Psychbull tables figures

Tables & Figures (psychbull-tables-figures)

A meta-analysis communicates through a small set of standard, expected exhibits. Psychological Bulletin reviewers look for a PRISMA flow diagram, a forest plot, funnel/bias plots, and MARS-ready summary tables, all in APA 7th-edition format. This skill covers exhibit design; the numbers come from the analysis skills.

When to trigger

• Building the figures and tables for the manuscript
• A reviewer asks for the PRISMA diagram, forest plot, or a study-characteristics table
• Making exhibits self-contained, accessible, and reproducible from the deposited scripts

The expected exhibits

1. PRISMA flow diagram — records identified → deduplicated → screened → full-text assessed → included, with exclusion counts and reasons at each stage (matches the search log).
2. Forest plot — each study's effect size and CI, its weight, and the pooled estimate with CI and (ideally) a prediction interval; order meaningfully (by year, effect, or subgroup).
3. Funnel plot (contour-enhanced) and any bias-diagnostic plots (e.g., PET-PEESE regression).
4. Moderator / meta-regression bubble plot — effect vs. continuous moderator, point size ∝ weight.
5. Study-characteristics table — one row per study: design, n, population, measures, effect size, moderator codes — the backbone of a MARS-compliant report.
6. Summary-of-findings table — pooled effect, CI, k, I²/τ², prediction interval, bias results.

APA 7th & accessibility

• APA 7th table/figure format: numbered, titled, with notes defining abbreviations.
• Self-contained: readable without the text; define every symbol and effect-size metric.
• Colorblind-safe palettes; legible in grayscale; vector output (PDF/EPS) for print.
• Exhibits must regenerate from the deposited scripts and match the reported numbers.

Execution bridge (StatsPAI / Stata MCP)

Generate exhibits from the fitted result, not by retyping numbers (the usual source of body-vs-supplement drift). Full map: execution-with-mcp. Psychological Bulletin is a meta-analytic review venue.

• Tables: etable (multi-model columns) or did_summary_to_latex straight from the result_id.
• Figures: plot_from_result / enhanced_event_study_plot / event_study_table — axis units and the SE/clustering note baked in.
• Every note names the estimator + clustering and states the effect size in interpretable units.

See a full fitted-result → exhibit chain in the JF execution walkthrough.

Anti-patterns

• No PRISMA diagram, or counts that don't reconcile with the search log
• A forest plot without weights, pooled estimate, or a prediction interval
• A funnel plot presented as proof of (no) bias on its own
• A study table missing the inputs needed to recompute effect sizes
• Figures that can't be regenerated from the deposited code (numbers drift from text)

Exhibit expectations at the APA review flagship

Psychological Bulletin referees scan the exhibits before the prose: a synthesis missing its standard visual vocabulary signals an immature manuscript. The decision table they apply:

Exhibit	Referee expects	Common desk-reject pattern
PRISMA flow	Counts that reconcile to the search log and text	Diagram numbers that don't add up to the reported k
Forest plot	Per-study CI, weights, pooled diamond, prediction interval	A bare list of dots with no pooled estimate or PI
Funnel/bias	Contour-enhanced, paired with a formal test	Funnel alone, captioned "no bias" — over-reading a picture
Study table	One row per study, all effect-size inputs recoverable	Missing ns/SDs, so effect sizes cannot be reverified
Summary-of-findings	k, pooled g, CI, I²/τ², PI, bias result in one place	Scattered numbers a reader must reassemble

Worked vignette — what the exhibits must show

Illustrative figures, not real data. For the k = 42, g = 0.34, I² = 68% self-affirmation synthesis above, the exhibit set this skill requires looks like:

• PRISMA diagram: 2,310 identified → 1,640 after dedup → 1,640 screened → 188 full-text → 42 included; exclusion reasons tallied so the bottom box equals the analyzed k.
• Forest plot: 42 rows ordered by year, each with g and CI and an inverse-variance weight; a pooled diamond at 0.34 [0.24, 0.44] and a wider prediction interval roughly [−0.10, 0.78] that visibly exceeds the CI — making the 68% heterogeneity legible at a glance.
• Contour-enhanced funnel beside an Egger caption (p = 0.03), not standing alone as "proof."
• Bubble plot for the delivery-format moderator, point size proportional to weight.
• Summary-of-findings table: one line carrying k, g, CI, I², τ², prediction interval, and the trim-and-fill / selection-model sensitivity bounds.

Referee pushback → venue-specific fix

• "Your forest plot has no prediction interval." → Add the PI band; with I² = 68% the CI alone understates the spread of true effects.
• "PRISMA counts don't match the text." → Reconcile the diagram, the search log, and the reported k so every box is auditable.
• "The funnel plot is presented as evidence of no bias." → Re-caption as one diagnostic among several and cross-reference the Egger/selection-model results.

Output format

【PRISMA diagram】present + reconciles with search log? [Y/N]
【Forest plot】weights + pooled + prediction interval? [Y/N]
【Funnel / bias plots】present? [Y/N]
【Study-characteristics table】MARS-complete? [Y/N]
【APA 7th + accessible】numbered, colorblind-safe, vector? [Y/N]
【Reproducible】regenerates from scripts? [Y/N]
【Next】psychbull-writing-style

Supplementary resources

• ../../resources/external_tools.md — PRISMA flow diagram, metafor forest/funnel plots, exhibit tooling
• ../../resources/official-source-map.md — MARS/PRISMA reporting and APA 7th formatting