paratests

The goal of paratests is to make performing (non-)parametric tests in R easier and more reproducible. Today this package contains four functions:

• anova(): print the p value of an analysis of variance summary
• cor_scatterplot(): scatterplot of variables and their correlation test coefficient and p value
• mean_barchart(): barchart of a variable mean and standard deviation per group
• sw_tidy(): print the p value of a Shapiro Wilk normality test

Every function has to be performed on a tidy dataset.

Installation

Paratests depends on the following packages, make sure these are installed and loaded with library() first:

# install.packages("usethis")
# install.packages("devtools")
# install.packages("dplyr")
# install.packages("ggplot2")
# install.packages("magrittr")
# install.packages("palmerpenguins")
# install.packages("stats")

You can then install and use the the most recent version of paratests from this GitHub with:

devtools::install_github("stephaniedewit/paratests")
library(paratests)

NOTE: {paratests} anova() function masks the {stats} anova() function. To use the latter use stats::anova().

Examples

For a description of each function use ?anova(), ?cor_scatterplot(), ?mean_barchart() and ?sw_tidy. For a vignette with a short analysis combining the four functions use browseVignettes("paratests").

To try for yourself, two example datasets can be loaded into the Environment with data(PlantGrowth_edit) and data(potato).