# interaction2wt

From HH v3.1-39
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##### 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.

Keywords
hplot, design
##### Usage
interaction2wt(x, ...)# S3 method for formula
interaction2wt(x, data = sys.parent(), 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 Texts in Statistics. Springer. ISBN 978-1-4939-2121-8. Heiberger, Richard M. and Holland, Burt (2004b). Statistical Analysis and Data Display: An Intermediate Course with Examples in S-Plus, R, and SAS. Springer Texts in Statistics. Springer. ISBN 0-387-40270-5. ##### See Also panel.interaction2wt ##### Aliases • interaction2wt • interaction2wt.formula • interaction2wt.default ##### 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)

# }

Documentation reproduced from package HH, version 3.1-39, License: GPL (>= 2)

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