README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# icebrrrg

<!-- badges: start -->
<!-- badges: end -->

The goal of icebrrrg is to speed statistic analyses as well as use of machine learning models
through several helper functions. In other words, this augments many standard functions, 
organizing them into summary tables or providing additional structured data that can be useful for 
expanding on existing analyses or machine learning models.

## Installation

You can install the development version of icebrrrg from [GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("chop-dbhi/icebrrrg")
```
## single_or()

Generate a Fisher's Exact Test summary table based on a single comparator between two cohorts in a single dataframe

### Example

This is a basic example of the single_or function:

```{r example}
library(icebrrrg)
## basic example code
icebrrrg::single_or(
  data = iris,
  case_cohort = Petal.Length > 1.2,
  control_cohort = Petal.Length <= 1.2,
  comparator = Species
  )
```
---

# License Summary

Use of this software is available to academic and non-profit institutions for research purposes subject to the terms of the 2-Clause BSD License (see copy below). For use or transfers of the software to commercial entities, please inquire with kaufmanmc@chop.edu. © 2023 CHOP. The FreeBSD Copyright

Copyright and License Information

Copyright (c) 2023, Children's Hospital of Philadelphia CHOP Invention 2023-059

Authors: Michael Kaufman, Alexander Gonzalez, Julie Xian, Shridhar Parthasarathy