/bias-detection

name: bias-detection
description: 'Assess systematic biases in the evidence body — publication bias, reporting
  bias, and selective outcome reporting. Budget: 40 studies, 40 effect sizes, 40 web
  searches.'
dependencies:
  tactics:
  - effect-size-extraction
  - evidence-synthesis-planning
  - quality-assessment-protocol
  sops:
  - data-extraction-form
  - effect-size-planning
  - heterogeneity-source-analysis
  - inclusion-criteria-design
  - meta-analysis-synthesis
  - pico-formulation
  - publication-bias-assessment
  - risk-of-bias-assessment
  - sensitivity-analysis-design

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

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

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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