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lmeresampler
View on CRAN: Click
here
Download and install lmeresampler package within the R console
Install from CRAN:
install.packages("lmeresampler")
Install from Github:
library("remotes")
install_github("cran/lmeresampler") Install by package version:
library("remotes")
install_version("lmeresampler", "0.2.4") Attach the package and use:
library("lmeresampler")
Maintained by
Adam Loy
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-07-15
Latest Update: 2023-02-11
Description:
Bootstrap routines for nested linear mixed effects models fit using
either 'lme4' or 'nlme'. The provided 'bootstrap()' function implements the
parametric, residual, cases, random effect block (REB), and wild bootstrap
procedures. An overview of these procedures can be found
in Van der Leeden et al. (2008) ,
Carpenter, Goldstein & Rasbash (2003) ,
and Chambers & Chandra (2013) .
How to cite:
Adam Loy (2016). lmeresampler: Bootstrap Methods for Nested Linear Mixed-Effects Models. R package version 0.2.4, https://cran.r-project.org/web/packages/lmeresampler. Accessed 11 Jun. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for lmeresampler
Functions, R codes and Examples using
the lmeresampler R package
Some associated functions: bootstrap . bootstrap_pvals . case_bootstrap . combine . combine_pvals . confint . extract_parameters . jsp728 . lmeresampler . parametric_bootstrap . pipe . plot . print.coef_tbl . print . reb_bootstrap . resid_bootstrap . summary . wild_bootstrap .
Some associated R codes: bootstrap_lme4.R . bootstrap_nlme.R . combine_lmersamp.R . complete.R . confint.R . data.R . error_messages.R . generics.R . lme4_invlink.R . lme4_utility_functions.R . lme_utilities.R . lmeresampler.R . plot.R . print.R . pvals.R . resamplers.R . setup.R . summary.R . utils-pipe.R . Full lmeresampler package functions and examples
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