avPlots
Added-Variable Plots
These functions construct added-variable (also called partial-regression) plots for linear and generalized linear models.
- Keywords
- hplot, regression
Usage
avPlots(model, terms=~., intercept=FALSE, layout=NULL, ask, main, ...)avp(...)
avPlot(model, ...)
# S3 method for lm
avPlot(model, variable,
id.method = list(abs(residuals(model, type="pearson")), "x"),
labels,
id.n = if(id.method[1]=="identify") Inf else 0,
id.cex=1, id.col=palette()[1], id.location="lr",
col = palette()[1], col.lines = palette()[2],
xlab, ylab, pch = 1, lwd = 2,
main=paste("Added-Variable Plot:", variable),
grid=TRUE,
ellipse=FALSE, ellipse.args=NULL,
marginal.scale=FALSE, ...)
# S3 method for glm
avPlot(model, variable,
id.method = list(abs(residuals(model, type="pearson")), "x"),
labels,
id.n = if(id.method[1]=="identify") Inf else 0,
id.cex=1, id.col=palette()[1], id.location="lr",
col = palette()[1], col.lines = palette()[2],
xlab, ylab, pch = 1, lwd = 2, type=c("Wang", "Weisberg"),
main=paste("Added-Variable Plot:", variable), grid=TRUE,
ellipse=FALSE, ellipse.args=NULL, ...)
Arguments
- model
model object produced by
lm
orglm
.- terms
A one-sided formula that specifies a subset of the predictors. One added-variable plot is drawn for each term. For example, the specification
terms = ~.-X3
would plot against all terms except forX3
. If this argument is a quoted name of one of the terms, the added-variable plot is drawn for that term only.- intercept
Include the intercept in the plots; default is
FALSE
.- variable
A quoted string giving the name of a regressor in the model matrix for the horizontal axis
- layout
If set to a value like
c(1, 1)
orc(4, 3)
, the layout of the graph will have this many rows and columns. If not set, the program will select an appropriate layout. If the number of graphs exceed nine, you must select the layout yourself, or you will get a maximum of nine per page. Iflayout=NA
, the function does not set the layout and the user can use thepar
function to control the layout, for example to have plots from two models in the same graphics window.- main
The title of the plot; if missing, one will be supplied.
- ask
If
TRUE
, ask the user before drawing the next plot; ifFALSE
don't ask.- …
avPlots
passes these arguments toavPlot
.avPlot
passes them toplot
.- id.method,labels,id.n,id.cex,id.col,id.location
Arguments for the labelling of points. The default is
id.n=0
for labeling no points. SeeshowLabels
for details of these arguments.- col
color for points; the default is the second entry in the current color palette (see
palette
andpar
).- col.lines
color for the fitted line.
- pch
plotting character for points; default is
1
(a circle, seepar
).- lwd
line width; default is
2
(seepar
).- xlab
x-axis label. If omitted a label will be constructed.
- ylab
y-axis label. If omitted a label will be constructed.
- type
if
"Wang"
use the method of Wang (1985); if"Weisberg"
use the method in the Arc software associated with Cook and Weisberg (1999).- grid
If
TRUE
, the default, a light-gray background grid is put on the graph.- ellipse
If
TRUE
, plot a concentration ellipse; default isFALSE
.- ellipse.args
Arguments to pass to the
link{dataEllipse}
function, in the form of a list with named elements; e.g.,ellipse.args=list(robust=TRUE))
will cause the ellipse to be plotted using a robust covariance-matrix.- marginal.scale
Consider an added-variable plot of Y versus X given Z. If this argument is
FALSE
then the limits on the horizontal axis are determined by the range of the residuals from the regression of X on Z and the limits on the vertical axis are determined by the range of the residuals from the regressnio of Y on Z. If the argument isTRUE
, then the limits on the horizontal axis are determined by the range of X minus it mean, and on the vertical axis by the range of Y minus its means; adjustment is made if necessary to include outliers. This scaling allows visualization of the correlations between Y and Z and between X and Z. For example, if the X and Z are highly correlated, then the points will be concentrated on the middle of the plot.
Details
The function intended for direct use is avPlots
(for which avp
is an abbreviation).
Value
These functions are used for their side effect id producing plots, but also invisibly return the coordinates of the plotted points.
References
Cook, R. D. and Weisberg, S. (1999) Applied Regression, Including Computing and Graphics. Wiley.
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.
Wang, P C. (1985) Adding a variable in generalized linear models. Technometrics 27, 273--276.
Weisberg, S. (2014) Applied Linear Regression, Fourth Edition, Wiley.
See Also
residualPlots
, crPlots
, ceresPlots
, link{dataEllipse}
Examples
# NOT RUN {
avPlots(lm(prestige~income+education+type, data=Duncan))
avPlots(glm(partic != "not.work" ~ hincome + children,
data=Womenlf, family=binomial))
m1 <- lm(partic ~ tfr + menwage + womwage + debt + parttime, Bfox)
par(mfrow=c(1,3))
plot(partic ~ womwage, Bfox) # marginal plot, ignoring other predictors
abline(lm(partic ~ womwage, Bfox), col="red", lwd=2)
grid()
avPlots(m1, ~ womwage) # av Plot, adjusting for others
avPlots(m1, ~ womwage, marginal.scale=TRUE) # av Plot, adjusting and scaling as in marginal plot
# }