ArticleBiostatistics (Oxford, England)2022
Marginal modeling of cluster-period means and intraclass correlations in stepped wedge designs with binary outcomes.
Article in Biostatistics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed, 36 citations in OpenAlex.
- Evaluation of the type I error rate when using parametric bootstrap analysis of a cluster randomized controlled trial with binary outcomes and a small number of clusters.Computer methods and programs in biomedicine · 2022Trial
- From waste to resource: development of selenium-enhanced iron-carbon galvanic materials from landfill leachate for efficient mercury and thallium detoxification in contaminated waters.Journal of advanced research · 2026Article
- Finite-Sample Adjustments in Estimating Equations for Correlated Overdispersed Count Outcomes With Application to Cluster Randomized Trials.Statistics in medicine · 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: A Tutorial Using Marginal Models.Statistics in medicine · 2026Article
- Network generalized estimating equations for complexly correlated data with applications to cluster randomized trials.Biostatistics (Oxford, England) · 2025Article
- Power calculation for cross-sectional stepped wedge cluster randomized trials with a time-to-event endpoint.Biometrics · 2025Article
- Analysis of Cohort Stepped Wedge Cluster-Randomized Trials With Nonignorable Dropout via Joint Modeling.Statistics in medicine · 2025Article
- A review of current practice in the design and analysis of extremely small stepped-wedge cluster randomized trials.Clinical trials (London, England) · 2025Review
- Clinical significance of glomerular IgM deposit in IgA nephropathy: a 5-year follow-up study.Renal failure · 2024Article
- Maintaining the validity of inference from linear mixed models in stepped-wedge cluster randomized trials under misspecified random-effects structures.Statistical methods in medical research · 2024Article
- Optimal designs using generalized estimating equations in cluster randomized crossover and stepped wedge trials.Statistical methods in medical research · 2024Article
- Robust analysis of stepped wedge trials using composite likelihood models.Statistics in medicine · 2024Article
- Adherence to key recommendations for design and analysis of stepped-wedge cluster randomized trials: A review of trials published 2016-2022.Clinical trials (London, England) · 2024Review
- Information content of stepped wedge designs under the working independence assumption.Journal of statistical planning and inference · 2024Article
- Planning stepped wedge cluster randomized trials to detect treatment effect heterogeneity.Statistics in medicine · 2024Article
- Estimating intra-cluster correlation coefficients for planning longitudinal cluster randomized trials: a tutorial.International journal of epidemiology · 2023Article
- Generalizing the information content for stepped wedge designs: A marginal modeling approach.Scandinavian journal of statistics, theory and applications · 2023Article
- Accounting for expected attrition in the planning of cluster randomized trials for assessing treatment effect heterogeneity.BMC medical research methodology · 2023Article
- GEEMAEE: A SAS macro for the analysis of correlated outcomes based on GEE and finite-sample adjustments with application to cluster randomized trials.Computer methods and programs in biomedicine · 2023Article
Corrections and comments
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Authors and funding
5 authors at 5 institutions in 1 country.
Funding
Abstract
Stepped wedge cluster randomized trials (SW-CRTs) with binary outcomes are increasingly used in prevention and implementation studies. Marginal models represent a flexible tool for analyzing SW-CRTs with population-averaged interpretations, but the joint estimation of the mean and intraclass correlation coefficients (ICCs) can be computationally intensive due to large cluster-period sizes. Motivated by the need for marginal inference in SW-CRTs, we propose a simple and efficient estimating equations approach to analyze cluster-period means. We show that the quasi-score for the marginal mean defined from individual-level observations can be reformulated as the quasi-score for the same marginal mean defined from the cluster-period means. An additional mapping of the individual-level ICCs into correlations for the cluster-period means further provides a rigorous justification for the cluster-period approach. The proposed approach addresses a long-recognized computational burden associated with estimating equations defined based on individual-level observations, and enables fast point and interval estimation of the intervention effect and correlations. We further propose matrix-adjusted estimating equations to improve the finite-sample inference for ICCs. By providing a valid approach to estimate ICCs within the class of generalized linear models for correlated binary outcomes, this article operationalizes key recommendations from the CONSORT extension to SW-CRTs, including the reporting of ICCs.
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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.