“Statistical Significance” and Statistical Reporting: Moving Beyond Binary

Blakeley B. McShane*, Eric T. Bradlow, John G. Lynch, Robert J. Meyer

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

Null hypothesis significance testing (NHST) is the default approach to statistical analysis and reporting in marketing and the biomedical and social sciences more broadly. Despite its default role, NHST has long been criticized by both statisticians and applied researchers, including those within marketing. Therefore, the authors propose a major transition in statistical analysis and reporting. Specifically, they propose moving beyond binary: abandoning NHST as the default approach to statistical analysis and reporting. To facilitate this, they briefly review some of the principal problems associated with NHST. They next discuss some principles that they believe should underlie statistical analysis and reporting. They then use these principles to motivate some guidelines for statistical analysis and reporting. They next provide some examples that illustrate statistical analysis and reporting that adheres to their principles and guidelines. They conclude with a brief discussion.

Original languageEnglish (US)
Pages (from-to)1-19
Number of pages19
JournalJournal of marketing
Volume88
Issue number3
DOIs
StatePublished - May 2024

Keywords

  • P-value
  • null hypothesis significance testing
  • replication
  • sociology of science
  • statistical significance

ASJC Scopus subject areas

  • Business and International Management
  • Marketing

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