The Interactive Trial Data Analysis app is designed to provide advanced data visualization and imputation techniques for clinical trial data. It employs the mice package to handle missing data and offers dynamic, interactive visualizations to enhance data interpretation.
The app includes multiple components each tailored to specific analysis needs:
- Data Imputation App: Enables the imputation of missing data for C-peptide and Glucose measurements using multiple imputation methods.
- Summary Plots App: Provides tools for visualizing summary statistics for the clinical trial data.
- AUC Calculation App: Calculates the Area Under the Curve (AUC) for selected measurements and visualizes the results.
- Index Calculation App: Computes and visualizes the index for Glucose and C-peptide measurements based on AUC.
To run this app, you will need R installed on your system along with the Shiny package and other dependencies.
- R (Version 4.0 or later recommended)
- RStudio (Optional, but recommended for ease of use)
install.packages(c("shiny", "plotly", "dplyr", "mice", "shinyjs", "gt", "shinyWidgets", "shinycssloaders"))
To run the app locally:
- Clone or download this repository to your local machine.
- Open
app.Rin RStudio or your preferred R environment. - Load the required libraries and run the app using:
library(shiny)
runApp("app.R")
After launching the app, navigate through the various tabs to access different functionalities:
- Set imputation parameters and run the imputation.
- View and interact with the generated plots and tables for both raw and imputed data.
- Calculate and visualize AUC and Index values, adjusting parameters as needed for detailed analysis.
Contributions to enhance the app or add new features are welcome. Please fork the repository and submit pull requests with your proposed changes.
This project is open-sourced under the MIT License. See the LICENSE file for more details.
For any queries or further assistance with setting up or running the app, please contact: