Sample Size Calculator for Clinical Research
Calculate the sample size for your clinical trial, cohort study, or RCT. Free, no login required. Generates a methods paragraph ready to paste into your manuscript.
Calculate Sample Size
How to Calculate Sample Size for Clinical Research
Sample size calculation is a critical step in study design. An underpowered study wastes resources and may miss clinically important differences. An overpowered study exposes unnecessary participants to research risks.
Key Concepts
- Power (1-beta): The probability of detecting a true difference. Standard is 80% or 90%.
- Alpha (significance level): The probability of a false positive. Standard is 0.05 (5%).
- Effect size: The minimum clinically important difference you want to detect.
- Variability: How spread out your data is (standard deviation for continuous outcomes).
When to Use Each Formula
| Study Design | Formula | When to Use |
|---|---|---|
| Chi-squared (proportions) | Comparing two rates or proportions | Mortality rates, complication rates, response rates |
| T-test (means) | Comparing two group means | Blood pressure, length of stay, lab values |
| Survival (Freedman-Schoenfeld) | Time-to-event analysis | Overall survival, progression-free survival |
Common Mistakes in Sample Size Calculation
- Using an unrealistically large effect size to get a small sample size
- Forgetting to account for dropout (add 10-20% to your calculated N)
- Not specifying the primary outcome clearly before calculating
- Using the wrong formula for your study design
- Not documenting the calculation in your methods section
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