SEMsens: A Tool for Sensitivity Analysis in Structural Equation Modeling

Perform sensitivity analysis in structural equation modeling using meta-heuristic optimization methods (e.g., ant colony optimization and others). The references for the proposed methods are: (1) Leite, W., & Shen, Z., Marcoulides, K., Fish, C., & Harring, J. (2022). <doi:10.1080/10705511.2021.1881786> (2) Harring, J. R., McNeish, D. M., & Hancock, G. R. (2017) <doi:10.1080/10705511.2018.1506925>; (3) Fisk, C., Harring, J., Shen, Z., Leite, W., Suen, K., & Marcoulides, K. (2022). <doi:10.1177/00131644211073121>; (4) Socha, K., & Dorigo, M. (2008) <doi:10.1016/j.ejor.2006.06.046>. We also thank Dr. Krzysztof Socha for sharing his research on ant colony optimization algorithm with continuous domains and associated R code, which provided the base for the development of this package.

Version: 1.5.5
Depends: R (≥ 3.5.0)
Imports: lavaan, stats
Suggests: knitr, rmarkdown
Published: 2022-08-30
DOI: 10.32614/CRAN.package.SEMsens
Author: Walter Leite [aut, cre], Zuchao Shen [aut], Charles Fisk [aut], King Yiu Suen [aut], Katerina Marcoulides [aut], Gail Fish [ctb], YongSeok Lee [ctb], Sanaz Nazari [ctb], Jia Quan [ctb], Eric Wright [ctb], Huibin Zhang [ctb]
Maintainer: Walter Leite <walter.leite at coe.ufl.edu>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
In views: Psychometrics
CRAN checks: SEMsens results

Documentation:

Reference manual: SEMsens.html , SEMsens.pdf
Vignettes: A Sensitivity Analysis of Toward a Greater Understanding of How Dissatisfaction Drives Employee Turnover by Peter W. Hom and Angelo J. Kinicki (source, R code)
Package 'SEMsens' (source, R code)
A sensitivity analysis of predicting continued use of online teacher professional development and the influence of social presence and sociability by Jo A. Smith and Stephen A. Sivo (source, R code)
A Sensitivity Analysis of a Model for Parenting Risk and Resilience, Social-emotional Readiness, and Reading Achievement in Kindergarten Children from Low-income Families Model by Smith-Adcock, Leite, Kaya and Amatea (source, R code)

Downloads:

Package source: SEMsens_1.5.5.tar.gz
Windows binaries: r-devel: SEMsens_1.5.5.zip, r-release: SEMsens_1.5.5.zip, r-oldrel: SEMsens_1.5.5.zip
macOS binaries: r-release (arm64): SEMsens_1.5.5.tgz, r-oldrel (arm64): SEMsens_1.5.5.tgz, r-release (x86_64): SEMsens_1.5.5.tgz, r-oldrel (x86_64): SEMsens_1.5.5.tgz
Old sources: SEMsens archive

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