Joint Models for a Primary Endpoint and Multiple Longitudinal Covariate Processes

DOI10.1111/j.1541-0420.2007.00822.xzbMath1274.62812OpenAlexW1999449968WikidataQ35645467 ScholiaQ35645467MaRDI QIDQ5449905

Erning Li, Naisyin Wang, Nae-Yuh Wang

Publication date: 19 March 2008

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4443486

zbMATH Keywords

asymptotic biasvariance componentsmeasurement errorconditional scoresufficiency scoregeneralized linear modelmultivariate longitudinal data

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Related Items (10)

Review and Comparison of Computational Approaches for Joint Longitudinal and Time‐to‐Event Models ⋮ An alternative REML estimation of covariance matrices in linear mixed models ⋮ A joint marginalized multilevel model for longitudinal outcomes ⋮ Semiparametric estimation for joint modeling of colorectal cancer risk and functional biomarkers measured with errors ⋮ Bayesian Nonparametric Regression Analysis of Data with Random Effects Covariates from Longitudinal Measurements ⋮ A fast EM algorithm for fitting joint models of a binary response and multiple longitudinal covariates subject to detection limits ⋮ A review on joint models in biometrical research ⋮ Comments on: Dynamic relations for sparsely sampled Gaussian processes ⋮ Consistent estimation of a joint model for multivariate longitudinal and survival data with latent variables ⋮ Logistic regression when covariates are random effects from a non-linear mixed model

Uses Software

• SAS

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Likelihood and pseudo-likelihood methods for semiparametric joint models for a primary endpoint and longitudinal data
• Using empirical partially Bayes inference for increased efficiency
• The effect of misspecifying the random-effects distribution in linear mixed models for longitudinal data
• Misspecified maximum likelihood estimates and generalised linear mixed models
• A semiparametric estimator for the proportional hazards model with longitudinal covariates measured with error
• A Semiparametric Likelihood Approach to Joint Modeling of Longitudinal and Time-to-Event Data
• An Approach to the Analysis of Repeated Measurements
• Conditional Estimation for Generalized Linear Models When Covariates Are Subject‐Specific Parameters in a Mixed Model for Longitudinal Measurements
• Joint Analysis of Longitudinal Data Comprising Repeated Measures and Times to Events
• Heteroscedastic Nonlinear Regression
• A Joint Model for Survival and Longitudinal Data Measured with Error
• Regression Analysis When Covariates Are Regression Parameters of a Random Effects Model for Observed Longitudinal Measurements
• Informative Drop-Out in Longitudinal Data Analysis
• Joint modelling of longitudinal measurements and event time data
• Functional methods for logistic regression on random-effect-coefficients for longitudinal measurements

This page was built for publication: Joint Models for a Primary Endpoint and Multiple Longitudinal Covariate Processes