A characterization of missingness at random in a generalized shared-parameter joint modeling framework for longitudinal and time-to-event data, and sensitivity analysis

EN Njagi, G Molenberghs, MG Kenward, G Verbeke, Dimitris Rizopoulos

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9 Citations (Scopus)


We consider a conceptual correspondence between the missing data setting, and joint modeling of longitudinal and time-to-event outcomes. Based on this, we formulate an extended shared random effects joint model. Based on this, we provide a characterization of missing at random, which is in line with that in the missing data setting. The ideas are illustrated using data from a study on liver cirrhosis, contrasting the new framework with conventional joint models.
Original languageUndefined/Unknown
Pages (from-to)1001-1015
Number of pages15
JournalBiometrical Journal
Issue number6
Publication statusPublished - 2014

Research programs

  • EMC NIHES-01-66-01

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