summary.eff {effects}R Documentation

Summarizing, Printing, and Plotting Effects

Description

summary, print, plot, and [ methods for eff, effpoly, and efflist objects.

Usage

## S3 method for class 'eff'
print(x, type=c("response", "link"), ...)
## S3 method for class 'effpoly'
print(x, type=c("probability", "logits"), ...)
## S3 method for class 'efflatent'
print(x, ...)
## S3 method for class 'efflist'
print(x, ...)
## S3 method for class 'summary.eff'
print(x, ...)
## S3 method for class 'eff'
summary(object, type=c("response", "link"), ...)
## S3 method for class 'effpoly'
summary(object, type=c("probability", "logits"), ...)
## S3 method for class 'efflatent'
summary(object, ...)
## S3 method for class 'efflist'
summary(object, ...)
## S3 method for class 'eff'
plot(x, x.var = which.max(levels), z.var = which.min(levels), 
    multiline = is.null(x$se), rug = TRUE, xlab, ylab, main = paste(effect, 
        "effect plot"), colors = palette(), symbols = 1:10, lines = 1:10, 
    cex = 1.5, ylim, factor.names = TRUE, type = c("response", 
        "link"), ticks = list(at = NULL, n = 5), alternating = TRUE, 
    rotx = 0, roty = 0, grid = FALSE, layout, rescale.axis = TRUE, 
    key.args = NULL, row = 1, col = 1, nrow = 1, ncol = 1, more = FALSE, 
    ...)
## S3 method for class 'effpoly'
plot(x, type = c("probability", "logit"), x.var = which.max(levels), 
    rug = TRUE, xlab, ylab = paste(x$response, " (", type, ")", 
        sep = ""), main = paste(effect, "effect plot"), colors, 
    symbols = 1:10, lines = 1:10, cex = 1.5, factor.names = TRUE, 
    style = c("lines", "stacked"), confint = (style == "lines" && 
        !is.null(x$confidence.level)), ylim, rotx = 0, alternating = TRUE, 
    roty = 0, grid = FALSE, layout, key.args = NULL, row = 1, 
    col = 1, nrow = 1, ncol = 1, more = FALSE, ...)
## S3 method for class 'efflist'
plot(x, selection, rows, cols, ask=TRUE, graphics=TRUE, ...)
## S3 method for class 'efflist'
x[...]

Arguments

x

an object of class "eff", "effpoly", "efflist", or "summary.eff", as appropriate.

object

an object of class "eff", "effpoly", or "efflist", as appropriate.

type

for linear and generalized linear models, if "response" (the default), effects are printed or the vertical axis is labelled on the scale of the response variable; if "link", effects are printed or the vertical axis labelled on the scale of the linear predictor. For polytomous logit models, this argument takes either "probability" or "logit", with the former as the default.

x.var

the index (number) or quoted name of the covariate or factor to place on the horizontal axis of each panel of the effect plot. The default is the predictor with the largest number of levels or values.

z.var

for linear, generalized linear or mixed models, the index (number) or quoted name of the covariate or factor for which individual lines are to be drawn in each panel of the effect plot. The default is the predictor with the smallest number of levels or values. This argument is only used if multiline = TRUE.

multiline

for linear, generalized linear or mixed models, if TRUE, each panel of the display represents combinations of values of two predictors, with one predictor (corresponding to x.var) on the horzontal axis, and the other (corresponding to z.var) used to define lines in the graph; defaults to TRUE if there are no standard errors in the object being plotted, and FALSE otherwise.

confint

plot point-wise confidence bands around fitted effects (for multinomial and proportional-odds logit models); defaults to TRUE, in which case separate panels are used for different response levels.

rug

if TRUE, the default, a rug plot is shown giving the marginal distribution of the predictor on the horizontal axis, if this predictor is a covariate.

xlab

the label for the horizontal axis of the effect plot; if missing, the function will use the name of the predictor on the horizontal axis.

ylab

the label for the vertical axis of the effect plot; the default is constructed from the name of the response variable for the model from which the effect was computed.

main

the title for the plot, printed at the top; the default title is constructed from the name of the effect.

colors

colors[1] is used to plot effects, colors[2] to plot confidence bands. In a mulitline plot, the successive colors correspond to the levels of the z.var covariate or factor. In a stacked plot or a plot without confidence bands for a multinomial or proportional-odds logit model, the successive colors correspond to the levels of the response factor. In all but stacked plots, colors defaults to palette(); for stacked multinomial-logit plots, colors defaults to rainbow_hcl(levels), where levels is the number of levels of the response variable; for stacked proportional-odds model plots, colors defautls to sequential_hcl(levels). Warning: This argument cannot be abbreviated to col, which is used for a different purpose (see below).

symbols, lines

corresponding to the levels of the z.var covariate or factor on a multiline plot, or to the successive levels of the response factor in a line plot for a polytomous logit model. These arguments are used only if multiline = TRUE or for polytomous logit models where the effects are plotted without confidence bands; in these cases a legend is drawn at the top of the display.

cex

character expansion for plotted symbols; default is 1.5.

ylim

2-element vector containing the lower and upper limits of the vertical axes; if NULL, the default, then the vertical axes are scaled from the data.

factor.names

a logical value, default TRUE, that controls the inclusion of factor names in conditioning-variable labels.

style

(for multinomial or proportional-odds logit models) "lines" (the default for a line plot, or "stacked" for a stacked-bar or stacked-area plot. In the latter case only fitted probabilities may be plotted and confidence envelopes cannot be shown.

ticks

a two-item list controlling the placement of tick marks on the vertical axis, with elements at and n. If at=NULL (the default), the program attempts to find ‘nice’ locations for the ticks, and the value of n (default, 5) gives the approximate number of tick marks desired; if at is non-NULL, then the value of n is ignored.

alternating

if TRUE (the default), the tick labels alternate by panels in multi-panel displays from left to right and top to bottom; if FALSE, tick labels appear at the bottom and on the left.

rotx, roty

rotation angles for the horizontal and vertical tick marks, respectively. Default is 0.

grid

if TRUE, add grid lines to the plot. Default is FALSE.

layout

the layout argument to the lattice function xyplot (or, in some cases densityplot), which is used to draw the effect display; if not specified, the plot will be formatted so that it appears on a single page.

rescale.axis

if TRUE (the default), the tick marks on the vertical axis are labelled on the response scale (e.g., the probability scale for effects computed on the logit scale for a binomial GLM).

key.args

additional arguments to be passed to the key trellis argument to xyplot or densityplot, e.g., to position the key (legend) in the plotting region.

row, col, nrow, ncol, more

These arguments are used to graph an effect as part of an array of plots; row, col, nrow, and ncol are used to compose the split argument and more the more argument to print.trellis. Normally these arguments are not set by the user, but by plot.efflist. Warning: Note that col is not used to specify colors; use colors instead (see above).

selection

the optional index (number) or quoted name of the effect in an effect list to be plotted; if not supplied, a menu of high-order terms is presented or all effects are plotted.

rows, cols

Number of rows and columns in the “meta-array” of plots produced for an efflist object; if either argument is missing, then the meta-layout will be computed by the plot method.

ask

if selection is not supplied and ask is TRUE (the default), a menu of high-order terms is presented; if ask is FALSE, effects for all high-order terms are plotted in an array.

graphics

if TRUE (the default), then the menu of terms to plot is presented in a dialog box rather than as a text menu.

...

arguments to be passed down.

Details

In a generalized linear model, by default, the print and summary methods for eff objects print the computed effects on the scale of the response variable using the inverse of the link function. In a logit model, for example, this means that the effects are expressed on the probability scale.

By default, effects in a GLM are plotted on the scale of the linear predictor, but the vertical axis is labelled on the response scale. This preserves the linear structure of the model while permitting interpretation on what is usually a more familiar scale. This approach may also be used with linear models, for example to display effects on the scale of the response even if the data are analyzed on a transformed scale, such as log or square-root.

In a polytomous (multinomial or proportional-odds) logit model, by default effects are plotted on the probability scale; they may be alternatively plotted on the scale of the individual-level logits.

Value

The summary method for "eff" objects returns a "summary.eff" object with the following components (those pertaining to confidence limits need not be present):

header

a character string to label the effect.

effect

an array containing the estimated effect.

lower.header

a character string to label the lower confidence limits.

lower

an array containing the lower confidence limits.

upper.header

a character string to label the upper confidence limits.

upper

an array containing the upper confidence limits.

The [ method for "efflist" objects is used to subset an "efflist" object and returns an object of the same class.

Author(s)

John Fox jfox@mcmaster.ca and Jangman Hong.

See Also

effect, allEffects, xyplot, densityplot, print.trellis rainbow_hcl, sequential_hcl

Examples

mod.cowles <- glm(volunteer ~ sex + neuroticism*extraversion, 
    data=Cowles, family=binomial)
eff.cowles <- allEffects(mod.cowles, xlevels=list(neuroticism=0:24, 
    extraversion=seq(0, 24, 6)))
eff.cowles

plot(eff.cowles, 'sex', ylab="Prob(Volunteer)", grid=TRUE, rotx=90)

plot(eff.cowles, 'neuroticism:extraversion', ylab="Prob(Volunteer)",
    ticks=list(at=c(.1,.25,.5,.75,.9)))

plot(eff.cowles, 'neuroticism:extraversion', multiline=TRUE, 
    ylab="Prob(Volunteer)", key.args = list(x = 0.75, y = 0.75, corner = c(0, 0)))
    
plot(effect('sex:neuroticism:extraversion', mod.cowles,
    xlevels=list(neuroticism=0:24, extraversion=seq(0, 24, 6))), multiline=TRUE)

mod.beps <- multinom(vote ~ age + gender + economic.cond.national +
				economic.cond.household + Blair + Hague + Kennedy +
				Europe*political.knowledge, data=BEPS)
plot(effect("Europe*political.knowledge", mod.beps, 
	xlevels=list(Europe=1:11, political.knowledge=0:3)))
	
plot(effect("Europe*political.knowledge", mod.beps, 
		xlevels=list(Europe=1:11, political.knowledge=0:3),
		given.values=c(gendermale=0.5)),
	style="stacked", colors=c("blue", "red", "orange"), rug=FALSE)
	
mod.wvs <- polr(poverty ~ gender + religion + degree + country*poly(age,3),
	data=WVS)
plot(effect("country*poly(age, 3)", mod.wvs))

plot(effect("country*poly(age, 3)", mod.wvs), style="stacked", 
	colors=c("gray75", "gray50", "gray25"))
	
plot(effect("country*poly(age, 3)", latent=TRUE, mod.wvs))

mod.pres <- lm(prestige ~ log(income, 10) + poly(education, 3) + poly(women, 2), 
    data=Prestige)
eff.pres <- allEffects(mod.pres, default.levels=50)
plot(eff.pres, ask=FALSE)
plot(eff.pres[1:2], ask=FALSE)


[Package effects version 2.1-0 Index]