ArticleStatistics in medicine2024
Planning stepped wedge cluster randomized trials to detect treatment effect heterogeneity.
Article in Statistics in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 5 citations in OpenAlex.
- The design of embedded pragmatic clinical trials: methodological developments and statistical lessons learned from the first cycle of the NIA IMPACT collaboratory.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Model-robust standardization in stepped wedge cluster randomized trials.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2026Article
- A tutorial on conducting sample size and power calculations for detecting treatment effect heterogeneity in cluster randomized trials with linear mixed models.International journal of epidemiology · 2026Article
- Group Sequential Design and Monitoring of Clustered Data in Randomized Eye Trials.Statistics in biopharmaceutical research · 2025Article
- Designing Stepped Wedge Cluster Randomized Trials With a Baseline Measurement of the Outcome.Statistics in medicine · 2025Article
- Permutation tests for detecting treatment effect heterogeneity in cluster randomized trials.Statistical methods in medical research · 2025Article
- Sample size and power calculation for testing treatment effect heterogeneity in cluster randomized crossover designs.Statistical methods in medical research · 2024Article
Corrections and comments
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Authors and funding
5 authors at 5 institutions in 1 country.
Funding
Abstract
Stepped wedge design is a popular research design that enables a rigorous evaluation of candidate interventions by using a staggered cluster randomization strategy. While analytical methods were developed for designing stepped wedge trials, the prior focus has been solely on testing for the average treatment effect. With a growing interest on formal evaluation of the heterogeneity of treatment effects across patient subpopulations, trial planning efforts need appropriate methods to accurately identify sample sizes or design configurations that can generate evidence for both the average treatment effect and variations in subgroup treatment effects. To fill in that important gap, this article derives novel variance formulas for confirmatory analyses of treatment effect heterogeneity, that are applicable to both cross-sectional and closed-cohort stepped wedge designs. We additionally point out that the same framework can be used for more efficient average treatment effect analyses via covariate adjustment, and allows the use of familiar power formulas for average treatment effect analyses to proceed. Our results further sheds light on optimal design allocations of clusters to maximize the weighted precision for assessing both the average and heterogeneous treatment effects. We apply the new methods to the Lumbar Imaging with Reporting of Epidemiology Trial, and carry out a simulation study to validate our new methods.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.