A Joint Model for Longitudinal Measurements and Survival Data in the Presence of Multiple Failure Types
From MaRDI portal
Publication:3530092
DOI10.1111/j.1541-0420.2007.00952.xzbMath1170.62067OpenAlexW1985233017WikidataQ30490523 ScholiaQ30490523MaRDI QIDQ3530092
Robert M. Elashoff, Gang Li, Ning Li
Publication date: 15 October 2008
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc2751647
Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)
Related Items
Joint modeling of recurrent event processes and intermittently observed time-varying binary covariate processes, Joint analysis of longitudinal and interval-censored failure time data, Comparison of imputation methods for interval censored time-to-event data in joint modelling of tree growth and mortality, On the predictive performance of two Bayesian joint models: a simulation study, A joint modelling of socio-professional trajectories and cause-specific mortality, Identification of Longitudinal Biomarkers in Survival Analysis for Competing Risks Data, Bayesian inference on longitudinal-survival data with multiple features, Identification of longitudinal biomarkers for survival by a score test derived from a joint model of longitudinal and competing risks data, A flexible joint model for multiple longitudinal biomarkers and a time‐to‐event outcome: With applications to dynamic prediction using highly correlated biomarkers, Bayesian semiparametric joint model of multivariate longitudinal and survival data with dependent censoring, Dynamic risk score modeling for multiple longitudinal risk factors and survival, Dynamic prediction of mortality among patients in intensive care using the sequential organ failure assessment (SOFA) score: a joint competing risk survival and longitudinal modeling approach, Joint models with multiple longitudinal outcomes and a time-to-event outcome: a corrected two-stage approach, 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, Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule, Unnamed Item, Simultaneous inference of a misclassified outcome and competing risks failure time data, Simulated maximum likelihood estimation in joint models for multiple longitudinal markers and recurrent events of multiple types, in the presence of a terminal event, Bayesian varying coefficient mixed-effects joint models with asymmetry and missingness, An exploration of fixed and random effects selection for longitudinal binary outcomes in the presence of nonignorable dropout, Multiple-Imputation-Based Residuals and Diagnostic Plots for Joint Models of Longitudinal and Survival Outcomes, Semicompeting risks in aging research: methods, issues and needs, Regression analysis of interval-censored failure time data with time-dependent covariates, A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects, Bayesian inference of the fully specified subdistribution model for survival data with competing risks, Joint models for multiple longitudinal processes and time-to-event outcome, Assessing importance of biomarkers: A Bayesian joint modelling approach of longitudinal and survival data with semi-competing risks, Competing risks joint models using R-INLA, Joint modelling of longitudinal and survival data in the presence of competing risks with applications to prostate cancer data, Quantile regression-based Bayesian joint modeling analysis of longitudinal-survival data, with application to an AIDS cohort study, Joint model for left-censored longitudinal data, recurrent events and terminal event: Predictive abilities of tumor burden for cancer evolution with application to the FFCD 2000-05 trial, Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data, 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, Accelerated failure time models for recurrent event data analysis and joint modeling
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Longitudinal data analysis using generalized linear models
- Random-Effects Models for Longitudinal Data
- Asymptotic results for maximum likelihood estimators in joint analysis of repeated measurements and survival time
- Simultaneous modelling of survival and longitudinal data with an application to repeated quality of life measures
- A Semiparametric Likelihood Approach to Joint Modeling of Longitudinal and Time-to-Event Data
- A Bayesian Semiparametric Joint Hierarchical Model for Longitudinal and Survival Data
- Models for Longitudinal Data: A Generalized Estimating Equation Approach
- Joint Analysis of Longitudinal Data Comprising Repeated Measures and Times to Events
- Latent Pattern Mixture Models for Informative Intermittent Missing Data in Longitudinal Studies
- Joint modelling of accelerated failure time and longitudinal data
- Estimation of the parameters of a regression model with a multivariate t error variable
- Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
- The Analysis of Failure Times in the Presence of Competing Risks
- A Joint Model for Survival and Longitudinal Data Measured with Error
- Jointly Modeling Longitudinal and Event Time Data With Application to Acquired Immunodeficiency Syndrome
- Asymptotic Bias in the Linear Mixed Effects Model Under Non-Ignorable Missing Data Mechanisms
- Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data
- Modelling Progression of CD4-Lymphocyte Count and Its Relationship to Survival Time
- Modeling the Drop-Out Mechanism in Repeated-Measures Studies
- Joint modelling of longitudinal measurements and event time data