pairwise-ma-methodology

pairwise-ma-methodology is a skill for Claude Code from choxos/BiostatAgent. It costs 40 tokens per session (2,008 once invoked), scanned A, original, MIT.

Method guidance for pairwise meta-analysis, which combines results from studies comparing the same two treatments or approaches. It covers fixed-effect and random-effects models, study differences, and publication bias.

In plain words
What is it for?
It helps plan or review a pairwise meta-analysis, assess heterogeneity, choose between fixed and random effects, examine publication bias, and design sensitivity analyses.
Why use it?
It helps avoid unsuitable models and makes differences between studies and uncertainty in the combined result explicit.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the itc-modeling plugin — 6 skills, 2 commands, 7 agents shipped together

Good fit It helps plan or review a pairwise meta-analysis, assess heterogeneity, choose between fixed and random effects, examine publication bias, and design sensitivity analyses.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/choxos/biostatagent/pairwise-ma-methodology
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add choxos/BiostatAgent --skill pairwise-ma-methodology
Clone the repo
git clone --depth 1 https://github.com/choxos/BiostatAgent

Made for: Claude Code.

Or install itc-modeling, the plugin that ships this one along with the rest of its 6 skills, 2 commands, 7 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for pairwise-ma-methodology

README.md
[![agentmods](https://agentmods.dev/badge/skills/choxos/biostatagent/pairwise-ma-methodology.svg)](https://agentmods.dev/skills/choxos/biostatagent/pairwise-ma-methodology)
Your own site
<a href="https://agentmods.dev/skills/choxos/biostatagent/pairwise-ma-methodology"><img src="https://agentmods.dev/badge/skills/choxos/biostatagent/pairwise-ma-methodology.svg" alt="Measured on agentmods" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,008 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.02008
Opus 5 $0.00020 $0.01004
Sonnet 5 $0.00008 $0.00402
Haiku 4.5 $0.00004 $0.00201

Measured 8d ago against content hash 4671c29bd689, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

pairwise-ma-methodology scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/itc-modeling/skills/pairwise-ma-methodology/SKILL.md · 325 lines

How it starts

The opening of the file, as written. The whole thing — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Pairwise Meta-Analysis Methodology

Comprehensive methodological guidance for conducting rigorous pairwise meta-analysis following Cochrane and PRISMA guidelines.

When to Use This Skill

  • Planning a pairwise meta-analysis
  • Choosing between fixed and random effects models
  • Interpreting heterogeneity statistics
  • Assessing publication bias
  • Designing sensitivity analyses
  • Reviewing pairwise MA code or results

Fixed vs Random Effects

Decision Framework

Are studies functionally identical?
├── Yes → Fixed-effect model appropriate
│   - Same population, intervention, comparator, outcome
│   - Estimating single "true" effect
│
└── No (usually the case) → Random-effects model
    - Studies differ in ways that affect true effect
    - Estimating mean of distribution of effects
    - More generalizable inference

When to Use Fixed-Effect

  • Studies are very similar (rare in practice)
  • Want to estimate effect in "identical" studies
  • Very few studies (< 5) - random effects unreliable
  • Sensitivity analysis alongside random effects

When to Use Random-Effects

  • Studies differ in populations, settings, methods
  • Want inference applicable beyond included studies
  • Default choice for most meta-analyses
  • Use with appropriate adjustments (Knapp-Hartung)

Key Differences

Aspect Fixed-Effect Random-Effects
Assumption Common true effect Distribution of true effects
Weights Based on precision only Includes between-study variance
Small study More weight Less weight
Large study Less relative weight More weight
CI width Narrower (if heterogeneity exists) Wider (appropriately)
Inference To identical studies To broader population

Heterogeneity Assessment

Statistics Overview

Q Statistic (Cochran's Q)
  • Tests null hypothesis of homogeneity
  • Follows chi-square distribution under null
  • Low power with few studies
  • Overpowered with many studies

Read the full file on GitHub · 325 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 325 lines · 40 tokens per session scan A 4671c29bd689

Subscribe to this mod's changes

pairwise-ma-methodology is a skill published in the GitHub repository choxos/BiostatAgent (11 stars, last pushed 3mo ago), licensed MIT. It adds 40 tokens to every session and 2,008 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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