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The harmonic mean χ2 test to substantiate scientific findings


Held, Leonhard (2020). The harmonic mean χ2 test to substantiate scientific findings. Journal of the Royal Statistical Society: Series C, 69(3):697-708.

Abstract

Statistical methodology plays a crucial role in drug regulation. Decisions by the US Food and Drug Administration or European Medicines Agency are typically made based on multiple primary studies testing the same medical product, where the two‐trials rule is the standard requirement, despite shortcomings. A new approach is proposed for this task based on the harmonic mean of the squared study‐specific test statistics. Appropriate scaling ensures that, for any number of independent studies, the null distribution is a χ2‐distribution with 1 degree of freedom. This gives rise to a new method for combining one‐sided p‐values and calculating confidence intervals for the overall treatment effect. Further properties are discussed and a comparison with the two‐trials rule is made, as well as with alternative research synthesis methods. An attractive feature of the new approach is that a claim of success requires each study to be convincing on its own to a certain degree depending on the overall level of significance and the number of studies. The new approach is motivated by and applied to data from five clinical trials investigating the effect of carvedilol for the treatment of patients with moderate to severe heart failure.

Abstract

Statistical methodology plays a crucial role in drug regulation. Decisions by the US Food and Drug Administration or European Medicines Agency are typically made based on multiple primary studies testing the same medical product, where the two‐trials rule is the standard requirement, despite shortcomings. A new approach is proposed for this task based on the harmonic mean of the squared study‐specific test statistics. Appropriate scaling ensures that, for any number of independent studies, the null distribution is a χ2‐distribution with 1 degree of freedom. This gives rise to a new method for combining one‐sided p‐values and calculating confidence intervals for the overall treatment effect. Further properties are discussed and a comparison with the two‐trials rule is made, as well as with alternative research synthesis methods. An attractive feature of the new approach is that a claim of success requires each study to be convincing on its own to a certain degree depending on the overall level of significance and the number of studies. The new approach is motivated by and applied to data from five clinical trials investigating the effect of carvedilol for the treatment of patients with moderate to severe heart failure.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
04 Faculty of Medicine > Center for Reproducible Science
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Social Sciences & Humanities > Statistics, Probability and Uncertainty
Uncontrolled Keywords:Statistics, Probability and Uncertainty, Statistics and Probability
Language:English
Date:1 June 2020
Deposited On:13 Jan 2021 13:23
Last Modified:24 Jun 2024 01:42
Publisher:Royal Statistical Society
ISSN:0035-9254
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1111/rssc.12410
  • Content: Published Version
  • Licence: Creative Commons: Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)