doi:10.31219/osf.io/pe5bj> and detailed description are given in Irmer et al. (2024b) <doi:10.3758/s13428-024-02476-3>.">

powerNLSEM: Simulation-Based Power Estimation (MSPE) for Nonlinear SEM (original) (raw)

Model-implied simulation-based power estimation (MSPE) for nonlinear (and linear) SEM, path analysis and regression analysis. A theoretical framework is used to approximate the relation between power and sample size for given type I error rates and effect sizes. The package offers an adaptive search algorithm to find the optimal N for given effect sizes and type I error rates. Plots can be used to visualize the power relation to N for different parameters of interest (POI). Theoretical justifications are given in Irmer et al. (2024a) <doi:10.31219/osf.io/pe5bj> and detailed description are given in Irmer et al. (2024b) <doi:10.3758/s13428-024-02476-3>.

Version: 0.1.2
Depends: ggplot2, stats, utils
Imports: crayon, lavaan (≥ 0.6.16), mvtnorm, numDeriv, pbapply, rlang (≥ 1.1.0), stringr
Suggests: knitr, MplusAutomation (≥ 0.7-2), rmarkdown, semTools, simsem
Published: 2024-09-27
DOI: 10.32614/CRAN.package.powerNLSEM
Author: Julien Patrick IrmerORCID iD [aut, cre, cph]
Maintainer: Julien Patrick Irmer
BugReports: https://github.com/jpirmer/powerNLSEM/issues
License: GPL-3
URL: https://github.com/jpirmer/powerNLSEM
NeedsCompilation: no
Citation: powerNLSEM citation info
Materials: README, NEWS
CRAN checks: powerNLSEM results

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