Pages that link to "Item:Q614171"

The following pages link to An approach for jointly modeling multivariate longitudinal measurements and discrete time-to-event data (Q614171):

Displaying 20 items.

• Faster Monte Carlo estimation of joint models for time-to-event and multivariate longitudinal data (Q830615) (← links)
• Semiparametric Bayesian joint models of multivariate longitudinal and survival data (Q1623585) (← links)
• Survival models and health sequences (Q2274641) (← links)
• A joint model for longitudinal continuous and time-to-event outcomes with direct marginal interpretation (Q2857488) (← links)
• Estimating Time to Event From Longitudinal Categorical Data (Q3632591) (← links)
• Two-step and likelihood methods for joint models of longitudinal and survival data (Q4638799) (← links)
• Conditional Modeling of Longitudinal Data With Terminal Event (Q4690963) (← links)
• (Q4690976) (← links)
• Jointly modelling multiple transplant outcomes by a competing risk model via functional principal component analysis (Q5058223) (← links)
• The analysis of student paths at the University using the multivariate joint models (Q5860760) (← links)
• Joint models for longitudinal and discrete survival data in credit scoring (Q6167389) (← links)
• Semiparametric multivariate joint model for skewed-longitudinal and survival data: a Bayesian approach (Q6560485) (← links)
• Shared random parameter models: a legacy of the biostatistics program at the National Heart, Lung, and Blood Institute (Q6625653) (← links)
• Flexible multivariate joint model of longitudinal intensity and binary process for medical monitoring of frequently collected data (Q6627714) (← links)
• Joint modeling of longitudinal data with informative cluster size adjusted for zero-inflation and a dependent terminal event (Q6627955) (← links)
• Graphical models for mean and covariance of multivariate longitudinal data (Q6627998) (← links)
• A joint model for multiple dynamic processes and clinical endpoints: application to Alzheimer's disease (Q6628727) (← links)
• Incorporating longitudinal biomarkers for dynamic risk prediction in the era of big data: a pseudo-observation approach (Q6629825) (← links)
• Joint models of longitudinal and time-to-event data with more than one event time outcome: a review (Q6636164) (← links)
• A novel block-coordinate gradient descent algorithm for simultaneous grouped selection of fixed and random effects in joint modeling (Q6652620) (← links)