Combining diverse information sources with the II-CC-FF paradigm, with applications in meta-analysis & beyond
Meta-analysis and Systematic Reviews Theme
Combining diverse information sources with the II-CC-FF paradigm, with applications in meta-analysis and beyond by Celine Cunen, University of Oslo
Abstract: Combining information across different sources is an important statistical challenge, arising in many different fields. Combination is especially difficult when the sources are very diverse, requiring approaches beyond standard meta-analysis methods. The II-CC-FF paradigm (Independent Inspection, Confidence Conversion, Focused Fusion) is a general three-step method for such problems. The first step, II, uses different techniques to translate the information from each source to confidence distributions.
Then these confidence distributions are transformed into confidence log-likelihoods in the CC-step, before being combined in the FF step. In this talk, the II-CC-FF scheme will be presented and illustrated by several non-standard applications. Demonstrating that II-CC-FF can be applied successfully both in traditional meta-analysis settings and in more challenging cases, where we need to combine classical experimental data (hard data) with less systematically collected information (soft data).