Optimal allocation of subjects in a matched pair cluster-randomized trial with fixed number of heterogeneous clusters

© 2020 Informa UK Limited, trading as Taylor & Francis Group.

Bibliographische Detailangaben
Veröffentlicht in:Journal of applied statistics. - 1991. - 48(2021), 9 vom: 18., Seite 1527-1540
1. Verfasser: Singh, Satya Prakash (VerfasserIn)
Weitere Verfasser: Yadav, Pradeep
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2021
Zugriff auf das übergeordnete Werk:Journal of applied statistics
Schlagworte:Journal Article Bayesian design cluster-randomized trials efficiency matched pair clusters optimal design power
Beschreibung
Zusammenfassung:© 2020 Informa UK Limited, trading as Taylor & Francis Group.
In cluster-randomized trials, investigators randomize clusters of individuals such as households, medical practices, schools or classrooms despite the unit of interest are the individuals. It results in the loss of efficiency in terms of the estimation of the unknown parameters as well as the power of the test for testing the treatment effects. To recoup this efficiency loss, some studies pair similar clusters and randomize treatment within pairs. However, the clusters within a treatment arm might be heterogeneous in nature. In this article, we propose a locally optimal design that accounts the clusters heterogeneity and optimally allocates the subjects within each cluster. To address the dependency of design on the unknown parameters, we also discuss Bayesian optimal designs. Performances of proposed designs are investigated numerically through some data examples
Beschreibung:Date Revised 27.08.2024
published: Electronic-eCollection
Citation Status PubMed-not-MEDLINE
ISSN:0266-4763
DOI:10.1080/02664763.2020.1779195