pairwise-synthesis

Research

Compare two methods across multiple studies — paired meta-analysis protocol design. Budget: 30 studies, 30 effect sizes, 40 web searches.

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Pairwise Synthesis Strategy

Design a pairwise meta-analysis protocol comparing method A vs method B across multiple independent studies.

Purpose

When two methods (interventions, algorithms, approaches) have been compared across multiple studies, synthesize the evidence into a single quantitative estimate of relative performance. This strategy produces the complete protocol — stopping before computation.

Budget

Resource	Floor	Target
Studies identified	20	30
Effect sizes extracted	20	30
Web searches	25	40
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 | 25 | 40 | BLOCKED |
| Quality assessed | 0 | 15 | 30 | BLOCKED |
</HARD-GATE>

Available Tactics

Tactic	When to Use
effect-size-extraction	After study identification, extract paired effect sizes
quality-assessment-protocol	Assess RoB for each included study
evidence-synthesis-planning	After extraction, plan the statistical model

Available SOPs

SOP	When to Use
pico-formulation	First — frame the comparison question
inclusion-criteria-design	After PICO — define what studies qualify
effect-size-planning	Determine which effect size metric to use
data-extraction-form	Design the extraction template
risk-of-bias-assessment	Per-study quality assessment
sensitivity-analysis-design	Plan robustness checks
publication-bias-assessment	Assess reporting bias
meta-analysis-synthesis	Final protocol assembly

Execution Guidance

Frame — Run pico-formulation to structure the comparison
Scope — Run inclusion-criteria-design to define eligibility
Search — Use dare-scholar and dare-ss to find candidate studies
Extract — Use effect-size-extraction tactic for each study
Assess — Use quality-assessment-protocol tactic for bias risk
Plan — Use evidence-synthesis-planning tactic for model selection
Synthesize — Run meta-analysis-synthesis to produce protocol

Iterate steps 3-5 until budget floor is met. Check state ledger before each iteration.

Output Format

protocol:
  question: [PICO-structured question]
  inclusion_criteria: [eligibility rules]
  studies_included: [list with metadata]
  effect_size_type: [SMD/OR/RR/MD]
  model: [fixed-effect/random-effects]
  heterogeneity_plan: [I2, tau2, subgroup, meta-regression]
  sensitivity_plan: [leave-one-out, influence diagnostics]
  bias_assessment_plan: [funnel plot, Egger's, trim-and-fill]
  reporting: PRISMA-2020

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
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