# power-analysis

Works out statistical power, the sample size you need, and the minimum detectable effect for a study design, then drafts a registry-ready power section.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · ★ 1671
- Author: Claude Code Academic Workflow
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/pedrohcgs/claude-code-my-workflow/tree/HEAD/.claude/skills/power-analysis/SKILL.md
- Updated: 2026-09-27
- HTML: https://affpapa.org/en/nevibecode/skills/power-analysis

## What it does

The skill handles the three linked quantities of an ex-ante design calculation: power, required N, and minimum detectable effect. Pin two down and it solves for the third. It will not reverse-engineer a power figure from an estimate you already have — post-hoc power tells you nothing about whether the design was sound.

Standard designs go through the analytical route: two-arm RCTs, clustered randomisation with ICC, and multi-arm comparisons. Under the hood it uses R `pwr` / `WebPower` or closed-form `power.t.test` / `power.prop.test`, inflating variance by `DEFF = 1 + (m − 1)·ρ` for clusters. Stata (`power twomeans`, `power twoproportions`) and Python (`statsmodels.stats.power`) are covered too. Non-standard setups — DiD and event studies, IV, panels — fall back to simulation following the `/simulation-study` pattern: a seeded DGP, the same estimator you plan to run on real data, the rejection share as power, and a size check under the null. A simulated number without a Monte Carlo SE and a verified size check is not an answer yet.

You need to supply the design parameters: the outcome, one- or two-sided test, `alpha`, allocation ratio, and ICC plus cluster size when randomisation is clustered. Anything missing gets asked once instead of guessed. If the estimand or the SD source is unclear, the skill stops and waits. Output lands in `quality_reports/power/` as a power and MDE table, power curves, and a methods paragraph, with a reproducible script under `scripts/R/`.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add pedrohcgs/claude-code-my-workflow --skill power-analysis -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/power-analysis/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/power-analysis/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add pedrohcgs/claude-code-my-workflow --skill power-analysis -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/power-analysis/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add pedrohcgs/claude-code-my-workflow --skill power-analysis -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/power-analysis/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install pedrohcgs/claude-code-my-workflow power-analysis
```

2. **Manually: put the files in place**
- File: `.github/skills/power-analysis/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add pedrohcgs/claude-code-my-workflow --skill power-analysis -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/pedrohcgs/claude-code-my-workflow --path .claude/skills/power-analysis
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/power-analysis/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add pedrohcgs/claude-code-my-workflow --skill power-analysis -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/pedrohcgs/claude-code-my-workflow/tree/HEAD/.claude/skills/power-analysis/SKILL.md

## When to use it
- pick a sample size that hits a target MDE at 80–90% power
- work out the design effect for cluster randomisation with ICC
- adjust alpha for the number of comparisons in a multi-arm trial
- get power for a DiD or IV design with no closed-form SE
- draft the power justification for an RCT registry entry

## Example prompts
- Compute the MDE for a two-arm RCT: effect 0.2 SD, N = 800, power 0.80
- How many clusters do I need with ICC 0.05 and an average cluster size of 30?
- Run a power simulation for a staggered DiD with 40 periods

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 1c4ff4dc2c36e740.

BEGIN THIRD-PARTY FILE 1c4ff4dc2c36e740
```text
---
name: power-analysis
description: Compute statistical power, required sample size, and minimum detectable effect (MDE) for a study design, then write a registry-ready power section. Handles two-arm RCTs (with clustering / ICC and unequal allocation), multiple-arm corrections, and a simulation-based power option for non-standard designs (DiD/event-study, IV, panel). Use when user says "power analysis", "power calculation", "MDE", "minimum detectable effect", "how big a sample do I need", "is my study powered", "power for an RCT", or when /preregister needs a power section for an experiment. Produces a power/MDE table, power curves, and a methods paragraph to paste into a preregistration.
argument-hint: "[--mode mde|n|power] [--design rct|cluster|multiarm|sim] [--input <spec-or-description>]"
disable-model-invocation: true
allowed-tools: ["Read", "Write", "Edit", "Bash", "Agent", "Task"]
effort: high
metadata:
  author: Claude Code Academic Workflow
  version: 1.0.0
---

# `/power-analysis` — Power / MDE for study design

Compute the three interlocking quantities of an ex-ante design calculation — **power**, **required N**, and **minimum detectable effect (MDE)** — and emit a power section the user can paste straight into a preregistration. Analytical for standard designs; simulation-based (reusing the `/simulation-study` harness pattern) for non-standard ones.

**Core principle:** a power calculation is a *design-time commitment made before the data exist*. Fix any two of {effect size, N, power} and solve for the third; never back out a "power" number from a realised estimate (that is post-hoc power, and it is uninformative — see "What this skill does NOT do").

## When to use

- **Before launching an RCT / field / survey experiment** — to choose N (or clusters) for a target MDE at 80–90% power.
```
END THIRD-PARTY FILE 1c4ff4dc2c36e740

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