Package: granovaGG
Version: 1.0
Date: 2011-09-03
Title: Graphical Analysis of Variance Using ggplot2
Author: Brian A. Danielak <brian@briandk.com>, Robert M. Pruzek
        <RMPruzek@yahoo.com>, with contributions from: William E. J.
        Doane <wil@DrDoane.com>, James E. Helmreich
        <James.Helmreich@Marist.edu>, Jason Bryer <jason@bryer.org>
Maintainer: Brian A. Danielak <brian@briandk.com>
Depends: R (>= 2.13.0), ggplot2 (>= 0.8.9), RColorBrewer, gridExtra,
        MASS
Suggests: mgcv, rgl, tcltk, MASS
Collate: 'theme-defaults.R' 'shared-functions.R' 'granovagg.1w.R'
        'granovagg.contr.R' 'granovagg.ds.R' 'granovaGG-package.R'
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.
License: GPL (>= 2)
Packaged: 2011-09-03 18:28:36 UTC; briandanielak
Repository: CRAN
Date/Publication: 2011-09-04 05:18:54
