Provides computational tools for nonlinear longitudinal models, in particular the intrinsically nonlinear models, in four scenarios: (1) univariate longitudinal processes with growth factors, with or without covariates including time-invariant covariates (TICs) and time-varying covariates (TVCs); (2) multivariate longitudinal processes that facilitate the assessment of correlation or causation between multiple longitudinal variables; (3) multiple-group models for scenarios (1) and (2) to evaluate differences among manifested groups, and (4) longitudinal mixture models for scenarios (1) and (2), with an assumption that trajectories are from multiple latent classes. The methods implemented are introduced in Jin Liu (2023) <doi:10.48550/arXiv.2302.03237>.
| Version: | 0.3 |
| Depends: | R (≥ 4.0.0), OpenMx (≥ 2.21.8) |
| Imports: | ggplot2, dplyr, tidyr, stringr, Matrix, nnet, readr, methods |
| Suggests: | knitr, rmarkdown |
| Published: | 2023-09-12 |
| DOI: | 10.32614/CRAN.package.nlpsem |
| Author: | Jin Liu [aut, cre] |
| Maintainer: | Jin Liu <Veronica.Liu0206 at gmail.com> |
| BugReports: | https://github.com/Veronica0206/nlpsem/issues |
| License: | GPL (≥ 3.0) |
| URL: | https://github.com/Veronica0206/nlpsem |
| NeedsCompilation: | no |
| CRAN checks: | nlpsem results |
| Reference manual: | nlpsem.pdf |
| Vignettes: |
getLCSM_examples getLGCM_examples getMGM_examples getMGroup_examples getMIX_examples getMediation_examples getTVC_examples |
| Package source: | nlpsem_0.3.tar.gz |
| Windows binaries: | r-devel: nlpsem_0.3.zip, r-release: nlpsem_0.3.zip, r-oldrel: nlpsem_0.3.zip |
| macOS binaries: | r-release (arm64): nlpsem_0.3.tgz, r-oldrel (arm64): nlpsem_0.3.tgz, r-release (x86_64): nlpsem_0.3.tgz, r-oldrel (x86_64): nlpsem_0.3.tgz |
| Old sources: | nlpsem archive |
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