rigr: Regression, Inference, and General Data Analysis Tools for R
rigr is an
R package to streamline data analysis in
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
provides easy-to-use interfaces for descriptive statistics, one- and
two-sample inference, and regression analyses.
rigr output includes
key information while omitting unncessary 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 and generalized linear 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:
You can install the development version of
rigr from GitHub using the
If this produces an error, please run
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
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,
Maintainer: Amy Willis
Do you have a question? Please first check out the vignettes, then please post on the Discussions.
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