Statistical power and small effect sizes
Small effect sizes decrease statistical power and increase the needed sample size
Small effect sizes are hard to detect. More observations are needed to detect the small nuances of variance. However, sometimes these small clinical effects can push clinicians past a test or treatment threshold.
Investigate small effect sizes with an understanding that many more observations will be needed to detect statistically and clinically meaningful effects. Small effect sizes that are measured for at a continuous level will be much easier to detect in comparison to effect sizes measured at an ordinal or categorical level. Regardless, small effect sizes decrease statistical power and increase the needed sample size.
Investigate small effect sizes with an understanding that many more observations will be needed to detect statistically and clinically meaningful effects. Small effect sizes that are measured for at a continuous level will be much easier to detect in comparison to effect sizes measured at an ordinal or categorical level. Regardless, small effect sizes decrease statistical power and increase the needed sample size.
Small effect sizes decrease statistical power and increased the needed sample size.
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