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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=nlpsem to link to this page.
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