IDEAS home Printed from https://ideas.repec.org/a/bla/scjsta/v49y2022i2p625-656.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/sjos.12530
    Download Restriction: no

    File URL: https://libkey.io/10.1111/sjos.12530?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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, October.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guang Yang & Dungang Liu & Junyuan Wang & Min‐ge Xie, 2016. "Meta‐analysis framework for exact inferences with application to the analysis of rare events," Biometrics, The International Biometric Society, vol. 72(4), pages 1378-1386, December.
    2. Tang, Lu & Zhou, Ling & Song, Peter X.-K., 2020. "Distributed simultaneous inference in generalized linear models via confidence distribution," Journal of Multivariate Analysis, Elsevier, vol. 176(C).
    3. Liu, Xuhua & Li, Na & Hu, Yuqin, 2015. "Combining inferences on the common mean of several inverse Gaussian distributions based on confidence distribution," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 136-142.
    4. La Vecchia, Davide & Moor, Alban & Scaillet, Olivier, 2023. "A higher-order correct fast moving-average bootstrap for dependent data," Journal of Econometrics, Elsevier, vol. 235(1), pages 65-81.
    5. Xiaokang Luo & Tirthankar Dasgupta & Minge Xie & Regina Y. Liu, 2021. "Leveraging the Fisher randomization test using confidence distributions: Inference, combination and fusion learning," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 777-797, September.
    6. Zhao, Xiujie & Chen, Piao & Gaudoin, Olivier & Doyen, Laurent, 2021. "Accelerated degradation tests with inspection effects," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1099-1114.
    7. Veronese, Piero & Melilli, Eugenio, 2018. "Some asymptotic results for fiducial and confidence distributions," Statistics & Probability Letters, Elsevier, vol. 134(C), pages 98-105.
    8. Jiang, Rong & Yu, Keming, 2020. "Single-index composite quantile regression for massive data," Journal of Multivariate Analysis, Elsevier, vol. 180(C).
    9. Ruoyu Wang & Qihua Wang & Wang Miao, 2023. "A robust fusion-extraction procedure with summary statistics in the presence of biased sources," Biometrika, Biometrika Trust, vol. 110(4), pages 1023-1040.
    10. Randy C. S. Lai & Jan Hannig & Thomas C. M. Lee, 2015. "Generalized Fiducial Inference for Ultrahigh-Dimensional Regression," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(510), pages 760-772, June.
    11. Wei Wang & Shou‐En Lu & Jerry Q. Cheng & Minge Xie & John B. Kostis, 2022. "Multivariate survival analysis in big data: A divide‐and‐combine approach," Biometrics, The International Biometric Society, vol. 78(3), pages 852-866, September.
    12. Nezakati, Ensiyeh & Pircalabelu, Eugen, 2021. "Unbalanced distributed estimation and inference for precision matrices," LIDAM Discussion Papers ISBA 2021031, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    13. Xuhua Liu & Xingzhong Xu, 2016. "Confidence distribution inferences in one-way random effects model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 59-74, March.
    14. Hector, Emily C. & Luo, Lan & Song, Peter X.-K., 2023. "Parallel-and-stream accelerator for computationally fast supervised learning," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    15. Andrea C. Garcia‐Angulo & Gerda Claeskens, 2023. "Exact uniformly most powerful postselection confidence distributions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 358-382, March.
    16. Ionut Bebu & George Luta & Thomas Mathew & Brian K. Agan, 2016. "Generalized Confidence Intervals and Fiducial Intervals for Some Epidemiological Measures," IJERPH, MDPI, vol. 13(6), pages 1-13, June.
    17. Wu, Suofei & Hannig, Jan & Lee, Thomas C.M., 2022. "Uncertainty quantification for honest regression trees," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
    18. 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.
    19. Delbianco Fernando & Tohmé Fernando, 2023. "What is a relevant control?: An algorithmic proposal," Asociación Argentina de Economía Política: Working Papers 4643, Asociación Argentina de Economía Política.
    20. Kitagawa, Toru & Muris, Chris, 2016. "Model averaging in semiparametric estimation of treatment effects," Journal of Econometrics, Elsevier, vol. 193(1), pages 271-289.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:scjsta:v:49:y:2022:i:2:p:625-656. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0303-6898 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.