Individual skill
calc-sample-size
Use when planning how many patients or cases a study needs before data collection (power analysis, IRB justification). Walks a decision tree to the right test and returns reproducible R/Python code and IRB-ready justification text. Analyzing collected data is /analyze-stats.
skills/calc-sample-size/SKILL.md
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- Last checked
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- Repository last updated
- Nov 10, 2026
- License
- MIT
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- biostatistics Repository topic
- claude-code Repository topic
- claude-skills Repository topic
- clinical-research Repository topic
- diagnostic-accuracy Repository topic
- literature-review Repository topic
- manuscript Repository topic
- medical-ai Repository topic
- medical-research Repository topic
- meta-analysis Repository topic
- data Derived category
- testing Derived category
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SKILL.mdcore · 11,713 bytesSKILL.mdcore · 11,713 bytesSKILL.mdcore · 11,713 bytesreferences/formulas.mddoc · 56,078 bytesreferences/justification_examples.mddoc · 4,790 bytesreferences/mrmc_reader_study_sample_size.mddoc · 5,867 bytesreferences/multi_model_comparison_sample_size.mddoc · 9,045 bytesreferences/observational_cohort.mddoc · 2,142 bytesreferences/prediction_model_sample_size.mddoc · 6,721 bytesreferences/segmentation_acceptability_sample_size.mddoc · 8,465 bytesreferences/segmentation_metric_sample_size.mddoc · 4,671 bytesskill.ymlasset · 3,136 bytestests/test_worked_examples.pyruns · 22,534 bytes
Read excerpt
# Calc-Sample-Size Skill
## Decision Tree
Walk the user through this tree one question at a time; do not assume answers. Reader studies,
segmentation and model-comparison designs sit outside the tree: see Tests 14–17.
```
What is your primary outcome?
|
+-- Binary (yes/no, positive/negative)
| |
| +-- Paired data (same subjects, two methods)?
| | +-- YES --> [5] McNemar test