Failure to consider statistical power prevents the accurate interpretation of negative research results.
Is it true that failure to consider statistical power prevents the accurate interpretation of negative research results?
Yes. Failing to account for statistical power makes it impossible to distinguish between a true lack of effect and an inconclusive underpowered study, thereby preventing the accurate interpretation of negative results.
Verdict: SUPPORTED · 3 sources for, 0 against · Last checked
The retrieved literature consistently confirms that failing to consider statistical power (Type II error risk, sample size, and effect size) severely hampers the correct interpretation of negative results, as many non-significant findings merely reflect underpowered study designs rather than true null effects. Papers 0, 4, and 9 directly support this relationship, and no papers refute it.
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Giuffrida, M. A. (2014). Type II error and statistical power in reports of small animal clinical trials. doi.org. https://doi.org/10.2460/javma.244.9.1075
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H, M., SJ, W., V, R., & FB, N. (2026). Powering Neurology Drug Development Trials to Reduce False Negative Results.. doi.org. https://doi.org/10.1111/cts.70722
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WM, N., A, D., S, K., AA, P., M, B., A, P., PK, K., & R, M. (2026). Sample size determination across study designs in health professions education research: a methodology guide.. doi.org. https://doi.org/10.12688/f1000research.185853.2
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