A Joint Model for Survival and Longitudinal Data Measured with Error
From MaRDI portal
Publication:4351031
DOI10.2307/2533118zbMath0874.62140OpenAlexW2034945547WikidataQ36860282 ScholiaQ36860282MaRDI QIDQ4351031
Anastasios A. Tsiatis, Michael S. Wulfsohn
Publication date: 9 November 1997
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.2307/2533118
Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10) Linear inference, regression (62J99)
Related Items
Joint modelling of longitudinal binary data and survival data ⋮ Joint models for a GLM-type longitudinal response and a time-to-event with smooth random effects ⋮ Joint analysis of longitudinal and interval-censored failure time data ⋮ Joint Modeling of Longitudinal and Survival Data via a Common Frailty ⋮ Bayesian Approach for Joint Modeling Longitudinal Data and Survival Data Simultaneously in Public Health Studies ⋮ Joint model of multiple longitudinal measures and a binary outcome: An application to predict orthostatic hypertension for subacute stroke patients ⋮ Joint Modeling of Survival and Longitudinal Data: Likelihood Approach Revisited ⋮ Analysis of Survival Data with Missing Measurements of a Time-Dependent Binary Covariate ⋮ On the predictive performance of two Bayesian joint models: a simulation study ⋮ The joint modeling approach with a simulation study for evaluating the association between the trajectory of serum albumin levels and mortality in peritoneal dialysis patients ⋮ A discrete time event‐history approach to informative drop‐out in mixed latent Markov models with covariates ⋮ Simultaneous variable selection for joint models of longitudinal and survival outcomes ⋮ JOINT MODEL PREDICTION AND APPLICATION TO INDIVIDUAL-LEVEL LOSS RESERVING ⋮ How the mechanism of missing data on longitudinal biomarkers influences the survival analysis ⋮ Simultaneous Bayesian modeling of longitudinal and survival data in breast cancer patients ⋮ Joint modelling of longitudinal response and time-to-event data using conditional distributions: a Bayesian perspective ⋮ On longitudinal prediction with time‐to‐event outcome: Comparison of modeling options ⋮ Partial least squares for functional joint models with applications to the Alzheimer's disease neuroimaging initiative study ⋮ A shared parameter mixture model for longitudinal income data with missing responses and zero rounding ⋮ Simultaneous variable selection and estimation for joint models of longitudinal and failure time data with interval censoring ⋮ Quantifying direct and indirect effect for longitudinal mediator and survival outcome using joint modeling approach ⋮ Joint modelling of longitudinal measurements and survival times via a multivariate copula approach ⋮ Variable Selection for Interval‐censored Failure Time Data ⋮ An efficient estimation approach to joint modeling of longitudinal and survival data ⋮ A flexible joint model for multiple longitudinal biomarkers and a time‐to‐event outcome: With applications to dynamic prediction using highly correlated biomarkers ⋮ Regression Analysis of Spatially Correlated Event Durations With Missing Origins Annotated by Longitudinal Measures ⋮ Bayesian semiparametric joint model of multivariate longitudinal and survival data with dependent censoring ⋮ Dynamic risk score modeling for multiple longitudinal risk factors and survival ⋮ Flexible link functions in a joint hierarchical Gaussian process model ⋮ Joint modeling of longitudinal count and time-to-event data with excess zero using accelerated failure time model: an application with CD4 cell counts ⋮ Biased estimation with shared parameter models in the presence of competing dropout mechanisms ⋮ Joint model for survival and multivariate sparse functional data with application to a study of Alzheimer's Disease ⋮ Review and Comparison of Computational Approaches for Joint Longitudinal and Time‐to‐Event Models ⋮ 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 ⋮ Spatial joint models through Bayesian structured piecewise additive joint modelling for longitudinal and time-to-event data ⋮ Bayesian latent multi‐state modeling for nonequidistant longitudinal electronic health records ⋮ Bayesian design of clinical trials using joint cure rate models for longitudinal and time-to-event data ⋮ Comparing crossing hazard rate functions by joint modelling of survival and longitudinal data ⋮ A Gaussian copula joint model for longitudinal and time-to-event data with random effects ⋮ 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 ⋮ Stable non-linear generalized Bayesian joint models for survival-longitudinal data ⋮ Bayesian estimation of two‐part joint models for a longitudinal semicontinuous biomarker and a terminal event with INLA: Interests for cancer clinical trial evaluation ⋮ Joint models for longitudinal and discrete survival data in credit scoring ⋮ Joint models of multivariate longitudinal outcomes and discrete survival data with INLA: an application to credit repayment behaviour ⋮ Handling missingness value on jointly measured time-course and time-to-event data ⋮ A two-stage approach for Bayesian joint models: reducing complexity while maintaining accuracy ⋮ Variable selection for partially linear proportional hazards model with covariate measurement error ⋮ Mixed-Poisson point process with partially observed covariates: ecological momentary assessment of smoking ⋮ A joint marginalized multilevel model for longitudinal outcomes ⋮ A Joint Model for Longitudinal Measurements and Survival Data in the Presence of Multiple Failure Types ⋮ Analysis of Longitudinal Data in the Presence of Informative Observational Times and a Dependent Terminal Event, with Application to Medical Cost Data ⋮ Longitudinal profiles of bounded outcome scores as predictors for disease activity in rheumatoid arthritis patients: a joint modeling approach ⋮ Frequentist and Bayesian approaches for a joint model for prostate cancer risk and longitudinal prostate-specific antigen data ⋮ Joint modelling of longitudinal biomarker and gap time between recurrent events: copula-based dependence ⋮ Semiparametric models of longitudinal and time-to-event data with applications to HIV viral dynamics and CD4 counts ⋮ Joint Modelling of Repeated Measurements and Time-to-Event Outcomes: Flexible Model Specification and Exact Likelihood Inference ⋮ Joint analysis of longitudinal data and competing terminal events in the presence of dependent observation times with application to chronic kidney disease ⋮ Application of trajectories from growth curve in identification of longitudinal biomarker for the multivariate survival 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 ⋮ Inference in randomized trials with death and missingness ⋮ Semiparametric Modeling of Longitudinal Measurements and Time‐to‐Event Data–A Two‐Stage Regression Calibration Approach ⋮ Two-step and likelihood methods for joint models of longitudinal and survival data ⋮ An exploration of fixed and random effects selection for longitudinal binary outcomes in the presence of nonignorable dropout ⋮ Partly Conditional Survival Models for Longitudinal Data ⋮ Multiple-Imputation-Based Residuals and Diagnostic Plots for Joint Models of Longitudinal and Survival Outcomes ⋮ On Corrected Score Approach for Proportional Hazards Model with Covariate Measurement Error ⋮ Bayesian Influence Measures for Joint Models for Longitudinal and Survival Data ⋮ Time‐Varying Latent Effect Model for Longitudinal Data with Informative Observation Times ⋮ A Bayesian Semiparametric Survival Model with Longitudinal Markers ⋮ Nonparametric Two-Sample Tests of Longitudinal Data with Termination Events ⋮ Advances in medical statistics arising from the AIDS epidemic ⋮ Simultaneous analysis of quality of life and survival data ⋮ Multi-state models for event history analysis ⋮ Techniques for incorporating longitudinal measurements into analyses of survival data from clinical trials ⋮ Correcting for Measurement Error in Individual‐Level Covariates in Nonlinear Mixed Effects Models ⋮ Regression Analysis When Covariates Are Regression Parameters of a Random Effects Model for Observed Longitudinal Measurements ⋮ Dynamic Prediction by Landmarking in Event History Analysis ⋮ Joint modelling of mixed outcome types using latent variables ⋮ Generalized shared-parameter models and missingness at random ⋮ Joint Models for a Primary Endpoint and Multiple Longitudinal Covariate Processes ⋮ Prospective Accuracy for Longitudinal Markers ⋮ Joint Analysis of Longitudinal Data with Informative Right Censoring ⋮ A Semiparametric Method for Estimating Population Size for Capture-Recapture Experiments with Random Covariates in Continuous Time ⋮ Local sensitivity to non-ignorability in joint models ⋮ Joint modelling of longitudinal and repeated time-to-event data using nonlinear mixed-effects models and the stochastic approximation expectation–maximization algorithm ⋮ Joint models for multiple longitudinal processes and time-to-event outcome ⋮ Random Changepoint Model for Joint Modeling of Cognitive Decline and Dementia ⋮ Joint modelling of longitudinal and survival data in the presence of competing risks with applications to prostate cancer data ⋮ Proportional Hazards Model With Covariate Measurement Error and Instrumental Variables ⋮ Estimation in captureâ recapture models when covariates are subject to measurement errors and missing data ⋮ Joint Models for Multivariate Longitudinal and Multivariate Survival 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 ⋮ Analysis of panel count data with measurement errors in the covariates ⋮ Analysis of a Partially Observed Binary Covariate Process and a Censored Failure Time in the Presence of Truncation and Competing Risks ⋮ A likelihood based approach for joint modeling of longitudinal trajectories and informative censoring process ⋮ Joint modeling of recurrent event processes and intermittently observed time-varying binary covariate processes ⋮ Estimation of the Asymptotic Variance of Semiparametric Maximum Likelihood Estimators in the Cox Model with a Missing Time-Dependent Covariate ⋮ Asymptotic theory for relative-risk models with missing time-dependent covariates ⋮ A flexible link for joint modelling longitudinal and survival data accounting for individual longitudinal heterogeneity ⋮ Using the Score Test to Identify the Longitudinal Biomarker Considering Accelerate Failure Time Model with the Frailty in Survival Analysis ⋮ Semiparametric Bayesian joint models of multivariate longitudinal and survival data ⋮ A fast approximate EM algorithm for joint models of survival and multivariate longitudinal data ⋮ Regression analysis of censored data with nonignorable missing covariates and application to Alzheimer disease ⋮ Faster Monte Carlo estimation of joint models for time-to-event and multivariate longitudinal data ⋮ Asymptotic results for maximum likelihood estimators in joint analysis of repeated measurements and survival time ⋮ Simultaneous Bayesian modelling of skew-normal longitudinal measurements with non-ignorable dropout ⋮ Semiparametric analysis of panel count data with correlated observation and follow-up times ⋮ Comparison of imputation methods for interval censored time-to-event data in joint modelling of tree growth and mortality ⋮ A Kernel Smooth Approach for Joint Modeling of Accelerated Failure Time and Longitudinal Data ⋮ Latent-Model Robustness in Joint Models for a Primary Endpoint and a Longitudinal Process ⋮ Estimation in Semiparametric Transition Measurement Error Models for Longitudinal Data ⋮ Regression Analysis of Longitudinal Data with Time-Dependent Covariates and Informative Observation Times ⋮ The Identification of Potential Longitudinal Biomarkers and Measurements of Effectiveness for Biomarkers as Surrogates in Multivariate Survival Data ⋮ Generalized log-logistic proportional hazard model with applications in survival analysis ⋮ Joint modeling of longitudinal and survival data with the Cox model and two-phase sampling ⋮ A joint modelling of socio-professional trajectories and cause-specific mortality ⋮ Joint latent class model of survival and longitudinal data: an application to CPCRA study ⋮ An update on statistical boosting in biomedicine ⋮ Identification of Longitudinal Biomarkers in Survival Analysis for Competing Risks Data ⋮ Bayesian inference on longitudinal-survival data with multiple features ⋮ An approach for jointly modeling multivariate longitudinal measurements and discrete time-to-event data ⋮ Empirical likelihood inference for longitudinal data with covariate measurement errors: an application to the LEAN study ⋮ Generalized linear mixed joint model for longitudinal and survival outcomes ⋮ Identification of longitudinal biomarkers for survival by a score test derived from a joint model of longitudinal and competing risks data ⋮ Accounting for dependent errors in predictors and time-to-event outcomes using electronic health records, validation samples and multiple imputation ⋮ A more flexible joint latent model for longitudinal and survival time data ⋮ Joint models with multiple longitudinal outcomes and a time-to-event outcome: a corrected two-stage approach ⋮ Semiparametric analysis of longitudinal data with informative observation times ⋮ Penalized likelihood approach for simultaneous analysis of survival time and binary longitudinal outcome ⋮ Joint modeling of longitudinal drug using pattern and time to first relapse in cocaine dependence treatment data ⋮ Longitudinal data with follow-up truncated by death: match the analysis method to research aims ⋮ 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 ⋮ The joint model of the logistic model and linear random effect model -- an application to predict orthostatic hypertension for subacute stroke patients ⋮ Estimation of reliability using failure-degradation data with explanatory variables ⋮ Joint modeling for mixed-effects quantile regression of longitudinal data with detection limits and covariates measured with error, with application to AIDS studies ⋮ An overview of semiparametric models in survival analysis ⋮ Analysis of joint multiple failure mode and linear degradation data with renewals ⋮ Varying-coefficient models for longitudinal processes with continuous-time informative dropout ⋮ A marginalized conditional linear model for longitudinal binary data when informative dropout occurs in continuous time ⋮ Measurement error in proportional hazards models for survival data with long-term survivors ⋮ Approximate nonparametric corrected-score method for joint modeling of survival and longitudinal data measured with error ⋮ Inference in the additive risk model with time-varying covariates subject to measurement errors ⋮ A latent process model for dementia and psychometric tests ⋮ Functional approach of flexibly modelling generalized longitudinal data and survival time ⋮ Bias in the last observation carried forward method under informative dropout ⋮ A fast EM algorithm for fitting joint models of a binary response and multiple longitudinal covariates subject to detection limits ⋮ Joint modeling of failure time data with transformation model and longitudinal data when covariates are measured with errors ⋮ Modeling left-truncated and right-censored survival data with longitudinal covariates ⋮ Regression analysis of longitudinal data with time-dependent covariates in the presence of informative observation and censoring times ⋮ Stochastic model for analysis of longitudinal data on aging and mortality ⋮ Asymptotic theory for the Cox model with missing time-dependent covariate ⋮ A review on joint models in biometrical research ⋮ Assessing the association between trends in a biomarker and risk of event with an application in pediatric HIV/AIDS ⋮ Survival models and health sequences ⋮ A corrected pseudo-score approach for additive hazards model with longitudinal covariates measured with error ⋮ Using Frailty Models to Identify the Longitudinal Biomarkers in Survival Analysis ⋮ A Score Test for Association of a Longitudinal Marker and an Event with Missing Data ⋮ Semiparametric transformation joint models for longitudinal covariates and interval-censored failure time ⋮ Two-stage joint model for multivariate longitudinal and multistate processes, with application to renal transplantation data ⋮ Regression analysis of interval-censored failure time data with time-dependent covariates ⋮ Mixed effects models for recurrent events data with partially observed time-varying covariates: Ecological momentary assessment of smoking ⋮ Estimating a unitary effect summary based on combined survival and quantitative outcomes ⋮ Identification of potential longitudinal biomarkers under the accelerated failure time model in multivariate survival data ⋮ Joint modeling of longitudinal data with a dependent terminal event ⋮ The Evaluation of Multiple Surrogate Endpoints ⋮ Survival Analysis Using Auxiliary Variables Via Multiple Imputation, with Application to AIDS Clinical Trial Data ⋮ 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 Bayesian Approach for Joint Modeling of Cluster Size and Subunit-Specific Outcomes ⋮ Bayesian Approaches to Joint Cure-Rate and Longitudinal Models with Applications to Cancer Vaccine Trials ⋮ The Cox Proportional Hazards Model with a Continuous Latent Variable Measured by Multiple Binary Indicators ⋮ 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 ⋮ Analyzing longitudinal data with informative observation times under biased sampling ⋮ Joint Model of Clustered Failure Time Data with Informative Cluster Size ⋮ Likelihood and pseudo-likelihood methods for semiparametric joint models for a primary endpoint and longitudinal data ⋮ 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 ⋮ Logistic regression when covariates are random effects from a non-linear mixed model ⋮ Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data ⋮ Mixed-effects Tobit joint models for longitudinal data with skewness, detection limits, and measurement errors ⋮ Analysis of longitudinal and survival data: joint modeling, inference methods, and issues ⋮ A Comparative Study of Approaches for Predicting Prostate Cancer from Longitudinal Data ⋮ Statistical analysis of zero-inflated nonnegative continuous data: a review ⋮ Partly Conditional Estimation of the Effect of a Time‐Dependent Factor in the Presence of Dependent Censoring ⋮ Marker-dependent observation and carry-forward of internal covariates in Cox regression ⋮ Adjusting regression attenuation in the Cox proportional hazards model ⋮ The proportional hazards model with covariate measurement error ⋮ A new approach for joint modelling of longitudinal measurements and survival times with a cure fraction ⋮ Simultaneous modelling of survival and longitudinal data with an application to repeated quality of life measures ⋮ Accelerated failure time models for recurrent event data analysis and joint modeling ⋮ Modelling Survival Events with Longitudinal Covariates Measured with Error ⋮ Non-parametric estimation from simultaneous renewal -- failure -- degradation data with competing risks ⋮ A joint-modeling approach to assess the impact of biomarker variability on the risk of developing clinical outcome
