Clinical trials disruption has always represented a non negligible part of the ending of interventional studies.
Applications
This article introduces the 50stateSimulations, a collection of simulated congressional districting plans and underlying code developed by the Algorithm-Assisted Redistricting Methodology (ALARM) Project.
Applications Computers and Society
We consider two-arm randomized controlled trials with a primary composite binary endpoint and an endpoint that consists only of the clinically more important component of the composite endpoint.
Methodology Applications
In this study, we aim to analyse the complex regulatory network that drives the formation of mature red blood cells and platelets from their common precursor.
Methodology
Neural demyelination and brain damage accumulated in white matter appear as hyperintense areas on MRI scans in the form of lesions.
Methodology Applications
Bayesian inference under a set of priors, called robust Bayesian analysis, allows for estimation of parameters within a model and quantification of epistemic uncertainty in quantities of interest by bounded (or imprecise) probability.
Computation Methodology 62L20 (Primary), 62P12 (Secondary) G.3
We provide a tight oracle inequality, proving that our method is adaptive to the rank of the coefficient matrix.
Methodology Statistics Theory Computation Statistics Theory
This is recognised in practice in the sense that results from different models are often considered, and sometimes combined.
Methodology Risk Management Applications 91G70, 91G60, 62P05, 91B30
Deterministic compartmental models are predominantly used in the modeling of infectious diseases, though stochastic models are considered more realistic, yet are complicated to estimate due to missing data.
Computation Applications Methodology
The paper presents a new perspective on the mixture of Dirichlet process model which allows the recovery of full and correct uncertainty quantification associated with the full model, even after having integrated out the random distribution function.
Computation
