65 citations · 252 across the 18 of their papers we have counts for
19 papers
Calculating the Expected Value of Sample Information for Observational Studies affected by Confounding
Luca Benetti, Gianluca Baio, Anna Heath
Background: The Expected Value of Sample Information (EVSI) quantifies the value of collecting additional evidence to inform a health economic model. Existing EVSI methods typicall…
Calculating the Expected Value of Sample Information accounting for missing data
Luca Benetti, Gianluca Baio, Anna Heath
The Expected Value of Sample Information (EVSI) is a powerful instrument to determine the value of additional evidence to inform an economic model. However, EVSI has been applied o…
Methodological considerations for novel approaches to covariate-adjusted indirect treatment comparisons
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
We examine four important considerations in the development of covariate adjustment methodologies for indirect treatment comparisons. Firstly, we consider potential advantages of w…
Model-based standardization using multiple imputation
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
When studying the association between treatment and a clinical outcome, a parametric multivariable model of the conditional outcome expectation is often used to adjust for covariat…
Designing a Bayesian adaptive clinical trial to evaluate novel mechanical ventilation strategies in acute respiratory failure using Integrated Nested Laplace Approximations
Reyhaneh Hosseini, Ziming Chen, Ewan Goligher +7
Background: We aimed to design a Bayesian adaption trial through extensive simulations to determine values for key design parameters, demonstrate error rates, and establish the exp…
BCEA: An R Package for Cost-Effectiveness Analysis
Nathan Green, Anna Heath, Gianluca Baio
We describe in detail how to perform health economic cost-effectiveness analyses (CEA) using the R package (Bayesian Cost-Effectiveness Analysis). CEA consist of an…
Parametric G-computation for Compatible Indirect Treatment Comparisons with Limited Individual Patient Data
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
Population adjustment methods such as matching-adjusted indirect comparison (MAIC) are increasingly used to compare marginal treatment effects when there are cross-trial difference…
Calculating Expected Value of Sample Information Adjusting for Imperfect Implementation
Anna Heath
Background: The Expected Value of Sample Information (EVSI) calculates the value of collecting additional information through a study with a given design. Standard EVSI analyses as…
Conflating marginal and conditional treatment effects: Comments on 'Assessing the performance of population adjustment methods for anchored indirect comparisons: A simulation study'
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
In this commentary, we highlight the importance of: (1) carefully considering and clarifying whether a marginal or conditional treatment effect is of interest in a population-adjus…
Effect modification in anchored indirect treatment comparisons: Comments on "Matching-adjusted indirect comparisons: Application to time-to-event data"
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
This commentary regards a recent simulation study conducted by Aouni, Gaudel-Dedieu and Sebastien, evaluating the performance of different versions of matching-adjusted indirect co…
Marginalization of Regression-Adjusted Treatment Effects in Indirect Comparisons with Limited Patient-Level Data
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
Population adjustment methods such as matching-adjusted indirect comparison (MAIC) are increasingly used to compare marginal treatment effects when there are cross-trial difference…
A Bayesian response-adaptive dose finding and comparative effectiveness trial
Anna Heath, Maryna Yaskina, Petros Pechlivanoglou +5
Aims: Combinations of treatments can offer additional benefit over the treatments individually. However, trials of these combinations are lower priority than the development of nov…
Methods for Population Adjustment with Limited Access to Individual Patient Data: A Review and Simulation Study
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
Population-adjusted indirect comparisons estimate treatment effects when access to individual patient data is limited and there are cross-trial differences in effect modifiers. Pop…
Computing the Expected Value of Sample Information Efficiently: Expertise and Skills Required for Four Model-Based Methods
Natalia R. Kunst, Edward Wilson, Fernando Alarid-Escudero +11
Objectives: Value of information (VOI) analyses can help policy-makers make informed decisions about whether to conduct and how to design future studies. Historically, a computatio…
Calculating the Expected Value of Sample Information in Practice: Considerations from Three Case Studies
Anna Heath, Natalia R. Kunst, Christopher Jackson +6
Investing efficiently in future research to improve policy decisions is an important goal. Expected Value of Sample Information (EVSI) can be used to select the specific design and…
Estimating the Expected Value of Sample Information across Different Sample Sizes using Moment Matching and Non-Linear Regression
Anna Heath, Ioanna Manolopoulou, Gianluca Baio
Background: The Expected Value of Sample Information (EVSI) determines the economic value of any future study with a specific design aimed at reducing uncertainty in a health econo…
Calculating the Expected Value of Sample Information using Efficient Nested Monte Carlo: A Tutorial
Anna Heath, Gianluca Baio
Objective: The Expected Value of Sample Information (EVSI) quantifies the economic benefit of reducing uncertainty in a health economic model by collecting additional information.…
Efficient Monte Carlo Estimation of the Expected Value of Sample Information using Moment Matching
Anna Heath, Ioanna Manolopoulou, Gianluca Baio
The Expected Value of Sample Information (EVSI) is used to calculate the economic value of a new research strategy. While this value would be important to both researchers and fund…
Estimating the Expected Value of Partial Perfect Information in Health Economic Evaluations using Integrated Nested Laplace Approximation
Anna Heath, Ioanna Manolopoulou, Gianluca Baio
The Expected Value of Perfect Partial Information (EVPPI) is a decision-theoretic measure of the "cost" of parametric uncertainty in decision making used principally in health econ…