rigr is an R package to streamline data analysis in R. Learning
both R and introductory statistics at the same time can be
challenging, and so we created rigr to facilitate common data analysis
tasks and enable learners to focus on statistical concepts.
rigr, formerly known as
uwIntroStats,
provides easy-to-use interfaces for descriptive statistics, one- and
two-sample inference, and regression analyses. rigr output includes
key information while omitting unnecessary details that can be confusing
to beginners. Heteroskedasticity-robust (“sandwich”) standard errors are
returned by default, and multiple partial F-tests and tests for
contrasts are easy to specify. A single regression function
(regress()) can fit both linear models, generalized linear models, and
proportional hazards models, allowing students to more easily make
connections between different classes of models.
You can install the stable release of rigr from CRAN as follows:
install.packages("rigr")
You can install the development version of rigr from GitHub using the
code below. The installment is through the R package remotes.
#> Using GitHub PAT from the git credential store.
#> Skipping install of 'rigr' from a github remote, the SHA1 (8b901ee9) has not changed since last install.
#> Use `force = TRUE` to force installation
If this produces an error, please run install.packages("remotes")
first then try the above line again.
rigr is maintained by the StatDivLab,
but relies on community support to log issues and implement new
features. Is there a method you would like to have implemented? Please
submit a pull request or start a
discussion!
Examples of how to use the main functions in rigr are provided in
three vignettes. One details the regress function and its utilities,
one details the descrip function for descriptive statistics, and the
third details functions used for one- and two-sample inference,
including ttest, wilcoxon, and proptest.
Maintainer: Amy Willis
Authors: Scott S Emerson, Brian D Williamson, Charles Wolock, Taylor Okonek, Yiqun T Chen, Jim Hughes, Amy Willis, Andrew J Spieker and Travis Y Hee Wai.
If you encounter any bugs, please file an issue. Better yet, submit a pull request!
Do you have a question? Please first check out the vignettes, then please post on the Discussions.
Please note that the rigr project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.