What This Calculator Measures

Estimate sample size for power using effect size, alpha, and power targets.

By combining practical inputs into a structured model, this calculator helps you move from vague estimation to clear planning actions you can execute consistently.

This calculator estimates sample size for power-based studies.

How to Use This Well

Enter effect size, alpha, and power target.
Add standard deviation and allocation ratio.
Set dropoff percent.
Review total sample size.
Adjust effect size assumptions.

Formula Breakdown

n = 2 x (zα + zβ)^2 x σ^2 / d^2

Total: n x (1 + ratio).

Adjusted: total / (1 - dropoff).

Group 1: total / (1 + ratio).

Worked Example

Effect size 0.4 with 80% power.
Base sample around 98 per group.
Total around 196 before dropoff.

Interpretation Guide

Range	Meaning	Action
Under 80	Light.	Broader effects only.
80-150	Standard.	Typical power.
150-250	High.	Tighter effects.
250+	Very high.	Large study.

Optimization Playbook

Increase effect size: lower sample needs.
Balance groups: set ratio near 1.
Reduce dropoff: improve retention.
Check variance: lower std dev if possible.

Scenario Planning

Baseline: current effect size.
Higher power: raise to 90%.
Lower alpha: reduce to 0.01.
Decision rule: keep total under 250 if possible.

Common Mistakes to Avoid

Overestimating effect size.
Ignoring dropoff.
Using wrong alpha.
Skipping variance check.

Implementation Checklist

Estimate effect size.
Set power target.
Plan recruitment.
Monitor dropoff.

Measurement Notes

Treat this calculator as a directional planning instrument. Output quality improves when your inputs are anchored to recent real data instead of one-off assumptions.

Run multiple scenarios, document what changed, and keep the decision tied to trends, not a single result snapshot.

Power Sample Size Curve Calculator

Quick Facts

Your Results

Power Plan