granovaGG-package: Elemental Graphics for Analysis of Variance Using ggplot2
Description
This collection of functions in granovaGG provides what we call
elemental graphics for display of anova results. The term
elemental derives from the fact that each function is
aimed at construction of graphical displays that afford
direct visualizations of data with respect to the
fundamental questions that drive the particular anova
methods. This package represents a modification of the
original granova package; the key change is to use ggplot2,
Hadley Wickham's package based on Grammar of Graphics
concepts (due to Wilkinson). The main function is granovagg.1w
(a graphic for one way anova); two other functions (granovagg.ds
and granovagg.contr) are to construct graphics for dependent
sample analyses and contrast-based analyses respectively. (The
function granova.2w, which entails dynamic displays of data, is
not currently part of granovaGG.) The granovaGG functions are
to display data for any number of groups, regardless of
their sizes (however, very large data sets or numbers of
groups can be problematic). For granovagg.1w a
specialized approach is used to construct data-based
contrast vectors for which anova data are displayed. The
result is that the graphics use a straight line to facilitate clear
interpretations while being faithful to the standard
effect test in anova. The graphic results are
complementary to standard summary tables; indeed, numerical
summary statistics are provided as side effects of the graphic
constructions. granovagg.ds and granovagg.contr provide
graphic displays and numerical outputs for a dependent
sample and contrast-based analyses. The graphics based on
these functions can be especially helpful for learning
how the respective methods work to answer the basic
question(s) that drive the analyses. This means they can be particularly
helpful for students and non-statistician analysts. But
these methods can be of assistance for work-a-day
applications of many kinds, as they can help to
identify outliers, clusters or patterns, as well as
highlight the role of non-linear transformations of data.
In the case of granovagg.1w and granovagg.ds
several arguments are provided to facilitate flexibility
in the construction of graphics that accommodate diverse
features of data, according to their corresponding
display requirements. See the help files for individual
functions.
Arguments
Details
Package:
granovaGG
Version:
1.0
License:
GPL (>= 2)
References
Wickham, H. (2009). Ggplot2: Elegant Graphics for Data Analysis. New York: Springer.
Wilkinson, L. (1999). The Grammar of Graphics. Statistics and computing. New York: Springer.