This is a preview. Log in through your library . Abstract Log-linear models have been shown to be useful for smoothing contingency tables when categorical outcomes are subject to nonignorable ...

BhGLM is a freely available R package that implements Bayesian hierarchical modeling for high-dimensional clinical and genomic data. It consists of functions for setting up various Bayesian ...

Here’s our estimate of public support for vouchers, broken down by religion/ethnicity, income, and state: (Click on image to see larger version.) We’re mapping estimates from a hierarchical Bayes ...

The Annals of Applied Statistics, Vol. 15, No. 1 (March 2021), pp. 391-411 (21 pages) Gene expression deconvolution is a powerful tool for exploring the microenvironment of complex tissues comprised ...

We present a spatial Bayesian hierarchical model for seasonal extreme precipitation. At the first level of hierarchy, the seasonal maximum precipitation (i.e. block maxima) at any location is assumed ...

A Bayesian hierarchical model was developed to estimate the parameters in a physiologically based pharmacokinetic (PBPK) model for chloroform using prior information and biomarker data from different ...

We adapt a semi-Bayesian hierarchical modeling framework to jointly characterize the space–time variability of seasonal precipitation totals and precipitation extremes across the Northern Great Plains ...

Predisposition to a disease is usually caused by cumulative effects of a multitude of exposures and lifestyle factors in combination with individual susceptibility. Failure to include all relevant ...

Cobimetinib Plus Vemurafenib in Patients With Colorectal Cancer With BRAF Mutations: Results From the Targeted Agent and Profiling Utilization Registry (TAPUR) Study We divided the borrowing ...