survivalModel, a crucial element of the MEPHAS suite, provides a robust user interface for conducting survival analysis on diverse datasets. Survival analysis is a statistical method used to analyze the time until an event of interest occurs. As part of the open-source MEPHAS platform, survivalModel caters to researchers by facilitating the calculation of descriptive statistics, plotting variables, and building simple or multiple survival analysis models. Users benefit from efficient and user-friendly tools that allow them to perform KM Survival Analysis, Cox Regression, or Accelerated Failure Time (AFT) model analysis. It's important to note that KM Survival Analysis is non-parametric and uses a single binary predictor, while Cox Regression is semi-parametric and supports both continuous and binary predictors. This distinction enhances the versatility of survivalModel for diverse analytical needs. original publication: BMC Bioinformatics. 2020 May 11;21(1):183.

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