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In this work we apply the methodology of integral priors to handle Bayesian model selection in binomial regression models with a general link function. These models are very often used to investigate associations and risks in…

Methodology · Statistics 2013-07-01 Diego Salmeron , Juan Antonio Cano , C. P. Robert

Accurate estimates of the under-5 mortality rate (U5MR) in a developing world context are a key barometer of the health of a nation. This paper describes new models to analyze survey data on mortality in this context. We are interested in…

Meta-analyses in orphan diseases and small populations generally face particular problems including small numbers of studies, small study sizes, and heterogeneity of results. However, the heterogeneity is difficult to estimate if only very…

Methodology · Statistics 2018-09-11 Tim Friede , Christian Röver , Simon Wandel , Beat Neuenschwander

Reports from the Health Department in the Philippines show that cases of Human Immunodeficiency Virus (HIV) are increasing despite management and control efforts by the government. Worldwide, the Philippines has one of the fastest growing…

Applications · Statistics 2019-11-14 Analaine May A. Tatoy , Roel F. Ceballos

The two-phase sampling design is a cost-effective strategy widely used in public health research. Analyzing the Phase II sample often involves creating subsample-specific weights. However, these weights can be highly variable, leading to…

Methodology · Statistics 2026-04-07 Xinru Wang , Anyu Zhu , Lauren Kennedy , Abigail Greenleaf , Qixuan Chen

This article introduces epidemia, an R package for Bayesian, regression-oriented modeling of infectious diseases. The implemented models define a likelihood for all observed data while also explicitly modeling transmission dynamics: an…

HIV pre-exposure Prophylaxis (PrEP) has become essential for global HIV control, but its implementation coincides with rising bacterial STI rates among men who have sex with men (MSM). While risk-compensation behavioral changes like reduced…

Expectation Propagation (Minka, 2001) is a widely successful algorithm for variational inference. EP is an iterative algorithm used to approximate complicated distributions, typically to find a Gaussian approximation of posterior…

Computation · Statistics 2016-04-01 Guillaume Dehaene , Simon Barthelmé

While Gaussian probability densities are omnipresent in applied mathematics, Gaussian cumulative probabilities are hard to calculate in any but the univariate case. We study the utility of Expectation Propagation (EP) as an approximate…

Machine Learning · Statistics 2013-12-02 John P. Cunningham , Philipp Hennig , Simon Lacoste-Julien

Bayesian estimation is increasingly popular for performing model based inference to support policymaking. These data are often collected from surveys under informative sampling designs where subject inclusion probabilities are designed to…

Methodology · Statistics 2018-07-13 Luis G. Leon-Novelo , Terrance D. Savitsky

A prediction interval covers a future observation from a random process in repeated sampling, and is typically constructed by identifying a pivotal quantity that is also an ancillary statistic. Analogously, a tolerance interval covers a…

Methodology · Statistics 2022-01-19 Geoffrey S Johnson

Dynamic models have been successfully used in producing estimates of HIV epidemics at national level, due to their epidemiological nature and their ability to simultaneously estimate prevalence, incidence, and mortality rates. Recently, HIV…

Methodology · Statistics 2016-02-19 Le Bao , Ben Sheng , Xiaoyue Niu , Yuan Tang , Tim Brown , Peter D. Ghys , Jeff W. Eaton

Bayesian predictive probabilities of success (PPoS) use interim trial data to calculate the probability of trial success. These quantities can be used to optimize trial size or to stop for futility. In this paper, we describe a…

In small area estimation, it is sometimes necessary to use model-based methods to produce estimates in areas with little or no data. In official statistics, we often require that some aggregate of small area estimates agree with a national…

Methodology · Statistics 2023-01-31 Taylor Okonek , Jon Wakefield

Existing methods to estimate the prevalence of chronic hepatitis C (HCV) in New York City (NYC) are limited in scope and fail to assess hard-to-reach subpopulations with highest risk such as injecting drug users (IDUs). To address these…

Applications · Statistics 2018-01-16 Sarah Tan , Susanna Makela , Daliah Heller , Kevin Konty , Sharon Balter , Tian Zheng , James H. Stark

In stopping the spread of infectious diseases, pathogen genomic data can be used to reconstruct transmission events and characterize population-level sources of infection. Most approaches for identifying transmission pairs do not account…

Purpose: The use of cumulative measures of exposure to raised HIV viral load (viremia copy-years) is an increasingly common in HIV prevention and treatment epidemiology due to the high biological plausibility. We sought to estimate the…

Applications · Statistics 2019-05-10 Maia Lesosky , Tracy Glass , Brian Rambau , Nei-Yuan Hsiao , Elaine J Abrams , Landon Myer

Parameter estimates for associated genetic variants, report ed in the initial discovery samples, are often grossly inflated compared to the values observed in the follow-up replication samples. This type of bias is a consequence of the…

Applications · Statistics 2011-04-15 Lizhen Xu , Radu V. Craiu , Lei Sun

When surveillance data of infectious disease incidence (e.g. weekly case counts) are disaggregated by demographic indicators, disparities in long-run health outcomes between these groups become apparent. Accurate identification of high-risk…

Methodology · Statistics 2026-05-29 Miles Moran , Rob Trangucci , Lisa Madsen

Sexual contacts are the main spreading route of HIV. This puts sex workers at higher risk of infection even in populations where HIV prevalence is moderate or low. Alongside condom use, Pre-Exposure Prophylaxis (PrEP) is an effective tool…

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