Spatially-dependent Bayesian model selection for disease mapping
نویسندگان
چکیده
منابع مشابه
Bayesian Melding of Deterministic Models and Kriging for Analysis of Spatially Dependent Data
The link between geographic information systems and decision making approach own the invention and development of spatial data melding method. These methods combine different data sets, to achieve better results. In this paper, the Bayesian melding method for combining the measurements and outputs of deterministic models and kriging are considered. Then the ozone data in Tehran city are analyze...
متن کاملBayesian variable selection for multivariate spatially varying coefficient regression.
Physical activity has many well-documented health benefits for cardiovascular fitness and weight control. For pregnant women, the American College of Obstetricians and Gynecologists currently recommends 30 minutes of moderate exercise on most, if not all, days; however, very few pregnant women achieve this level of activity. Traditionally, studies have focused on examining individual or interpe...
متن کاملA Bayesian Integrative Model for Genetical Genomics with Spatially Informed Variable Selection
We consider a Bayesian hierarchical model for the integration of gene expression levels with comparative genomic hybridization (CGH) array measurements collected on the same subjects. The approach defines a measurement error model that relates the gene expression levels to latent copy number states. In turn, the latent states are related to the observed surrogate CGH measurements via a hidden M...
متن کاملDisease Mapping with Spatially Uncertain Data
Objective Uncertainty regarding the location of disease acquisition, as well as selective identification of cases, may bias maps of risk. We propose an extension to a distance-based mapping method (DBM) that incorporates weighted locations to adjust for these biases. We demonstrate this method by mapping potential drug-resistant tuberculosis (DRTB) transmission hotspots using programmatic data ...
متن کاملBayesian Model Selection
Traditionally, Bayes factors, posterior odds and posterior model probabilities are used in Bayesian model selection. This approach has, however, the problem that the conclusions are often too sensitive to prior specifications. Another approach is to use discrepancy measures in model comparison and posterior predictive checks in the assesment of model adequecy. These approaches are briefly summa...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistical Methods in Medical Research
سال: 2016
ISSN: 0962-2802,1477-0334
DOI: 10.1177/0962280215627298