Regression & Modeling · TOOL GUIDE

Log-Linear Analysis

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Understand the method. Use it with confidence.

Analyze relationships between categorical variables. Quantly runs the method against your active analysis context and returns structured results for review and interpretation.

01

When to use it

Use this tool to quantify relationships, explain variation, or predict an outcome from one or more features.
Use it only when the selected variables and study design match the method's requirements.

02

How to use it

  1. Open the tool from the Quantly Tools panel.
  2. Confirm the active dataset and analysis session.
  3. Set Categorical Variables (Required): Select two or more categorical columns to analyze.
  4. Set Stabilize for Zero Counts (Optional): Adds a small constant (0.5) to all cell counts. This is a standard method to prevent errors when some combinations of categories have zero observations.
  5. Set Generate Mosaic Plot (Optional): Visualize observed frequencies. Available for 2 or 3 variables.
  6. Set Generate Coefficient Plot (Optional): Plot the coefficients and confidence intervals for the best-fitting model.
  7. Set Generate Residuals Heatmap (Optional): Visualize where the best model's predictions differ from observed counts. Available for 2 or 3 variables.
  8. Set Generate Interaction Plot (Optional): Visualize a three-way interaction. Available only for 3 variables.
  9. Review optional or advanced settings and keep defaults unless your design requires a change.
  10. Run the tool, inspect warnings and diagnostics, then save or export the result with its assumptions.
03

How to interpret results

Review coefficients or feature effects, uncertainty, validation metrics, residual diagnostics, and leakage risk. Association is not causation, and performance should be evaluated on data not used for fitting.