Joint Latent Process Models
Overview
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.
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- Exported functions with examples
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- Documented parameters
- 100%
- Return-value docs
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- Help pages citing references
- 22%
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Checks run against github.com/vivianephilipps/jlpm on 2026-10-18.
GitHub Pages site last deployed 2026-07-16
pkgdown site last built 2026-04-30, before release 1.0.4 (2026-05-04)
Dependencies
Installing JLPM adds 17 packages (11 with compiled code, 21 MB of source tarballs). Heaviest: stringi 11 MB, spacefillr 3.1 MB, Rcpp 1.8 MB.
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- 1.0.4Latest
- 1.0.32026-04-27 · diff ↗ ·
added 12 exports
IRT4Sselecting, IRT4Sstaging, REconddensity, WaldMult, convert, createFargs, createX0, diffSojournTime, loglik, predictRE, removeNA, sojournTime - RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 1.0.22023-10-06 · diff ↗
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 1.0.12022-03-31
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2022-03-31
- Total releases
- 4 / 4 yrs
- License
- GPL (>= 2.0)
- Minimum R
- ≥ 3.5.0
- Download size
- 97 KB
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