A Frequentist Alternative to Significance Testing, p -Values, and Confidence Intervals
David Trafimow ()
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David Trafimow: Department of Psychology, MSC 3452, New Mexico State University, P.O. Box 30001, Las Cruces, NM 88003-8001, USA
Econometrics, 2019, vol. 7, issue 2, 1-14
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.
Keywords: a priori procedure; null hypothesis significance testing; confidence intervals; p -values; estimation; hypothesis testing (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:26-:d:237276
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