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The P Value and Statistical Significance: Misunderstandings, Explanations, Challenges, and Alternatives

The calculation of a P value in research and especially the use of a threshold to declare the statistical significance of the P value have both been challenged in recent years. There are at least two important reasons for this challenge: research data contain much more meaning than is summarized in...

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Detalles Bibliográficos
Autor principal: Andrade, Chittaranjan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6532382/
https://www.ncbi.nlm.nih.gov/pubmed/31142921
http://dx.doi.org/10.4103/IJPSYM.IJPSYM_193_19
Descripción
Sumario:The calculation of a P value in research and especially the use of a threshold to declare the statistical significance of the P value have both been challenged in recent years. There are at least two important reasons for this challenge: research data contain much more meaning than is summarized in a P value and its statistical significance, and these two concepts are frequently misunderstood and consequently inappropriately interpreted. This article considers why 5% may be set as a reasonable cut-off for statistical significance, explains the correct interpretation of P < 0.05 and other values of P, examines arguments for and against the concept of statistical significance, and suggests other and better ways for analyzing data and for presenting, interpreting, and discussing the results.