network-comparison

Research

Compare N methods simultaneously including indirect evidence — network meta-analysis protocol design. Budget: 50 studies, 80 effect sizes, 60 web searches.

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Network Comparison Strategy

Design a network meta-analysis (NMA) protocol comparing N>=3 methods simultaneously, leveraging both direct and indirect evidence.

Purpose

When multiple methods have been compared in various head-to-head studies but no single study compares all methods, network meta-analysis synthesizes direct and indirect evidence to rank all methods simultaneously. This strategy produces the complete NMA protocol.

Budget

Resource	Floor	Target
Studies identified	35	50
Effect sizes extracted	55	80
Web searches	40	60
Network nodes (methods)	3	N
Quality assessments	25	50

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

State Ledger

<HARD-GATE>
| Metric | Current | Floor | Target | Status |
|--------|---------|-------|--------|--------|
| Studies found | 0 | 35 | 50 | BLOCKED |
| Effect sizes planned | 0 | 55 | 80 | BLOCKED |
| Web searches done | 0 | 40 | 60 | BLOCKED |
| Network nodes | 0 | 3 | N | BLOCKED |
| Quality assessed | 0 | 25 | 50 | BLOCKED |
</HARD-GATE>

Available Tactics

Tactic	When to Use
effect-size-extraction	Extract effect sizes from each study arm
quality-assessment-protocol	Assess RoB + CINeMA framework for NMA
evidence-synthesis-planning	Plan NMA model (consistency, ranking)

Available SOPs

SOP	When to Use
pico-formulation	Frame the multi-method comparison
inclusion-criteria-design	Define eligibility across all comparisons
effect-size-planning	Standardize effect sizes across study designs
data-extraction-form	Multi-arm extraction template
risk-of-bias-assessment	Per-study + network-level bias
evidence-network-construction	Build the network geometry graph
heterogeneity-source-analysis	Assess transitivity assumption
sensitivity-analysis-design	Node-splitting, exclusion sensitivity
publication-bias-assessment	Comparison-adjusted funnel plots
meta-analysis-synthesis	Final NMA protocol assembly

Execution Guidance

Frame — Run pico-formulation for the multi-method question
Scope — Run inclusion-criteria-design covering all treatment nodes
Search — Systematic search for all pairwise comparisons
Network — Run evidence-network-construction to map the geometry
Extract — Use effect-size-extraction tactic per study arm
Assess — Use quality-assessment-protocol (RoB2 + CINeMA)
Transitivity — Run heterogeneity-source-analysis to verify transitivity
Plan — Use evidence-synthesis-planning for NMA model selection
Synthesize — Run meta-analysis-synthesis for final protocol

Iterate steps 3-6 until budget floor met. Verify network connectivity after each batch.

Output Format

protocol:
  question: [PICO with multiple interventions]
  network_geometry:
    nodes: [list of methods/interventions]
    edges: [direct comparisons available]
    connected: [yes/no]
  inclusion_criteria: [eligibility rules]
  studies_included: [list with arm-level metadata]
  effect_size_type: [standardized across network]
  model: [consistency/inconsistency NMA model]
  transitivity_assessment: [effect modifiers balanced?]
  ranking_method: [SUCRA/P-score/mean ranks]
  heterogeneity_plan: [global I2, tau2, between-design heterogeneity]
  inconsistency_plan: [node-splitting, design-by-treatment interaction]
  sensitivity_plan: [network reduction, node exclusion]
  bias_assessment_plan: [comparison-adjusted funnel, small-study effects]
  reporting: PRISMA-NMA extension

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
evidence-network-construction	Build evidence network graph for network meta-analysis — nodes, edges, geometry assessment
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