TY - JOUR

T1 - The Practical Alternative to the p Value Is the Correctly Used p Value

AU - Lakens, Daniël

PY - 2021

Y1 - 2021

N2 - Because of the strong overreliance on p values in the scientific literature, some researchers have argued that we need to move beyond p values and embrace practical alternatives. When proposing alternatives to p values statisticians often commit the “statistician’s fallacy,” whereby they declare which statistic researchers really “want to know.” Instead of telling researchers what they want to know, statisticians should teach researchers which questions they can ask. In some situations, the answer to the question they are most interested in will be the p value. As long as null-hypothesis tests have been criticized, researchers have suggested including minimum-effect tests and equivalence tests in our statistical toolbox, and these tests have the potential to greatly improve the questions researchers ask. If anyone believes p values affect the quality of scientific research, preventing the misinterpretation of p values by developing better evidence-based education and user-centered statistical software should be a top priority. Polarized discussions about which statistic scientists should use has distracted us from examining more important questions, such as asking researchers what they want to know when they conduct scientific research. Before we can improve our statistical inferences, we need to improve our statistical questions.

AB - Because of the strong overreliance on p values in the scientific literature, some researchers have argued that we need to move beyond p values and embrace practical alternatives. When proposing alternatives to p values statisticians often commit the “statistician’s fallacy,” whereby they declare which statistic researchers really “want to know.” Instead of telling researchers what they want to know, statisticians should teach researchers which questions they can ask. In some situations, the answer to the question they are most interested in will be the p value. As long as null-hypothesis tests have been criticized, researchers have suggested including minimum-effect tests and equivalence tests in our statistical toolbox, and these tests have the potential to greatly improve the questions researchers ask. If anyone believes p values affect the quality of scientific research, preventing the misinterpretation of p values by developing better evidence-based education and user-centered statistical software should be a top priority. Polarized discussions about which statistic scientists should use has distracted us from examining more important questions, such as asking researchers what they want to know when they conduct scientific research. Before we can improve our statistical inferences, we need to improve our statistical questions.

KW - equivalence tests

KW - null-hypothesis testing

KW - p values

KW - statistical inferences

UR - http://www.scopus.com/inward/record.url?scp=85101020619&partnerID=8YFLogxK

U2 - 10.1177/1745691620958012

DO - 10.1177/1745691620958012

M3 - Article

C2 - 33560174

AN - SCOPUS:85101020619

VL - XX

JO - Perspectives on Psychological Science

JF - Perspectives on Psychological Science

SN - 1745-6916

IS - XX

ER -