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A general method for calculating power for GEE analysis of complete and incomplete stepped wedge cluster randomized trials

Stepped wedge designs have uni-directional crossovers at randomly assigned time points (steps) where clusters switch from control to intervention condition. Incomplete stepped wedge designs are increasingly used in cluster randomized trials of health care interventions and have periods without data...

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Autores principales: Zhang, Ying, Preisser, John S, Turner, Elizabeth L, Rathouz, Paul J, Toles, Mark, Li, Fan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814029/
https://www.ncbi.nlm.nih.gov/pubmed/36253078
http://dx.doi.org/10.1177/09622802221129861
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author Zhang, Ying
Preisser, John S
Turner, Elizabeth L
Rathouz, Paul J
Toles, Mark
Li, Fan
author_facet Zhang, Ying
Preisser, John S
Turner, Elizabeth L
Rathouz, Paul J
Toles, Mark
Li, Fan
author_sort Zhang, Ying
collection PubMed
description Stepped wedge designs have uni-directional crossovers at randomly assigned time points (steps) where clusters switch from control to intervention condition. Incomplete stepped wedge designs are increasingly used in cluster randomized trials of health care interventions and have periods without data collection due to logistical, resource and patient-centered considerations. The development of sample size formulae for stepped wedge trials has primarily focused on complete designs and continuous responses. Addressing this gap, a general, fast, non-simulation based power procedure is proposed for generalized estimating equations analysis of complete and incomplete stepped wedge designs and its predicted power is compared to simulated power for binary and continuous responses. An extensive set of simulations for six and twelve clusters is based upon the Connect-Home trial with an incomplete stepped wedge design. Results show that empirical test size is well controlled using a t-test with bias-corrected sandwich variance estimator for as few as six clusters. Analytical power agrees well with a simulated power in scenarios with twelve clusters. For six clusters, analytical power is similar to simulated power with estimation using the correctly specified model-based variance estimator. To explore the impact of study design choice on power, the proposed fast GEE power method is applied to the Connect-Home trial design, four alternative incomplete stepped wedge designs and one complete design.
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spelling pubmed-98140292023-01-06 A general method for calculating power for GEE analysis of complete and incomplete stepped wedge cluster randomized trials Zhang, Ying Preisser, John S Turner, Elizabeth L Rathouz, Paul J Toles, Mark Li, Fan Stat Methods Med Res Original Research Articles Stepped wedge designs have uni-directional crossovers at randomly assigned time points (steps) where clusters switch from control to intervention condition. Incomplete stepped wedge designs are increasingly used in cluster randomized trials of health care interventions and have periods without data collection due to logistical, resource and patient-centered considerations. The development of sample size formulae for stepped wedge trials has primarily focused on complete designs and continuous responses. Addressing this gap, a general, fast, non-simulation based power procedure is proposed for generalized estimating equations analysis of complete and incomplete stepped wedge designs and its predicted power is compared to simulated power for binary and continuous responses. An extensive set of simulations for six and twelve clusters is based upon the Connect-Home trial with an incomplete stepped wedge design. Results show that empirical test size is well controlled using a t-test with bias-corrected sandwich variance estimator for as few as six clusters. Analytical power agrees well with a simulated power in scenarios with twelve clusters. For six clusters, analytical power is similar to simulated power with estimation using the correctly specified model-based variance estimator. To explore the impact of study design choice on power, the proposed fast GEE power method is applied to the Connect-Home trial design, four alternative incomplete stepped wedge designs and one complete design. SAGE Publications 2022-10-17 2023-01 /pmc/articles/PMC9814029/ /pubmed/36253078 http://dx.doi.org/10.1177/09622802221129861 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research Articles
Zhang, Ying
Preisser, John S
Turner, Elizabeth L
Rathouz, Paul J
Toles, Mark
Li, Fan
A general method for calculating power for GEE analysis of complete and incomplete stepped wedge cluster randomized trials
title A general method for calculating power for GEE analysis of complete and incomplete stepped wedge cluster randomized trials
title_full A general method for calculating power for GEE analysis of complete and incomplete stepped wedge cluster randomized trials
title_fullStr A general method for calculating power for GEE analysis of complete and incomplete stepped wedge cluster randomized trials
title_full_unstemmed A general method for calculating power for GEE analysis of complete and incomplete stepped wedge cluster randomized trials
title_short A general method for calculating power for GEE analysis of complete and incomplete stepped wedge cluster randomized trials
title_sort general method for calculating power for gee analysis of complete and incomplete stepped wedge cluster randomized trials
topic Original Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814029/
https://www.ncbi.nlm.nih.gov/pubmed/36253078
http://dx.doi.org/10.1177/09622802221129861
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