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lmeresampler  

Bootstrap Methods for Nested Linear Mixed-Effects Models
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]
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 Apr. 2025.
Previous versions and publish date:
0.1.0 (2016-07-15 00:31), 0.1.1 (2020-01-31 18:00), 0.2.0 (2021-05-01 18:20), 0.2.1 (2022-03-23 11:00), 0.2.2 (2022-04-30 00:50), 0.2.3 (2023-01-30 23:20)
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Complete documentation for lmeresampler
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