Planning a method for covariate adjustment in individually randomised trials: a practical guide

• Main Authors: Morris, T.P (Author), Walker, A.S (Author), White, I.R (Author), Williamson, E.J (Author)
• Format: Article
• Language: English
• Published: BioMed Central Ltd 2022
• Subjects: Clinical trials; controlled study; Covariate adjustment; Estimands; human; Humans; Inverse probability of treatment weighting; methodology; Missing data; probability; Probability; Randomised controlled trials; randomized controlled trial; Research Design; sample size; Sample Size; Standardisation
• Online Access: View Fulltext in Publisher

 Background: It has long been advised to account for baseline covariates in the analysis of confirmatory randomised trials, with the main statistical justifications being that this increases power and, when a randomisation scheme balanced covariates, permits a valid estimate of experimental error. There are various methods available to account for covariates but it is not clear how to choose among them. Methods: Taking the perspective of writing a statistical analysis plan, we consider how to choose between the three most promising broad approaches: direct adjustment, standardisation and inverse-probability-of-treatment weighting. Results: The three approaches are similar in being asymptotically efficient, in losing efficiency with mis-specified covariate functions and in handling designed balance. If a marginal estimand is targeted (for example, a risk difference or survival difference), then direct adjustment should be avoided because it involves fitting non-standard models that are subject to convergence issues. Convergence is most likely with IPTW. Robust standard errors used by IPTW are anti-conservative at small sample sizes. All approaches can use similar methods to handle missing covariate data. With missing outcome data, each method has its own way to estimate a treatment effect in the all-randomised population. We illustrate some issues in a reanalysis of GetTested, a randomised trial designed to assess the effectiveness of an electonic sexually transmitted infection testing and results service. Conclusions: No single approach is always best: the choice will depend on the trial context. We encourage trialists to consider all three methods more routinely. © 2022, The Author(s).