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A joint confidence region for an overall ranking of populations

Author

Listed:
  • Martin Klein
  • Tommy Wright
  • Jerzy Wieczorek

Abstract

National statistical agencies lack statistical methodology to express uncertainty in their released estimated overall rankings. For example, the US Census Bureau produced an ‘explicit’ ranking of the states based on observed sample estimates during 2011 of mean travel time to work. Current literature provides measures of uncertainty in estimated individual ranks, but not a direct measure of uncertainty for the estimated overall ranking. We construct and visualize a joint confidence region for the true unknown overall ranking that provides a measure of uncertainty in the estimated overall ranking.

Suggested Citation

  • Martin Klein & Tommy Wright & Jerzy Wieczorek, 2020. "A joint confidence region for an overall ranking of populations," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(3), pages 589-606, June.
    • Handle: RePEc:bla:jorssc:v:69:y:2020:i:3:p:589-606
    DOI: 10.1111/rssc.12402
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    References listed on IDEAS

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    1. 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.
    2. Schenker N. & Gentleman J. F., 2001. "On Judging the Significance of Differences by Examining the Overlap Between Confidence Intervals," The American Statistician, American Statistical Association, vol. 55, pages 182-186, August.
    3. Tommy Wright & Martin Klein & Jerzy Wieczorek, 2019. "A Primer on Visualizations for Comparing Populations, Including the Issue of Overlapping Confidence Intervals," The American Statistician, Taylor & Francis Journals, vol. 73(2), pages 165-178, April.
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    Citations

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    Cited by:

    1. Magne Mogstad & Joseph P Romano & Azeem M Shaikh & Daniel Wilhelm, 2024. "Inference for Ranks with Applications to Mobility across Neighbourhoods and Academic Achievement across Countries," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(1), pages 476-518.
    2. Sergei Bazylik & Magne Mogstad & Joseph P. Romano & Azeem Shaikh & Daniel Wilhelm, 2021. "Finite- and Large-Sample Inference for Ranks using Multinomial Data with an Application to Ranking Political Parties," NBER Working Papers 29519, National Bureau of Economic Research, Inc.
    3. Denis Chetverikov & Daniel Wilhelm, 2023. "Inference for rank-rank regressions," IFS Working Papers WCWP23/23, Institute for Fiscal Studies.
    4. Denis Chetverikov & Daniel Wilhelm, 2023. "Inference for Rank-Rank Regressions," Papers 2310.15512, arXiv.org, revised Jul 2024.
    5. Denis Chetverikov & Daniel Wilhelm, 2023. "Inference for rank-rank regressions," CeMMAP working papers 23/23, Institute for Fiscal Studies.
    6. Will Davis & Alexander Gordan & Rusty Tchernis, 2021. "Measuring the spatial distribution of health rankings in the United States," Health Economics, John Wiley & Sons, Ltd., vol. 30(11), pages 2921-2936, November.
    7. Denis Chetverikov & Daniel Wilhelm, 2024. "Inference for rank-rank regressions," IFS Working Papers WCWP11/24, Institute for Fiscal Studies.

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