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Statistical significance testing and p-values: Defending the indefensible? A discussion paper and position statement
Peter Griffiths1, Jack Needleman2
1University of Southampton, UK and Executive Editor, International Journal of Nursing Studies, United Kingdom.
International Journal of Nursing Studies
|August 24, 2019
Summary
Statistical significance tests and p-values are often misinterpreted. Researchers should prioritize effect sizes and confidence intervals for clearer interpretation of study results.
Area of Science:
- Statistics
- Scientific Research Methodology
Background:
- Null hypothesis significance testing (NHST) is prevalent in statistical education and research.
- Misinterpretations of statistical significance and p-values are common and persistent.
- The arbitrary p < 0.05 threshold is frequently criticized, with some advocating for the complete removal of p-values.
Purpose of the Study:
- To outline problems associated with significance testing and p-values.
- To offer examples of misinterpretations from nursing research.
- To discuss potential solutions and provide guidance for reporting statistical analyses.
Main Methods:
- Review of statistical testing practices and common misinterpretations.
- Analysis of examples from the International Journal of Nursing Studies.
- Discussion of alternative reporting methods and proposed guidelines.
Main Results:
- P-values and significance tests are intrinsically misleading and do not accurately represent effect size or importance.
- Point estimates and confidence intervals provide direct information on effect size and uncertainty.
- Over-reliance on arbitrary p-value cutoffs hinders the understanding of results.
Conclusions:
- Authors and journals should emphasize effect sizes and confidence intervals over p-values.
- The use of arbitrary cutoffs (e.g., p < 0.05) for decision-making should be avoided.
- When reporting statistical analyses, clarity regarding 'statistical significance' versus 'importance' is crucial, with a recommendation to use effect sizes for the latter.
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