Agent Skills
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cogpsych-tables-figures
GitHub专为Cognitive Psychology期刊设计，指导构建以模型拟合数据为核心的图表。强调展示分布、不确定性及参数估计，避免仅显示均值条形图。涵盖主图设计、模型对比表制作及正文与附录的内容分配决策。
Trigger Scenarios
设计展示模型拟合效果的主图或模型对比表
决定图表应置于正文还是补充材料
审稿人要求展示拟合而非仅均值
可视化数据分布、个体数据及模型预测的不确定性
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cogpsych-tables-figures -g -y
SKILL.md
Frontmatter
{
"name": "cogpsych-tables-figures",
"description": "Use when building tables and figures for a Cognitive Psychology (Elsevier) manuscript. Exhibits here carry the experiment-to-model-fit argument — they should overlay model predictions on data, show distributions and uncertainty, and report parameter estimates, not just bars of means. Designs exhibits; it does not run the analysis or fit the model."
}
Tables & Figures (cogpsych-tables-figures)
In Cognitive Psychology the central exhibit usually shows the model fitting the data — observed patterns with the model's predictions overlaid — because the contribution is the model, not the bare effect. Exhibits should reveal distributions and uncertainty, report parameter estimates with intervals, and let a reader judge model comparison at a glance. Bars of means hide exactly what this venue cares about.
When to trigger
- Designing the main model-fit figure or a model-comparison table
- Deciding what goes in the article vs. the supplementary material / appendix
- A reviewer found an exhibit unclear, or said "show the fit, not just the means"
- Visualizing distributions, individual data, model predictions, and uncertainty
Principles
- Overlay model on data. The headline figure shows observed data (with uncertainty) and the model's predicted curve/points superimposed, ideally for the rival model too, so the reader sees which account tracks the data. This is the venue's signature exhibit.
- Show the data and uncertainty. Prefer distributions/individual points with means and confidence/credible intervals over bar-of-means plots; for model parameters, plot estimates with intervals.
- Make model comparison legible. A table reports each model's fit (AIC/BIC/BF or cross-validated score), free-parameter count, and the winning criterion — so the comparison is checkable, not asserted.
- Self-contained. Titles, notes, axes, Ns, trial counts, units, and "intervals are 95% CIs/CrIs" make each exhibit intelligible alone, following the journal's (Elsevier/APA-style) conventions.
- Reproducible + accessible. Generated by the deposited model/analysis code so values match; colorblind-safe and grayscale-legible.
Worked micro-example — the main model-fit figure (illustrative)
For the recognition-memory program, the primary figure must show the fit, not the means.
Figure 1. Observed and model-predicted z-ROCs, Experiments 1-3.
Geometry: observed confidence-ROC points with 95% CIs, UVSD predicted
curve overlaid (solid) and DPSD predicted curve overlaid
(dashed) — the reader sees UVSD track the linear z-ROC.
Panels: one per experiment; shared axes for comparison.
Annotation: z-ROC slope 0.78 [0.72, 0.84]; dBIC = 14 favoring UVSD.
Note: defines the ROC metric, Ns, trials/bin, exclusion count, and
that bands are 95% intervals - readable without the main text.
Source: rendered by the deposited model-fitting script so values match.
Table 1. Model comparison: free parameters, -2logL, AIC, BIC, BF, by model.
Exhibit triage — article vs. supplementary material
| Exhibit | Home | Reason |
|---|---|---|
| Observed data + model fit (headline) | main text | this is the contribution |
| Model-comparison table (criteria + k) | main text | the comparison must be checkable |
| Parameter-recovery / model-recovery plots | supplement | needed for credibility, not the headline |
| Full per-subject fits | supplement | costs space, secondary to the group story |
| Stimulus lists / counterbalancing tables | supplement / materials deposit | provenance, not narrative |
Exhibit-stage reviewer pushback and the venue fix
- "Bar chart hides the spread" → switch to distribution/points + intervals; show individual data where N allows.
- "Show the fit, not the means" → overlay model predictions (and the rival's) on the observed data.
- "I can't compare the models from this" → add the model-comparison table with criteria and parameter counts.
- "Figure values don't match Table 1" → regenerate both from the single deposited model script.
Exhibit calibration anchors
- The figure that wins a Cognitive Psychology paper is the one where the reader sees one model track the data and the rival miss; design for that, not for a decorative bar chart.
- Show parameter estimates with intervals so the model's psychological claims are inspectable, and put recovery plots in the supplement so the comparison is trustworthy.
- Make the model-comparison table do real work: free-parameter counts and a penalized criterion guard against the "better fit = overfitting" objection before a reviewer raises it.
- Accessibility is part of credibility: colorblind-safe palettes and grayscale-legible line styles so the model-vs-data distinction survives printing.
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. Cognitive Psychology is experimental — within-subject designs and mixed models dominate; report the model, the effect size, and multiple-comparison control.
- Tables:
etable(multi-model columns) ordid_summary_to_latexstraight from theresult_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
- Bar plots of means that hide distribution, uncertainty, and the fit
- A results figure with no model overlay in a model-driven paper
- Asserting a model "fits best" with no comparison table (criteria + parameter counts)
- Exhibits that need the prose to be intelligible (not self-contained)
- Figure/table values that don't match the deposited model code
Output format
【Main exhibit】observed data + model fit (and rival)? [Y/N]
【Shows distribution + uncertainty + parameter intervals?】[Y/N]
【Model-comparison table】criteria + free-parameter counts? [Y/N]
【Self-contained + accessible?】notes, Ns, trials, grayscale/colorblind-safe? [Y/N]
【Reproducible?】matches deposited model script? [Y/N]
【Next】cogpsych-writing-style
Supplementary resources
../../resources/external_tools.md— plotting tools, model-fit visualization, recovery plots../../resources/official-source-map.md— exhibit and house-style expectations
Version History
- 1839142 Current 2026-07-05 12:37
