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A Frequentist Alternative to Significance Testing, p-Values, and Confidence Intervals

Department of Psychology, MSC 3452, New Mexico State University, P.O. Box 30001, Las Cruces, NM 88003-8001, USA
Econometrics 2019, 7(2), 26; https://doi.org/10.3390/econometrics7020026
Received: 27 March 2019 / Revised: 24 May 2019 / Accepted: 24 May 2019 / Published: 4 June 2019
(This article belongs to the Special Issue Towards a New Paradigm for Statistical Evidence)
There has been much debate about null hypothesis significance testing, p-values without null hypothesis significance testing, and confidence intervals. The first major section of the present article addresses some of the main reasons these procedures are problematic. The conclusion is that none of them are satisfactory. However, there is a new procedure, termed the a priori procedure (APP), that validly aids researchers in obtaining sample statistics that have acceptable probabilities of being close to their corresponding population parameters. The second major section provides a description and review of APP advances. Not only does the APP avoid the problems that plague other inferential statistical procedures, but it is easy to perform too. Although the APP can be performed in conjunction with other procedures, the present recommendation is that it be used alone. View Full-Text
Keywords: a priori procedure; null hypothesis significance testing; confidence intervals; p-values; estimation; hypothesis testing a priori procedure; null hypothesis significance testing; confidence intervals; p-values; estimation; hypothesis testing
MDPI and ACS Style

Trafimow, D. A Frequentist Alternative to Significance Testing, p-Values, and Confidence Intervals. Econometrics 2019, 7, 26.

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