effect-size-extraction

Research

Systematically extract effect sizes and conditions from papers for meta-analytic synthesis

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Effect Size Extraction Tactic

Systematically extract quantitative effect sizes, study conditions, and precision metrics from included studies.

Stages

Stage 1: Paper Identification

Identify the specific sections of each paper containing quantitative results.

Locate results tables, figures, and statistical reporting sections
Identify primary and secondary outcomes
Flag studies reporting insufficient statistics for effect size calculation

Tools: dare-scholar (paper_content, paper_reading), alphaxiv (answer_pdf_queries)

Stage 2: Data Point Location

For each study, locate the exact data points needed for effect size calculation.

Sample sizes per group (N treatment, N control)
Central tendency (means, proportions, hazard ratios)
Variability (SD, SE, CI, IQR)
Test statistics (t, F, chi-square, z) when direct data unavailable
p-values as last resort for back-calculation

SOPs: effect-size-planning (determine what to extract)

Stage 3: Effect Size Calculation Planning

Plan the calculation method for each study based on available data.

Direct calculation from means + SDs
Conversion from test statistics (t → d, F → d, r → z)
Conversion between effect size families (OR ↔ d, r ↔ d)
Handling of multi-arm studies (shared control correction)
Cluster-adjusted effect sizes (design effect)

SOPs: effect-size-planning

Stage 4: Condition Recording

Record all study-level conditions and moderator variables.

Population characteristics (N, demographics, baseline severity)
Intervention details (dose, duration, delivery mode)
Comparison conditions (active control, placebo, waitlist)
Outcome measurement (tool, timing, blinding)
Study design features (randomization, allocation concealment)

SOPs: data-extraction-form

Stage 5: Quality Annotation

Annotate each extracted effect size with quality indicators.

Intention-to-treat vs per-protocol
Handling of missing data (complete case, imputation)
Outcome measurement reliability
Potential for selective reporting (registered vs reported)
Confidence in the extracted value (high/medium/low)

SOPs: risk-of-bias-assessment

Minimum Yield

Per execution of this tactic:

At least 5 studies processed
At least 5 effect sizes extracted or calculation planned
All moderator variables recorded for extracted studies
Quality annotation complete for all extractions

Output Format

extractions:
  - study_id: [identifier]
    effect_size_type: [SMD/OR/RR/MD/r]
    point_estimate: [value or calculation formula]
    precision: [SE/CI/variance]
    sample_size: [N_treatment, N_control]
    conditions: [moderator variables]
    quality: [high/medium/low confidence]
    notes: [calculation method, assumptions]

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
risk-of-bias-assessment	Assess methodological bias using RoB2, PROBAST, or QUADAS-2 validated tools