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Combining information across diverse sources: The II‐CC‐FF paradigm

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  • Céline Cunen
  • Nils Lid Hjort

Abstract

We introduce and develop a general paradigm for combining information across diverse data sources. In broad terms, suppose φ is a parameter of interest, built up via components ψ1,…,ψk from data sources 1, … , 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) Cj(ψj) for the relevant focus parameter ψj associated with data source j. Second, confidence conversion (CC) techniques are used 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 φ=φ(ψ1,…,ψk), 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.

Suggested Citation

  • Céline Cunen & Nils Lid Hjort, 2022. "Combining information across diverse sources: The II‐CC‐FF paradigm," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(2), pages 625-656, June.
    • Handle: RePEc:bla:scjsta:v:49:y:2022:i:2:p:625-656
    DOI: 10.1111/sjos.12530
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    1. Kristensen, Kasper & Nielsen, Anders & Berg, Casper W. & Skaug, Hans & Bell, Bradley M., 2016. "TMB: Automatic Differentiation and Laplace Approximation," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 70(i05).
    2. Dungang Liu & Regina Y. Liu & Minge Xie, 2015. "Multivariate Meta-Analysis of Heterogeneous Studies Using Only Summary Statistics: Efficiency and Robustness," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 326-340, March.
    3. Maria Durban & I. D. Currie, 2000. "Adjustment of the Profile Likelihood for a Class of Normal Regression Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(3), pages 535-542, September.
    4. Claeskens,Gerda & Hjort,Nils Lid, 2008. "Model Selection and Model Averaging," Cambridge Books, Cambridge University Press, number 9780521852258.
    5. Xie, Minge & Singh, Kesar & Strawderman, William E., 2011. "Confidence Distributions and a Unifying Framework for Meta-Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 106(493), pages 320-333.
    6. Min-ge Xie & Kesar Singh, 2013. "Confidence Distribution, the Frequentist Distribution Estimator of a Parameter: A Review," International Statistical Review, International Statistical Institute, vol. 81(1), pages 3-39, April.
    7. Steven E. Stern, 1997. "A Second‐order Adjustment to the Profile Likelihood in the Case of a Multidimensional Parameter of Interest," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(3), pages 653-665.
    8. Céline Cunen & Nils Lid Hjort & Håvard Mokleiv Nygård, 2020. "Statistical sightings of better angels: Analysing the distribution of battle-deaths in interstate conflict over time," Journal of Peace Research, Peace Research Institute Oslo, vol. 57(2), pages 221-234, March.
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