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 doi:10.1016/j.ymeth.2022.03.003.
- Version1.0.2
- R version≥ 2.14.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release10/06/2023
Team
Viviane Philipps
Cecile Proust-Lima
Show author detailsRolesAuthorTiphaine Saulnier
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- Depends1 package
- Imports4 packages