Pages that link to "Item:Q5295355"
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The following pages link to A Nonlinear Model with Latent Process for Cognitive Evolution Using Multivariate Longitudinal Data (Q5295355):
Displaying 18 items.
- Multidimensional latent Markov models in a developmental study of inhibitory control and attentional flexibility in early childhood (Q615675) (← links)
- Discussion of: ``Predictive comparison of joint longitudinal-survival modeling: a case study illustrating competing approaches'' (Q746088) (← links)
- Isotone additive latent variable models (Q746242) (← links)
- A latent process model for dementia and psychometric tests (Q953241) (← links)
- Joint modelling of multivariate longitudinal outcomes and a time-to-event: a nonlinear latent class approach (Q961251) (← links)
- Analysis of multivariate non-Gaussian functional data: a semiparametric latent process approach (Q2078559) (← links)
- Conditional functional clustering for longitudinal data with heterogeneous nonlinear patterns (Q2154229) (← links)
- Dealing with death when studying disease or physiological marker: the stochastic system approach to causality (Q2274687) (← links)
- Efficient Estimation of the Nonparametric Mean and Covariance Functions for Longitudinal and Sparse Functional Data (Q3121179) (← links)
- Residual‐Based Diagnostics for Structural Equation Models (Q3623745) (← links)
- Modelling Sparse Generalized Longitudinal Observations with Latent Gaussian Processes (Q3631468) (← links)
- A multivariate finite mixture latent trajectory model with application to dementia studies (Q5138186) (← links)
- Scalable and robust latent trajectory class analysis using artificial likelihood (Q6076526) (← links)
- A universal approximate cross-validation criterion for regular risk functions (Q6593499) (← links)
- Mixture of longitudinal factor analyzers and their application to the assessment of chronic pain (Q6626850) (← links)
- Pathway testing for longitudinal metabolomics (Q6628087) (← links)
- A joint model for multiple dynamic processes and clinical endpoints: application to Alzheimer's disease (Q6628727) (← links)
- A latent variable approach to jointly modeling longitudinal and cumulative event data using a weighted two-stage method (Q6656320) (← links)
