Joint modeling of survival time and longitudinal outcomes with flexible random effects
DOI10.1007/s10985-017-9405-4zbMath1468.62378OpenAlexW2751997988WikidataQ38601043 ScholiaQ38601043MaRDI QIDQ1698947
Donglin Zeng, Jaeun Choi, Jianwen Cai, Andrew F. Olshan
Publication date: 16 February 2018
Published in: Lifetime Data Analysis (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc5756108
maximum likelihood estimatorGaussian mixturesrandom effectgeneralized linear mixed modelsimultaneous modelingstratified Cox proportional hazards model
Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02) Reliability and life testing (62N05)
Related Items (2)
Cites Work
- Linear Mixed Models with Flexible Distributions of Random Effects for Longitudinal Data
- Semi-Nonparametric Maximum Likelihood Estimation
- A joint model of longitudinal and competing risks survival data with heterogeneous random effects and outlying longitudinal measurements
- Inferences for joint modelling of repeated ordinal scores and time to event data
- A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects
- Examples in which misspecification of a random effects distribution reduces efficiency, and possible remedies
- Flexible random intercept models for binary outcomes using mixtures of normals
- Estimating the dimension of a model
- Penalized likelihood approach for simultaneous analysis of survival time and binary longitudinal outcome
- Modified likelihood ratio test in finite mixture models with a structural parameter
- 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
- Misspecified maximum likelihood estimates and generalised linear mixed models
- A semiparametric estimator for the proportional hazards model with longitudinal covariates measured with error
- The Evaluation of Multiple Surrogate Endpoints
- 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
- A Linear Mixed-Effects Model With Heterogeneity in the Random-Effects Population
- Simulation-Extrapolation: The Measurement Error Jackknife
- Latent-Model Robustness in Joint Models for a Primary Endpoint and a Longitudinal Process
- Joint Analysis of Time‐to‐Event and Multiple Binary Indicators of Latent Classes
- Joint Analysis of Longitudinal Data Comprising Repeated Measures and Times to Events
- Estimation and Comparison of Changes in the Presence of Informative Right Censoring by Modeling the Censoring Process
- Modeling Longitudinal Data with Nonparametric Multiplicative Random Effects Jointly with Survival Data
- Semiparametric Approaches for Joint Modeling of Longitudinal and Survival Data with Time-Varying Coefficients
- A Two-Part Joint Model for the Analysis of Survival and Longitudinal Binary Data with Excess Zeros
- A Joint Model for Longitudinal Measurements and Survival Data in the Presence of Multiple Failure Types
- Semiparametric Modeling of Longitudinal Measurements and Time‐to‐Event Data–A Two‐Stage Regression Calibration Approach
- Joint modelling of accelerated failure time and longitudinal data
- Shared parameter models under random effects misspecification
- An Algorithm for Computing the Nonparametric MLE of a Mixing Distribution
- Simulation-Extrapolation Estimation in Parametric Measurement Error Models
- A Joint Model for Survival and Longitudinal Data Measured with Error
- Jointly Modeling Longitudinal and Event Time Data With Application to Acquired Immunodeficiency Syndrome
- Latent Class Models for Joint Analysis of Longitudinal Biomarker and Event Process Data
- A Semiparametric Bayesian Approach to the Random Effects Model
- Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm
- Regression Analysis When Covariates Are Regression Parameters of a Random Effects Model for Observed Longitudinal Measurements
- Modeling Repeated Count Data Subject to Informative Dropout
- Penalized minimum‐distance estimates in finite mixture models
- Modeling the Relationship of Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4 Counts in Patients with AIDS
- A factor mixture analysis model for multivariate binary data
- Estimating Heterogeneity in Random Effects Models for Longitudinal Data
- A shared parameter model of longitudinal measurements and survival time with heterogeneous random-effects distribution
- Joint Modeling of Survival and Longitudinal Data: Likelihood Approach Revisited
- Bayesian latent variable models for mixed discrete outcomes
- Latent-model robustness in structural measurement error models
- Joint modelling of longitudinal measurements and event time data
- Bayesian Variable Selection with Joint Modeling of Categorical and Survival Outcomes: An Application to Individualizing Chemotherapy Treatment in Advanced Colorectal Cancer
- Linear mixed models for longitudinal data
- Unnamed Item
This page was built for publication: Joint modeling of survival time and longitudinal outcomes with flexible random effects