Abstract
The shared frailty model described in Chapter 7 is very useful for bivariate data with common risk dependence, but in many cases, we do need extensions. In particular, for truly multivariate data, that is, when there are three or more observations, we need more models with varying degrees of dependence. This general frailty approach can be used to create a random treatment by group interaction, or other models with several sources of variation. Secondly, combining subgroups with different degrees of dependence in a single model, for example, monozygotic and dizygotic twins, is difficult in a shared frailty model. Furthermore, this extension can be an improvement for the consideration of effects of covariates in frailty models.
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© 2000 Springer Science+Business Media New York
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Hougaard, P. (2000). Multivariate frailty models. In: Analysis of Multivariate Survival Data. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1304-8_10
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DOI: https://doi.org/10.1007/978-1-4612-1304-8_10
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