverseGamma distribution as a default prior for a top-level scale parameter in Bayesian hierarchical models, at least for cases… (More)
BACKGROUND
Apart from individuals with clinical psychosis, community surveys have shown that many otherwise well individuals endorse items designed to identify psychosis. The aim of this study was to… (More)
BACKGROUND
Surveys have found that otherwise well individuals report delusional experiences. Previous studies have shown an association between psychotic symptoms and exposure to trauma.
AIMS
To… (More)