Journal article
Joint longitudinal and time-to-event models for multilevel hierarchical data
SL Brilleman, MJ Crowther, M Moreno-Betancur, J Buros Novik, J Dunyak, N Al-Huniti, R Fox, J Hammerbacher, R Wolfe
Statistical Methods in Medical Research | SAGE PUBLICATIONS LTD | Published : 2019
Abstract
Joint modelling of longitudinal and time-to-event data has received much attention recently. Increasingly, extensions to standard joint modelling approaches are being proposed to handle complex data structures commonly encountered in applied research. In this paper, we propose a joint model for hierarchical longitudinal and time-to-event data. Our motivating application explores the association between tumor burden and progression-free survival in non-small cell lung cancer patients. We define tumor burden as a function of the sizes of target lesions clustered within a patient. Since a patient may have more than one lesion, and each lesion is tracked over time, the data have a three-level hi..
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Awarded by AstraZeneca
Funding Acknowledgements
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: SLB is funded by an Australian National Health and Medical Research Council (NHMRC) Postgraduate Scholarship (ref: APP1093145), with additional support from an NHMRC Centre of Research Excellence grant (ref: 1035261) awarded to the Victorian Centre for Biostatistics (ViCBiostat). MJC is partly funded by a UK Medical Research Council (MRC) New Investigator Research Grant (ref: MR/P015433/1).