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stats (version 3.3.3)

interaction.plot: Two-way Interaction Plot

Description

Plots the mean (or other summary) of the response for two-way combinations of factors, thereby illustrating possible interactions.

Usage

interaction.plot(x.factor, trace.factor, response, fun = mean,
                 type = c("l", "p", "b", "o", "c"), legend = TRUE,
                 trace.label = deparse(substitute(trace.factor)),
                 fixed = FALSE,
                 xlab = deparse(substitute(x.factor)),
                 ylab = ylabel,
                 ylim = range(cells, na.rm = TRUE),
                 lty = nc:1, col = 1, pch = c(1:9, 0, letters),
                 xpd = NULL, leg.bg = par("bg"), leg.bty = "n",
                 xtick = FALSE, xaxt = par("xaxt"), axes = TRUE,
                 …)

Arguments

x.factor
a factor whose levels will form the x axis.
trace.factor
another factor whose levels will form the traces.
response
a numeric variable giving the response
fun
the function to compute the summary. Should return a single real value.
type
the type of plot (see plot.default): lines or points or both.
legend
logical. Should a legend be included?
trace.label
overall label for the legend.
fixed
logical. Should the legend be in the order of the levels of trace.factor or in the order of the traces at their right-hand ends?
xlab,ylab
the x and y label of the plot each with a sensible default.
ylim
numeric of length 2 giving the y limits for the plot.
lty
line type for the lines drawn, with sensible default.
col
the color to be used for plotting.
pch
a vector of plotting symbols or characters, with sensible default.
xpd
determines clipping behaviour for the legend used, see par(xpd). Per default, the legend is not clipped at the figure border.
leg.bg, leg.bty
arguments passed to legend().
xtick
logical. Should tick marks be used on the x axis?
xaxt, axes, …
graphics parameters to be passed to the plotting routines.

Details

By default the levels of x.factor are plotted on the x axis in their given order, with extra space left at the right for the legend (if specified). If x.factor is an ordered factor and the levels are numeric, these numeric values are used for the x axis. The response and hence its summary can contain missing values. If so, the missing values and the line segments joining them are omitted from the plot (and this can be somewhat disconcerting). The graphics parameters xlab, ylab, ylim, lty, col and pch are given suitable defaults (and xlim and xaxs are set and cannot be overridden). The defaults are to cycle through the line types, use the foreground colour, and to use the symbols 1:9, 0, and the capital letters to plot the traces.

References

Chambers, J. M., Freeny, A and Heiberger, R. M. (1992) Analysis of variance; designed experiments. Chapter 5 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.

Examples

Run this code
require(graphics)

with(ToothGrowth, {
interaction.plot(dose, supp, len, fixed = TRUE)
dose <- ordered(dose)
interaction.plot(dose, supp, len, fixed = TRUE, col = 2:3, leg.bty = "o")
interaction.plot(dose, supp, len, fixed = TRUE, col = 2:3, type = "p")
})

with(OrchardSprays, {
  interaction.plot(treatment, rowpos, decrease)
  interaction.plot(rowpos, treatment, decrease, cex.axis = 0.8)
  ## order the rows by their mean effect
  rowpos <- factor(rowpos,
                   levels = sort.list(tapply(decrease, rowpos, mean)))
  interaction.plot(rowpos, treatment, decrease, col = 2:9, lty = 1)
})

with(esoph, {
  interaction.plot(agegp, alcgp, ncases/ncontrols, main = "'esoph' Data")
  interaction.plot(agegp, tobgp, ncases/ncontrols, trace.label = "tobacco",
                   fixed = TRUE, xaxt = "n")
})
## deal with NAs:
esoph[66,] # second to last age group: 65-74
esophNA <- esoph; esophNA$ncases[66] <- NA
with(esophNA, {
  interaction.plot(agegp, alcgp, ncases/ncontrols, col = 2:5)
                                # doesn't show *last* group either
  interaction.plot(agegp, alcgp, ncases/ncontrols, col = 2:5, type = "b")
  ## alternative take non-NA's  {"cheating"}
  interaction.plot(agegp, alcgp, ncases/ncontrols, col = 2:5,
                   fun = function(x) mean(x, na.rm = TRUE),
                   sub = "function(x) mean(x, na.rm=TRUE)")
})
rm(esophNA) # to clear up

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