car (version 1.0-4)

leverage.plots: Regression Leverage Plots

Description

These functions display a generalization, due to Sall (1990), of added-variable plots to multiple-df terms in a linear model. When a term has just 1 df, the leverage plot is a rescaled version of the usual added-variable (partial-regression) plot.

Usage

leverage.plots(model, term.name, ask=missing(term.name), ...)

leverage.plot(model, ...)

leverage.plot.lm(model, term.name, 
  labels=names(residuals(model)[!is.na(residuals(model))]),  
  identify.points=TRUE, las=par('las'), col=palette()[2], pch=1, lwd=2, 
  main="Leverage Plot", ...)

leverage.plot.glm(model, ...)

Arguments

model
model object produced by lm
term.name
name of term in the model to be plotted; this argument is usually omitted for leverage.plots.
ask
if TRUE, a menu is provided in the R Console for the user to select the term(s) to plot.
labels
observation names.
identify.points
if TRUE, then identify points interactively.
las
if 0, ticks labels are drawn parallel to the axis; set to 1 for horizontal labels (see par).
col
color for points and lines; the default is the second entry in the current color palette (see palette and par).
pch
plotting character for points; default is 1 (a circle, see par).
lwd
line width; default is 2 (see par).
main
title for plot.
...
arguments passed down to method functions.

Value

  • NULL. These functions are used for their side effect: producing plots.

Details

The function intended for direct use is leverage.plots. By default, this function is used interactively through a text menu. The model can contain factors and interactions. A leverage plot can be drawn for each term in the model, including the constant. leverage.plot.glm is a dummy function, which generates an error message.

References

Fox, J. (1997) Applied Regression, Linear Models, and Related Methods. Sage. Sall, J. (1990) Leverage plots for general linear hypotheses. American Statistician 44, 308--315.

See Also

av.plots

Examples

Run this code
data(Duncan)
leverage.plots(lm(prestige~(income+education)*type, data=Duncan))

Run the code above in your browser using DataCamp Workspace