Cogpsych Tables Figures

---
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

1. **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.
2. **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.
3. **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.
4. **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.
5. **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`](../../../shared-resources/empirical-methods/execution-with-mcp.md). 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) 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](../../../Journal-of-Finance-Skills/resources/worked-examples/02-execution-walkthrough.md).
## 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`](../../resources/external_tools.md) — plotting tools, model-fit visualization, recovery plots
- [`../../resources/official-source-map.md`](../../resources/official-source-map.md) — exhibit and house-style expectations