Editorial Commentary: The Power of Interpretation: Utilizing the P Value as a Spectrum, in Addition to Effect Size, Will Lead to Accurate Presentation of Results
Authors
Sabetian PW, Domb BG
Journal
Arthroscopy, April 2022
Background
The P value is commonly used to determine statistical significance in studies, but relying solely on it can lead to misinterpretations, especially when determining the effectiveness of treatments or interventions.
Methods
This commentary discusses how interpreting P values as a binary measure (significant vs. non-significant) is limiting and how combining them with effect size can provide a fuller understanding of study results.
Key Findings
- The P value should not be viewed as the sole measure of statistical significance.
- Effect size, which shows the magnitude of differences between groups, should be considered alongside P values for a more complete picture.
- This approach helps avoid the misleading conclusion of “no effect” in cases where there might still be a clinically meaningful difference.
Conclusions
Statistical results should be interpreted as a spectrum, not just through a dichotomous lens based on P values, to avoid biases and to accurately represent study findings.
What Does This Mean For Patients
Understanding that statistical significance does not always imply clinical relevance means that patients should discuss both the effect size and the practical significance of treatment outcomes with their healthcare providers.