Free Sample Size Calculator for Medical Research
Determine the exact number of participants needed for statistically valid studies. Our sample size calculator uses validated formulas from G*Power and methods recommended by PubMed and Cochrane.
Supported Tests
Editverse Sample Size Calculator
Free Tool for Medical ResearchQuick Guide
- Select your study design from the dropdown
- Enter the expected effect size or group parameters
- Adjust dropout rate if participants may leave the study
- Click Calculate to see required sample size
Tip: Hover over the (?) icons for detailed explanations of each parameter.
How to Use: Choose Your Statistical Test
Select the appropriate test based on your study design and data type
Tests for Comparing Means
Two-Sample T-Test
When to use: Comparing means between two independent groups
Typical values:
- Blood pressure: Mean diff =
5-10mmHg, SD =12-15 - HbA1c: Mean diff =
0.5-1.0%, SD =1.2-1.5
Paired T-Test
When to use: Before/after measurements on same subjects
Typical values:
- Pain score: Mean diff =
2, SD of diff =3 - BP after treatment: Mean diff =
10mmHg, SD =12
One-Sample T-Test
When to use: Compare sample mean to known reference
Typical values:
- Reference =
100, Expected =105, SD =15
ANOVA (3+ Groups)
When to use: Comparing means across 3+ groups
Effect size (Cohen’s f):
- Small:
0.10| Medium:0.25| Large:0.40
Tests for Comparing Proportions
Two Proportions (Chi-Square)
When to use: Comparing rates between two groups
Typical values:
- Response: Control =
30%, Treatment =50% - Adverse events: Drug A =
15%, Drug B =8%
Single Proportion
When to use: Compare observed rate to known value
Typical values:
- Historical =
20%, Expected =12%
Clinical Trial Designs
Superiority Trial
When to use: Prove new treatment is better than control
- Mean diff =
10, SD =20
Non-Inferiority Trial
When to use: Prove new treatment is not worse
- Margin =
-10%(clinically acceptable)
Equivalence Trial
When to use: Prove treatments are equal (bioequivalence)
- Margin =
±20%or±15%
Survival Analysis
Log-Rank Test
When to use: Time-to-event analysis
- Overall survival: HR =
0.75, Event rate =30% - Progression-free: HR =
0.65, Event rate =50%
Correlation & Regression
Correlation
Correlation strength (r):
- Small:
0.10| Medium:0.30| Large:0.50
Linear Regression
Effect size (R²):
- Small:
0.10| Medium:0.25| Large:0.40
Logistic Regression
Rule: 10-20 events per predictor
Diagnostic Studies
Sensitivity/Specificity
- Screening: Sensitivity =
90%, Precision =±5% - Confirmatory: Specificity =
95%, Precision =±3%
ROC Curve (AUC)
- AUC
0.50= Random |0.70-0.80= Acceptable |>0.80= Excellent
How We Compare: Editverse vs Other Calculators
See why researchers choose Editverse for power analysis
| Feature | Editverse | G*Power | PS Power | OpenEpi | Sealed Envelope |
|---|---|---|---|---|---|
| Price | ✓ Free | Free | Free | Free | Freemium |
| Platform | ✓ Web (No Download) | Desktop only | Desktop only | Web | Web |
| Mobile Friendly | ✓ Yes | ✗ No | ✗ No | Limited | Limited |
| Clinical Trial Designs | ✓ All 3 Types | Limited | Yes | ✗ No | Yes |
| Survival Analysis | ✓ Log-Rank | Yes | Yes | ✗ No | Limited |
| Interactive Charts | ✓ Yes | Yes | ✗ No | ✗ No | ✗ No |
| Publication Reports | ✓ Yes | ✗ No | ✗ No | ✗ No | ✗ No |
| Dropout Adjustment | ✓ Built-in | Manual | Manual | ✗ No | Yes |
| ROC/AUC | ✓ Yes | ✗ No | ✗ No | ✗ No | ✗ No |
| Registration | ✓ Not Required | No | No | No | Some features |
How to Cite This Calculator
Use these formats for your methodology section, ethics applications, and publications
📝 In-Text (Methods Section)
Sample size was calculated using the Editverse Sample Size Calculator (Editverse, 2025), a validated online power analysis tool for medical research.
📚 APA 7th Edition
Editverse. (2025). Editverse Sample Size Calculator [Online tool]. https://editverse.com/free-sample-size-calculator-power-analysis-tool-for-researchers/
📖 Vancouver/ICMJE
Editverse. Editverse Sample Size Calculator [Internet]. 2025 [cited 2025 Jan 6]. Available from: https://editverse.com/free-sample-size-calculator-power-analysis-tool-for-researchers/
🔬 Full Methodology Example
Sample Size Calculation: The required sample size was determined using the Editverse Sample Size Calculator (https://editverse.com). Based on a two-sample t-test with α = 0.05, 80% power, mean difference of 10 units, and SD of 25 units, we calculated 78 participants per group (156 total). Accounting for 20% dropout, we planned to enroll 196 total.
💡 Tips for Ethics Committees & Grant Applications
- Justify effect size: Reference pilot data or published literature
- Explain alpha and power: Standard is α=0.05, power=80%
- Account for dropouts: Use our built-in dropout slider
- Include parameters: Reviewers want to verify your numbers
- Use Report feature: Generate publication-ready text with one click
Frequently Asked Questions
What is sample size calculation?
Sample size calculation determines the minimum participants needed to detect a statistically significant effect. It ensures adequate power while avoiding unnecessary recruitment.
How do I calculate sample size for a clinical trial?
Select your trial design, enter expected treatment difference, standard deviation, significance level (α=0.05), and power (80%). Our calculator computes required participants per arm.
What is statistical power?
Statistical power (1-β) is the probability of detecting a true effect. 80% power means 80% chance of finding significance if the effect is real. Higher power needs larger samples.
What effect size should I use?
Base effect size on: (1) pilot data, (2) published literature, or (3) minimum clinically important difference. Cohen’s d: 0.2=small, 0.5=medium, 0.8=large.
Is this calculator free?
Yes! 100% free for academic and commercial use. No registration, no download, no limitations. Use directly in your browser.
How accurate vs G*Power?
We use the same validated statistical formulas. Results are equivalent for same inputs. Advantage: web-based access without installation.
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