500 citations · 735 across the 9 of their papers we have counts for
11 papers
Multiple imputation of partially observed data after treatment-withdrawal
Suzie Cro, James H Roger, James R Carpenter
The ICH E9(R1) Addendum (International Council for Harmonization 2019) suggests treatment-policy as one of several strategies for addressing intercurrent events such as treatment w…
Framework for the Treatment And Reporting of Missing data in Observational Studies: The TARMOS framework
Katherine J Lee, Kate Tilling, Rosie P Cornish +5
Missing data are ubiquitous in medical research. Although there is increasing guidance on how to handle missing data, practice is changing slowly and misapprehensions abound, parti…
A review and evaluation of standard methods to handle missing data on time-varying confounders in marginal structural models
Clemence Leyrat, James R Carpenter, Sebastien Bailly +1
Marginal structural models (MSMs) are commonly used to estimate causal intervention effects in longitudinal non-randomised studies. A common issue when analysing data from observat…
Propensity scores using missingness pattern information: a practical guide
Helen A. Blake, Clemence Leyrat, Kathryn E. Mansfield +4
Electronic health records are a valuable data source for investigating health-related questions, and propensity score analysis has become an increasingly popular approach to addres…
Local average treatment effects estimation via substantive model compatible multiple imputation
Karla DiazOrdaz, James Carpenter
Non-adherence to assigned treatment is common in randomised controlled trials (RCTs). Recently, there has been an increased interest in estimating causal effects of treatment recei…
Information-Anchored Sensitivity Analysis: Theory and Application
Suzie Cro, James R Carpenter, Michael G Kenward
Analysis of longitudinal randomised controlled trials is frequently complicated because patients deviate from the protocol. Where such deviations are relevant for the estimand, we…