medplot: a web application for dynamic summary and analysis of longitudinal medical data based on R

Area of Science:

• Biomedical Informatics
• Statistical Computing
• Data Science

Background:

• Longitudinal data analysis in biomedical studies is complex and often challenging for researchers with limited statistical expertise.
• Existing spreadsheet software lacks advanced analytical capabilities for longitudinal data.
• Specialized statistical software can have a steep learning curve for non-statisticians.

Purpose of the Study:

• To develop an interactive web application, medplot, for simplified exploration and analysis of longitudinal biomedical data.
• To provide researchers with limited statistical knowledge an accessible tool for data summarization, visualization, and analysis.
• To offer advanced analytical features not typically found in spreadsheet programs.

Main Methods:

• Development of medplot, an interactive, web-based application with a graphical user interface (GUI).
• Implementation of tools for data summarization, visualization, and advanced statistical analysis, including correction for multiple testing and repeated measures analysis.
• Demonstration of medplot's utility using real-world data from a clinical study of early Lyme borreliosis.

Main Results:

• medplot provides publication-ready tables and graphs for data summarization.
• The application enables advanced analyses such as correction for multiple testing and flexible non-linear modeling.
• medplot is freely available, open-source, and accessible via a web browser, requiring no local installation.

Conclusions:

• medplot effectively simplifies the exploration and analysis of longitudinal biomedical data for researchers.
• The application bridges the gap between basic spreadsheet tools and complex statistical software.
• medplot empowers researchers to perform sophisticated data analyses, enhancing biomedical research capabilities.