Open Access. Powered by Scholars. Published by Universities.®
Other Statistics and Probability Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Other Statistics and Probability
Estimating The Prevalence Of Two Or More Diseases Using Outcomes From Multiplex Group Testing, Md S. Warasi, Joshua M. Tebbs, Christopher S. Mcmahan, Christopher R. Bilder
Estimating The Prevalence Of Two Or More Diseases Using Outcomes From Multiplex Group Testing, Md S. Warasi, Joshua M. Tebbs, Christopher S. Mcmahan, Christopher R. Bilder
Department of Statistics: Faculty Publications
When screening a population for infectious diseases, pooling individual specimens (e.g., blood, swabs, urine, etc.) can provide enormous cost savings when compared to testing specimens individually. In the biostatistics literature, testing pools of specimens is commonly known as group testing or pooled testing. Although estimating a population-level prevalence with group testing data has received a large amount of attention, most of this work has focused on applications involving a single disease, such as human immunodeficiency virus. Modern methods of screening now involve testing pools and individuals for multiple diseases simultaneously through the use of multiplex assays. Hou et al. (2017, …
A Genomic Bayesian Multi-Trait And Multi-Environment Model, Osval A. Montesinos-López, Abelardo Montesinos-López, José Crossa, Fernando Toledo, Oscar Pérez-Hernández, Kent M. Eskridge, Jessica Rutkoski
A Genomic Bayesian Multi-Trait And Multi-Environment Model, Osval A. Montesinos-López, Abelardo Montesinos-López, José Crossa, Fernando Toledo, Oscar Pérez-Hernández, Kent M. Eskridge, Jessica Rutkoski
Department of Statistics: Faculty Publications
When information on multiple genotypes evaluated in multiple environments is recorded, a multi-environment single trait model for assessing genotype × environment interaction (G×E) is usually employed. Comprehensive models that simultaneously take into account the correlated traits and trait × genotype × environment interaction (T×G×E) are lacking. In this research, we propose a Bayesian model for analyzing multiple traits and multiple environments for whole-genome prediction (WGP) model. For this model, we used Half-𝑡 priors on each standard deviation term and uniform priors on each correlation of the covariance matrix. These priors were not informative and led to posterior inferences that were …