Basic sample size calculator for clinical research planning with common statistical scenarios
Basic sample size estimation for clinical research planning.
test_type: Type of test (t_test, chi_square, proportion)alpha: Significance level (default 0.05)power: Statistical power (default 0.80)effect_size: Expected effect sizebaseline_rate: Baseline proportion (for proportion tests)Input: Two-sample t-test, alpha=0.05, power=0.80, effect_size=0.5 Output: n=64 per group, total=128 subjects
| Risk Indicator | Assessment | Level |
|---|---|---|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |
# Python dependencies
pip install -r requirements.txt