Object of class aov or lm for which marginal
deviations from the mean and the residuals distribution is displayed.
stacked
logical. If TRUE and if it is necessary the dots are
stacked, otherwise all points are displayed at same level with possible
overlapping.
base
logical. By default a base line is displayed for each factor.
If FALSE this line is omitted.
axes
logical. By default a scaled axes is drawn for each factor.
If FALSE the axes are omitted.
faclab
logical. By default factor effect names and
‘Residuals’ are used to label each dot plot. No axis is labelled otherwise.
labels
logical. By default, dots are used to the display.
If labels=TRUE then factor levels are displayed for the factor dots
plots and sequential enumeration is used for the residuals.
cex
numeric. Expansion factor of the character used for labelling the factor levels.
cex.lab
numeric. Expansion factor of the character used for labelling each factor.
...
additional parameters passed to the dots function.
Details
Dots plot are displayed for the scaled deviations of factor levels from
the grand mean and the distribution of the residuals is shown at the bottom
of the plot for graphical comparison. The scaled factor for the factor
deviations is sqrt(n / k), where k and n
are the factor and residuals degrees of freedom reported by anova(obj).
If labels=TRUE then the factor levels are used for as points
instead of dots. This option is useful to post labelling the dot plots.
See dots function.
The Anova plot is built in a (0,1)x(0,1) plot
area. The area plot is divided to accommodate each of the factors and
the residual at the bottom of the plotting area. The function returns a
list with the coordinates of all the dots displayed.
Value
The function is called for graphical display of factor levels mean and
residuals as reference distribution. An invisible list with the actual (x,y)
coordinates used for each of
the factors and residuals.
warning
The function identifies as an interaction factor any factor
with the colon character ":" in its name. Factors like "I(A:B)"
will give you problems.
Note
The anova plot presented here is thought for graphical comparison of
factor effects in one-layer balanced designed experiments. The function
is not prepared for general situations. However, representation of some
simple split-plot experiments is possible.
Author(s)
Ernesto Barrios
References
Box G. E. P. (2000). Box on Quality.
Edited by G. C. Tiao et al. New York: Wiley.
Box G. E. P, Hunter, J. S. and Hunter, W. C. (2005).
Statistics for Experimenters II. New York: Wiley.
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BHH2)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/BHH2/anovaPlot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: anovaPlot
> ### Title: Graphical Anova
> ### Aliases: anovaPlot
> ### Keywords: design hplot regression
>
> ### ** Examples
>
> library(BHH2)
> data(heads.data)
> heads.data$periods <- factor(heads.data$periods)
> heads.data$heads <- factor(heads.data$heads)
>
> heads.aov <- aov(resp~periods+heads,data=heads.data)
> anovaPlot(heads.aov)
>
> anovaPlot(heads.aov,labels=TRUE,faclab=TRUE)
>
>
>
>
>
>
> dev.off()
null device
1
>