Premium
A cluster‐adjusted rank‐based test for a clinical trial concerning multiple endpoints with application to dietary intervention assessment
Author(s) -
Zhang Wei,
Liu Aiyi,
Tang Larry L.,
Li Qizhai
Publication year - 2019
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.13029
Subject(s) - statistics , cluster (spacecraft) , test (biology) , cluster randomised controlled trial , rank (graph theory) , medicine , intervention (counseling) , mathematics , computer science , econometrics , randomized controlled trial , biology , paleontology , combinatorics , programming language , psychiatry
Multiple endpoints are often naturally clustered based on their scientific interpretations. Tests that compare these clustered outcomes between independent groups may lose efficiency if the cluster structures are not properly accounted for. For the two‐sample generalized Behrens‐Fisher hypothesis concerning multiple endpoints we propose a cluster‐adjusted multivariate test procedure for the comparison and demonstrate its gain in efficiency over test procedures that ignore the clusters. Data from a dietary intervention trial are used to illustrate the methods.