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

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 e ects 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.

Publication year:2014

Keywords:censoring, coarsening, missing at random, missingness, missing not at random, pattern-mixture model, selection model, shared-parameter model.

BOF-keylabel:yes

IOF-keylabel:yes

BOF-publication weight:1

CSS-citation score:1

Authors:International

Authors from:Higher Education

Accessibility:Open