Clinical Trial Sample Size Calculator

Calculate the required number of participants for your clinical study. Set significance level, statistical power, and expected effect size to determine sample size for a two-sample comparison.

Two-sided test. Z = 1.96

Z = 0.842

Small = 0.2, Medium = 0.5, Large = 0.8

Typical range: 10-20% for Phase III trials

Estimated Sample Size

Per Arm

32

subjects

Total Required

64

2 arms

With 15% Dropout

76

to enrol

Formula used: n = ((Zα/2 + Zβ) / d)2 where Zα/2 = 1.96, Zβ = 0.842, d = 0.5. Total = 2n for two-arm parallel design. Adjusted for 15% dropout: N = n / (1 - 0.15).

This calculator provides an estimate for planning purposes. Final sample size determination should account for primary endpoint type, expected variability, interim analyses, and regulatory requirements. Consult a biostatistician for your protocol.

Effect Size Guide

Cohen's dMagnitudeTypical Example
0.2SmallSubtle treatment improvement over placebo
0.5MediumClinically meaningful difference in most contexts
0.8LargeObvious effect, strong treatment response
1.0+Very LargeDramatic effect, e.g. curative intervention

About this calculator

This calculator uses the standard formula for a two-sample, two-sided t-test comparison of means. It provides an approximate sample size per group. For complex study designs (crossover, cluster-randomised, non-inferiority, equivalence), or for categorical endpoints, consult a biostatistician. The calculator does not account for dropout rates — add 10-20% to the calculated N for attrition.

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Frequently Asked Questions

Why is sample size calculation important for clinical trials?
Sample size calculation ensures your clinical trial has sufficient statistical power to detect a meaningful treatment effect if one exists. An underpowered study risks failing to detect a real effect (Type II error), wasting resources and participant time. An overpowered study exposes more participants to experimental treatments than necessary. Regulatory bodies like CDSCO and FDA require justified sample size calculations in clinical trial protocols.
What factors determine clinical trial sample size?
Four primary factors: (1) Significance level (alpha) — typically 0.05, representing the acceptable false-positive rate. (2) Statistical power (1-beta) — typically 0.80 or 0.90, representing the probability of detecting a true effect. (3) Effect size — the minimum clinically meaningful difference you want to detect. (4) Variability — the expected standard deviation of the outcome measure. Other factors include dropout rate, study design (parallel vs. crossover), and whether the primary endpoint is continuous or categorical.
Does Auriga Research provide biostatistics services for clinical trials?
Yes. Our CRO biostatistics team provides sample size calculation, randomisation, statistical analysis plans (SAP), interim analyses, and final study reports. We support Phase I-IV trials with CDSCO-compliant documentation. Learn about our biostatistics services.

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