Improved prediction of extreme random effects in joint models: WRaPs (opens in new tab)

Mixed models are popular for the prediction of subject-specific repeated outcomes or center performance among many centers. When the goal is to identify extreme or poor outcomes, standard random effects predictions may, however, suffer from regression to the mean and underestimate values in the tail of their distribution. Optimally weighted random effect estimators have recently been proposed to mitigate this. Motivated by clinical settings wher...