Computationally efficient Bayesian inference for semi-parametric joint models of competing risks survival and skewed longitudinal data using integrated nested Laplace approximation
The application and simulation results revealed that both approaches provide accurate statistical estimation and inference. However, INLA significantly reduces the computational burden of the proposed joint models.
Authors
- Ding‐Geng Chen (ORCID: https://orcid.org/0000-0002-3199-8665)
- Melkamu Molla Ferede (ORCID: https://orcid.org/0000-0003-2213-7254)
- Najmeh Nakhaei Rad (ORCID: https://orcid.org/0000-0002-7831-5614)
Institutions
- Arizona State University (US)
- University of Pretoria (ZA)
- University of Gondar (ET)
Publication Details
- Journal
- BMC Medical Research Methodology
- Published
- 2025-09-02
- DOI
- https://doi.org/10.1186/s12874-025-02662-7
- Primary Topic
- Statistical Methods and Inference
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Research Foundation
- South African Medical Research Council
- University of Pretoria
- Department of Science and Technology, Ministry of Science and Technology, India
- University of Gondar
- Medical Research Council