Welcome to StatAid

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. 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/.

Local version

You can install the development version from GitHub either by cloning the repository or directly by downloading the package in R:

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

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.

Troubleshooting and contribution

All troubleshooting and contributions can be found on the Github page.

Bug report

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

• Create a new issue 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 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.