Impact of dependent left truncation in semiparametric competing risks methods: A simulation study
If you need an accessible version of this item, please email your request to digschol@iu.edu so that they may create one and provide it to you.
Date
2017
Language
English
Embargo Lift Date
Committee Members
Degree
Degree Year
Department
Grantor
Journal Title
Journal ISSN
Volume Title
Found At
Taylor & Francis
Abstract
In this study, we investigated the robustness of the methods that account for independent left truncation when applied to competing risks settings with dependent left truncation. We specifically focused on the methods for the proportional cause-specific hazards model and the Fine–Gray model. Simulation experiments showed that these methods are not in general robust against dependent left truncation. The magnitude of the bias was analogous to the strength of the association between left truncation and failure times, the effect of the covariate on the competing cause of failure, and the baseline hazard of left truncation time.
Description
Keywords
item.page.description.tableofcontents
item.page.relation.haspart
Cite As
Bakoyannis, G., & Touloumi, G. (2017). Impact of dependent left truncation in semiparametric competing risks methods: a simulation study. Communications in Statistics-Simulation and Computation, 46(3), 2025-2042. http://dx.doi.org/10.1080/03610918.2015.1030415
ISSN
Publisher
Series/Report
Sponsorship
Major
Extent
Identifier
Relation
Journal
Communications in Statistics-Simulation and Computation
Source
Author
Alternative Title
Type
Article
Number
Volume
Conference Dates
Conference Host
Conference Location
Conference Name
Conference Panel
Conference Secretariat Location
Permanent Link
Version
Author's manuscript