LegacyArguments {effects}

Legacy Arguments for plot and Effect Methods

Description

Prior to verson 4.0-0 of the effects package, there were many (literally dozens) of arguments to the plot methods for "eff" and "effpoly" objects.

In version 4.0-0 of the package, we have consolidated these arguments into a much smaller number of arguments (e.g., lines, points, axes) that take lists of specifications. We have similarly consolidated some of the arguments to Effect methods into the confint and fixed.predictors arguments.

For backwards compatibility, we have to the extent possible retained the older arguments. If specified, these legacy arguments take precedence over the newer list-style arguments

Details

Here is the correspondence between the old and new arguments.

For plot methods:

multiline=TRUE/FALSE

lines=list(multiline=TRUE/FALSE)

type=c("rescale", "link", "response")

For models with a link function, "link" plots in linear predictor scale, "response" plots in the response scale, and the default "rescale" plots in linear predictor scale but labels tick-marks in response scale.

z.var=which.min(levels)

lines=list(z.var=which.min(levels)) relevant only when lines=list(multiline=TRUE)

colors={vector of colors}

lines=list(col={vector of colors})

lty={vector of line types}

lines=list(lty={vector of line types})

lwd={vector of line widths}

lines=list(lwd={vector of line widths})

use.splines=TRUE/FALSE

lines=list(splines=TRUE/FALSE)

cex={number}

points=list(cex={number})

rug=TRUE/FALSE

axes=list(x=list(rug=TRUE/FALSE)

xlab={"axis title"}

axes=list(x=list(lab={"axis title"}))

xlim={c(min, max)}

axes=list(x=list(lim={c(min, max)}))

rotx={degrees}

axes=list(x=list(rot={degrees}))

ticks.x=list({tick specifications})

axes=list(x=list(ticks=list({tick specifications})))

transform.x=list(link={function}, inverse={function})

axes=list(x=list(transform=list({lists of transformations by predictors})))

ylab={"axis title"}

axes=list(y=list(lab={"axis title"}))

ylim={c(min, max)}

axes=list(y=list(lim={c(min, max)}))

roty={degrees}

axes=list(y=list(rot={degrees}))

ticks=list({tick specifications})

axes=list(y=list(ticks=list({tick specifications})))

alternating=TRUE/FALSE

axes=list(alternating=TRUE/FALSE)

grid=TRUE/FALSE

axes=list(grid=TRUE/FALSE)

ci.style="bands"/"lines"/"bars"/"none"

confint=list(style="bands"/"lines"/"bars"/"none")

band.transparency={number}

confint=list(alpha={number})

band.colors={vector of colors}

confint=list(col={vector of colors})

residuals.color={color}

partial.residuals=list(col={color})

residuals.pch={plotting character}

partial.residuals=list(pch={plotting character})

residuals.cex={number}

partial.residuals=list(cex={number})

smooth.residuals=TRUE/FALSE

partial.residuals=list(smooth=TRUE/FALSE)

residuals.smooth.color={color}

partial.residuals=list(smooth.col={color})

span={number}

partial.residuals=list(span={number})

show.fitted=TRUE/FALSE

partial.residuals=list(fitted=TRUE/FALSE)

factor.names=TRUE/FALSE

lattice=list(strip=list(factor.names=TRUE/FALSE))

show.strip.values=TRUE/FALSE

lattice=list(strip=list(values=TRUE/FALSE))

layout={lattice layout}

lattice=list(layout={lattice layout})

key.args={lattice key args}

lattice=list(key.args={lattice key args})

style="lines"/"stacked"

for plot.effpoly, axes=list(y=list(style="lines"/"stacked"))

rescale.axis=TRUE/FALSE

type="rescale"/"response"/"link"

For Effect methods:

confint=TRUE/FALSE or a list

may be substituted for the se argument.

confidence.level={number}

se=list(level={number})

given.values={named vector}

fixed.predictors=list(given.values={named vector})

typical={function}

fixed.predictors=list(typical={function})

offset={function}

fixed.predictors=list(offset={function})

partial.residuals=TRUE/FALSE

residuals=TRUE/FALSE

transformation

This argument to Effect is not needed to compute effects. It can now be set directly with the plot method with the argument axes = list(y = list(transformation=specification)).

Author(s)

John Fox [e-mail]

See Also

Effect, plot.eff, plot.effpoly