Landmarking 2.0: Bridging the gap between joint models and landmarking.

ABSTRACT: The problem of dynamic prediction with time-dependent covariates, given by biomarkers, repeatedly measured over time, has received much attention over the last decades. Two contrasting approaches have become in widespread use. The first is joint modeling, which attempts to jointly model the longitudinal markers and the event time. The second is landmarking, a more pragmatic approach that avoids modeling the marker process. Landmarking has been shown to be less efficient than correctly specified joint models in simulation studies, when data are generated from the joint model. When the mean model is misspecified, however, simulation has shown that joint models may be inferior to landmarking. The objective of this article is to develop methods that improve the predictive accuracy of landmarki

SUBMITTER: Putter H 

PROVIDER: S-EPMC9304216 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature