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

Handling misclassified stratification variables in the analysis of randomised trials with continuous outcomes

Yelland, Lisa N; Louise, Jennie; Kahan, Brennan C; Morris, Tim P; Lee, Katherine J; Sullivan, Thomas R; (2023) Handling misclassified stratification variables in the analysis of randomised trials with continuous outcomes. Statistics in Medicine 10.1002/sim.9818. (In press). Green open access

[thumbnail of Handling misclassified stratification variables.pdf]
Preview
PDF
Handling misclassified stratification variables.pdf - Published Version

Download (1MB) | Preview

Abstract

Many trials use stratified randomisation, where participants are randomised within strata defined by one or more baseline covariates. While it is important to adjust for stratification variables in the analysis, the appropriate method of adjustment is unclear when stratification variables are affected by misclassification and hence some participants are randomised in the incorrect stratum. We conducted a simulation study to compare methods of adjusting for stratification variables affected by misclassification in the analysis of continuous outcomes when all or only some stratification errors are discovered, and when the treatment effect or treatment-by-covariate interaction effect is of interest. The data were analysed using linear regression with no adjustment, adjustment for the strata used to perform the randomisation (randomisation strata), adjustment for the strata if all errors are corrected (true strata), and adjustment for the strata after some errors are discovered and corrected (updated strata). The unadjusted model performed poorly in all settings. Adjusting for the true strata was optimal, while the relative performance of adjusting for the randomisation strata or the updated strata varied depending on the setting. As the true strata are unlikely to be known with certainty in practice, we recommend using the updated strata for adjustment and performing subgroup analyses, provided the discovery of errors is unlikely to depend on treatment group, as expected in blinded trials. Greater transparency is needed in the reporting of stratification errors and how they were addressed in the analysis.

Type: Article
Title: Handling misclassified stratification variables in the analysis of randomised trials with continuous outcomes
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/sim.9818
Publisher version: https://doi.org/10.1002/sim.9818
Language: English
Additional information: © 2023 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/).
Keywords: covariate misclassification, covariate-adaptive randomisation, randomisation error, stratification error, stratified randomisation
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/10172635
Downloads since deposit
23Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item