activity
20192022
most citedA comparison of strategies for selecting auxiliary variables for multiple imputation

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

stat.ME2022

Evaluation of multiple imputation to address intended and unintended missing data in case-cohort studies with a binary endpoint

Melissa Middleton, Cattram Nguyen, John B. Carlin +2

Case-cohort studies are conducted within cohort studies, wherein collection of exposure data is limited to a subset of the cohort, leading to a large proportion of missing data by…

stat.ME20221 cited

A comparison of strategies for selecting auxiliary variables for multiple imputation

Rheanna M. Mainzer, Cattram D. Nguyen, John B. Carlin +3

Multiple imputation (MI) is a popular method for handling missing data. Auxiliary variables can be added to the imputation model(s) to improve MI estimates. However, the choice of…

stat.ME2020

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…

stat.ME2019

Mediation effects that emulate a target randomised trial: Simulation-based evaluation of ill-defined interventions on multiple mediators

Margarita Moreno-Betancur, Paul Moran, Denise Becker +2

Many epidemiological questions concern potential interventions to alter the pathways presumed to mediate an association. For example, we consider a study that investigates the bene…