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Significance Testing: We Can Do Better
Author(s) -
Dyckman Thomas R.
Publication year - 2016
Publication title -
abacus
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.632
H-Index - 45
eISSN - 1467-6281
pISSN - 0001-3072
DOI - 10.1111/abac.12078
Subject(s) - statistical hypothesis testing , null hypothesis , process (computing) , empirical research , psychology , replication (statistics) , econometrics , computer science , data science , statistics , mathematics , operating system
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.