Skip to main content
ClaudeWave
Skill331 repo starsupdated today

bias-detection

The bias-detection skill designs a systematic protocol to identify and quantify threats to meta-analytic validity, including publication bias, outcome reporting bias, and citation bias. Use this skill when synthesizing evidence from multiple studies to ensure pooled estimates remain valid through funnel plot analysis, statistical testing, sensitivity analyses, and quality assessment across at least five bias domains before drawing conclusions.

Install in Claude Code
Copy
git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine /tmp/bias-detection && cp -r /tmp/bias-detection/skills/bias-detection ~/.claude/skills/bias-detection
Then start a new Claude Code session; the skill loads automatically.

SKILL.md

# Bias Detection Strategy

Design a protocol to systematically assess biases that threaten the validity of meta-analytic conclusions.

## Purpose

Bias in the evidence body (publication bias, outcome reporting bias, citation bias, time-lag bias, language bias) can invalidate pooled estimates. This strategy designs the complete bias detection and adjustment protocol — funnel plots, statistical tests, sensitivity analyses, and GRADE certainty downgrading.

## Budget

| Resource | Floor | Target |
|----------|-------|--------|
| Studies identified | 28 | 40 |
| Effect sizes extracted | 28 | 40 |
| Web searches | 28 | 40 |
| Bias domains assessed | 5 | 8 |
| Quality assessments | 20 | 40 |

Budget gate: cannot exit until 80% of floor met.

## State Ledger

```
<HARD-GATE>
| Metric | Current | Floor | Target | Status |
|--------|---------|-------|--------|--------|
| Studies found | 0 | 28 | 40 | BLOCKED |
| Effect sizes planned | 0 | 28 | 40 | BLOCKED |
| Web searches done | 0 | 28 | 40 | BLOCKED |
| Bias domains assessed | 0 | 5 | 8 | BLOCKED |
| Quality assessed | 0 | 20 | 40 | BLOCKED |
</HARD-GATE>
```

## Available Tactics

| Tactic | When to Use |
|--------|-------------|
| effect-size-extraction | Extract effect sizes with precision (SE, CI) |
| quality-assessment-protocol | Full RoB2 assessment per study |
| evidence-synthesis-planning | Plan bias-adjusted models |

## Available SOPs

| SOP | When to Use |
|-----|-------------|
| pico-formulation | Frame the evidence assessment question |
| inclusion-criteria-design | Include grey literature, preprints |
| effect-size-planning | Ensure precision metrics extracted |
| data-extraction-form | Template capturing reporting completeness |
| risk-of-bias-assessment | Per-study RoB (core of this strategy) |
| publication-bias-assessment | Core SOP — funnel plots, statistical tests |
| sensitivity-analysis-design | Trim-and-fill, selection models |
| heterogeneity-source-analysis | Bias as heterogeneity driver |
| meta-analysis-synthesis | Final bias assessment protocol |

## Execution Guidance

1. **Frame** — Run `pico-formulation` for the evidence reliability question
2. **Scope** — Run `inclusion-criteria-design` maximizing source diversity (grey lit, preprints, registries)
3. **Search** — Search for published AND unpublished studies, trial registries
4. **Extract** — Use `effect-size-extraction` with precision metrics (SE, CI, N)
5. **Assess** — Use `quality-assessment-protocol` for comprehensive RoB2
6. **Detect** — Run `publication-bias-assessment` for statistical detection plan
7. **Investigate** — Run `heterogeneity-source-analysis` for bias-driven heterogeneity
8. **Adjust** — Run `sensitivity-analysis-design` for bias-adjustment methods
9. **Synthesize** — Run `meta-analysis-synthesis` for final protocol

Web searches target: trial registries, grey literature databases, dissertation repositories, conference abstracts.

## Output Format

```yaml
protocol:
  question: [Is the evidence body for X biased?]
  bias_domains:
    publication_bias:
      visual: [funnel plot, contour-enhanced funnel]
      statistical: [Egger's test, Begg's test, Peters' test]
      adjustment: [trim-and-fill, Copas selection model, PET-PEESE]
    outcome_reporting_bias:
      detection: [registry-publication comparison]
      tool: [ROB-ME, ORBIT]
    time_lag_bias:
      detection: [time-to-publication analysis]
    citation_bias:
      detection: [citation network analysis]
    language_bias:
      mitigation: [multi-language search strategy]
    small_study_effects:
      detection: [funnel asymmetry, regression tests]
      adjustment: [limit meta-analysis]
  grey_literature_search: [databases, registries, contacts]
  grade_assessment:
    domain: publication_bias
    downgrading_criteria: [when to downgrade certainty]
  sensitivity_plan: [selection model, 3PSM, p-curve, z-curve]
  reporting: PRISMA-2020 + ROB-ME guidelines
```

<!-- BEGIN available-tables (generated) -->

## Available Tactics

Optional, no fixed order; the final leaf is always a sop.

| Tactic | When to use |
| --- | --- |
| effect-size-extraction | Systematically extract effect sizes and conditions from papers for meta-analytic synthesis |
| evidence-synthesis-planning | Plan the statistical synthesis approach — model selection, heterogeneity strategy, and reporting |
| quality-assessment-protocol | Methodological quality and bias risk assessment of included studies using validated tools |

## Available SOPs

Optional, no fixed order; the final leaf is always a sop.

| SOP | When to use |
| --- | --- |
| data-extraction-form | Design structured data extraction form for systematic meta-analysis data collection |
| effect-size-planning | Determine effect size types and calculation methods for meta-analytic synthesis |
| heterogeneity-source-analysis | Identify and classify sources of between-study heterogeneity (clinical, methodological, statistical) |
| inclusion-criteria-design | Define inclusion/exclusion criteria for systematic study selection in meta-analysis |
| meta-analysis-synthesis | Produce final meta-analysis protocol document assembling all planning outputs into PRISMA-compliant protocol |
| pico-formulation | Construct PICO/PECO framework for the meta-analysis research question |
| publication-bias-assessment | Plan funnel plots, Egger's test, trim-and-fill, p-curve, and selection model analyses for publication bias |
| risk-of-bias-assessment | Assess methodological bias using RoB2, PROBAST, or QUADAS-2 validated tools |
| sensitivity-analysis-design | Design leave-one-out, influence diagnostics, subgroup analyses, and robustness checks |

<!-- END available-tables (generated) -->