Fitting phase-type frailty models
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Frailty models are survival analysis models which account for heterogeneity and random effects in the data. In these models, the random effect (the frailty) is assumed to have a multiplicative effect on the hazard. In this paper, we present frailty models using phase-type distributions as the frailties. We explore the properties of the proposed frailty models and derive expectation-maximization algorithms for maximum-likelihood estimation. The algorithms' performance is illustrated in several numerical examples of practical significance.
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