R: Spread-Level Plots

spreadLevelPlot {car}

R Documentation

Spread-Level Plots

Description

Creates plots for examining the possible dependence of spread on level, or an extension of these plots to the studentized residuals from linear models.

Usage

spreadLevelPlot(x, ...)

slp(...)

## S3 method for class 'formula'
spreadLevelPlot(x, data=NULL, subset, na.action, 
    main=paste("Spread-Level Plot for", varnames[response], 
    "by", varnames[-response]), ...)

## Default S3 method:
spreadLevelPlot(x, by, robust.line=TRUE, 
	start=0, xlab="Median", ylab="Hinge-Spread", point.labels=TRUE, las=par("las"),
	main=paste("Spread-Level Plot for", deparse(substitute(x)), 
		"by", deparse(substitute(by))), col=palette()[1], col.lines=palette()[2],
    pch=1, lwd=2, grid=TRUE, ...)

## S3 method for class 'lm'
spreadLevelPlot(x, robust.line=TRUE, 
	xlab="Fitted Values",
	ylab="Absolute Studentized Residuals", las=par("las"),
	main=paste("Spread-Level Plot for\n", deparse(substitute(x))),
	pch=1, col=palette()[1], col.lines=palette()[2], lwd=2, grid=TRUE, ...)
	  
## S3 method for class 'spreadLevelPlot'
print(x, ...)

Arguments

`x`	a formula of the form `y ~ x`, where `y` is a numeric vector and `x` is a factor, or an `lm` object to be plotted; alternatively a numeric vector.
`data`	an optional data frame containing the variables to be plotted. By default the variables are taken from the environment from which `spreadLevelPlot` is called.
`subset`	an optional vector specifying a subset of observations to be used.
`na.action`	a function that indicates what should happen when the data contain `NA`s. The default is set by the `na.action` setting of `options`.
`by`	a factor, numeric vector, or character vector defining groups.
`robust.line`	if `TRUE` a robust line is fit using the `rlm` function in the `MASS` package; if `FALSE` a line is fit using `lm`.
`start`	add the constant `start` to each data value.
`main`	title for the plot.
`xlab`	label for horizontal axis.
`ylab`	label for vertical axis.
`point.labels`	if `TRUE` label the points in the plot with group names.
`las`	if `0`, ticks labels are drawn parallel to the axis; set to `1` for horizontal labels (see `par`).
`col`	color for points; the default is the first entry in the current color palette (see `palette` and `par`).
`col.lines`	color for lines; default is the second entry in the current palette
`pch`	plotting character for points; default is `1` (a circle, see `par`).
`lwd`	line width; default is `2` (see `par`).
`grid`	If TRUE, the default, a light-gray background grid is put on the graph
`...`	arguments passed to plotting functions.

Details

Except for linear models, computes the statistics for, and plots, a Tukey spread-level plot of log(hinge-spread) vs. log(median) for the groups; fits a line to the plot; and calculates a spread-stabilizing transformation from the slope of the line.

For linear models, plots log(abs(studentized residuals) vs. log(fitted values).

The function slp is an abbreviation for spreadLevelPlot.

Value

An object of class spreadLevelPlot containing:

`Statistics`	a matrix with the lower-hinge, median, upper-hinge, and hinge-spread for each group. (Not for an `lm` object.)
`PowerTransformation`	spread-stabilizing power transformation, calculated as 1 - slope of the line fit to the plot.

Author(s)

John Fox jfox@mcmaster.ca

References

Fox, J. (2008) Applied Regression Analysis and Generalized Linear Models, Second Edition. Sage.

Fox, J. and Weisberg, S. (2011) An R Companion to Applied Regression, Second Edition, Sage.

Hoaglin, D. C., Mosteller, F. and Tukey, J. W. (Eds.) (1983) Understanding Robust and Exploratory Data Analysis. Wiley.

Examples

spreadLevelPlot(interlocks + 1 ~ nation, data=Ornstein)
slp(lm(interlocks + 1 ~ assets + sector + nation, data=Ornstein))

[Package car version 2.0-12 Index]