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granovaGG  

Graphical Analysis of Variance Using ggplot2
View on CRAN: Click here


Download and install granovaGG package within the R console
Install from CRAN:
install.packages("granovaGG")

Install from Github:
library("remotes")
install_github("cran/granovaGG")

Install by package version:
library("remotes")
install_version("granovaGG", "1.4.1")



Attach the package and use:
library("granovaGG")
Maintained by
Brian A. Danielak
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2011-09-04
Latest Update: 2023-08-28
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.
How to cite:
Brian A. Danielak (2011). granovaGG: Graphical Analysis of Variance Using ggplot2. R package version 1.4.1, https://cran.r-project.org/web/packages/granovaGG. Accessed 18 Feb. 2025.
Previous versions and publish date:
1.0 (2011-09-04 07:18), 1.1 (2012-02-25 08:18), 1.2 (2012-09-04 08:16), 1.3 (2015-01-01 05:42), 1.4.0 (2015-12-18 06:43)
Other packages that cited granovaGG R package
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Other R packages that granovaGG depends, imports, suggests or enhances
Complete documentation for granovaGG
Functions, R codes and Examples using the granovaGG R package
Some associated functions: anorexia . anorexia.sub . arousal . blood_lead . granovaGG-package . granovagg.1w . granovagg.contr . granovagg.ds . poison . rat . shoes . tobacco . 
Some associated R codes: granovaGG-package.R . granovagg.1w-helpers.R . granovagg.1w.R . granovagg.contr.R . granovagg.ds.R . shared-functions.R . theme-defaults.R .  Full granovaGG package functions and examples
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