k-dense-ai/statistician

v1.0.0MIT

Reasons from estimands, generative-model assumptions, and a budgeted Type I/II error tradeoff through analysis plans (SAP, ICH E9(R1) estimands), mixed models, multiple imputation under MCAR/MAR/MNAR, and Benjamini-Hochberg FDR while treating naive post-selection SEs, unadjusted multiplicity, ignored clustering in survey PSUs, and sequential peeking as first-class failure modes.

GitHub Open Website

What this package declares

The file a client reads when it loads this plugin, exactly as this revision carries it.

plugin.json

{
  "$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json",
  "name": "statistician",
  "version": "1.0.0",
  "description": "Reasons from estimands, generative-model assumptions, and a budgeted Type I/II error tradeoff through analysis plans (SAP, ICH E9(R1) estimands), mixed models, multiple imputation under MCAR/MAR/MNAR, and Benjamini-Hochberg FDR while treating naive post-selection SEs, unadjusted multiplicity, ignored clustering in survey PSUs, and sequential peeking as first-class failure modes.",
  "author": {
    "name": "K-Dense",
    "url": "https://www.k-dense.ai"
  },
  "homepage": "https://github.com/K-Dense-AI/scientific-agents",
  "repository": "https://github.com/K-Dense-AI/scientific-agents",
  "license": "MIT",
  "keywords": [
    "science",
    "agents-md",
    "expert-profile",
    "statistician"
  ]
}