Pages that link to "Item:Q660020"

The following pages link to A penalized likelihood approach to joint modeling of longitudinal measurements and time-to-event data (Q660020):

Displaying 18 items.

• A fast EM algorithm for fitting joint models of a binary response and multiple longitudinal covariates subject to detection limits (Q62047) (← links)
• Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule (Q425636) (← links)
• Joint modeling of longitudinal proportional measurements and survival time with a cure fraction (Q525900) (← links)
• Penalized likelihood approach for simultaneous analysis of survival time and binary longitudinal outcome (Q1698208) (← links)
• A Bayesian inference for the penalized spline joint models of longitudinal and time-to-event data: a prior sensitivity analysis (Q1985373) (← links)
• Jointly modeling longitudinal proportional data and survival times with an application to the quality of life data in a breast cancer trial (Q2356621) (← links)
• A Semiparametric Likelihood Approach to Joint Modeling of Longitudinal and Time-to-Event Data (Q3079019) (← links)
• Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data (Q3100782) (← links)
• Simultaneous variable selection for joint models of longitudinal and survival outcomes (Q3465745) (← links)
• Semiparametric Modeling of Longitudinal Measurements and Time‐to‐Event Data–A Two‐Stage Regression Calibration Approach (Q3549419) (← links)
• Penalized spline joint models for longitudinal and time-to-event data (Q4598617) (← links)
• Simultaneous Bayesian modeling of longitudinal and survival data in breast cancer patients (Q5079048) (← links)
• Joint models for multiple longitudinal processes and time-to-event outcome (Q5221561) (← links)
• Using the SAEM algorithm for mechanistic joint models characterizing the relationship between nonlinear PSA kinetics and survival in prostate cancer patients (Q5347442) (← links)
• A likelihood based approach for joint modeling of longitudinal trajectories and informative censoring process (Q5866044) (← links)
• A joint model for longitudinal outcomes with potential ceiling and floor effects and survival times, with applications to analysis of quality of life data from a cancer clinical trial (Q6543820) (← links)
• A joint model for dynamic prediction in uveitis (Q6625590) (← links)
• Joint modeling of binary response and survival for clustered data in clinical trials (Q6627304) (← links)