Multivariate Survival Models
Sometimes, survival data come in clusters, and multivariate, or frailty, models are appropriate to use. Ever since the paper by J. Vaupel, K. Manton & E. Stallard, the concept of frailty has spread in even wider circles of the research community. Although their primary purpose was to show various consequences of admitting individual frailties, the effect was that people started to implement their frailty model in Cox regression models. A heuristic explanation to all this is the dynamics of the problem. The weaker individuals die first, and the proportion stronger will steadily grow as time goes by. Another terminology is to distinguish between individual and population hazards. Frailty models in survival analysis correspond to hierarchical models in linear or generalized linear models. They are also called mixed effects models. A simple way to eliminate the effect of clustering is to stratify on the clusters.