500 citations · 559 across the 13 of their papers we have counts for
14 papers
Estimating hypothetical estimands with causal inference and missing data estimators in a diabetes trial
Camila Olarte Parra, Rhian M. Daniel, David Wright +1
The recently published ICH E9 addendum on estimands in clinical trials provides a framework for precisely defining the treatment effect that is to be estimated, but says little abo…
G-formula for causal inference via multiple imputation
Jonathan W. Bartlett, Camila Olarte Parra, Emily Granger +3
G-formula is a popular approach for estimating treatment or exposure effects from longitudinal data that are subject to time-varying confounding. G-formula estimation is typically…
Standard and reference-based conditional mean imputation
Marcel Wolbers, Alessandro Noci, Paul Delmar +3
Clinical trials with longitudinal outcomes typically include missing data due to missed assessments or structural missingness of outcomes after intercurrent events handled with a h…
Hypothetical estimands in clinical trials: a unification of causal inference and missing data methods
Camila Olarte Parra, Rhian M. Daniel, Jonathan W. Bartlett
The ICH E9 addendum introduces the term intercurrent event to refer to events that happen after randomisation and that can either preclude observation of the outcome of interest or…
Reference based multiple imputation -- what is the right variance and how to estimate it
Jonathan W. Bartlett
Reference based multiple imputation methods have become popular for handling missing data in randomised clinical trials. Rubin's variance estimator is well known to be biased compa…
Bootstrap Inference for Multiple Imputation under Uncongeniality and Misspecification
Jonathan W. Bartlett, Rachael A. Hughes
Multiple imputation has become one of the most popular approaches for handling missing data in statistical analyses. Part of this success is due to Rubin's simple combination rules…