Flexible link functions in a joint hierarchical Gaussian process model. Issue 2 (28th May 2020)
- Record Type:
- Journal Article
- Title:
- Flexible link functions in a joint hierarchical Gaussian process model. Issue 2 (28th May 2020)
- Main Title:
- Flexible link functions in a joint hierarchical Gaussian process model
- Authors:
- Su, Weiji
Wang, Xia
Szczesniak, Rhonda D. - Abstract:
- Abstract: Many longitudinal studies often require jointly modeling a biomarker and an event outcome, in order to provide more accurate inference and dynamic prediction of disease progression. Cystic fibrosis (CF) studies have illustrated the benefits of these models, primarily examining the joint evolution of lung‐function decline and survival. We propose a novel joint model within the shared‐parameter framework that accommodates nonlinear lung‐function trajectories, in order to provide more accurate inference on lung‐function decline over time and to examine the association between evolution of lung function and risk of a pulmonary exacerbation (PE) event recurrence. Specifically, a two‐level Gaussian process (GP) is used to estimate the nonlinear longitudinal trajectories and a flexible link function is introduced for a more accurate depiction of the binary process on the event outcome. Bayesian model assessment is used to evaluate each component of the joint model in simulation studies and an application to longitudinal data on patients receiving care from a CF center. A nonlinear structure is suggested by both longitudinal continuous and binary evaluations. Including a flexible link function improves model fit to these data. The proposed hierarchical GP model with a flexible power link function where Laplace distribution is the baseline (spep) has the best fit of all joint models considered, characterizing how accelerated lung‐function decline corresponds to increasedAbstract: Many longitudinal studies often require jointly modeling a biomarker and an event outcome, in order to provide more accurate inference and dynamic prediction of disease progression. Cystic fibrosis (CF) studies have illustrated the benefits of these models, primarily examining the joint evolution of lung‐function decline and survival. We propose a novel joint model within the shared‐parameter framework that accommodates nonlinear lung‐function trajectories, in order to provide more accurate inference on lung‐function decline over time and to examine the association between evolution of lung function and risk of a pulmonary exacerbation (PE) event recurrence. Specifically, a two‐level Gaussian process (GP) is used to estimate the nonlinear longitudinal trajectories and a flexible link function is introduced for a more accurate depiction of the binary process on the event outcome. Bayesian model assessment is used to evaluate each component of the joint model in simulation studies and an application to longitudinal data on patients receiving care from a CF center. A nonlinear structure is suggested by both longitudinal continuous and binary evaluations. Including a flexible link function improves model fit to these data. The proposed hierarchical GP model with a flexible power link function where Laplace distribution is the baseline (spep) has the best fit of all joint models considered, characterizing how accelerated lung‐function decline corresponds to increased odds of experiencing another PE. … (more)
- Is Part Of:
- Biometrics. Volume 77:Issue 2(2021)
- Journal:
- Biometrics
- Issue:
- Volume 77:Issue 2(2021)
- Issue Display:
- Volume 77, Issue 2 (2021)
- Year:
- 2021
- Volume:
- 77
- Issue:
- 2
- Issue Sort Value:
- 2021-0077-0002-0000
- Page Start:
- 754
- Page End:
- 764
- Publication Date:
- 2020-05-28
- Subjects:
- Bayesian joint model -- Bayesian model assessment -- cystic fibrosis -- flexible link function -- Gaussian process -- medical monitoring
Biometry -- Periodicals
570.15195 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1111/biom.13291 ↗
- Languages:
- English
- ISSNs:
- 0006-341X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 2088.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17328.xml