nlpsem
0.4Nonlinear Longitudinal Process in Structural Equation Modeling
Overview
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 Liu (2025) doi:10.3758/s13428-025-02596-4.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-04-2512 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-03-109 OK · 4 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
Documentation
- Examples that run
- 88%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 37%
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Code & Tests
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Package metadata
- First published
- 2023-05-29
- Total releases
- 6 / 3 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 4.0.0
- Bundled data
- 72 KB / 1 file
- Download size
- 4.6 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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