A unified framework for complex survival data: accounting for clustering, cure fractions, and competing risks

Mixture cure models are widely used in survival analysis to represent populations comprising both cured and susceptible subgroups. Moving beyond conventional approaches that address isolated challenges, this study introduces an integrated systems framework for analyzing complex survival data. The proposed model simultaneously accounts for three interdependent components: (1) the existence of a cured fraction, (2) the presence of incurable competing risks, and (3) within-cluster correlations. To