Important Issues in Statistical Testing and Recommended Improvements in Accounting Research
Thomas R. Dyckman () and
Stephen A. Zeff ()
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Thomas R. Dyckman: Accounting Department, Cornell University, Ithaca, NY 14850, USA
Stephen A. Zeff: Accounting Department, Rice University, Houston, TX 77005, USA
Econometrics, 2019, vol. 7, issue 2, 1-11
A great deal of the accounting research published in recent years has involved statistical tests. Our paper proposes improvements to both the quality and execution of such research. We address the following limitations in current research that appear to us to be ignored or used inappropriately: (1) unaddressed situational effects resulting from model limitations and what has been referred to as “data carpentry,” (2) limitations and alternatives to winsorizing, (3) necessary improvements to relying on a study’s calculated “ p -values” instead of on the economic or behavioral importance of the results, and (4) the information loss incurred by under-valuing what can and cannot be learned from replications.
Keywords: model specification; model testing; reporting results ( p -values); replications (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:7:y:2019:i:2:p:18-:d:229157
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