plot.design
Plot Univariate Effects of a Design or Model
Description
Plot univariate effects of one or more factor
s, typically for a designed experiment as analyzed by aov()
.
Usage
plot.design(x, y = NULL, fun = mean, data = NULL, ..., ylim = NULL, xlab = "Factors", ylab = NULL, main = NULL, ask = NULL, xaxt = par("xaxt"), axes = TRUE, xtick = FALSE)
Arguments
x | either a data frame containing the design factors and optionally the response, or a |
y | the response, if not given in x. |
fun | a function (or name of one) to be applied to each subset. It must return one number for a numeric (vector) input. |
data | data frame containing the variables referenced by |
... | graphical parameters such as |
ylim | range of y values, as in |
xlab | x axis label, see |
ylab | y axis label with a ‘smart’ default. |
main | main title, see |
ask | logical indicating if the user should be asked before a new page is started – in the case of multiple y's. |
xaxt | character giving the type of x axis. |
axes | logical indicating if axes should be drawn. |
xtick | logical indicating if ticks (one per factor) should be drawn on the x axis. |
Details
The supplied function will be called once for each level of each factor in the design and the plot will show these summary values. The levels of a particular factor are shown along a vertical line, and the overall value of fun()
for the response is drawn as a horizontal line.
Note
A big effort was taken to make this closely compatible to the S version. However, col
(and fg
) specifications have different effects.
In S this was a method of the plot
generic function for design
objects.
Author(s)
Roberto Frisullo and Martin Maechler
References
Chambers, J. M. and Hastie, T. J. eds (1992) Statistical Models in S. Chapman & Hall, London, the white book, pp. 546–7 (and 163–4).
Freeny, A. E. and Landwehr, J. M. (1990) Displays for data from large designed experiments; Computer Science and Statistics: Proc.\ 22nd Symp\. Interface, 117–126, Springer Verlag.
See Also
interaction.plot
for a ‘standard graphic’ of designed experiments.
Examples
require(stats) plot.design(warpbreaks) # automatic for data frame with one numeric var. Form <- breaks ~ wool + tension summary(fm1 <- aov(Form, data = warpbreaks)) plot.design( Form, data = warpbreaks, col = 2) # same as above ## More than one y : utils::str(esoph) plot.design(esoph) ## two plots; if interactive you are "ask"ed ## or rather, compare mean and median: op <- par(mfcol = 1:2) plot.design(ncases/ncontrols ~ ., data = esoph, ylim = c(0, 0.8)) plot.design(ncases/ncontrols ~ ., data = esoph, ylim = c(0, 0.8), fun = median) par(op)
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Licensed under the GNU General Public License.