intxplot: Interaction plot, with an option to print standard error...

In HH: Statistical Analysis and Data Display: Heiberger and Holland

Interaction plot, with an option to print standard error bars.

Description

Interaction plot, with an option to print standard error bars. There is an option to offset group lines to prevent the bars from overprinting.

Usage

intxplot(x, data=NULL, groups.in,
          scales,
          key.length=1,
          key.lines,
          key=TRUE,
          trace.factor.name=deparse(substitute(groups.in)),
          x.factor.name=x.factor,
          xlab=x.factor.name,
          main=list(main.title, cex=main.cex),
          condition.name="condition",
          panel="panel.intxplot",
          summary.function="sufficient",
          se,
          ...,
          data.is.summary=FALSE,
          main.title=paste(
            "Interactions of", trace.factor.name, "and",
            x.factor.name,
            if (length(x[[3]]) > 1)
            paste("|", condition.name.to.use)),
          main.cex=1.5,
          col, lwd, lty, alpha)

panel.intxplot(x, y, subscripts, groups, type = "l", se, cv=1.96,
               offset.use=(!missing(groups) && !missing(se)),
               offset.scale=2*max(as.numeric(groups)),
               offset=
               as.numeric(groups[match(levels(groups), groups)]) / offset.scale,
               rug.use=offset.use,
               col, lwd, lty, alpha,
               ...)

Arguments

x	For intxplot, a formula with a factor as the predictor variable. For panel.intxplot, standard argument for panel functions.
data	data.frame, as used in xyplot.
groups.in	groups.in, as used in xyplot.
scales	Optional, additional arguments for the standard scales in xyplot.
key.length	Number of columns in the key.
key.lines	default value for the lines argument of key.
key	logical. If TRUE, draw the key.
trace.factor.name	Name of the grouping variable.
x.factor.name	name of the dependent variable.
xlab	as in xyplot, defaults to the name of the predictor variable from the formula.
main	as in xyplot. Defaults to the main.title argument.
panel	as in xyplot. Defaults to the "panel.intxplot".
condition.name	name of the conditioning variable.
summary.function	The default sufficient finds the mean, standard deviation, and sample size of the response variable for each level of the conditioning factor. See sufficient.
se	standard errors to be passed to panel.intxplot. se Missing, logical, or a numeric vector. If missing or FALSE, standard errors are not plotted. If se=TRUE in intxplot, the standard errors are calculated from the sufficient statistics for each group as the group's standard deviation divided by the square root of the group's observation count. If se is numeric vector, it is evaluated in the environment of the sufficient statistics. the se argument to panel.intxplot must be numeric.

,

...	In intxplot, arguments for panel.intxplot. In panel.intxplot, arguments for panel.superpose.
data.is.summary	logical, defaults to FALSE under the assumption that the input data.frame is the original data and the intxplot function will generate the summary information (primarily standard deviation sd and number of observations nobs for each group). When TRUE, the standard error calculation assumes variables sd and nobs are in the dataset.
main.title	Default main title for plot.
main.cex	Default character expansion for main title.
y, subscripts, groups, type	Standard arguments for panel functions.
cv	critical value for confidence intervals. Defaults to 1.96.
offset.use	logical. If TRUE, offset the endpoints of each group.
offset.scale	Scale number indicating how far apart the ends of the groups will be placed. Larger numbers make them closer together.
offset	Actual numbers by which the end of the groups are offset from their nominal location which is the as.numeric of the group levels.
rug.use	logical. If TRUE, display a rug for the endpoints of each group.
col, lwd, lty, alpha	Arguments to trellis.par.set(superpose.line=list()).

Value

"trellis" object.

Author(s)

Richard M. Heiberger <[e-mail]>

See Also

sufficient

Examples

## This uses the same data as the HH Section 12.13 rhizobium example.

data(rhiz.clover)

## interaction plot, no SE
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover,
         main="Interaction Plot. No SE")

## interaction plot, individual SE for each treatment combination
## Rescaled to allow the CI bars to stay within the plot region
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover, se=TRUE,
         ylim=c(17,47),
         main="Interaction Plot. Rescaled to keep CI bars within the plot region")

## Common SE based on ANOVA table. Rescaled to allow the CI bars to stay within the plot region
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover,
         se=sqrt(sum((nobs-1)*sd^2)/(sum(nobs-1)))/sqrt(5),
         ylim=c(16,41),
         main=paste("Interaction Plot. Common SE based on ANOVA table.\n",
                    "Rescaled to keep CI bars within the plot region"))

## change distance between endpoints
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover, se=TRUE,
         offset.scale=10, ylim=c(18,46),
         main="Interaction plot. Change distance between endpoints")

## When data includes the nobs and sd variables, data.is.summary=TRUE is needed.
intxplot(Npg ~ strain, groups=comb,
         se=sqrt(sum((nobs-1)*sd^2)/(sum(nobs-1)))/sqrt(5),
         data=sufficient(rhiz.clover, y="Npg", c("strain","comb")),
         data.is.summary=TRUE,
         ylim=c(16,41),
         main=paste("Interaction plot. When data includes the nobs and sd variables,\n",
           "'data.is.summary=TRUE' is needed"))

HH documentation built on May 29, 2024, 6:24 a.m.