StatAid

StatAid: An R package with a graphical user interface for data analysis - Published in JOSS (2020)

https://github.com/vincentalcazer/stataid

Keywords

Scientific Fields

Repository

StatAid is a Shiny app built in an R package to guide researchers and clinicians through data analysis

README.Rmd

---
output: github_document
---



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

# Welcome to StatAid


[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)


`StatAid` is a free open-source software provided as an R package allowing clinicians and researchers to perform statistical analysis through an intuitive graphical interface. It has been developed with the R software, using the [Shiny package](https://shiny.rstudio.com/). [Golem](https://github.com/ThinkR-open/golem) has been used for package compilation and deployment.  

 The software guides the users through the steps of a good data analysis, including multiple features such as:
 Exploratory data analysis: distribution, count, missing-values and outliers check
 Descriptive analysis, simple comparative analysis and publication ready 'table 1' output 
 Publication-ready graph customization
 Paired data analysis (matched case-control studies, repeated measures) 
 Univariate analysis and models for continuous and categorical outcome: Correlation, linear and logistic regression
 Univariate analysis and models for time-dependent outcome: Kaplan-Meier curves and cox regression 
 Multivariate analysis and models for continuous, categorical and time-dependent outcomes 
 ROC Curves 


# Getting started

## Online version 

StatAid has a ready-to-use online version available at [https://vincentalcazer.shinyapps.io/StatAid/](https://vincentalcazer.shinyapps.io/StatAid/).

## Local version

You can install the development version from [GitHub](https://github.com/VincentAlcazer/StatAid) either by cloning the repository or directly by downloading the package in R:

```{r Github install, eval = F }

install.packages("remotes")
remotes::install_github("VincentAlcazer/StatAid")

StatAid::run_app()
```

## Quick-start user guide

If you are not familiar with StatAid or just want to have an overview of the different possibilities, you can check the [StatAid's quick-start user guide](https://github.com/VincentAlcazer/StatAid/blob/master/STATAID_QUICK_START_USER_GUIDE.pdf)

## Citing StatAid

If you found StatAid useful and used it for your research, please cite the [paper published in the Journal of Open Source Software.](https://joss.theoj.org/papers/10.21105/joss.02630) [![DOI](https://joss.theoj.org/papers/10.21105/joss.02630/status.svg)](https://doi.org/10.21105/joss.02630)


# Troubleshooting and contribution

All troubleshooting and contributions can be found on the [Github page.](https://github.com/VincentAlcazer/StatAid/issues)

## Bug report

If you encounter any problem with the software or find a bug, please report it on GitHub:

- Create a [new issue](https://github.com/VincentAlcazer/StatAid/issues) on the Github page
- Try to describe the problem/bug with reproductible steps

## Feature request

To ask for new feature implementation/current feature enhancemenet:

- Create a [new issue](https://github.com/VincentAlcazer/StatAid/issues) on the Github page
- Briefly describe the research question you want to answer and the type of data you have
- If possible: provide pictures of the graph you would like to make or references from the paper you saw the analysis in.

## Contribution proposal

Contributions to new features or code enhancement are welcomed by creating a new [pull request.](https://github.com/VincentAlcazer/StatAid/pulls)

Owner

JOSS Publication

StatAid: An R package with a graphical user interface for data analysis

Published

October 29, 2020

DOI

10.21105/joss.02630

Volume 5, Issue 54, Page 2630

Authors

Vincent Alcazer
Cancer Research Center of Lyon, INSERM U1052, Lyon, FRANCE, Hospices Civils de Lyon, Lyon, FRANCE

Editor

Mikkel Meyer Andersen

Tags

Data analysis Medicine Science Survival analysis

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