Add statistical consistency checker

README.md

@@ -1,2 +1,4 @@
 # deepevents.ai
 deepevents.ai main codebase
+
+- `statistical-consistency-checker/` adds statistical methods, unit, artifact, and review readiness checks for research packets.

statistical-consistency-checker/README.md

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+# Statistical Consistency Checker
+
+This module adds a focused research review slice for statistical method consistency.
+
+It covers:
+
+- p-value, alpha, and reported-significance alignment
+- effect size and confidence interval consistency
+- null-value checks for significant and non-significant findings
+- multiple-comparison correction review
+- sample-size and small-group warnings
+- unit mismatches and linked data/code artifact availability
+- reviewer actions, audit events, and deterministic digests
+
+The implementation is dependency-free and uses synthetic sample data only.
+
+## Run
+
+```bash
+npm run check
+npm test
+npm run demo
+```
+
+## Demo Assets
+
+- short demo video: `docs/demo.webm`
+- `docs/demo.svg`
+
+## API
+
+```js
+import {
+  evaluateStatisticalConsistency,
+  renderStatisticalConsistencyReport
+} from "./src/statistical-consistency-checker.js";
+
+const result = evaluateStatisticalConsistency(input);
+console.log(renderStatisticalConsistencyReport(result));
+```

statistical-consistency-checker/data/sample-statistics-input.json

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+{
+  "generatedAt": "2026-05-16T16:35:00Z",
+  "manuscript": {
+    "id": "ms-neuroimmune-042",
+    "title": "Neuroimmune Marker Study",
+    "domain": "neuroscience"
+  },
+  "artifacts": [
+    {
+      "id": "data-raw-csf",
+      "type": "dataset",
+      "available": true,
+      "hash": "sha256:5c1c8b"
+    },
+    {
+      "id": "code-model-r",
+      "type": "analysis-script",
+      "available": false,
+      "hash": "sha256:missing"
+    },
+    {
+      "id": "code-summary-r",
+      "type": "analysis-script",
+      "available": true,
+      "hash": "sha256:af4d22"
+    }
+  ],
+  "analyses": [
+    {
+      "id": "primary-csf-marker",
+      "claim": "Marker levels were higher in responders.",
+      "test": "welch-t-test",
+      "pValue": 0.031,
+      "alpha": 0.05,
+      "reportedSignificant": true,
+      "effectSize": 0.82,
+      "confidenceInterval": [0.12, 0.65],
+      "direction": "positive",
+      "sampleSize": 28,
+      "groups": [
+        { "name": "responders", "n": 8 },
+        { "name": "non-responders", "n": 20 }
+      ],
+      "multipleComparisons": {
+        "tests": 6,
+        "correction": "none"
+      },
+      "units": [
+        {
+          "variable": "CSF marker",
+          "expected": "ng/mL",
+          "observed": "pg/mL"
+        }
+      ],
+      "primaryOutcome": true,
+      "preregistered": false,
+      "dataArtifactId": "data-raw-csf",
+      "codeArtifactId": "code-model-r"
+    },
+    {
+      "id": "secondary-cognition-score",
+      "claim": "Cognitive score change was not statistically significant.",
+      "test": "linear-model",
+      "pValue": 0.18,
+      "alpha": 0.05,
+      "reportedSignificant": false,
+      "effectSize": 0.09,
+      "confidenceInterval": [-0.11, 0.32],
+      "direction": "positive",
+      "sampleSize": 64,
+      "groups": [
+        { "name": "treatment", "n": 32 },
+        { "name": "control", "n": 32 }
+      ],
+      "multipleComparisons": {
+        "tests": 1,
+        "correction": "not reported"
+      },
+      "units": [
+        {
+          "variable": "score delta",
+          "expected": "points",
+          "observed": "points"
+        }
+      ],
+      "primaryOutcome": false,
+      "preregistered": true,
+      "dataArtifactId": "data-raw-csf",
+      "codeArtifactId": "code-summary-r"
+    }
+  ]
+}

statistical-consistency-checker/docs/requirement-map.md

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+# Requirement Map
+
+This slice targets the peer-review diagnostics part of issue #13.
+
+| Requirement | Coverage |
+| --- | --- |
+| Statistical error detection | Checks p-values, confidence intervals, effect sizes, significance labels, and null-value consistency. |
+| Compliance-style review packet | Emits reviewer actions, audit events, deterministic manifest digests, and finding digests. |
+| Citation/review workflow fit | Links each finding to an analysis and includes artifact ids where artifact checks apply. |
+| Batch-ready local workflow | `npm run demo` evaluates a synthetic review packet with no external services. |
+| Tests | `npm test` covers clean packets, invalid p-values, interval mismatches, unit mismatches, artifact gaps, and deterministic output. |

statistical-consistency-checker/package.json

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+{
+  "name": "statistical-consistency-checker",
+  "version": "1.0.0",
+  "description": "Deterministic statistical consistency checks for research review packets.",
+  "type": "module",
+  "scripts": {
+    "check": "node --check src/statistical-consistency-checker.js && node --check scripts/demo.js && node --check test/statistical-consistency-checker.test.js",
+    "demo": "node scripts/demo.js",
+    "test": "node --test test/*.test.js"
+  },
+  "engines": {
+    "node": ">=18"
+  },
+  "license": "MIT"
+}

statistical-consistency-checker/scripts/demo.js

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+import fs from "node:fs";
+import path from "node:path";
+import { fileURLToPath } from "node:url";
+import {
+  evaluateStatisticalConsistency,
+  renderStatisticalConsistencyReport
+} from "../src/statistical-consistency-checker.js";
+
+const __dirname = path.dirname(fileURLToPath(import.meta.url));
+const inputPath = path.join(__dirname, "..", "data", "sample-statistics-input.json");
+const input = JSON.parse(fs.readFileSync(inputPath, "utf8"));
+
+const result = evaluateStatisticalConsistency(input);
+console.log(renderStatisticalConsistencyReport(result));