influencePlot: Regression Influence Plot

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/influencePlot.R

Description

This function creates a “bubble” plot of Studentized residuals versus hat values, with the areas of the circles representing the observations proportional to the value Cook's distance. Vertical reference lines are drawn at twice and three times the average hat value, horizontal reference lines at -2, 0, and 2 on the Studentized-residual scale.

Usage

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influencePlot(model, ...)

## S3 method for class 'lm'
influencePlot(model, scale=10,  
 xlab="Hat-Values", ylab="Studentized Residuals", id=TRUE, ...)

## S3 method for class 'lmerMod'
influencePlot(model, ...)

Arguments

model

a linear, generalized-linear, or linear mixed model; the "lmerMod" method calls the "lm" method and can take the same arguments.

scale

a factor to adjust the size of the circles.

xlab, ylab

axis labels.

id

settings for labelling points; see link{showLabels} for details. To omit point labelling, set id=FALSE; the default, id=TRUE is equivalent to id=list(method="noteworthy", n=2, cex=1, col=carPalette()[1], location="lr"). The default method="noteworthy" is used only in this function and indicates setting labels for points with large Studentized residuals, hat-values or Cook's distances. Set id=list(method="identify") for interactive point identification.

...

arguments to pass to the plot and points functions.

Value

If points are identified, returns a data frame with the hat values, Studentized residuals and Cook's distance of the identified points. If no points are identified, nothing is returned. This function is primarily used for its side-effect of drawing a plot.

Author(s)

John Fox jfox@mcmaster.ca, minor changes by S. Weisberg sandy@umn.edu

References

Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.

Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.

See Also

cooks.distance, rstudent, hatvalues, showLabels

Examples

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influencePlot(lm(prestige ~ income + education, data=Duncan))
## Not run: 
influencePlot(lm(prestige ~ income + education, data=Duncan), 
    id=list(method="identify"))

## End(Not run)

Example output

Loading required package: carData
               StudRes        Hat      CookD
minister     3.1345186 0.17305816 0.56637974
reporter    -2.3970224 0.05439356 0.09898456
conductor   -1.7040324 0.19454165 0.22364122
RR.engineer  0.8089221 0.26908963 0.08096807

car documentation built on June 27, 2021, 5:07 p.m.