Analysis for a continuous response for one group factor

A convenience function that creates an analysis for a continuous response variable with one grouping factor. The function creates a number of graphs and tables relevant for the analysis.

Usage

OneFactor(Response, Factor, Data = NULL, HSD = TRUE, AlphaE = 0.05, 
Filename = NULL, Folder = NULL, 
VI = getOption("BrailleR.VI"), Latex = getOption("BrailleR.Latex"), 
View = getOption("BrailleR.View"), Modern=TRUE)

Arguments

Response: Name of the continuous response variable.
Factor: The grouping factor.
Data: The data.frame that contains both the response and the factor.
HSD: Logical: Should Tukey's HSD be evaluated for the data?
AlphaE: The family-wise Type I error rate for Tukey's HSD calculations.
Filename: Name of the Rmarkdown and HTML files to be created. A default will be created that uses the names of the variables if this is left set to NULL.
Folder: Name of the folder to store graph and LaTeX files. A default will be created based on the name of the data.frame being used.
VI: Logical: Should the VI method for blind users be employed?
Latex: Logical: Should the tabulated sections be saved in LaTeX format?
View: Logical: Should the HTML file be opened for inspection?
Modern: Logical: Should the graphics be created using ggplot?

Details

This function writes an R markdown file that is knitted into HTML and purled into an R script. All graphs are saved in subdirectories in png, eps, pdf and svg formats. Tabulated results are stored in files suitable for importing into LaTeX documents.

Value

This function is used for creation of the files saved in the working directory and a few of its subdirectories.

Author

A. Jonathan R. Godfrey and Timothy P. Bilton

Examples

DIR = getwd()
setwd(tempdir())
data(airquality)
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
library(knitr)
# the following line  returns an error:
## OneFactor("Ozone", "Month", airquality, View=FALSE)
# so we make a copy of the data.frame, and fix that:
airquality2 = airquality |> mutate(Month = as.factor(Month))
# and now all is good to try:
OneFactor("Ozone", "Month", airquality2)
#> Error in get(DataName): object 'airquality2' not found
# N.B. Various files and a folder were created in a temporary directory. 
# Please investigate them to see how this function worked.
setwd(DIR)