Package: rsem 0.5.1

rsem: Robust Structural Equation Modeling with Missing Data and Auxiliary Variables

A robust procedure is implemented to estimate means and covariance matrix of multiple variables with missing data using Huber weight and then to estimate a structural equation model.

Authors:Ke-Hai Yuan and Zhiyong Zhang

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rsem.pdf |rsem.html✨
rsem/json (API)

# Install 'rsem' in R:
install.packages('rsem', repos = c('https://johnnyzhz.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.89 score 2 packages 13 scripts 501 downloads 53 mentions 23 exports 6 dependencies

Last updated 1 years agofrom:1e9cd9cbb6. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-winOKOct 31 2024
R-4.5-linuxOKOct 31 2024
R-4.4-winOKOct 31 2024
R-4.4-macOKOct 31 2024
R-4.3-winOKOct 31 2024
R-4.3-macOKOct 31 2024

Exports:rsemrsem.Ascovrsem.DPrsem.emmusigrsem.fitrsem.gnamersem.indexrsem.indexvrsem.indexvcrsem.lavaanrsem.patternrsem.printrsem.sersem.ssqrsem.switchrsem.switch.gammarsem.vecrsem.vechrsem.weightsemdiag.call.eqssemdiag.combinationssemdiag.read.eqssemdiag.run.eqs

Dependencies:lavaanMASSmnormtnumDerivpbivnormquadprog