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Akaike Memorial Lecture 2020: Some of the challenges of statistical applications

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  • John Copas

    (University College London
    University of Warwick)

Abstract

There has always been a close link between statistical applications and the development of new statistical theory and methods. Even straightforward applications of standard methods can give rise to theoretical challenges leading to new statistical ideas. In my lecture, I will briefly review a few of the statistical developments in my own published papers and describe the applications which gave rise to them. I will then outline some current work on publication bias, one of the outstanding problems in the interpretation of literature reviews, particularly in the medical sciences.

Suggested Citation

  • John Copas, 2022. "Akaike Memorial Lecture 2020: Some of the challenges of statistical applications," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(4), pages 615-637, August.
    • Handle: RePEc:spr:aistmt:v:74:y:2022:i:4:d:10.1007_s10463-022-00831-9
    DOI: 10.1007/s10463-022-00831-9
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    References listed on IDEAS

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    1. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    2. John Copas & Shinto Eguchi, 2010. "Likelihood for statistically equivalent models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(2), pages 193-217, March.
    3. John B. Copas, 2013. "A likelihood-based sensitivity analysis for publication bias in meta-analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(1), pages 47-66, January.
    4. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    5. Kerry Dwan & Carrol Gamble & Paula R Williamson & Jamie J Kirkham & the Reporting Bias Group, 2013. "Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias — An Updated Review," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-37, July.
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