A Review on Joint Models in Biometrical Research

Journal of statistical theory and practice 12/2009; 3(4). DOI: 10.1080/15598608.2009.10411965
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In some fields of biometrical research joint modelling of longitudinal measures and event time data has become very popular. This article reviews the work in that area of recent fruitful research by classifying approaches on joint models in three categories: approaches with focus on serial trends, approaches with focus on event time data and approaches with equal focus on both outcomes. Typically longitudinal measures and event time data are modelled jointly by introducing shared random effects or by considering conditional distributions together with marginal distributions. We present the approaches in an uniform nomenclature, comment on sub-models applied to longitudinal measures and event time data outcomes individually and exemplify applications in biometrical research.

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Available from: Christian Heumann, Aug 25, 2014
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    • "Joint models were introduced during the 1990s [8] [43] [46] and since then have been applied to a great variety of studies in epidemiological and biomedical areas. In turn, these studies have fed a wide methodological research on the subject, with models focused on event times, longitudinal patterns, or both ([24] [42] are excellent reviews up to date). "
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