powRICLPM: Perform Power Analysis for the Random Intercept Cross-Lagged Panel Model

Perform user-friendly power analyses for the bivariate random intercept cross-lagged panel model (RI-CLPM). The strategy as proposed by Mulder (2022) <doi:10.1080/10705511.2022.2122467> is implemented. Extended power analysis options include the use of bounded estimation, inclusion of measurement error in the data generating model and estimation model (i.e., the stable trait autoregressive trait state, STARTS, model), imposing various constraints over time on the parameters of the estimation model, among others.

Version: 0.1.1
Depends: R (≥ 4.0.0), stats, utils
Imports: dplyr, furrr, future, ggplot2, lavaan (≥ 0.6.7), progressr, purrr, rlang
Suggests: knitr, rmarkdown, testthat
Published: 2023-02-07
Author: Jeroen Mulder ORCID iD [aut, cre], Netherlands Organization for Scientific Research [fnd]
Maintainer: Jeroen Mulder <j.d.mulder at uu.nl>
BugReports: https://github.com/JeroenDMulder/powRICLPM/issues/
License: MIT + file LICENSE
URL: https://jeroendmulder.github.io/powRICLPM/
NeedsCompilation: no
Citation: powRICLPM citation info
Materials: README NEWS
CRAN checks: powRICLPM results

Documentation:

Reference manual: powRICLPM.pdf
Vignettes: FAQ
Mulder (2022)
Extensions
Using Mplus
Get started

Downloads:

Package source: powRICLPM_0.1.1.tar.gz
Windows binaries: r-devel: powRICLPM_0.1.1.zip, r-release: powRICLPM_0.1.1.zip, r-oldrel: powRICLPM_0.1.1.zip
macOS binaries: r-release (arm64): powRICLPM_0.1.1.tgz, r-oldrel (arm64): powRICLPM_0.1.1.tgz, r-release (x86_64): powRICLPM_0.1.1.tgz
Old sources: powRICLPM archive

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