| .github | ||
| data-raw | ||
| examples | ||
| inst | ||
| man | ||
| pkgdown | ||
| R | ||
| renv | ||
| tests | ||
| vignettes | ||
| .gitignore | ||
| .png | ||
| .Rbuildignore | ||
| .Rprofile | ||
| _pkgdown.yml | ||
| CITATION.cff | ||
| CODE_OF_CONDUCT.md | ||
| DESCRIPTION | ||
| favicon.png | ||
| FreesearchR.Rproj | ||
| LICENSE.md | ||
| NAMESPACE | ||
| NEWS.md | ||
| QA.md | ||
| README.md | ||
| renv.lock | ||
| ROADMAP.md | ||
| SESSION.md | ||
| umami-page.html | ||
FreesearchR 
The FreesearchR is a simple, clinical health data exploration and analysis tool to democratise clinical research by assisting any researcher to easily evaluate and analyse data and export publication ready results.
FreesearchR is free and open-source, and is directly accessible here: link to the app freely hosted on shinyapps.io. The app can also run locally, please see below.
All feedback is welcome and can be shared as a GitHub issue. Any suggestions on collaboration is much welcomed. Please reach out!
Motivation
This app has the following simple goals:
-
help the health clinician getting an overview of data in quality improvement projects and clinical research
-
help learners get a good start analysing data and coding in R
-
ease quick data overview and basic visualisations for any clinical researcher
Install locally
The FreesearchR-tool can also be launched locally. Any data.frame available in the global environment will be accessible from the interface.
require("devtools")
devtools::install_github("agdamsbo/FreesearchR")
library(FreesearchR)
# By loading mtcars to the environment, it will be available
# in the interface like any other data.frame
data(mtcars)
launch_FreesearchR()
Code of Conduct
Please note that the FreesearchR project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
Acknowledgements
Like any other project, this project was never possible without the great work of others. These are some of the sources and packages I have used:
-
gtsummary: superb and flexible way to create publication-ready analytical and summary tables.
-
dreamRs: maintainers of a broad selection of great extensions and tools for Shiny.
-
easystats: the
performance::check_model()function was central in sparking the idea to create a data analysis tool. -
IDEAfilter: a visually appealing data filter function based on the {shinyDataFilter}.
This project was all written by a human and not by any AI-based tools.