rigr/README.Rmd at main · statdivlab/rigr · GitHub

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---
output: github_document
---

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```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
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  fig.path = "man/figures/README-",
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```

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# `rigr`: Regression, Inference, and General Data Analysis Tools for R

## Introduction

`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`](https://CRAN.R-project.org/package=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.

## Installation

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`.

```{r, echo=FALSE}
  # run the following code to make sure that the remote package it installed
  if (!requireNamespace("remotes", quietly = TRUE)) {
    install.package("remotes")
  }
  # install the package
  remotes::install_github("statdivlab/rigr")
```

If this produces an error, please run `install.packages("remotes")` first then try the above line again.

`rigr` is maintained by the [StatDivLab](https://statdivlab.github.io/), 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](https://github.com/statdivlab/rigr/discussions/)!

## Documentation

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`.

## Humans

Maintainer: [Amy Willis](https://statdivlab.github.io/)

Authors: [Scott S Emerson](http://www.emersonstatistics.com/), [Brian D Williamson](https://bdwilliamson.github.io/), [Charles Wolock](https://cwolock.github.io/), [Taylor Okonek](https://taylorokonek.github.io/), [Yiqun T Chen](https://yiqunchen.github.io/), [Jim Hughes](https://www.biostat.washington.edu/people/james-hughes), [Amy Willis](https://statdivlab.github.io/), [Andrew J Spieker](https://www.vumc.org/biostatistics/person/andrew-spieker) and Travis Y Hee Wai.

## Issues

If you encounter any **bugs**, please [file an issue](https://github.com/statdivlab/rigr/issues/). Better yet, [submit a pull request](https://github.com/statdivlab/rigr/pulls/)!

Do you have a **question**? Please first check out the vignettes, then please post on the [Discussions](https://github.com/statdivlab/rigr/discussions/).

## Code of Conduct

Please note that the rigr project is released with a [Contributor Code of Conduct](https://statdivlab.github.io/rigr/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.

## Citation

If you use `rigr` for your analysis, please cite our paper:

Chen, Y. T., et al. (2022). rigr: Regression, Inference, and General Data Analysis Tools in R. *Journal of Open Source Software*, 7(80), 4847. https://doi.org/10.21105/joss.04847.