// Plan the statistical synthesis approach — model selection, heterogeneity strategy, and reporting
| name | evidence-synthesis-planning |
| description | Plan the statistical synthesis approach — model selection, heterogeneity strategy, and reporting |
| execution | tactic |
| used-by | meta-analysis |
Plan the complete statistical synthesis approach: effect size standardization, model selection, heterogeneity quantification, sensitivity analyses, and PRISMA-compliant reporting.
Determine the appropriate effect size metric for the synthesis.
| Outcome Type | Effect Size | When |
|---|---|---|
| Continuous (same scale) | Mean Difference (MD) | All studies use same measurement |
| Continuous (different scales) | Standardized Mean Difference (SMD) | Studies use different instruments |
| Binary | Odds Ratio (OR) / Risk Ratio (RR) | Dichotomous outcomes |
| Time-to-event | Hazard Ratio (HR) | Survival data |
| Correlation | Fisher's z (transformed r) | Association studies |
| Count/rate | Incidence Rate Ratio (IRR) | Event rate data |
SOPs: effect-size-planning
Choose between fixed-effect and random-effects models.
Decision tree: If studies are clinically homogeneous AND methodologically identical → fixed-effect. Otherwise → random-effects with REML + Knapp-Hartung.
Plan heterogeneity quantification and investigation.
SOPs: heterogeneity-source-analysis
Design robustness checks for the primary analysis.
SOPs: sensitivity-analysis-design
Design PRISMA-2020 compliant reporting.
Per execution of this tactic:
synthesis_plan:
effect_size:
type: [SMD/OR/RR/MD/HR/z]
justification: [why this metric]
conversions_needed: [any transformations]
model:
type: [fixed-effect/random-effects]
estimator: [IV/MH/REML/DL/PM]
adjustment: [Knapp-Hartung/none]
justification: [rationale]
heterogeneity:
metrics: [I2, tau2, Q, prediction interval]
investigation:
subgroups: [list of categorical moderators]
meta_regression: [list of continuous moderators]
minimum_k_per_subgroup: [threshold]
sensitivity:
- leave_one_out
- influence_diagnostics
- alternative_model
- rob_exclusion
- [additional pre-specified]
reporting:
standard: PRISMA-2020
registration: [PROSPERO ID or plan]
grade_domains: [risk_of_bias, inconsistency, indirectness, imprecision, publication_bias]
SOTA Performance Baseline Campaign — 5 strategies for systematically collecting, standardizing, and analyzing performance data across methods. Produces standardized comparison tables, progress curves, and headroom analysis.
Assess systematic biases in the evidence body — publication bias, reporting bias, and selective outcome reporting. Budget: 40 studies, 40 effect sizes, 40 web searches.
Track evidence accumulation over time — cumulative meta-analysis protocol design. Budget: 40 studies, 40 effect sizes, 30 web searches.
Design structured data extraction form for systematic meta-analysis data collection
Systematically extract effect sizes and conditions from papers for meta-analytic synthesis
Determine effect size types and calculation methods for meta-analytic synthesis