Supplemental material
Open access
6,245
Views
18
CrossRef citations to date
0
Altmetric
Applications and Case Studies
Value of Information: Sensitivity Analysis and Research Design in Bayesian Evidence Synthesis
Christopher Jacksona MRC Biostatistics Unit, University of Cambridge, UK; Correspondence[email protected]
View further author information
, View further author information
Anne Presanisa MRC Biostatistics Unit, University of Cambridge, UK; View further author information
, Stefano Contib NHS England, Leeds, UKView further author information
& Daniela De Angelisa MRC Biostatistics Unit, University of Cambridge, UK; View further author information
Pages 1436-1449
|
Received 31 Aug 2017, Accepted 06 Dec 2018, Published online: 30 Apr 2019
Related Research Data
On a Measure of the Information Provided by an Experiment
Source:
The Institute of Mathematical Statistics
Estimation of HIV Burden through Bayesian Evidence Synthesis
Source:
Apollo - University of Cambridge Repository
A Nonparametric Regression Approach
Source:
SAGE Publications
Principles and Approaches
Source:
John Wiley & Sons, Ltd
An Efficient Estimator for the Expected Value of Sample Information.
Source:
SAGE Publications
A NOTE ON THE POWER PRIOR
Source:
Wiley
Bayesian Experimental Design: A Review
Source:
Institute of Mathematical Statistics
A Review of Modern Algorithms for Bayesian Design
Source:
Wiley
Value of Information: Sensitivity Analysis and Research Design in Bayesian Evidence Synthesis
Source:
Taylor & Francis
Cost-effectiveness of screening for HIV in primary care: a health economics modelling analysis
Source:
Elsevier
Bayesian Theory
Source:
John Wiley & Sons, Inc.
Multivariate Adaptive Regression Splines
Source:
Institute of Mathematical Statistics
Simulation-Based Confidence Intervals for Functions With Complicated Derivatives
Source:
Informa UK Limited
Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models
Source:
Elsevier BV
When Is a Model Good Enough? Deriving the Expected Value of Model Improvement via Specifying Internal Model Discrepancies
Source:
Society for Industrial and Applied Mathematics
Bayesian Theory
Source:
John Wiley & Sons, Inc.
Some Lessons from Recent UK Experience
Source:
Springer Science and Business Media LLC
Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates
Source:
Elsevier BV
Related research
People also read lists articles that other readers of this article have read.
Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.
Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.