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the claim

A nonsignificant result in a study can occur when the number of subjects is insufficient to detect a true effect.

the verdict
SUPPORTED
the evidence backs this
Recorded sources
6 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 a nonsignificant result in a study can occur when the number of subjects is insufficient to detect a true effect?

Yes. Multiple methodological studies confirm that a nonsignificant result in a study is frequently caused by insufficient sample size and low statistical power, leading to a Type II error where a true effect goes undetected.

Verdict: SUPPORTED · 6 sources for, 0 against · Last checked

The analysis

The retrieved literature consistently supports the claim that underpowered studies with insufficient subjects increase the risk of Type II errors, meaning true effects can fail to reach statistical significance.

Evidence for · 6
Understanding type I and type <scp>II</scp> errors, statistical power and sample size
2016
States that ensuring an adequate sample size is the primary way to minimize random errors like a Type II error.
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Akobeng, A. K. (2016). Understanding type I and type <scp>II</scp> errors, statistical power and sample size. doi.org. https://doi.org/10.1111/apa.13384

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More for · 5
Power and Error: Increased Risk of False Positive Results in Underpowered Studies
2010
Explains that low statistical power directly increases the probability of a Type II error, reducing the likelihood of detecting a true difference.
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Christley, R. M. (2010). Power and Error: Increased Risk of False Positive Results in Underpowered Studies. doi.org. https://doi.org/10.2174/1874297101003010016

‘No Effect’ Conclusions in Studies Reporting Nonsignificant Results Are Potentially Incorrect
2021
Demonstrates that studies concluding 'no effect' often report observed effect sizes that indicate potential true effects obscured by methodology.
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Uimonen, M., Ponkilainen, V., Raittio, L., & Reito, A. (2021). ‘No Effect’ Conclusions in Studies Reporting Nonsignificant Results Are Potentially Incorrect. doi.org. https://doi.org/10.1016/j.arthro.2021.08.036

Reduce or not reduce: a practical guide to calculate sample size for various experimental design in studies involving animals.
2026
Highlights that inadequate statistical planning and insufficient sample sizes routinely lead to underpowered studies whose results lack reliability.
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JX, M. & P, G. (2026). Reduce or not reduce: a practical guide to calculate sample size for various experimental design in studies involving animals.. doi.org. https://doi.org/10.3389/fphar.2026.1786234

Most oxytocin administration studies are statistically underpowered to reliably detect (or reject) a wide range of effect sizes
2020
Notes that studies with low statistical power are frequently unable to reliably detect or reject true effect sizes.
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Quintana, D. S. (2020). Most oxytocin administration studies are statistically underpowered to reliably detect (or reject) a wide range of effect sizes. doi.org. https://doi.org/10.31234/osf.io/kzp4n

Comment on "swedish massage versus hip strengthening exercises for pain and function in older adults with knee osteoarthritis: a randomized controlled trial".
2026
Identifies small sample sizes and insufficient statistical power as a major risk factor for failing to identify true differences (Type II errors).
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S, K. & S, P. (2026). Comment on "swedish massage versus hip strengthening exercises for pain and function in older adults with knee osteoarthritis: a randomized controlled trial".. doi.org. https://doi.org/10.1007/s40520-026-03418-z

What does the evidence say?

The retrieved literature consistently supports the claim that underpowered studies with insufficient subjects increase the risk of Type II errors, meaning true effects can fail to reach statistical significance.

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