= Shared frailty model
{title2=$\lambda_{ik}(t)=Y_{ik}(t)V_i h_{0k}(t)e^{z_i^{\mathsf T}\beta}$}
A <shared frailty model> assigns the same latent positive hazard multiplier $V_i$ to correlated event histories or group members. Gamma or lognormal frailty distributions are common examples. Modeling dependence through this latent effect yields conditional covariate effects; integrating out frailty can change the form of marginal hazards. Eligibility and event history still have to be encoded in the at-risk indicator.
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