Sample Size Calculator

Research Tool

Sample size for cross-sectional, cohort, and randomized clinical trials. Adjust parameters and calculate in real time.

Statistical Parameters

Configure your study parameters below to estimate the required sample size for an exposed/unexposed group comparison.

Two-Sided Significance Level (1-alpha) %

Standard clinical threshold: 95%

Power (1-beta) %

Chance of detecting a true effect — typically 80%

Ratio of Sample Size, Unexposed/Exposed

Number of unexposed subjects per exposed subject

Percent of Unexposed with Outcome

Expected outcome prevalence in the unexposed group

Percent of Exposed with Outcome

Expected outcome prevalence in the exposed group

Total Sample Size (Fleiss, Recommended)

— participants

How It Works

Understanding the Parameters

Each parameter directly influences your required sample size. Here's what each one means for your research.

Significance Level

The two-sided alpha controls your false-positive rate. A 95% significance level (alpha = 0.05) is the standard clinical threshold; 99% is more conservative and requires a larger sample.

Power

The probability of correctly detecting a true difference between exposed and unexposed groups if one exists. Most clinical and epidemiological studies target 80% or 90% power.

Outcome Proportions

The expected percentage of unexposed and exposed subjects who experience the outcome of interest. The gap between these two values drives the odds ratio, risk ratio, and risk difference — and therefore the required sample size.

Allocation Ratio

The ratio of unexposed to exposed subjects. A 1:1 ratio is most statistically efficient, but unequal ratios are common when one group is harder to recruit.

Clinical Application

This calculator follows the Kelsey and Fleiss methods used in cross-sectional, cohort, and randomized clinical trials (Kelsey et al., Methods in Observational Epidemiology; Fleiss, Statistical Methods for Rates and Proportions). For complex adaptive designs or multi-arm trials, consult BioAxion's biostatistics team.

Regulatory Alignment

Sample size justification is required in every regulatory submission. FDA and EMA guidelines mandate adequate statistical power (typically ≥80%) and documented assumptions. BioAxion provides complete SAP support aligned with global regulatory expectations.