Answers are grounded in this paper and cite their sources.
An added-variable plot is an effective way to show the correlation between an independent variable and a dependent variable conditional on other independent variables. For multivariate estimation, a simple scatterplot showing x versus y is not adequate to show the partial correlation of x with y, because it ignores the impact of the other covariates. Added-variable plots are especially effective for showing the correlation of a dummy x variable with y because the dummy variable conditional on other covariates becomes a continuous variable, making the relationship easier to visualize. Added-variable plots are also useful for spotting influential outliers in the data that affect the estimated regression parameters. Stata provides added-variable plots after ordinary least-squares regressions with the avplot command. I present a new command, avciplot, that adds a confidence interval and other options to the avplot command.
No takes yet. Share an insight, caveat, or question.
John L. Gallup (2019) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: