Information content of stepped wedge designs with unequal cluster-period sizes in linear mixed models: Informing incomplete designs.

cluster crossover trial cluster randomized trial generalized least squares intracluster correlation linear mixed model

Journal

Statistics in medicine
ISSN: 1097-0258
Titre abrégé: Stat Med
Pays: England
ID NLM: 8215016

Informations de publication

Date de publication:
30 03 2021
Historique:
received: 07 07 2020
revised: 13 12 2020
accepted: 16 12 2020
pubmed: 14 1 2021
medline: 30 6 2021
entrez: 13 1 2021
Statut: ppublish

Résumé

In practice, stepped wedge trials frequently include clusters of differing sizes. However, investigations into the theoretical aspects of stepped wedge designs have, until recently, typically assumed equal numbers of subjects in each cluster and in each period. The information content of the cluster-period cells, clusters, and periods of stepped wedge designs has previously been investigated assuming equal cluster-period sizes, and has shown that incomplete stepped wedge designs may be efficient alternatives to the full stepped wedge. How this changes when cluster-period sizes are not equal is unknown, and we investigate this here. Working within the linear mixed model framework, we show that the information contributed by design components (clusters, sequences, and periods) does depend on the sizes of each cluster-period. Using a particular trial that assessed the impact of an individual education intervention on log-length of stay in rehabilitation units, we demonstrate how strongly the efficiency of incomplete designs depends on which cells are excluded: smaller incomplete designs may be more powerful than alternative incomplete designs that include a greater total number of participants. This also serves to demonstrate how the pattern of information content can be used to inform a set of incomplete designs to be considered as alternatives to the complete stepped wedge design. Our theoretical results for the information content can be extended to a broad class of longitudinal (ie, multiple period) cluster randomized trial designs.

Identifiants

pubmed: 33438255
doi: 10.1002/sim.8867
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1736-1751

Informations de copyright

© 2021 John Wiley & Sons, Ltd.

Références

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Auteurs

Jessica Kasza (J)

School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.

Rhys Bowden (R)

School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.

Andrew B Forbes (AB)

School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.

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