Stable non-linear generalized Bayesian joint models for survival-longitudinal data

DOI10.1007/s13171-020-00233-0OpenAlexW3089772870MaRDI QIDQ6133713

Janet van Niekerk, Håvard Rue, Haakon Bakka

Publication date: 21 August 2023

Published in: Sankhyā. Series A (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10754/665413

zbMATH Keywords

survivallongitudinalINLAskew normallatent Gaussian modelBayesian smoothing spline

Mathematics Subject Classification ID

Bayesian inference (62F15) Estimation in survival analysis and censored data (62N02)

Cites Work

• Unnamed Item
• Unnamed Item
• Bayesian adaptive smoothing splines using stochastic differential equations
• Knot selection by boosting techniques
• Multivariate adaptive regression splines
• Penalising model component complexity: a principled, practical approach to constructing priors
• Joint model-based clustering of nonlinear longitudinal trajectories and associated time-to-event data analysis, linked by latent class membership: with application to AIDS clinical studies
• Knot selection for least-squares and penalized splines
• Approximate Bayesian Inference for Survival Models
• Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
• Extending Integrated Nested Laplace Approximation to a Class of Near-Gaussian Latent Models
• Improved dynamic predictions from joint models of longitudinal and survival data with time-varying effects using P-splines
• Development and validation of a dynamic prognostic tool for prostate cancer recurrence using repeated measures of posttreatment PSA: a joint modeling approach
• On the Second‐Order Random Walk Model for Irregular Locations
• Automatic Bayesian Curve Fitting
• A Joint Model for Survival and Longitudinal Data Measured with Error
• Flexible Bayesian additive joint models with an application to type 1 diabetes research
• Spatially Adaptive Regression Splines and Accurate Knot Selection Schemes
• Frequentist and Bayesian approaches for a joint model for prostate cancer risk and longitudinal prostate-specific antigen data
• Joint partially linear model for longitudinal data with informative drop‐outs
• Joint modelling of longitudinal measurements and event time data