Learning Centre Partitions from Summaries
This paper proposes a sequential "Clusters-of-Centres" algorithm that utilizes multivariate Cochran-type tests on summary statistics to identify and merge homogeneous groups in multi-centre studies, establishing asymptotic distributions and proving that a multi-round bootstrap variant can recover the true centre partition with high probability.