1 citations · 1 across the 3 of their papers we have counts for
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A roadmap for systematic identification and analysis of multiple biases in causal inference
Rushani Wijesuriya, Rachael A. Hughes, John B. Carlin +3
Observational studies examining causal effects rely on unverifiable assumptions, the violation of which can induce multiple biases. Quantitative bias analysis (QBA) methods examine…
The ideal trial: defining causal estimands that balance relevance and feasibility in target trial emulations and actual randomized trials
Margarita Moreno-Betancur, Rushani Wijesuriya, John B. Carlin
Causal inference is the goal of randomized trials and many observational studies. The first step in a formal causal inference framework is to define the causal estimand, and in bot…
Multiple imputation for longitudinal data: A tutorial
Rushani Wijesuriya, Margarita Moreno-Betancur, John B Carlin +3
Longitudinal studies are frequently used in medical research and involve collecting repeated measures on individuals over time. Observations from the same individual are invariably…
Evaluation of approaches for accommodating interactions and non-linear terms in multiple imputation of incomplete three-level data
Rushani Wijesuriya, Margarita Moreno-Betancur, John B. Carlin +2
Three-level data structures arising from repeated measures on individuals clustered within larger units are common in health research studies. Missing data are prominent in such st…