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Lifecycle: stable Project Status: Active - The project has reached a stable, usable state and is being actively developed. Code size Last Commit at Main R-CMD-check

(Version 0.10.3, updated on 2023-05-05, release history)

semlbci

This package includes functions for forming the likelihood-based confidence intervals (LBCIs) for parameters in structural equation modeling. It also supports the robust LBCI proposed by Falk (2018). It was described in the following manuscript:

Cheung, S. F., & Pesigan, I. J. A. (2023). semlbci: An R package for forming likelihood-based confidence intervals for parameter estimates, correlations, indirect effects, and other derived parameters. Structural Equation Modeling: A Multidisciplinary Journal. Advance online publication. https://doi.org/10.1080/10705511.2023.2183860

More information on this package:

https://sfcheung.github.io/semlbci/

Installation

The latest version can be installed by remotes::install_github:

remotes::install_github("sfcheung/semlbci")

How To Use It

Illustration with examples can be found in the Get Started guide (vignette("semlbci", package = "semlbci")).

Implementation

It currently implements the algorithm illustrated by Pek and Wu (2018), adapted from Wu and Neale (2012) without adjustment for parameters with attainable bounds. It also supports the robust LBCI proposed by Falk (2018). More on the implementation can be found in the technical appendices.

References

Cheung, S. F., & Pesigan, I. J. A. (2023). semlbci: An R package for forming likelihood-based confidence intervals for parameter estimates, correlations, indirect effects, and other derived parameters. Structural Equation Modeling: A Multidisciplinary Journal. Advance online publication. https://doi.org/10.1080/10705511.2023.2183860

Falk, C. F. (2018). Are robust standard errors the best approach for interval estimation with nonnormal data in structural equation modeling? Structural Equation Modeling: A Multidisciplinary Journal, 25(2), 244-266. https://doi.org/10.1080/10705511.2017.1367254

Pek, J., & Wu, H. (2015). Profile likelihood-based confidence intervals and regions for structural equation models. Psychometrika, 80(4), 1123-1145. https://doi.org/10.1007/s11336-015-9461-1

Wu, H., & Neale, M. C. (2012). Adjusted confidence intervals for a bounded parameter. Behavior Genetics, 42(6), 886-898. https://doi.org/10.1007/s10519-012-9560-z

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Find the likelihood based confidence intervals for parameters in structural equation modeling

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