“Statistical Significance” and Statistical Reporting: Moving Beyond Binary
Blakeley B. McShane, Eric T. Bradlow, John Lynch, Robert J. Meyer
Journal of Marketing
- 주제정보시스템 연구방법론 · 경영정보·의사결정
- 방법
- 현상
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.
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- 저널Journal of Marketing · 88(3) · 1–19
- 토픽Meta-analysis and systematic reviews · Statistics, Probability and Uncertainty
- DOI10.1177/00222429231216910
- 저자Blakeley B. McShane, Eric T. Bradlow, John Lynch, Robert J. Meyer