Joint modelling of accelerated failure time and longitudinal data
From MaRDI portal
Publication:3597961
DOI10.1093/biomet/92.3.587zbMath1152.62380OpenAlexW1985671636MaRDI QIDQ3597961
Jane-Ling Wang, Yi-Kuan Tseng, Fushing Hsieh
Publication date: 29 January 2009
Published in: Biometrika (Search for Journal in Brave)
Full work available at URL: https://semanticscholar.org/paper/69936f33a632927dabf55ab1ca5ce4a05bb78f98
EM algorithmsurvival datameasurement errorMonte Carlo integrationmissing datarandom effectbootstrap estimate
Applications of statistics to biology and medical sciences; meta analysis (62P10) Monte Carlo methods (65C05) Estimation in survival analysis and censored data (62N02)
Related Items
Joint modelling of longitudinal binary data and survival data ⋮ A flexible link for joint modelling longitudinal and survival data accounting for individual longitudinal heterogeneity ⋮ New estimates of odd exponents of infinite Burnside groups. ⋮ Using the Score Test to Identify the Longitudinal Biomarker Considering Accelerate Failure Time Model with the Frailty in Survival Analysis ⋮ Joint analysis of longitudinal and interval-censored failure time data ⋮ Semiparametric efficient estimation for shared-frailty models with doubly-censored clustered data ⋮ Joint model of multiple longitudinal measures and a binary outcome: An application to predict orthostatic hypertension for subacute stroke patients ⋮ A Kernel Smooth Approach for Joint Modeling of Accelerated Failure Time and Longitudinal Data ⋮ A Semiparametric Joint Model for Longitudinal and Survival Data with Application to Hemodialysis Study ⋮ GPU accelerated estimation of a shared random effect joint model for dynamic prediction ⋮ Joint modeling of multivariate longitudinal mixed measurements and time to event data using a Bayesian approach ⋮ Regression Analysis of Spatially Correlated Event Durations With Missing Origins Annotated by Longitudinal Measures ⋮ Time-to-Event Analysis with Unknown Time Origins via Longitudinal Biomarker Registration ⋮ Joint modeling of longitudinal count and time-to-event data with excess zero using accelerated failure time model: an application with CD4 cell counts ⋮ Review and Comparison of Computational Approaches for Joint Longitudinal and Time‐to‐Event Models ⋮ Spatial joint models through Bayesian structured piecewise additive joint modelling for longitudinal and time-to-event data ⋮ Modeling Longitudinal Data with Nonparametric Multiplicative Random Effects Jointly with Survival Data ⋮ A Two-Part Joint Model for the Analysis of Survival and Longitudinal Binary Data with Excess Zeros ⋮ Penalized likelihood approach for simultaneous analysis of survival time and binary longitudinal outcome ⋮ Joint modeling of survival time and longitudinal outcomes with flexible random effects ⋮ A Joint Model for Longitudinal Measurements and Survival Data in the Presence of Multiple Failure Types ⋮ The joint model of the logistic model and linear random effect model -- an application to predict orthostatic hypertension for subacute stroke patients ⋮ Joint modelling of longitudinal biomarker and gap time between recurrent events: copula-based dependence ⋮ Joint analysis of longitudinal data and competing terminal events in the presence of dependent observation times with application to chronic kidney disease ⋮ A shared parameter model of longitudinal measurements and survival time with heterogeneous random-effects distribution ⋮ Discussion of the paper ‘A general framework for functional regression modelling’ ⋮ Joint modeling of failure time data with transformation model and longitudinal data when covariates are measured with errors ⋮ Joint Inference on HIV Viral Dynamics and Immune Suppression in Presence of Measurement Errors ⋮ Modeling left-truncated and right-censored survival data with longitudinal covariates ⋮ Stochastic model for analysis of longitudinal data on aging and mortality ⋮ A review on joint models in biometrical research ⋮ Semiparametric transformation joint models for longitudinal covariates and interval-censored failure time ⋮ Regression analysis of interval-censored failure time data with time-dependent covariates ⋮ Joint model of accelerated failure time and mechanistic nonlinear model for censored covariates, with application in HIV/AIDS ⋮ Duration of long-term care: socio-economic factors, type of care interactions and evolution ⋮ Identification of potential longitudinal biomarkers under the accelerated failure time model in multivariate survival data ⋮ Predictive comparison of joint longitudinal-survival modeling: a case study illustrating competing approaches ⋮ A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects ⋮ The Method to Identify a Biomarker and to Evaluate Its Efficiency for Survival by Using the Joint Model of the Accelerate Failure Time and Longitudinal Data ⋮ Joint models for multiple longitudinal processes and time-to-event outcome ⋮ Semiparametric inference for survival models with step process covariates ⋮ Consistent estimation of a joint model for multivariate longitudinal and survival data with latent variables ⋮ Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data ⋮ Analysis of longitudinal and survival data: joint modeling, inference methods, and issues ⋮ A joint model for repeated events of different types and multiple longitudinal outcomes with application to a follow‐up study of patients after kidney transplant ⋮ Robust joint modeling of longitudinal measurements and time to event data using normal/independent distributions: A Bayesian approach ⋮ Accelerated failure time models for recurrent event data analysis and joint modeling ⋮ An issue about the efficacy for the time-to-event outcome based on accelerated failure time model with interaction of unrecognized heterogeneity and main effect
