Flexible modeling of multiple nonlinear longitudinal trajectories with censored and non-ignorable missing outcomes
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DOI: 10.1177/09622802221146312
Abstract: Multivariate nonlinear mixed-effects models (MNLMMs) have become a promising tool for analyzing multi-outcome longitudinal data following nonlinear trajectory patterns. However, such a classical analysis can be challenging due to censorship induced by detection limits of… read more here.
Keywords: modeling multiple; multiple nonlinear; flexible modeling; non ignorable ... See more keywords