Pages that link to "Item:Q3079019"
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The following pages link to A Semiparametric Likelihood Approach to Joint Modeling of Longitudinal and Time-to-Event Data (Q3079019):
Displaying 50 items.
- Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule (Q425636) (← links)
- A more flexible joint latent model for longitudinal and survival time data (Q626415) (← links)
- A penalized likelihood approach to joint modeling of longitudinal measurements and time-to-event data (Q660020) (← links)
- Modeling left-truncated and right-censored survival data with longitudinal covariates (Q693732) (← links)
- A review on joint models in biometrical research (Q715804) (← links)
- A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects (Q746093) (← links)
- Cox regression for mixed case interval-censored data with covariate errors (Q746150) (← links)
- Analysis of longitudinal and survival data: joint modeling, inference methods, and issues (Q764437) (← links)
- Bayesian analysis of multivariate t linear mixed models using a combination of IBF and Gibbs samplers (Q764498) (← links)
- Semiparametric analysis of panel count data with correlated observation and follow-up times (Q841055) (← links)
- ECM-based maximum likelihood inference for multivariate linear mixed models with autoregressive errors (Q962387) (← links)
- A latent factor model for spatial data with informative missingness (Q977647) (← links)
- A corrected pseudo-score approach for additive hazards model with longitudinal covariates measured with error (Q995814) (← links)
- Likelihood and pseudo-likelihood methods for semiparametric joint models for a primary endpoint and longitudinal data (Q1020673) (← links)
- Semiparametric Bayesian joint models of multivariate longitudinal and survival data (Q1623585) (← links)
- Penalized likelihood approach for simultaneous analysis of survival time and binary longitudinal outcome (Q1698208) (← links)
- Joint modeling of survival time and longitudinal outcomes with flexible random effects (Q1698947) (← links)
- Semiparametric transformation joint models for longitudinal covariates and interval-censored failure time (Q1796937) (← links)
- Consistent estimation of a joint model for multivariate longitudinal and survival data with latent variables (Q2057836) (← links)
- Semiparametric latent-class models for multivariate longitudinal and survival data (Q2119239) (← links)
- New approaches for censored longitudinal data in joint modelling of longitudinal and survival data, with application to HIV vaccine studies (Q2274672) (← links)
- Regression analysis of interval-censored failure time data with time-dependent covariates (Q2291291) (← links)
- An overview of semiparametric models in survival analysis (Q2454018) (← links)
- Analysis of joint multiple failure mode and linear degradation data with renewals (Q2455706) (← links)
- Functional approach of flexibly modelling generalized longitudinal data and survival time (Q2474384) (← links)
- A semiparametric estimator for the proportional hazards model with longitudinal covariates measured with error (Q2775639) (← links)
- Identification of potential longitudinal biomarkers under the accelerated failure time model in multivariate survival data (Q2807714) (← links)
- 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 (Q2815342) (← links)
- Partly conditional estimation of the effect of a time-dependent factor in the presence of dependent censoring (Q2846440) (← links)
- Joint models for longitudinal and time-to-event data. With applications in R (Q2889696) (← links)
- Using the Score Test to Identify the Longitudinal Biomarker Considering Accelerate Failure Time Model with the Frailty in Survival Analysis (Q2890113) (← links)
- A joint mixed effects dispersion model for menstrual cycle length and time-to-pregnancy (Q2912366) (← links)
- The Identification of Potential Longitudinal Biomarkers and Measurements of Effectiveness for Biomarkers as Surrogates in Multivariate Survival Data (Q2920068) (← links)
- Identification of Longitudinal Biomarkers in Survival Analysis for Competing Risks Data (Q2931542) (← links)
- Prediction of transplant-free survival in idiopathic pulmonary fibrosis patients using joint models for event times and mixed multivariate longitudinal data (Q2953284) (← links)
- Identification of longitudinal biomarkers for survival by a score test derived from a joint model of longitudinal and competing risks data (Q2953291) (← links)
- Cox regression for current status data with mismeasured covariates (Q3019144) (← links)
- Using Frailty Models to Identify the Longitudinal Biomarkers in Survival Analysis (Q3064066) (← links)
- On Estimating the Relationship between Longitudinal Measurements and Time-to-Event Data Using a Simple Two-Stage Procedure (Q3064295) (← links)
- Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data (Q3100782) (← links)
- Estimation of the Asymptotic Variance of Semiparametric Maximum Likelihood Estimators in the Cox Model with a Missing Time-Dependent Covariate (Q3155332) (← links)
- A Kernel Smooth Approach for Joint Modeling of Accelerated Failure Time and Longitudinal Data (Q3178529) (← links)
- Latent-Model Robustness in Joint Models for a Primary Endpoint and a Longitudinal Process (Q3183205) (← links)
- A Semiparametric Joint Model for Longitudinal and Survival Data with Application to Hemodialysis Study (Q3183207) (← links)
- Modeling Longitudinal Data with Nonparametric Multiplicative Random Effects Jointly with Survival Data (Q3506505) (← links)
- Semiparametric Approaches for Joint Modeling of Longitudinal and Survival Data with Time-Varying Coefficients (Q3506506) (← links)
- A Two-Part Joint Model for the Analysis of Survival and Longitudinal Binary Data with Excess Zeros (Q3506512) (← links)
- A Joint Model for Longitudinal Measurements and Survival Data in the Presence of Multiple Failure Types (Q3530092) (← links)
- Semiparametric Modeling of Longitudinal Measurements and Time‐to‐Event Data–A Two‐Stage Regression Calibration Approach (Q3549419) (← links)
- A Semi‐Parametric Shared Parameter Model to Handle Nonmonotone Nonignorable Missingness (Q3623742) (← links)
