Spatial joint models through Bayesian structured piecewise additive joint modelling for longitudinal and time-to-event data
From MaRDI portal
Publication:6089191
DOI10.1007/s11222-023-10293-5zbMath1523.62037arXiv2302.07020MaRDI QIDQ6089191
Thomas Kneib, Stefan Lang, Elisabeth Bergherr, Anja Rappl
Publication date: 17 November 2023
Published in: Statistics and Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2302.07020
Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Estimation in survival analysis and censored data (62N02)
Cites Work
- Unnamed Item
- Unnamed Item
- A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects
- Generalized linear mixed joint model for longitudinal and survival outcomes
- Piecewise exponential models for survival data with covariates
- Joint models with multiple longitudinal outcomes and a time-to-event outcome: a corrected two-stage approach
- Modular regression -- a Lego system for building structured additive distributional regression models with tensor product interactions
- Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data
- Modeling Longitudinal Data with Nonignorable Dropouts Using a Latent Dropout Class Model
- A discrete time event‐history approach to informative drop‐out in mixed latent Markov models with covariates
- Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time‐to‐event in presence of censoring and competing risks
- Estimation and Comparison of Changes in the Presence of Informative Right Censoring by Modeling the Censoring Process
- A Two-Part Joint Model for the Analysis of Survival and Longitudinal Binary Data with Excess Zeros
- Score Test for Conditional Independence Between Longitudinal Outcome and Time to Event Given the Classes in the Joint Latent Class Model
- Joint modelling of accelerated failure time and longitudinal data
- A Semi‐Parametric Shared Parameter Model to Handle Nonmonotone Nonignorable Missingness
- Partial likelihood
- Analysis of Censored Survival Data with Intermittently Observed Time-Dependent Binary Covariates
- A Joint Model for Survival and Longitudinal Data Measured with Error
- Boosting joint models for longitudinal and time‐to‐event data
- Flexible Bayesian additive joint models with an application to type 1 diabetes research
- Joint analysis of longitudinal and survival AIDS data with a spatial fraction of long‐term survivors: A Bayesian approach
- An Approximate Generalized Linear Model with Random Effects for Informative Missing Data
- A generalized additive model approach to time-to-event analysis
- Joint modelling of longitudinal measurements and event time data