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Estimation of diagnostic-test sensitivity and specificity through Bayesian modeling.
The primary goal is to provide veterinary researchers with a concise presentation of the computational aspects involved in using the Bayesian framework for test evaluation. Expand
Modeling Regression Error With a Mixture of Polya Trees
We model the error distribution in the standard linear model as a mixture of absolutely continuous Polya trees constrained to have median 0. By considering a mixture, we smooth out the partitioningExpand
A New Perspective on Priors for Generalized Linear Models
Abstract This article deals with specifications of informative prior distributions for generalized linear models. Our emphasis is on specifying distributions for selected points on the regressionExpand
Factors associated with prevalent and incident urinary incontinence in a cohort of midlife women: a longitudinal analysis of data: study of women's health across the nation.
Parity, diabetes, fibroids, andpoor social support were associated with prevalent incontinence, while high body mass index, high symptom sensitivity, and poor health were associatedWith incident incontinent. Expand
Correlation-adjusted estimation of sensitivity and specificity of two diagnostic tests
Models for multiple-test screening data generally require the assumption that the tests are independent conditional on disease state. This assumption may be unreasonable, especially when theExpand
The Bayesian Two-Sample t Test
This article shows how the pooled-variance two-sample t statistic arises from a Bayesian formulation of the two-sided point null testing problem, with emphasis on teaching. We identify a reasonableExpand
Must psychologists change the way they analyze their data?
It is argued that Wagenmakers, Wetzels, Borsboom, and van der Maas have incorrectly selected an unrealistic prior distribution for their analysis and that a bayesian analysis using a more reasonable distribution yields strong evidence in favor of the psi hypothesis. Expand
Bayesian modeling of animal- and herd-level prevalences.
A new model is presented that can be used to estimate the herd-level prevalence in a region, including the posterior probability that all herds are non-infected, and inferences for the distribution of prevalences, mean prevalence in the region, and predicted prevalence of herds in the Region are made. Expand
Bayesian nonparametric nonproportional hazards survival modeling.
We develop a dependent Dirichlet process model for survival analysis data. A major feature of the proposed approach is that there is no necessity for resulting survival curve estimates to satisfy theExpand
Estimation of sensitivity and specificity of diagnostic tests and disease prevalence when the true disease state is unknown.
This paper reviews methods for estimation of the accuracy of a diagnostic test when an imperfect reference test with known classification errors is available and focuses on available methods of estimation of test characteristics when the sensitivity and specificity of both tests are unknown. Expand