HH (version 3.1-42)

# interaction2wt: Plot all main effects and twoway interactions in a multifactor design

## Description

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.

## Usage

```interaction2wt(x, ...)# S3 method for formula
interaction2wt(x, data=NULL, responselab, ...)# S3 method for default
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

x

The object on which method dispatch is carried out.

For the `"formula"` method, a formula describing the response variable and factors. The formula is generally of the form `y ~ g1 + g2 + …`. There may be one or more factors in the formula.

For the `"default"` method, `data.frame` of factors. This is usually constructed by `formula` method from the input data and the input formula.

data

For the `formula` method, a data frame containing values for any variables in the formula. In the R version, if not found in `data`, or if `data` is unspecified, the variables are looked for in the environment of the formula.

responselab

Character name of response variable, defaults to the name of the response variable in the `formula`.

responselab.expression

`plotmath` or character name of response variable, defaults to `responselab`.

additional arguments, primarily trellis arguments.

response.var

For the `"default"` method, the response variable. This is usually constructed by `formula` method from the input data and the input formula.

simple

logical. `TRUE` if simple effects are to be displayed. Arguments `simple.offset`, `simple.scale`, and `col.by.row` may also be needed. See `panel.interaction2wt` for details.

box.ratio

## Value

`"trellis"` object containing the plot.

## References

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

## See Also

`panel.interaction2wt`

## Examples

```# NOT RUN {
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\$rate=with(esoph, ncases/ncontrols) ## 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)

# }
```