lmeresampler: Bootstrap Methods for Nested Linear Mixed-Effects Models

Bootstrap routines for nested linear mixed effects models fit using either 'lme4' or 'nlme'. The provided 'bootstrap()' function implements the parametric, residual, cases, semi-parametric (i.e., CGR), and random effect block (REB) bootstrap procedures. An overview of these procedures can be found in Van der Leeden et al. (2008) <doi:10.1007/978-0-387-73186-5_11>, Carpenter, Goldstein & Rasbash (2003) <doi:10.1111/1467-9876.00415>, and Chambers & Chandra (2013) <doi:10.1080/10618600.2012.681216>.

Version: 0.1.1
Depends: R (≥ 3.1.2)
Imports: boot, plyr, dplyr (≥ 0.8.0), Matrix, nlmeU, RLRsim
Suggests: lme4 (≥ 1.1-7), nlme, testthat, mlmRev
Published: 2020-01-31
Author: Adam Loy [aut, cre], Spenser steele [aut]
Maintainer: Adam Loy <loyad01 at gmail.com>
BugReports: https://github.com/aloy/lmeresampler/issues
License: GPL-3
URL: https://github.com/aloy/lmeresampler
NeedsCompilation: no
Materials: README NEWS
CRAN checks: lmeresampler results


Reference manual: lmeresampler.pdf
Package source: lmeresampler_0.1.1.tar.gz
Windows binaries: r-devel: lmeresampler_0.1.1.zip, r-release: lmeresampler_0.1.1.zip, r-oldrel: lmeresampler_0.1.1.zip
macOS binaries: r-release: lmeresampler_0.1.1.tgz, r-oldrel: lmeresampler_0.1.1.tgz
Old sources: lmeresampler archive

Reverse dependencies:

Reverse imports: varTestnlme


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