Plot all main effects and twoway interactions in a multifactor design
The main diagonal
displays boxplots for the main effects of each factor. The
off-diagonals show the interaction plots for each pair of factors.
The i,j
panel shows the same factors as the j,i
but with
the trace- and x-factor roles interchanged.
interaction2wt(x, ...) ## S3 method for class 'formula' interaction2wt(x, data=NULL, responselab, ...) ## Default S3 method: interaction2wt(x, response.var, responselab = deparse(substitute(response.var)), responselab.expression = responselab, relation = list(x = "same", y = "same"), x.relation = relation$x, y.relation = relation$y, digits = 3, x.between=1, y.between=1, between, cex = 0.75, rot=c(0,0), panel.input = panel.interaction2wt, strip.input = if (label.as.interaction.formula) strip.default else strip.interaction2wt, par.strip.text.input = trellis.par.get()$add.text, scales.additional, main.in = paste(responselab, ": ", c("main", "simple")[1+simple], " effects and 2-way interactions", sep=""), xlab = "", ylab = "", simple=FALSE, box.ratio=if (simple) .32 else 1, label.as.interaction.formula=TRUE, ..., main.cex, key.cex.title=.8, key.cex.text=.7, factor.expressions=names.x, simple.pch=NULL )
Arguments when x
is a formula.
x |
The object on which method dispatch is carried out. For the For the |
data |
For the |
responselab |
Character name of response variable, defaults to
the name of the response variable in the |
responselab.expression |
|
... |
additional arguments, primarily trellis arguments. |
response.var |
For the |
simple |
logical. |
box.ratio |
Trellis/Lattice arguments. Default values are set by the
the formula
method. The user may override the defaults.
See also
xyplot
.
relation |
|
x.relation |
|
y.relation |
|
digits |
doesn't do anything at the moment |
x.between |
|
y.between |
|
between |
trellis/lattice |
cex |
S-Plus: changes the size of the median dot in the boxplots. R: doesn't do anything. |
panel.input |
panel function. Default is |
label.as.interaction.formula |
logical. If |
strip.input |
strip function. Default depends on the value of
|
par.strip.text.input |
|
scales.additional |
additional arguments to |
main.in |
Text of main title. |
xlab |
No effect. |
ylab |
No effect. |
main.cex |
|
key.cex.title |
|
key.cex.text |
|
factor.expressions |
Expressions for titles of keys and
|
rot |
Rotation of x tick labels and y tick labels. Only 0 and 90 will look good. |
simple.pch |
Named list containing plotting characters for each
level of one or more of the factors. |
"trellis"
object containing the plot.
Richard M. Heiberger <rmh@temple.edu>
Heiberger, Richard M. and Holland, Burt (2015). Statistical Analysis and Data Display: An Intermediate Course with Examples in R. Second Edition. Springer-Verlag, New York. https://www.springer.com/us/book/9781493921218
data(vulcan) interaction2wt(wear ~ filler + pretreat + raw, data=vulcan, par.strip.text=list(cex=.7)) interaction2wt(wear ~ filler + pretreat + raw, data=vulcan) interaction2wt(wear ~ filler + raw, data=vulcan, simple=TRUE) interaction2wt(wear ~ filler + raw, data=vulcan, simple=TRUE, simple.scale=c(filler=.15, raw=.2), xlim=c(.3, 5.6)) ToothGrowth$dose <- positioned(ToothGrowth$dose) ## modify local copy anova(aov(len ~ supp*dose, data=ToothGrowth)) interaction2wt(len ~ supp + dose, data=ToothGrowth) esoph$ntotal <- with(esoph, ncases + ncontrols) ## modify local copy esoph$rate <- with(esoph, ncases/ntotal) ## modify local copy position(esoph$alcgp) <- 2:5 position(esoph$tobgp) <- 2:5 interaction2wt(rate ~ agegp + alcgp + tobgp, esoph, rot=c(90,0), par.strip.text=list(cex=.8)) interaction2wt(rate ~ agegp + alcgp + tobgp, esoph, rot=c(90,0), par.strip.text=list(cex=.8), factor.expressions=c( agegp=expression(Age~~(years)), alcgp=expression(Alcohol~ bgroup("(",scriptstyle(frac(gm, day)),")")), tobgp=expression(Tobacco~ bgroup("(",scriptstyle(frac(gm, day)),")"))), par.settings=list( par.xlab.text=list(cex=.8), par.ylab.text=list(cex=.8)), responselab.expression="Cancer\nRate", main=list( "Esophogeal Cancer Rate ~ Alcohol Consumption + Tobacco Consumption", cex=1.2)) esoph.aov <- aov(rate ~ agegp + alcgp + tobgp, data=esoph) anova(esoph.aov)
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