lmeInfo: Information Matrices for 'lmeStruct' and 'glsStruct' Objects

Provides analytic derivatives and information matrices for fitted linear mixed effects (lme) models and generalized least squares (gls) models estimated using lme() (from package 'nlme') and gls() (from package 'nlme'), respectively. The package includes functions for estimating the sampling variance-covariance of variance component parameters using the inverse Fisher information. The variance components include the parameters of the random effects structure (for lme models), the variance structure, and the correlation structure. The expected and average forms of the Fisher information matrix are used in the calculations, and models estimated by full maximum likelihood or restricted maximum likelihood are supported. The package also includes a function for estimating standardized mean difference effect sizes (Pustejovsky, Hedges, and Shadish (2014) <doi:10.3102/1076998614547577>) based on fitted lme or gls models.

Version: 0.3.2
Depends: R (≥ 4.0.0)
Imports: nlme, stats
Suggests: covr, testthat (≥ 2.1.0), knitr, rmarkdown, scdhlm, mlmRev, carData, lme4, Matrix, merDeriv
Published: 2023-04-17
DOI: 10.32614/CRAN.package.lmeInfo
Author: James Pustejovsky ORCID iD [aut], Man Chen [aut, cre]
Maintainer: Man Chen <manchen9005 at gmail.com>
BugReports: https://github.com/jepusto/lmeInfo/issues
License: GPL-3
URL: https://jepusto.github.io/lmeInfo/
NeedsCompilation: no
Language: en-US
Materials: NEWS
In views: MixedModels
CRAN checks: lmeInfo results


Reference manual: lmeInfo.pdf
Vignettes: Information-matrices-for-fitted-lme-models


Package source: lmeInfo_0.3.2.tar.gz
Windows binaries: r-devel: lmeInfo_0.3.2.zip, r-release: lmeInfo_0.3.2.zip, r-oldrel: lmeInfo_0.3.2.zip
macOS binaries: r-release (arm64): lmeInfo_0.3.2.tgz, r-oldrel (arm64): lmeInfo_0.3.2.tgz, r-release (x86_64): lmeInfo_0.3.2.tgz, r-oldrel (x86_64): lmeInfo_0.3.2.tgz
Old sources: lmeInfo archive

Reverse dependencies:

Reverse imports: predictmeans, scdhlm
Reverse suggests: merDeriv, quest


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