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Autor(en) / Beteiligte
Titel
A general method for calculating power for GEE analysis of complete and incomplete stepped wedge cluster randomized trials
Ist Teil von
  • Statistical methods in medical research, 2023-01, Vol.32 (1), p.71-87
Ort / Verlag
London, England: SAGE Publications
Erscheinungsjahr
2023
Link zum Volltext
Quelle
Applied Social Sciences Index & Abstracts (ASSIA)
Beschreibungen/Notizen
  • 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.
Sprache
Englisch
Identifikatoren
ISSN: 0962-2802
eISSN: 1477-0334
DOI: 10.1177/09622802221129861
Titel-ID: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9814029

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