Package: bootmlm 0.1.0.9000

bootmlm: Bootstrap Resampling for Multilevel Models

An implementation of functions for bootstrapping with multilevel data and models (and mixed-effect models). It implements multiple bootstrap methods under the parametric, residual, and case bootstrap categories. Currently it supports fitted objects from the lme4 package.

Authors:Mark Lai [aut, cre]

bootmlm_0.1.0.9000.tar.gz
bootmlm_0.1.0.9000.zip(r-4.7-any)bootmlm_0.1.0.9000.zip(r-4.6-any)bootmlm_0.1.0.9000.zip(r-4.5-any)
bootmlm_0.1.0.9000.tgz(r-4.6-any)bootmlm_0.1.0.9000.tgz(r-4.5-any)
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bootmlm_0.1.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
bootmlm/json (API)

# Install 'bootmlm' in R:

install.packages('bootmlm', repos = c('https://marklhc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/marklhc/bootmlm/issues

Pkgdown/docs site:https://marklhc.github.io

Datasets:

pop_syn - Synthetic Pupil Popularity Dataset

On CRAN:

5.19 score 4 stars 39 scripts 370 downloads 9 exports 14 dependencies

Last updated from:100e2390eb. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	166
source / vignettes	OK	188
linux-release	OK	160
macos-release	OK	247
macos-oldrel	OK	165
windows-devel	OK	129
windows-release	OK	124
windows-oldrel	OK	117
wasm-release	OK	100

Exports:bootstrap_mer devfun_mer devfun_mer2 empinf_mer empinf_merm prof_ci_icc scores_mer vcov_theta vcov_vc

Dependencies:boot lattice lme4 MASS Matrix minqa nlme nloptr numDeriv rbibutils Rcpp RcppEigen Rdpack reformulas

Comparing Different Multilevel Bootstrapping Methods

Rendered fromcompare.Rmdusingknitr::rmarkdown

Last update: 2026-05-05
Started: 2017-08-20

Using Multilevel Bootstrap for Derived Quantities

Data | Bootstrap-$t$ CI | On a Transformed Scale

Rendered fromderived_quantities.Rmdusingknitr::rmarkdown

Last update: 2026-05-05
Started: 2017-08-20

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Run Various Bootstrap for Mixed Models.	bootstrap_mer
Bootstrap confidence intervals for Two-Level Mixed Models	confint.boot
Deviance Function for Multilevel Models	devfun_mer devfun_mer2
Empirical Influence Values for Two-Level Mixed Models	empinf_mer empinf_merm
Synthetic Pupil Popularity Dataset	pop_syn
Profile Likelihood Confidence Interval for Intraclass Correlation	prof_ci_icc
Score Functions and Case-wise Derivatives	scores_mer
Get the square root of a matrix using eigenvalue decomposition, and solve for a linear system	solve_eigen_sqrt
Asymptotic Covariance Matrix for Cholesky Factor of Random Effects	vcov_theta
Asymptotic Covariance Matrix for Random Effects	vcov_vc