Sample size & power

How many subjects a trial needs — or, given a fixed sample size, how much power it has. All sample sizes are rounded up (ceiling), per regulatory convention.

1.1 · Two-sample t-test (continuous, superiority)

Sample size per group to detect a mean difference Δ between two independent arms.

two-sided
used in Power mode only
n per group (n₁)63
n in group 2 (n₂)63
Total N126
Total N, dropout-inflated126
Formula
n₁ = σ²(1 + 1/r)·(z₁₋α/₂ + z₁₋β)² / Δ²; n₂ = r·n₁
Reference
Chow, Shao & Wang, Sample Size Calculations in Clinical Research, 3rd ed. (2018), §3.2; Machin et al., Sample Size Tables for Clinical Studies, 3rd ed. (2008).
Assumptions & notes
  • Normal approximation; exact non-central-t calculation is a documented v1 limitation.
  • Warns when the standardized effect Δ/σ < 0.2.
Note
Normal approximation; exact noncentral-t calculation is a documented v1 limitation.

Exploratory / educational use only — not validated for regulatory submissions. See footer.

1.2 · Two proportions (superiority)

Sample size per group to detect a difference between two independent response rates.

two-sided
used in Power mode only
n per group93
Total N186
Total N, dropout-inflated186
Formula
n/group = [z₁₋α/₂·√(2p̄(1−p̄)) + z₁₋β·√(p₁(1−p₁) + p₂(1−p₂))]² / (p₁−p₂)²
Reference
Chow, Shao & Wang (2018), §4.2.1; Fleiss, Levin & Paik, Statistical Methods for Rates and Proportions, 3rd ed. (2003).
Assumptions & notes
  • Unpooled variance — standard for superiority.
  • Continuity correction is a planned v1 enhancement (currently off).
Note
Continuity correction is a planned v1 enhancement (currently off).

Exploratory / educational use only — not validated for regulatory submissions. See footer.

1.3a · One-sample mean vs. reference

Sample size to compare a single mean against a reference value.

two-sided
n32
n, dropout-inflated32
Formula
n = σ²·(z₁₋α/₂ + z₁₋β)² / Δ²
Reference
Chow, Shao & Wang (2018), §3.1.

Exploratory / educational use only — not validated for regulatory submissions. See footer.

1.3b · One-sample proportion vs. reference

Sample size to compare a single proportion against a reference rate.

two-sided
n63
n, dropout-inflated63
Formula
n = [z₁₋α/₂·√(p₀(1−p₀)) + z₁₋β·√(p₁(1−p₁))]² / (p₁−p₀)²
Reference
Chow, Shao & Wang (2018), §4.1.

Exploratory / educational use only — not validated for regulatory submissions. See footer.

1.4a · Non-inferiority — means

Sample size per group for a non-inferiority trial on a continuous endpoint, given a pre-specified margin.

default 0
one-sided
n per group393
Total N786
Total N, dropout-inflated786
Formula
n/group = 2σ²·(z₁₋α + z₁₋β)² / (δ+M)² (one-sided α)
Reference
Chow, Shao & Wang (2018), §3.3; FDA guidance Non-Inferiority Clinical Trials to Establish Effectiveness (2016).
Assumptions & notes
  • The margin must be pre-specified and clinically/statistically justified in the protocol — this tool does not validate the margin itself.
Note
The margin must be pre-specified and clinically/statistically justified in the protocol — this tool does not validate the margin itself.

Exploratory / educational use only — not validated for regulatory submissions. See footer.

1.4b · Non-inferiority — proportions

Sample size per group for a non-inferiority trial on a binary endpoint, given a pre-specified absolute risk-difference margin.

default 0
one-sided
n per group377
Total N754
Total N, dropout-inflated754
Formula
n/group = [z₁₋α·√(2p̄(1−p̄)) + z₁₋β·√(pT(1−pT)+pC(1−pC))]² / (δ+M)² (one-sided α)
Reference
Chow, Shao & Wang (2018), §3.3; FDA guidance Non-Inferiority Clinical Trials to Establish Effectiveness (2016).
Assumptions & notes
  • The margin must be pre-specified and clinically/statistically justified in the protocol — this tool does not validate the margin itself.
Note
The margin must be pre-specified and clinically/statistically justified in the protocol — this tool does not validate the margin itself.

Exploratory / educational use only — not validated for regulatory submissions. See footer.