Pages that link to "Item:Q1799810"
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The following pages link to Bayesian functional joint models for multivariate longitudinal and time-to-event data (Q1799810):
Displaying 11 items.
- BFLCRM: a Bayesian functional linear Cox regression model for predicting time to conversion to Alzheimer's disease (Q262406) (← links)
- Joint modeling of longitudinal continuous, longitudinal ordinal, and time-to-event outcomes (Q825203) (← links)
- Time-varying Markov regression random-effect model with Bayesian estimation procedures: Application to dynamics of functional recovery in patients with stroke (Q991537) (← links)
- Bayesian approach for joint longitudinal and time-to-event data with survival fraction (Q998806) (← links)
- Functional linear regression model with randomly censored data: predicting conversion time to Alzheimer 's disease (Q2189620) (← links)
- FLCRM: Functional linear cox regression model (Q3119810) (← links)
- Pairwise estimation of multivariate longitudinal outcomes in a Bayesian setting with extensions to the joint model (Q3389296) (← links)
- Joint modelling of longitudinal response and time-to-event data using conditional distributions: a Bayesian perspective (Q5092989) (← links)
- A Bayesian approach to joint modeling of matrix‐valued imaging data and treatment outcome with applications to depression studies (Q5128776) (← links)
- Joint model for survival and multivariate sparse functional data with application to a study of Alzheimer's Disease (Q6079458) (← links)
- A Gaussian copula joint model for longitudinal and time-to-event data with random effects (Q6113736) (← links)
