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|Title:||A two-part mixed-effects model for analyzing clustered time-to-event data with clumping at zero||Authors:||Zhao, Jian
Binns, Colin W
Lee, Andy H.
|Keywords:||Science::Biological sciences||Issue Date:||2020||Source:||Zhao, J., Zhao, Y., Xiang, L., Khanal, V., Binns, C. W. & Lee, A. H. (2020). A two-part mixed-effects model for analyzing clustered time-to-event data with clumping at zero. Support UsContactAdmin Computer Methods and Programs in Biomedicine, 187, 105196-. https://dx.doi.org/10.1016/j.cmpb.2019.105196||Journal:||Support UsContactAdmin Computer Methods and Programs in Biomedicine||Abstract:||In longitudinal epidemiological studies consisting of a baseline stage and a follow-up stage, observations at the baseline stage may contain a countable proportion of negative responses. The time-to-event outcomes of those observations corresponding to negative responses at baseline can be denoted as zeros, which are excluded from standard survival analysis. Consequently, some important information on these subjects is therefore lost in the analysis. Furthermore, subjects are often clustered within hospitals, communities or health service centers, resulting in correlated observations. The framework of the two-part model has been developed and utilized widely to analyze semi-continuous data or count data with excess zeros, but its application to clustered time-to-event data with clumping at zero remains sparse.||URI:||https://hdl.handle.net/10356/154900||ISSN:||0169-2607||DOI:||10.1016/j.cmpb.2019.105196||Rights:||© 2019 Elsevier B.V. All rights reserved||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||SPMS Journal Articles|
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