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06/27/2023
Bayesian Interrupted Time Series for evaluating policy change on mental well-being: an application to England's welfare reform
Factors contributing to social inequalities are also associated with neg...
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05/15/2023
Methodological considerations for novel approaches to covariate-adjusted indirect treatment comparisons
We examine four important considerations in the development of covariate...
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05/15/2023
Model-based standardization using multiple imputation
When studying the association between treatment and a clinical outcome, ...
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11/20/2022
Counterfactual Learning with Multioutput Deep Kernels
In this paper, we address the challenge of performing counterfactual inf...
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06/28/2022
A Bayesian hierarchical model for improving exercise rehabilitation in mechanically ventilated ICU patients
Patients who are mechanically ventilated in the intensive care unit (ICU...
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06/21/2022
Interpretable Deep Causal Learning for Moderation Effects
In this extended abstract paper, we address the problem of interpretabil...
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06/01/2022
Blended Survival Curves: A New Approach to Extrapolation for Time-to-Event Outcomes from Clinical Trial in Health Technology Assessment
Background Survival extrapolation is essential in the cost-effectiveness...
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03/18/2022
BCEA: An R Package for Cost-Effectiveness Analysis
We describe in detail how to perform health economic cost-effectiveness ...
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01/17/2022
A framework for estimating and visualising excess mortality during the COVID-19 pandemic
COVID-19 related deaths underestimate the pandemic burden on mortality b...
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08/27/2021
Parametric G-computation for Compatible Indirect Treatment Comparisons with Limited Individual Patient Data
Population adjustment methods such as matching-adjusted indirect compari...
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02/12/2021
Sparse Bayesian Causal Forests for Heterogeneous Treatment Effects Estimation
This paper develops a sparsity-inducing version of Bayesian Causal Fores...
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12/09/2020
Principled selection of effect modifiers: Comments on 'Matching-adjusted indirect comparisons: Application to time-to-event data'
In this commentary, we raise our concerns about a recent simulation stud...
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11/12/2020
Conflating marginal and conditional treatment effects: Comments on 'Assessing the performance of population adjustment methods for anchored indirect comparisons: A simulation s
In this commentary, we highlight the importance of: (1) carefully consid...
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09/14/2020
Estimating Individual Treatment Effects using Non-Parametric Regression Models: a Review
Large observational data are increasingly available in disciplines such ...
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08/12/2020
Predictive-Adjusted Indirect Comparison: A Novel Method for Population Adjustment with Limited Access to Patient-Level Data
Population adjustment methods such as matching-adjusted indirect compari...
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04/30/2020
Methods for Population Adjustment with Limited Access to Individual Patient Data: A Simulation Study
Population-adjusted indirect comparisons are used to estimate treatment ...
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03/26/2020
Dirichlet Process Mixture Models for Regression Discontinuity Designs
The Regression Discontinuity Design (RDD) is a quasi-experimental design...
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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...
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05/28/2019
Calculating the Expected Value of Sample Information in Practice: Considerations from Three Case Studies
Investing efficiently in future research to improve policy decisions is ...
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07/04/2018
Modeling outcomes of soccer matches
We compare various extensions of the Bradley-Terry model and a hierarchi...
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05/18/2018
Pitfalls of adjusting for mean baseline utilities/costs in trial-based cost-effectiveness analysis with missing data
Failure to account for baseline utilities/costs imbalance between treatm...
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05/18/2018
A Bayesian Parametric Approach to Handle Missing Longitudinal Outcome Data in Trial-Based Health Economic Evaluations
Trial-based economic evaluations are typically performed on cross-sectio...
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04/25/2018
Estimating the Expected Value of Sample Information across Different Sample Sizes using Moment Matching and Non-Linear Regression
Background: The Expected Value of Sample Information (EVSI) determines t...
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01/29/2018
