UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Sensitivity analysis for clinical trials with missing continuous outcome data using controlled multiple imputation: A practical guide

Cro, S; Morris, TP; Kenward, MG; Carpenter, JR; (2020) Sensitivity analysis for clinical trials with missing continuous outcome data using controlled multiple imputation: A practical guide. Statistics in Medicine 10.1002/sim.8569. (In press). Green open access

[thumbnail of 2020 - Cro - sensitivity analysis using controlled MI tutorial - stat med.pdf]
Preview
Text
2020 - Cro - sensitivity analysis using controlled MI tutorial - stat med.pdf - Published Version

Download (2MB) | Preview

Abstract

Missing data due to loss to follow-up or intercurrent events are unintended, but unfortunately inevitable in clinical trials. Since the true values of missing data are never known, it is necessary to assess the impact of untestable and unavoidable assumptions about any unobserved data in sensitivity analysis. This tutorial provides an overview of controlled multiple imputation (MI) techniques and a practical guide to their use for sensitivity analysis of trials with missing continuous outcome data. These include δ- and reference-based MI procedures. In δ-based imputation, an offset term, δ, is typically added to the expected value of the missing data to assess the impact of unobserved participants having a worse or better response than those observed. Reference-based imputation draws imputed values with some reference to observed data in other groups of the trial, typically in other treatment arms. We illustrate the accessibility of these methods using data from a pediatric eczema trial and a chronic headache trial and provide Stata code to facilitate adoption. We discuss issues surrounding the choice of δ in δ-based sensitivity analysis. We also review the debate on variance estimation within reference-based analysis and justify the use of Rubin's variance estimator in this setting, since as we further elaborate on within, it provides information anchored inference.

Type: Article
Title: Sensitivity analysis for clinical trials with missing continuous outcome data using controlled multiple imputation: A practical guide
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/sim.8569
Publisher version: https://doi.org/10.1002/sim.8569
Language: English
Additional information: This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Keywords: Clinical trials, controlled multiple imputation, missing data, multiple imputation, sensitivity analysis
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10097758
Downloads since deposit
103Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item