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Joint HGLM approach for repeated measures and survival data
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 Title & Authors
Joint HGLM approach for repeated measures and survival data
Ha, Il Do;
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 Abstract
In clinical studies, different types of outcomes (e.g. repeated measures data and time-to-event data) for the same subject tend to be observed, and these data can be correlated. For example, a response variable of interest can be measured repeatedly over time on the same subject and at the same time, an event time representing a terminating event is also obtained. Joint modelling using a shared random effect is useful for analyzing these data. Inferences based on marginal likelihood may involve the evaluation of analytically intractable integrations over the random-effect distributions. In this paper we propose a joint HGLM approach for analyzing such outcomes using the HGLM (hierarchical generalized linear model) method based on h-likelihood (i.e. hierarchical likelihood), which avoids these integration itself. The proposed method has been demonstrated using various numerical studies.
 Keywords
Frailty model;H-likelihood;hierarchical generalized linear model;joint model;random effects;
 Language
English
 Cited by
 References
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