--- name: jedpsych-tables-figures description: Use when building tables and figures for a Journal of Educational Psychology manuscript. JEP uses APA 7th-edition style and expects exhibits that report multilevel/SEM model results, effect sizes with uncertainty, and growth trajectories clearly, and that are anonymized for masked review. Designs exhibits; it does not run the analysis. --- # Tables & Figures (jedpsych-tables-figures) In the Journal of Educational Psychology, exhibits must carry the quantitative argument for **nested, model-based** results: multilevel/SEM estimates, **effect sizes with confidence intervals**, mediation paths, and growth trajectories. They follow **APA 7th-edition** conventions and — because review is **masked** — must not reveal author identity (school names, project sites, identifying acknowledgments). A good JEP figure makes the learning effect, its uncertainty, and its mechanism legible at a glance. ## When to trigger - Designing the main results table/figure (model results, mediation, growth) - Deciding what goes in the article vs. online supplemental material - A reviewer found an exhibit unclear, non-APA, or identity-revealing - Visualizing trajectories, variance components, and uncertainty (not just means) ## Principles 1. **Show model results, effect sizes, and uncertainty.** Tables report estimates with standard errors and **confidence intervals**, variance components/ICC for multilevel models, and fit indices for SEM — not just stars. Figures display trajectories or effects with CIs, not bare bar-of-means. 2. **Self-contained + APA 7th.** Titles, notes, variable definitions, Ns at each level, and units make each exhibit intelligible alone; follow APA 7th table/figure formatting (including a clear note row). 3. **Make the effect interpretable.** Where possible, annotate the educational meaning (months of progress, percentile shift, percent variance explained) so the magnitude is legible to readers and policy audiences. 4. **Earn the space.** Push secondary exhibits (full covariance matrices, every robustness model, measurement details) to **online supplemental material**; keep the article focused on the contribution. 5. **Anonymized + reproducible + accessible.** No identifying site/school names in exhibits or notes (masked review); values generated by the shared analysis script; colorblind-safe and grayscale-legible. ## Worked micro-example — the main results exhibits (illustrative) For the cluster-randomized reading trial, two exhibits carry the argument the prose summarizes. ``` Table 1. Two-level model of transfer comprehension. Rows: intercept, treatment (classroom level), pretest covariate, variance components (student, classroom), ICC. Columns: estimate, SE, 95% CI, standardized effect (g). Note: defines levels and Ns (48 classrooms, 1,089 students), the outcome metric, and that intervals are 95% CIs; no site names. Figure 1. Adjusted transfer-comprehension by condition, with mediation. Geometry: classroom means + 95% CI (dot/interval), NOT a bar of means; inset path diagram for the monitoring mediator (a, b, indirect). Annotation: g = 0.23, 95% CI [0.06, 0.40]; ~2.0 months of progress. Source: rendered by the deposited R script so values match Table 1. ``` ## Exhibit triage — article vs. online supplemental material | Exhibit | Home | Reason | |---------|------|--------| | Primary multilevel model + effect size with CI | main text | this is the contribution | | Mediation/moderation path result | main text | the mechanism is theory-central at JEP | | Full SEM covariance / measurement model | supplement | needed for rigor, not the headline | | Every robustness specification | supplement | summarize in one main-text sentence | | Item-level measure detail / fidelity tables | supplement | credibility, not the main claim | ## Exhibit-stage reviewer pushback and the venue fix - "Table reports only stars" → add SE, CI, and a standardized effect column; this is the post-reform expectation. - "Bar chart hides the spread" → switch to dot/interval with 95% CIs; show cluster means where N allows. - "No ICC / variance components shown" → report them; reviewers check that nesting was modeled. - "Figure names the school district" → strip identifying labels for masked review. - "Figure values don't match Table 1" → regenerate both from the single deposited script. ## Exhibit calibration anchors - Because JEP results are model-based, the table is where the nesting (ICC, variance components) and the effect size with its CI actually live; design it to stand alone if an editor reads only the exhibits. - A growth figure should show trajectories with uncertainty bands, not just endpoint means; a mediation figure should make the indirect path and its CI visible. - Masked review is easy to break in exhibits — site names, IRB identifiers, or a recognizable program logo in a figure can de-anonymize the paper; scrub them. - Accessibility is part of credibility: colorblind-safe palettes and grayscale-legible encodings. ## 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). JEdPsych mixes field/lab experiments and observational school data; multilevel (student-in-class-in-school) inference and many-outcome corrections matter most. - **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 nesting - Tables reporting only stars/p-values with no effect size, SE, or CI - Omitting ICC / variance components for a multilevel result - Identity-revealing labels (school, district, site) during masked review - Exhibit values that don't match the shared analysis script ## Output format ``` 【Main exhibit】what it shows + why a table/figure 【Model detail】effect size + CI + variance components/ICC (or SEM fit)? [Y/N] 【Educational meaning】magnitude annotated (months/percentile/variance)? [Y/N] 【APA 7th + self-contained + anonymized?】[Y/N] 【Article vs supplement】split decided 【Reproducible + accessible?】matches script, grayscale/colorblind-safe? [Y/N] 【Next】jedpsych-writing-style ``` ## Supplementary resources - [`../../resources/external_tools.md`](../../resources/external_tools.md) — `papaja`, `ggplot2`, plotting and APA-table tooling - [`../../resources/official-source-map.md`](../../resources/official-source-map.md) — APA 7th style and masked-review requirement