[coefficient-confidence] Coefficient Plot with Confidence Intervals

[MarkusNeusinger]

A coefficient plot displaying regression coefficients as points with horizontal error bars showing confidence intervals. Used to visualize effect sizes and statistical significance in regression models.

[claude]

✅ Spec ID: coefficient-confidence

Rationale: Describes a coefficient plot showing regression coefficients with confidence interval error bars - distinct from forest-basic (meta-analysis studies) and errorbar-basic (general data points).

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[github-actions]

✅ Specification Ready: coefficient-confidence

PR: #3578

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specification.md

coefficient-confidence: Coefficient Plot with Confidence Intervals

Description

A coefficient plot displays regression coefficients as points positioned along a horizontal axis, with horizontal error bars showing confidence intervals. This visualization makes it easy to assess effect sizes and statistical significance - coefficients whose confidence intervals cross zero are not statistically significant. Typically used to summarize results from linear, logistic, or other regression models in a clear, publication-ready format.

Applications

• Visualizing effect sizes and significance from multiple regression models
• Comparing predictor importance in linear or logistic regression analysis
• Presenting regression results in academic publications and reports
• Communicating which variables have significant effects in statistical models

Data

• variable (str) - Name of the predictor variable or coefficient
• coefficient (float) - Point estimate of the regression coefficient
• ci_lower (float) - Lower bound of the confidence interval
• ci_upper (float) - Upper bound of the confidence interval
• significant (bool, optional) - Whether the coefficient is statistically significant
• Size: 5-20 coefficients for optimal readability
• Example: Coefficients from a multiple linear regression predicting housing prices

Notes

• Vertical reference line at zero to indicate the null hypothesis threshold
• Variables typically ordered by coefficient magnitude for easier comparison
• Use different colors or markers to distinguish significant vs non-significant coefficients
• Horizontal layout (coefficients on y-axis, values on x-axis) preferred for readability with long variable names
• Include axis label indicating the effect measure (e.g., "Coefficient Estimate", "Log Odds Ratio")

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[github-actions]

🚀 Specification Merged!

Specification: coefficient-confidence
PR: #3578 (merged)

The specification is now in main and synced to PostgreSQL.

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Available libraries: matplotlib, seaborn, plotly, bokeh, altair, plotnine, pygal, highcharts, letsplot

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