ArticleStatistical methods in medical research2026
What is estimated in cluster randomized crossover trials with informative sizes? A survey of estimands and common estimators.
Article in Statistical methods in medical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- CRT-Estimands Framework: consensus based extension of the ICH E9(R1) addendum for cluster randomised trials.BMJ (Clinical research ed.) · 2026Article
- Model-robust standardization in stepped wedge cluster randomized trials.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2026Article
- Analysis of Stepped-Wedge Cluster Randomized Trials When Treatment Effects Vary by Exposure Time or Calendar Time.Statistics in medicine · 2025Article
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Authors and funding
8 authors.
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Abstract
The cluster randomized crossover (CRXO) trial, among other multi-period cluster randomized trial designs, can target average treatment effect (ATE) estimands that equally weigh the contributions of individuals (iATE), clusters (cATE), cluster-periods (cpATE), or periods (pATE). With these weighted ATE estimands, we define different forms of informative sizes, where the treatment effects vary according to cluster, period, and/or cluster-period sizes, causing these estimands to differ. Under such informative sizes, we survey which of the unweighted, inverse cluster-period size weighted, inverse cluster size weighted, and inverse period size weighted: (i) independence estimating equation, (ii) fixed effects model, (iii) exchangeable mixed effects model, and (iv) nested exchangeable mixed effects model treatment effect estimators are consistent for the aforementioned estimands in cross-sectional CRXO designs with continuous outcomes. We demonstrate that with informative sizes, the unweighted and weighted nested exchangeable mixed effects model estimators are not consistent for any meaningful estimand and can yield biased results. In contrast, the unweighted and weighted independence estimating equation, and under specific scenarios, the fixed effects model and exchangeable mixed effects model, can yield consistent and empirically unbiased estimators for meaningful estimands in CRXO trials.
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