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the claim

Failure to consider statistical power prevents the accurate interpretation of negative research results.

the verdict
SUPPORTED
the evidence backs this
Recorded sources
3 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

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 analysis

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.

Evidence for · 3
Type II error and statistical power in reports of small animal clinical trials
2014
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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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More for · 2
Powering Neurology Drug Development Trials to Reduce False Negative Results.
2026
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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

Sample size determination across study designs in health professions education research: a methodology guide.
2026
Get citation
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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