Article

Using joint models to adjust for informative drop-out when modelling a longitudinal biomarker: an application to type 2 diabetes disease progression

2021-06-17

Abstract excerpt

Linear mixed effects models are frequently used in biomedical statistics to model the trajectory of a repeatedly measured longitudinal variable, such as a biomarker, over time. However, population-level estimates may be biased by censoring bias resulting from exit criteria that depend on the variable in question. A joint longitudinal-survival model, in which the exit criteria and longitudinal variable are modelled...

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Literature Corpus work: 8ce133c7-7c26-5fdc-9097-b1c59f921219
DOI: 10.1101/2021.06.17.448796

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