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Title: | Bayesian model averaging in longitudinal studies using Bayesian variable selection methods | Authors: | YIMER, Belay Birlie OTAVA, Martin Degefa, Teshome Yewhalaw, Delenasaw SHKEDY, Ziv |
Issue Date: | 2023 | Publisher: | TAYLOR & FRANCIS INC | Source: | COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 52(6), p. 2646-2665 | Abstract: | Parameter estimation is often considered as a post model selection problem, i.e., the parameters of interest are often estimated based on "the best" model. However, this approach does not take into account that "the best" model was selected from a set of possible models. Ignoring this uncertainty may lead to bias in estimation. In this paper, we present a Bayesian variable selection (BVS) approach for model averaging which would address the model uncertainty. Although averaging would be preferred approach, BVS can be used as well for model selection if the interest is to select one among the set of candidate models. The performance of Bayesian variable selection is compared with the information criterion based model averaging on real longitudinal data and through simulations study. | Notes: | Yimer, BB (corresponding author), Univ Manchester, Ctr Epidemiol Versus Arthrit, Div Musculoskeletal & Dermatol Sci, Manchester M13 9PT, Lancs, England. belaybirlie.yimer@manchester.ac.uk |
Other: | Yimer, BB (corresponding author), Univ Manchester, Ctr Epidemiol Versus Arthrit, Div Musculoskeletal & Dermatol Sci, Manchester M13 9PT, Lancs, England. belaybirlie.yimer@manchester.ac.uk | Keywords: | Bayesian modeling;Bayesian variable selection;Clustering;Model selection;Multimodal inference;Information criteria | Document URI: | http://hdl.handle.net/1942/34076 | ISSN: | 0361-0918 | e-ISSN: | 1532-4141 | DOI: | 10.1080/03610918.2021.1914088 | ISI #: | WOS:000641535400001 | Rights: | 2021 Taylor & Francis Group, LLC | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2022 |
Appears in Collections: | Research publications |
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Bayesian model averaging in longitudinal studies using Bayesian variable selection methods.pdf Restricted Access | Early view | 4.22 MB | Adobe PDF | View/Open Request a copy |
BVS_Reviewed_V1.pdf | Peer-reviewed author version | 563.33 kB | Adobe PDF | View/Open |
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