Learn R Programming

HH (version 3.1-47)

intxplot: 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)

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)

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.

Value

"trellis" object.

See Also

sufficient

Examples

Run this code
# NOT RUN {
## 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)

## interaction plot, individual se for each treatment combination
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover, se=TRUE)

## Rescaled to allow the CI bars to stay within the plot region
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover, se=TRUE,
         ylim=range(rhiz.clover$Npg))

## interaction plot, common se based on ANOVA table
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover,
         se=sqrt(sum((nobs-1)*sd^2)/(sum(nobs-1)))/sqrt(5))

## 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=range(rhiz.clover$Npg))

## change distance between endpoints
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover,
         se=TRUE, offset.scale=20)

## 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=range(rhiz.clover$Npg))
# }

Run the code above in your browser using DataLab