Chapter 4

Effect Size, Power & NNT

From statistical significance to clinical meaning — ARR, RRR, NNT, Cohen's d, and power calculations.

Absolute / Relative Risk & NNT

The Hierarchy of Effect Measures

For binary outcomes

ARR (most honest) → NNT (most actionable) → RR (most used in research) → OR (case-control studies). RRR sounds the largest and is the most frequently presented — always demand ARR alongside it.

For continuous outcomes

Mean difference (most interpretable in clinical units) → Cohen's d (standardised, for cross-study comparisons). A d of 0.5 is medium. Context always matters more than the benchmark.

The power triangle

Effect size, power, and sample size are mathematically linked. Knowing any two determines the third. Sample size calculations before a trial are not bureaucracy — they are the honesty of specifying what your study can and cannot see.

Statistical vs. clinical significance

A large trial can find a tiny effect statistically significant. A small trial can miss a clinically important effect. p-value and effect size must always be reported together. One without the other is incomplete.

Disclaimer: This calculator is intended for educational purposes only. Results are provided to support statistical learning and should not be used as the sole basis for clinical decision-making. Always interpret statistical outputs in the context of study design, clinical relevance, and professional judgement. An Evidence Integration Lab Initiative.