JLPM
Joint Latent Process Models
Estimation of extended joint models with shared random effects. Longitudinal data are handled in latent process models for continuous (Gaussian or curvilinear) and ordinal outcomes while proportional hazard models are used for the survival part. We propose a frequentist approach using maximum likelihood estimation. See Saulnier et al, 2022
- Version1.0.2
- R version≥ 2.14.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release10/06/2023
Team
Viviane Philipps
Tiphaine Saulnier
Show author detailsRolesAuthorCecile Proust-Lima
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- Depends2 packages
- Imports4 packages