--- 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