Combining Information Across Diverse Sources: The II‐CC‐FF Paradigm

Speakers: Céline Cunen, Postdoc, and Nils Lid Hjort, Professor, Department of Mathematics, University of Oslo.

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We introduce and develop a general paradigm for combining information across diverse data sources. In broadterms, suppose \(\phi\) is a parameter of interest, built up via components \(\psi_1,\ldots,\psi_k\) from data sources \(1,\ldots,k\). The proposed scheme has three steps. First, the independent inspection (II) step amounts to investigating each separate data source, translating statistical information to a confidence distribution (CD) \(C_j(\psi_j)\) for the relevant focus parameter \(\psi_j\) associated with data source \(j\). Second, confidence conversion (CC) techniques areused to translate the CDs to confidence log-likelihood functions. Finally, the focused fusion (FF) step uses relevant and context-driven techniques to construct a confidence distribution for the primary focus parameter \(\phi=\phi(\psi_1,\ldots,\psi_k)\), acting on the combined confidence log-likelihood. In traditional setups, the II-CC-FF strategy amounts to versions of meta-analysis, and turns out to be competitive against state-of-the-art methods. Its potential lies in applications to harder problems, however. Illustrations are presented, related to actual applications.

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Published May 18, 2021 4:51 PM - Last modified Oct. 4, 2021 11:27 AM