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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
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.pdf
Vignettes: A Sensitivity Analysis of Toward a Greater Understanding of How Dissatisfaction Drives Employee Turnover by Peter W. Hom and Angelo J. Kinicki
Package 'SEMsens'
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
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

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

Linking:

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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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