An added-variable plot (also called a partial regression plot) is a regression diagnostic scatterplot that isolates the relationship between one predictor variable and the response by plotting the residuals of the response regressed on all other predictors against the residuals of that single predictor regressed on all other predictors. It allows inspection of linearity, outliers, and influential points for each covariate independently of the full model. The chart persists through statistical software implementations (R, Python, SAS), textbooks, and academic practice. [formal: en | substrate: mind | horizon: a moment | explicit: yes | epoch: 0.01]
Accepted ontology entry
added-variable plot
An added-variable plot (also called a partial regression plot) is a regression diagnostic scatterplot that isolates the relationship between one predictor variable and the response by plotting the residuals of the response regressed on all…
Definition
Why it is in scope
A human-made regression diagnostic visualization that shows the relationship between a single predictor and the response, after accounting for all other predictors in the model — also called a partial regression plot. Built to persist as a chart type in statistical practice and textbooks.
Names and aliases
- added-variable ploten · CANONICAL
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An added-variable plot (partial regression plot) is a specific kind of diagnostic plot — it visualizes the relationship between a response variable and one predictor, adjusting for other predictors, to diagnose model specification. A competent speaker calls it a diagnostic plot. Nearest kind confirmed as diagnostic plot.
- cmskx1k6305p8nobpedwgz05sDERIVED_FROM →
Added-variable plots (partial regression plots) were developed within regression diagnostics to visualize the marginal contribution of each predictor in a multiple regression. Historical: emerged from regression methodology.
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Record identity
- Created
- Aug 8, 2026, 1:20 PM UTC
- Content hash
- a3da139b1cac4d7e0860860baa05e712ab3d6bb9466d1434d845f47dae5dd3cc