技能 数据科学 学术研究展示图表最佳实践

学术研究展示图表最佳实践

v20260724
pubar-tables-figures
本指南提供了学术论文的图表设计最佳实践。它指导用户创建自包含、易于理解且专业展示的研究展示图表。核心目标是确保图表能清晰地传达效应大小和不确定性,服务于学术专家和公共政策实践者双方的需求。
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概览

Tables & Figures (pubar-tables-figures)

Exhibits are where an expert reviewer checks whether the result is real — and where a practitioner reads the magnitude that drives your Evidence for Practice. At PAR the word count excludes tables, figures, charts, and appendices (检索于 2026-06;以官网为准), so the constraint is clarity, not word budget: every exhibit must communicate a magnitude with its uncertainty, fast.

When to trigger

  • Designing the main results table/figure or a key descriptive exhibit
  • Deciding what belongs in the article vs. an online appendix/supplement
  • A reviewer found an exhibit unclear, mislabeled, or non-self-contained
  • Translating a coefficient into something a public manager can read

Principles

  1. Self-contained. A reader should understand each exhibit from its title, axis/column labels, and note alone. State units, sample, N, the estimator, and what the estimate is.
  2. Figures over dense tables for effects. Coefficient/forest plots, marginal-effects and predicted-probability plots, event-study and RD plots communicate magnitude and uncertainty better than a wall of coefficients. Show intervals — a practitioner needs the effect size, not stars.
  3. Accessible. Colorblind-safe palettes; legible in grayscale; no chartjunk, no 3D, no needless color. Reviewers and practitioner readers must parse it quickly.
  4. Main text vs. supplement. Keep the few exhibits that carry the argument in the article; move balance tables, full specifications, and robustness grids to the online supplement.
  5. Reproducible. Each exhibit is generated by the master script; numbers match the deposited materials exactly (TOP transparency — see pubar-transparency-and-data).

PA-specific exhibits

  • Event-study plots around a reform to show pre-trends and dynamics of an administrative change.
  • Predicted-probability / marginal-effects plots translating a model into managerial terms ("an agency at the 75th percentile of red tape is X points less likely to…").
  • Maps for cross-jurisdiction variation; network diagrams for collaborative-governance structure.
  • For qualitative/mixed work: process timelines, evidence tables linking claims to sources.

Execution bridge (StatsPAI / Stata MCP)

Generate exhibits from the fitted result, not by retyping numbers. Full map: execution-with-mcp. PAR is public administration — survey/observational and some experimental work; identification + clustered/multilevel inference, magnitude for practice.

  • Tables: etable (multi-model) 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 magnitude in interpretable units.

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

Anti-patterns

  • Tables that require the prose to be intelligible (not self-contained)
  • Reporting significance stars with no effect size or interval (practitioners can't act on it)
  • Cramming every robustness check into the main text (use the supplement)
  • Color-only encoding that fails in grayscale or for colorblind readers
  • Exhibit numbers/values that don't match the deposited code output

Output format

【Main exhibit】what it shows + why a figure/table
【Self-contained?】title + labels + note + N/units/estimator present? [Y/N]
【Magnitude legible to a manager?】effect size + interval shown? [Y/N]
【Accessible?】grayscale-legible + colorblind-safe? [Y/N]
【Article vs supplement】split decided
【Reproducible?】generated by master script, matches package? [Y/N]
【Next】pubar-writing-style

Referee-pushback patterns and the PAR fix

  • "I can't read the magnitude — the table is all stars." → Replace stars-only cells with effect sizes and intervals; add a marginal-effects or predicted-probability plot so a practitioner sees the size.
  • "The exhibit isn't self-contained." → Put the sample, N, units, estimator, and what the estimate is into the title and note, so the figure stands alone without the prose.
  • "This figure fails in grayscale / for colorblind readers." → Switch to a colorblind-safe palette and encode with shape/linetype, not color alone; check the grayscale print.
  • "The main text is buried under robustness tables." → Keep the few exhibits that carry the argument in the article and move balance/robustness grids to the online supplement.
  • "Numbers don't match the deposited code." → Regenerate every exhibit from the master script so the printed values and the deposited materials are identical (see pubar-transparency-and-data).

Calibration anchors (hedged)

  • A PAR exhibit serves two readers: an expert checking whether the result is real, and a practitioner reading the magnitude that drives the Evidence for Practice. Design for both.
  • Because the word count excludes tables, figures, charts, and appendices (检索于 2026-06;以官网为准), use the supplement freely for secondary exhibits — but keep the main argument to a few decisive ones.
  • Confirm the current figure/table formatting and file-type requirements on the journal's author page; Wiley production specs evolve.

Supplementary resources

信息
Category 数据科学
Name pubar-tables-figures
版本 v20260724
大小 6.09KB
更新时间 2026-07-29
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