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stat.ML2024
Causal machine learning for heterogeneous treatment effects in the presence of missing outcome data
Matthew Pryce, Karla Diaz-Ordaz, Ruth H. Keogh +1
When estimating heterogeneous treatment effects, missing outcome data can complicate treatment effect estimation, causing certain subgroups of the population to be poorly represent…
stat.ME2024★ 1 cited
Investigating the causal effects of multiple treatments using longitudinal data: a simulation study
Emily Granger, Gwyneth Davies, Ruth H. Keogh
Many clinical questions involve estimating the effects of multiple treatments using observational data. When using longitudinal data, the interest is often in the effect of treatme…