IDEAS home Printed from https://ideas.repec.org/a/bla/jorssa/v185y2022i4p1471-1496.html
   My bibliography  Save this article

Statistics in times of increasing uncertainty

Author

Listed:
  • Sylvia Richardson

Abstract

The statistical community mobilised vigorously from the start of the 2020 SARS‐CoV‐2 pandemic, following the RSS's long tradition of offering our expertise to help society tackle important issues that require evidence‐based decisions. This address aims to capture the highlights of our collective engagement in the pandemic, and the difficulties faced in delivering statistical design and analysis at pace and in communicating to the wider public the many complex issues that arose. I argue that these challenges gave impetus to fruitful new directions in the merging of statistical principles with constraints of agility, responsiveness and societal responsibilities. The lessons learned from this will strengthen the long‐term impact of the discipline and of the Society. The need to evaluate policies even in emergency, and to strive for statistical interoperability in future disease surveillance systems is highlighted. In my final remarks, I look towards the future landscape for statistics in the fast‐moving world of data science and outline a strategy of visible and growing engagement of the RSS with the data science ecosystem, building on the central position of statistics.

Suggested Citation

  • Sylvia Richardson, 2022. "Statistics in times of increasing uncertainty," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1471-1496, October.
  • Handle: RePEc:bla:jorssa:v:185:y:2022:i:4:p:1471-1496
    DOI: 10.1111/rssa.12957
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/rssa.12957
    Download Restriction: no

    File URL: https://libkey.io/10.1111/rssa.12957?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. David Spiegelhalter, 2017. "Trust in numbers," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 948-965, October.
    2. John Kingman & J. Durbin & David Cox & M. J. R. Healy, 1988. "Appendix: Statistical Requirements of the AIDS Epidemic," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 151(1), pages 127-130, January.
    3. Bianca Nogrady, 2021. "‘I hope you die’: how the COVID pandemic unleashed attacks on scientists," Nature, Nature, vol. 598(7880), pages 250-253, October.
    4. A. Goubar & A. E. Ades & D. De Angelis & C. A. McGarrigle & C. H. Mercer & P. A. Tookey & K. Fenton & O. N. Gill, 2008. "Estimates of human immunodeficiency virus prevalence and proportion diagnosed based on Bayesian multiparameter synthesis of surveillance data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(3), pages 541-580, June.
    5. Trystan Leng & Edward M. Hill & Alex Holmes & Emma Southall & Robin N. Thompson & Michael J. Tildesley & Matt J. Keeling & Louise Dyson, 2022. "Quantifying pupil-to-pupil SARS-CoV-2 transmission and the impact of lateral flow testing in English secondary schools," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    6. Laura Di Domenico & Giulia Pullano & Chiara E. Sabbatini & Pierre-Yves Boëlle & Vittoria Colizza, 2021. "Modelling safe protocols for reopening schools during the COVID-19 pandemic in France," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    7. John Pullinger, 2013. "Statistics making an impact," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(4), pages 819-840, October.
    8. Michael Blastland & Alexandra L. J. Freeman & Sander van der Linden & Theresa M. Marteau & David Spiegelhalter, 2020. "Five rules for evidence communication," Nature, Nature, vol. 587(7834), pages 362-364, November.
    9. David J. Hand, 2009. "Modern statistics: the myth and the magic," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(2), pages 287-306, April.
    10. Sheila M. Bird & Cox Sir David & Vern T. Farewell & Goldstein Harvey & Holt Tim & Smith Peter C., 2005. "Performance indicators: good, bad, and ugly," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(1), pages 1-27, January.
    11. Lorenzo Pellis & Paul J. Birrell & Joshua Blake & Christopher E. Overton & Francesca Scarabel & Helena B. Stage & Ellen Brooks‐Pollock & Leon Danon & Ian Hall & Thomas A. House & Matt J. Keeling & Jon, 2022. "Estimation of reproduction numbers in real time: Conceptual and statistical challenges," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S1), pages 112-130, November.
    12. David J. Spiegelhalter & Paul Aylin & Nicola G. Best & Stephen J. W. Evans & Gordon D. Murray, 2002. "Commissioned analysis of surgical performance using routine data: lessons from the Bristol inquiry," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(2), pages 191-221, June.
    13. Harvey Goldstein & David J. Spiegelhalter, 1996. "League Tables and Their Limitations: Statistical Issues in Comparisons of Institutional Performance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(3), pages 385-409, May.
    14. Peter J. Diggle, 2015. "Statistics: a data science for the 21st century," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 793-813, October.
    15. S. M. Gore & P. Armitage, 1988. "Royal Statistical Society Meeting on AIDS," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 151(1), pages 3-4, January.
    16. John Kingman, 1989. "Statistical Responsibility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 152(3), pages 277-285, May.
    17. D. Tim Holt, 2008. "Official statistics, public policy and public trust," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(2), pages 323-346, April.
    18. Deborah Ashby, 2019. "Pigeonholes and mustard seeds: growing capacity to use data for society," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(4), pages 1121-1137, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Eleni Verykouki & Christos T. Nakas, 2023. "Adaptations on the Use of p -Values for Statistical Inference: An Interpretation of Messages from Recent Public Discussions," Stats, MDPI, vol. 6(2), pages 1-13, April.

    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. George Leckie & Harvey Goldstein, 2009. "The limitations of using school league tables to inform school choice," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(4), pages 835-851, October.
    2. Isabella Sulis & Mariano Porcu, 2015. "Assessing Divergences in Mathematics and Reading Achievement in Italian Primary Schools: A Proposal of Adjusted Indicators of School Effectiveness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(2), pages 607-634, June.
    3. Gwyn Bevan & Richard Hamblin, 2009. "Hitting and missing targets by ambulance services for emergency calls: effects of different systems of performance measurement within the UK," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 161-190, January.
    4. Giuseppina Guagnano & Maria Rita Sebastiani, 2018. "Away from Dissatisfaction, Closer to Well-Being: A Multidimensional Synthetic Measure," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(3), pages 977-997, April.
    5. David I. Ohlssen & Linda D. Sharples & David J. Spiegelhalter, 2007. "A hierarchical modelling framework for identifying unusual performance in health care providers," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(4), pages 865-890, October.
    6. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    7. Andrew Zammit‐Mangion & Nathaniel K. Newlands & Wesley S. Burr, 2023. "Environmental data science: Part 1," Environmetrics, John Wiley & Sons, Ltd., vol. 34(1), February.
    8. Bornmann, Lutz & Leydesdorff, Loet & Wang, Jian, 2014. "How to improve the prediction based on citation impact percentiles for years shortly after the publication date?," Journal of Informetrics, Elsevier, vol. 8(1), pages 175-180.
    9. Davide Tosi & Alessandro Siro Campi, 2021. "How Schools Affected the COVID-19 Pandemic in Italy: Data Analysis for Lombardy Region, Campania Region, and Emilia Region," Future Internet, MDPI, vol. 13(5), pages 1-12, April.
    10. Arpino, Bruno & Varriale, Roberta, 2009. "Assessing the quality of institutions’ rankings obtained through multilevel linear regression models," MPRA Paper 19873, University Library of Munich, Germany.
    11. Mutz, Rüdiger & Daniel, Hans-Dieter, 2018. "The bibliometric quotient (BQ), or how to measure a researcher’s performance capacity: A Bayesian Poisson Rasch model," Journal of Informetrics, Elsevier, vol. 12(4), pages 1282-1295.
    12. Magne Mogstad & Joseph P. Romano & Azeem Shaikh & Daniel Wilhelm, 2020. "Inference for Ranks with Applications to Mobility across Neighborhoods and Academic Achievement across Countries," NBER Working Papers 26883, National Bureau of Economic Research, Inc.
    13. Daraio, Cinzia & Bonaccorsi, Andrea & Simar, Léopold, 2015. "Rankings and university performance: A conditional multidimensional approach," European Journal of Operational Research, Elsevier, vol. 244(3), pages 918-930.
    14. Christophe Ley & Yves Dominicy, 2017. "Mutual Point-winning Probabilities (MPW): a New Performance Measure for Table Tennis," Working Papers ECARES ECARES 2017-23, ULB -- Universite Libre de Bruxelles.
    15. Nicholas Longford & D. B. Rubin, 2006. "Performance assessment and league tables. Comparing like with like," Economics Working Papers 994, Department of Economics and Business, Universitat Pompeu Fabra.
    16. repec:lan:wpaper:991 is not listed on IDEAS
    17. Nils Gutacker & Andrew Street, 2015. "Multidimensional performance assessment using dominance criteria," Working Papers 115cherp, Centre for Health Economics, University of York.
    18. Nils Gutacker & Andrew Street, 2018. "Multidimensional performance assessment of public sector organisations using dominance criteria," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 13-27, February.
    19. Sheila M. Bird & Cox Sir David & Vern T. Farewell & Goldstein Harvey & Holt Tim & Smith Peter C., 2005. "Performance indicators: good, bad, and ugly," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(1), pages 1-27, January.
    20. Nan Li & Muzi Chen & Difang Huang, 2022. "How Do Logistics Disruptions Affect Rural Households? Evidence from COVID-19 in China," Sustainability, MDPI, vol. 15(1), pages 1-17, December.
    21. Sulis, Isabella & Giambona, Francesca & Porcu, Mariano, 2020. "Adjusted indicators of quality and equity for monitoring the education systems over time. Insights on EU15 countries from PISA surveys," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).

    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:jorssa:v:185:y:2022:i:4:p:1471-1496. 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: https://edirc.repec.org/data/rssssea.html .

    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.