468 citations · 586 across the 10 of their papers we have counts for
10 papers
Recoverability of Causal Effects under Presence of Missing Data: a Longitudinal Case Study
Anastasiia Holovchak, Helen McIlleron, Paolo Denti +1
Missing data in multiple variables is a common issue. We investigate the applicability of the framework of graphical models for handling missing data to a complex longitudinal phar…
Causal Fair Machine Learning via Rank-Preserving Interventional Distributions
Ludwig Bothmann, Susanne Dandl, Michael Schomaker
A decision can be defined as fair if equal individuals are treated equally and unequals unequally. Adopting this definition, the task of designing machine learning (ML) models that…
Causal Inference for Continuous Multiple Time Point Interventions
Michael Schomaker, Helen McIlleron, Paolo Denti +1
There are limited options to estimate the treatment effects of variables which are continuous and measured at multiple time points, particularly if the true dose-response curve sho…
The Delta-Method and Influence Function in Medical Statistics: a Reproducible Tutorial
Rodrigo Zepeda-Tello, Michael Schomaker, Camille Maringe +5
Approximate statistical inference via determination of the asymptotic distribution of a statistic is routinely used for inference in applied medical statistics (e.g. to estimate th…
Regression and Causality
Michael Schomaker
The causal effect of an intervention (treatment/exposure) on an outcome can be estimated by: i) specifying knowledge about the data-generating process; ii) assessing under what ass…
Estimating the Effect of Central Bank Independence on Inflation Using Longitudinal Targeted Maximum Likelihood Estimation
Philipp F. M. Baumann, Michael Schomaker, Enzo Rossi
The notion that an independent central bank reduces a country's inflation is a controversial hypothesis. To date, it has not been possible to satisfactorily answer this question be…