Significance Testing: We Can Do Better

24 Pages Posted: 14 Jun 2016

See all articles by Thomas R. Dyckman

Thomas R. Dyckman

Cornell University - Department of Accounting

Date Written: June 2016

Abstract

This paper advocates abandoning null hypothesis statistical tests (NHST) in favour of reporting confidence intervals. The case against NHST, which has been made repeatedly in multiple disciplines and is growing in awareness and acceptance, is introduced and discussed. Accounting as an empirical research discipline appears to be the last of the research communities to face up to the inherent problems of significance test use and abuse. The paper encourages adoption of a meta‐analysis approach which allows for the inclusion of replication studies in the assessment of evidence. This approach requires abandoning the typical NHST process and its reliance on p‐values. However, given that NHST has deep roots and wide ‘social acceptance’ in the empirical testing community, modifications to NHST are suggested so as to partly counter the weakness of this statistical testing method.

Keywords: Confidence interval reporting, Meta‐analysis, Frequentist, Bayesian

Suggested Citation

Dyckman, Thomas R., Significance Testing: We Can Do Better (June 2016). Abacus, Vol. 52, Issue 2, pp. 319-342, 2016. Available at SSRN: https://ssrn.com/abstract=2795333 or http://dx.doi.org/10.1111/abac.12078

Thomas R. Dyckman (Contact Author)

Cornell University - Department of Accounting ( email )

Ithaca, NY 14853
United States
607-255-3491 (Phone)
607-254-4590 (Fax)

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