| name | heterogeneity-investigation |
| description | Explain why different studies reach different conclusions — heterogeneity investigation protocol. Budget: 30 studies, 30 effect sizes, 50 web searches. |
Heterogeneity Investigation Strategy
Design a protocol to investigate and explain between-study heterogeneity — why studies of the same question reach different conclusions.
Purpose
When a meta-analysis reveals substantial heterogeneity (I2 > 50%, significant Q-test, large tau2), this strategy designs the investigation protocol: subgroup analyses, meta-regression, moderator identification, and outlier diagnostics. Produces the investigation plan, not the computation.
Budget
| Resource | Floor | Target |
|---|
| Studies identified | 20 | 30 |
| Effect sizes extracted | 20 | 30 |
| Web searches | 35 | 50 |
| Moderator candidates | 5 | 10+ |
| Quality assessments | 15 | 30 |
Budget gate: cannot exit until 80% of floor met.
State Ledger
<HARD-GATE>
| Metric | Current | Floor | Target | Status |
|--------|---------|-------|--------|--------|
| Studies found | 0 | 20 | 30 | BLOCKED |
| Effect sizes planned | 0 | 20 | 30 | BLOCKED |
| Web searches done | 0 | 35 | 50 | BLOCKED |
| Moderators identified | 0 | 5 | 10+ | BLOCKED |
| Quality assessed | 0 | 15 | 30 | BLOCKED |
</HARD-GATE>
Available Tactics
| Tactic | When to Use |
|---|
| effect-size-extraction | Extract effect sizes with full study characteristics |
| quality-assessment-protocol | Assess whether quality explains heterogeneity |
| evidence-synthesis-planning | Plan subgroup and meta-regression models |
Available SOPs
| SOP | When to Use |
|---|
| pico-formulation | Frame the heterogeneity question |
| inclusion-criteria-design | Broad inclusion to capture variation |
| effect-size-planning | Standardize for comparability |
| data-extraction-form | Rich moderator variable extraction |
| risk-of-bias-assessment | RoB as potential moderator |
| heterogeneity-source-analysis | Core SOP — classify heterogeneity sources |
| sensitivity-analysis-design | Outlier removal, influence diagnostics |
| publication-bias-assessment | Bias as heterogeneity source |
| meta-analysis-synthesis | Final investigation protocol |
Execution Guidance
- Frame — Run
pico-formulation emphasizing variation in P/I/C/O
- Scope — Run
inclusion-criteria-design with broad criteria (capture variation)
- Search — Systematic search + web research on known moderators
- Extract — Use
effect-size-extraction with rich study-level covariates
- Hypothesize — Run
heterogeneity-source-analysis to generate moderator hypotheses
- Assess — Use
quality-assessment-protocol (RoB as moderator)
- Plan — Use
evidence-synthesis-planning for subgroup + meta-regression
- Synthesize — Run
meta-analysis-synthesis for investigation protocol
Web searches focus on domain knowledge about why results might differ (methodological, clinical, statistical heterogeneity).
Output Format
protocol:
question: [Why do studies of X reach different conclusions?]
heterogeneity_metrics: [I2, tau2, Q-test, prediction interval]
moderator_candidates:
clinical: [population, intervention details, outcome timing]
methodological: [study design, RoB, measurement tools]
statistical: [effect size type, analysis method, sample size]
investigation_plan:
subgroup_analyses: [categorical moderators]
meta_regression: [continuous moderators]
outlier_diagnostics: [influence analysis, Baujat plot]
sensitivity: [leave-one-out, cumulative by quality]
a_priori_hypotheses: [pre-specified moderator hypotheses]
multiple_testing: [correction strategy]
reporting: PRISMA-2020 + heterogeneity reporting guidelines
