# 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.

Meeting ID: 643 1266 2291

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.