MEPHAS

MEPHAS provides statistical analysis for medical and pharmaceutical datasets using the R programming environment, implementing probability, hypothesis testing, regression models, and dimensional analyses.

Key Features:

• Comprehensive statistical functions: Implements probability calculations, hypothesis testing, regression models, and dimensional analyses.
• Advanced models: Includes extended Cox regression, partial least squares regression (PLS-R), and sparse partial least squares regression (SPLS-R).
• Results output: Generates plots and exports data tables as CSV files.

Scientific Applications:

• Clinical survival analysis: Time-to-event modeling using extended Cox regression for survival and prognostic studies.
• High-dimensional data analysis: Dimensional reduction and predictive modeling of multivariate or high-dimensional datasets using PLS-R and SPLS-R.
• Statistical inference in medical/pharmaceutical research: Probability calculations and hypothesis testing for experimental and observational studies.
• Regression-based covariate analysis: Application of regression models for assessment of associations and effects in clinical and pharmaceutical data.

Methodology:

Implemented in the R programming environment using the Shiny framework; includes implementations of extended Cox regression, partial least squares regression (PLS-R), and sparse partial least squares regression (SPLS-R); outputs tables as CSV and generates plots.