TestREnlme: Nonparametric Tests for Random Effects in Linear and Nonlinear Mixed-Effects Models

Package: TestREnlme 0.1.0

Germaine Uwimpuhwe

TestREnlme: Nonparametric Tests for Random Effects in Linear and Nonlinear Mixed-Effects Models

Provides nonparametric permutation tests for testing all or any subset of random effects in linear and nonlinear mixed-effects models, without requiring normality or other distributional assumptions on random effects or errors. Three distribution-free variance-component estimators are implemented: Variance Least Squares ('VLS'), Method of Moments ('MM'), and Method of Moments with First-Order Approximation ('MMF'). A permutation procedure is used to obtain finite-sample p-values. Plotting functions support data exploration, model evaluation, and communication of results. Methods are described in Uwimpuhwe, Drikvandi, and Blozis (2026) <doi:10.1002/sim.70605>.

Authors:Germaine Uwimpuhwe [aut, cre], Reza Drikvandi [aut], Shelley A. Blozis [aut]

TestREnlme_0.1.0.tar.gz
TestREnlme_0.1.0.tar.gz(r-4.7-any)TestREnlme_0.1.0.tar.gz(r-4.6-any)
TestREnlme_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
TestREnlme/json (API)

# Install 'TestREnlme' in R:

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

Bug tracker:https://github.com/germaine86/testrenlme/issues

Datasets:

SkillAcq - Skill acquisition data

On CRAN:

2.00 score 13 exports 40 dependencies

Last updated from:f061c1d5b6. Checks:4 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	180
source / vignettes	OK	210
linux-release-x86_64	OK	179
wasm-release	OK	160

Exports:Beta_hat bootstrap_se Dhypothesis_test Dmethod MM_base plot_condition plot_fitted plot_perm_hist plot_profiles plot_residuals plot_variance Tstat ZandYPred

Dependencies:cli cpp11 dplyr expm farver generics ggplot2 glue gtable isoband labeling lattice lhs lifecycle magrittr MASS Matrix matrixcalc mgsub minpack.lm nlme nls.multstart pillar pkgconfig purrr R6 RColorBrewer Rcpp rlang S7 scales stringi stringr tibble tidyr tidyselect utf8 vctrs viridisLite withr

TestREnlme: Testing Random Effects in Linear and Nonlinear Mixed-Effects Models

Rendered fromTestREnlme.Rmdusingknitr::rmarkdown

Help page	Topics
Estimate fixed effects by nonlinear least squares	Beta_hat
Bootstrap standard errors for variance component estimates	bootstrap_se
Permutation test for random effects in linear and nonlinear mixed-effects models	Dhypothesis_test
Non-parametric approach to estimate variance components in a linear and nonlinear mixed-effects model	Dmethod
Compute first-stage quantities for MM and MMF estimators	MM_base
Plot per-subject condition numbers	plot_condition
Plot fitted curves overlaid on observed data	plot_fitted
Histogram of the permutation null distribution	plot_perm_hist
Plot raw individual trajectories	plot_profiles
Plot residuals versus fitted values	plot_residuals
Compare variance component estimates across methods	plot_variance
Plot method for 'Dmethod' objects	plot.Dmethod
Plot method for 'Dtest' objects	plot.Dtest
Skill acquisition data	SkillAcq
Compute the observed test statistic	Tstat
Compute Jacobian matrix and fixed-effects predicted values	ZandYPred

Help page

Topics

Estimate fixed effects by nonlinear least squares

Beta_hat

Bootstrap standard errors for variance component estimates

bootstrap_se

Permutation test for random effects in linear and nonlinear mixed-effects models

Dhypothesis_test

Non-parametric approach to estimate variance components in a linear and nonlinear mixed-effects model

Dmethod

Compute first-stage quantities for MM and MMF estimators

MM_base