HH: intxplot – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

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.

Author(s)

Richard M. Heiberger <rmh@temple.edu>

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)

## 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))

HH

Statistical Analysis and Data Display: Heiberger and Holland

v3.1-43

GPL (>= 2)

Authors

Richard M. Heiberger

Initial release

2020-11-27