research
∙
08/30/2021
A Tutorial on Time-Dependent Cohort State-Transition Models in R using a Cost-Effectiveness Analysis Example
This tutorial shows how to implement time-dependent cohort state-transit...
share
research
∙
10/26/2020
BayCANN: Streamlining Bayesian Calibration with Artificial Neural Network Metamodeling
Purpose: Bayesian calibration is theoretically superior to standard dire...
research
∙
01/22/2020
Cohort state-transition models in R: From conceptualization to implementation
Decision models can synthesize evidence from different sources to provid...
research
∙
10/08/2019
Computing the Expected Value of Sample Information Efficiently: Expertise and Skills Required for Four Model-Based Methods
Objectives: Value of information (VOI) analyses can help policy-makers m...
research
∙
06/11/2019
Characterization and valuation of uncertainty of calibrated parameters in stochastic decision models
We evaluated the implications of different approaches to characterize un...
research
∙
05/28/2019
