65 citations · 284 across the 34 of their papers we have counts for
35 papers
Bayesian Interrupted Time Series for evaluating policy change on mental well-being: an application to England's welfare reform
Connor Gascoigne, Marta Blangiardo, Zejing Shao +4
Factors contributing to social inequalities are also associated with negative mental health outcomes leading to disparities in mental well-being. We propose a Bayesian hierarchical…
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…
Counterfactual Learning with Multioutput Deep Kernels
Alberto Caron, Gianluca Baio, Ioanna Manolopoulou
In this paper, we address the challenge of performing counterfactual inference with observational data via Bayesian nonparametric regression adjustment, with a focus on high-dimens…
Interpretable Deep Causal Learning for Moderation Effects
Alberto Caron, Gianluca Baio, Ioanna Manolopoulou
In this extended abstract paper, we address the problem of interpretability and targeted regularization in causal machine learning models. In particular, we focus on the problem of…
A Bayesian hierarchical model for improving exercise rehabilitation in mechanically ventilated ICU patients
Luke Hardcastle, Samuel Livingstone, Claire Black +2
Patients who are mechanically ventilated in the intensive care unit (ICU) participate in exercise as a component of their rehabilitation to ameliorate the long-term impact of criti…