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granovaGG (version 1.4.1)

Graphical Analysis of Variance Using ggplot2

Description

Create 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.

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install.packages('granovaGG')

Monthly Downloads

257

Version

1.4.1

License

MIT + file LICENSE

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Last Published

November 23rd, 2023

Functions in granovaGG (1.4.1)

blood_lead

Blood lead levels of lead workers' children matched with similar control children.
granovagg.ds

Elemental Graphic for Display of Dependent Sample Data
shoes

Shoe wear data of Box, Hunter and Hunter
arousal

Arousal in Rats
anorexia

Anorexia Data on Weight Change
rat

Weight gains of rats fed different diets
granovaGG-package

Elemental Graphics for Analysis of Variance Using ggplot2
anorexia.sub

Family Treatment Weight change data for young female anorexia patients (subset).
poison

Poison data from Biological Experiment
granovagg.1w

Elemental Graphic Display for One-Way ANOVA
granovagg.contr

Elemental Graphic Display for Contrast Effect of ANOVA
tobacco

Virus Preparation on Tobacco Leaves