R Observatory: Metrics for robustlmm version 3.5.0-2

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

robustlmm

3.5.0-2Package record

Robust Linear Mixed Effects Models

0packages dependsuggested by 5

81.6Kdownloads / year

39.0%test coverage

13/13flavors OK

Overview

About

Maintained by Manuel KollerCRAN page ↗GitHub ↗

Implements the Robust Scoring Equations estimator to fit linear mixed effects models robustly. Robustness is achieved by modification of the scoring equations combined with the Design Adaptive Scale approach.

Changes in 3.5.0-2

Bug fixes

calcTau() no longer refuses to solve its fixed point when the starting value exceeds 1. The tau <= 1 constraint sat in the loop condition, so a start above 1 skipped the iteration entirely and the post-loop clamp returned exactly 1; it now starts from min(tau, 1). This is what let the weighted-tau bug of 3.5.0 reach method = "DAStau" (see that release's entry for who should refit; that part was fixed in 3.5.0, this guard was not). No fit produced by the current code reaches the condition -- the largest starting value observed over a randomised search is 0.99948 -- so the change is defensive and is a no-op on current behaviour; tests/tau.R now pins the fixed point to be independent of the starting value.

Show all changes in 3.5.0-2Hide the rest of the changes in 3.5.0-2

**init = "ransac" estimated the model on the RANSAC subsample instead of on your data, in 3.4-5 and 3.5.0-1.** If you have used init = "ransac", rlmer_ransac() or fitDatasets_rlmer_ransac/_ransac_bisq with either version, refit: the returned object was an estimate on roughly half the observations. Nothing else is affected, and no other init form is affected. An lmerMod passed as init supplies the *model*, not only the starting values -- the working object is built from it, so formula and data stop mattering from that point on. That is correct and efficient for a starting fit on the same data, which is what the argument was designed for. But ransac_lme4()$fit is fitted on the winning RANSAC subsample, so resolving init = "ransac" to that object silently dropped the rest of the data. On a two-dimensional random-effect block with m = 50 clusters and n = 1000 observations, the fit used 510 observations and 27 of the 50 clusters. rlmer() now takes fixef, sigma and theta from the RANSAC fit and estimates the model on the full data. u is deliberately not carried over: it has one entry per random-effect coefficient of the fit it came from, and zeroing it instead is not a neutral choice -- combined with a theta from elsewhere it drives the random-effect covariance onto the boundary (theta = 0). Instead the effects are re-solved at the supplied sigma and theta. That solve is the robust IRLS step for beta and u *jointly*, run to convergence, so the RANSAC fixef acts as a warm start rather than as a value that is held fixed; sigma and theta are the parameters actually held. Two supporting changes. The components of the list form of init are now optional; anything omitted keeps the value from the internal lmer initialisation, which is what makes the above expressible. And passing an lmerMod fitted on a different number of observations than data has rows now warns, since that is the same silent data-loss trap in user code. It is a warning rather than an error because dropping rows with NAs is a legitimate reason for the counts to differ. Four call sites were affected, in three independent copies of the pattern: init = "ransac", rlmer_ransac(), and the inline start in fitDatasets_rlmer_ransac and fitDatasets_rlmer_ransac_bisq (which do not route through rlmer_ransac()). All four are fixed. Found while running the estimator against the simulation design of Sugasawa, Hui and Welsh (2026, *JCGS* 35(2):720-733). Regression test: tests/ransac-init-fullwdata.R, which covers all four entry points.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("robustlmm", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("kollerma/robustlmm")

Development version from kollerma/robustlmm. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-robustlmm

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-robustlmm

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-robustlmm

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 15.3 min · r-oldrel-macos-x86_64

Status changes

OK13 OK2026-10-17
WARNING12 OK, 1 WARNING2026-10-01
OK13 OK2026-09-25
ERROR12 OK, 1 ERROR2026-09-18
OK13 OK2026-08-05

Show 10 earlier changesHide 10 earlier changes

NOTE12 OK, 1 NOTE2026-07-31
OK13 OK2026-07-18
WARNING12 OK, 1 WARNING2026-07-16
OK13 OK2026-06-27
WARNING7 OK, 5 NOTE, 1 WARNING2026-06-14
NOTE11 OK, 2 NOTE2026-05-05
OK13 OK2026-05-02
NOTE11 OK, 1 NOTE2026-04-25
ERROR10 OK, 3 NOTE, 1 ERROR2026-04-18
NOTE11 OK, 3 NOTE2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 3.5.0-2

READMEYes · 409 wordsVignettesYes · 3 · dynamicNEWSYes · 67% structured · mentions 3.5.0-2Citation fileYes · cites a publicationWebsitenot declared in DESCRIPTION

Cites a JSS article

Help pages: 56 (2 internal)includes a package overview page
Examples that run: 80%28 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran) · 6 never run
Exported functions with examples: 72%
Documented parameters: 96%
Return-value docs: 79%
Help pages citing references: 18%

Vignettes (3)

How these are measured

Downloads

81.6K

CRAN downloads in the past year

Rank #1,451 · ~223/day · ~6.8K/mo

Releases R versions

Daily download trend is not available in this view yet.

5.3K30 days

17.9K90 days

81.6K1 year

Compare downloads with other packages →

Also on2.1K r2u3 autocran196 c2d4u

How downloads are counted

Repository

kollerma/robustlmm ↗Account: kollerma

31Stars

9Forks

0Open issues

0Open PRs

0Releases

109Commits

7Commit identities

109 commits · Last activity 2026-07-30 · 0% stars, 30d

Responsiveness

How these are sampled

PRs merged (all time): 100%
Median days to close, 50 most recently updated closed issues: 7
Median days to close, 50 most recently updated closed PRs: 7

Stars over time

2025-07-10 · 282026-07-07 · 31

How these are measured

PracticesBeta

5 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/kollerma/robustlmm on 2026-10-18.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

CRAN release process (1)

cran-comments.md

Lint, format, editor (2)

VS CodeRStudio project

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

24 external dependencies (excludes base and recommended)

Installing robustlmm adds 14 packages (9 with compiled code, 15 MB of source tarballs). Heaviest: lme4 4.1 MB, robustbase 2.2 MB, nloptr 2.1 MB.

Depends (3)

R >= 3.5.0lme4Matrix

Imports (12)

latticenlmemethodsrobustbase xtable Rcpp (>= 0.12.2)fastGHQuad numDerivparallelrlangutilsreformulas

LinkingTo (3)

Rcpp robustbaseMatrix

Suggests (15)

ggplot2 reshape2 microbenchmark emmeans estimability lqmmMASSRColorBrewer skewt fs dplyr ggh4x testthat robustvarComp confintROB

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Suggested by 5

Suggests, most downloaded first

insight effects marginaleffects misty confintROB

How these are counted

Code & Tests

People & History

People (1)

Manuel Koller

Author, Maintainer since 1.0 (2013)

Releases (47)

Pick two releases to compare their code metrics.

3.5.0-2Latest
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2026-07-30 · current release · diff ↗
3.5.0-1
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2026-07-10 · diff ↗ ·
added 6 exports
generateRepeatedMeasuresDatasets, fitDatasets_rlmer_cs, fitDatasets_rlmer_ar1, makeRobustbasePsi, lqqPsi, ransac_basin_radius
3.4-5
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2026-06-21 · diff ↗ ·
added 11 exports
caseweightIF, vcov_sandwich, implicitIF_full, fitDatasets_rlmer_DAStau_bisq, fitDatasets_rlmer_DAStau_sizeOBR, fitDatasets_rlmer_ransac, fitDatasets_rlmer_ransac_bisq, makeBisquarePsi, bisquarePsi, ransac_lme4, rlmer_ransac
R
R 4.6.0 released · 2026-04-24
3.4-3
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2026-04-20 · diff ↗
3.4-2
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2026-01-28 · diff ↗ ·
added 2 exports
generateLongitudinalDatasets, plotLongitudinalBySubject
3.3-3
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2025-05-26 · diff ↗
3.3-2
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2025-05-04 · diff ↗
R
R 4.5.0 released · 2025-04-11
R
R 4.4.0 released · 2024-04-24
3.3-1
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2023-12-15 · diff ↗
3.2-5
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2023-11-14 · diff ↗
3.2-3
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2023-10-06 · diff ↗
3.2-2
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2023-08-18 · diff ↗
R
R 4.3.0 released · 2023-04-21
3.2-0
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2023-03-25 · diff ↗

Show 47 earlier eventsHide 47 earlier events

3.1-2
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2022-12-08 · diff ↗
3.1-1
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2022-12-02 · diff ↗ ·
removed 1 export
rlmerRcpp
3.0-4
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2022-09-17 · diff ↗
R
R 4.2.0 released · 2022-04-22
R
R 4.1.0 released · 2021-05-18
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R 4.0.0 released · 2020-04-24
R
R 3.6.0 released · 2019-04-26
R
R 3.5.0 released · 2018-04-23
R
R 3.4.0 released · 2017-04-21
R
R 3.3.0 released · 2016-05-03
R
R 3.2.0 released · 2015-04-16
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R 3.1.0 released · 2014-04-10
3.0.3
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2014-02-12 · diff ↗
3.0-2
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2022-08-26 · diff ↗
3.0.2
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2013-09-17 · diff ↗ ·
removed 3 exports
fixef, sigma, VarCorr

added 2 exports
huberPsi, plot.rlmerMod
3.0-1
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2022-08-07 · diff ↗ ·
added 50 exports
generateAnovaDatasets, prepareMixedEffectDataset, generateMixedEffectDatasets, generateSensitivityCurveDatasets, bindDatasets, splitDatasets, createDatasetsFromList, saveDatasets, lapplyDatasets, fitDatasets_lmer, fitDatasets_lmer_bobyqa, fitDatasets_lmer_Nelder_Mead, fitDatasets_rlmer, createRhoFunction, extractTuningParameter, extractPredefinedTuningParameter, fitDatasets_rlmer_DAStau, fitDatasets_rlmer_DAStau_lmerNoFit, fitDatasets_rlmer_DASvar, fitDatasets_rlmer_DAStau_noAdj, fitDatasets_rlmer_DAStau_k_0_5, fitDatasets_rlmer_DAStau_k_0_5_noAdj, fitDatasets_rlmer_DAStau_k_2, fitDatasets_rlmer_DAStau_k_2_noAdj, fitDatasets_rlmer_DAStau_k_5, fitDatasets_rlmer_DAStau_k_5_noAdj, fitDatasets_heavyLme, fitDatasets_lqmm, fitDatasets_rlme, fitDatasets_varComprob and 20 more
R
R 3.0.0 released · 2013-04-03
R
R 2.15.0 released · 2012-03-30
2.15.0
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2012-03-08 · diff ↗ ·
added 12 exports
compare, cPsi, fixef, getInfo, getME, lmerNoFit, psiFuncCached, rlmer, sigma, smoothPsi, theta, VarCorr
2.5-1
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2022-03-23 · diff ↗
2.5-0
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2022-02-15 · diff ↗
2.4-5
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2021-10-06 · diff ↗
2.4-4
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2021-05-24 · diff ↗
2.4-3
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2021-02-10 · diff ↗
2.4-2
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2021-01-31 · diff ↗
2.3
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2019-02-03 · diff ↗
2.2-1
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2018-04-29 · diff ↗ ·
added 1 export
rlmerRcpp
2.1-4
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2017-11-19 · diff ↗
2.1-3
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2017-04-09 · diff ↗
2.1-2
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2016-12-18 · diff ↗
2.1
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2016-12-01 · diff ↗ ·
removed 2 exports
huberPsi, psiFuncCached

added 1 export
huberPsiRcpp
1.8
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2016-01-03 · diff ↗
1.7-6
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2015-08-30 · diff ↗
1.7-4
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2015-07-14 · diff ↗
1.7-2
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2015-06-05 · diff ↗
1.6
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2014-07-11 · diff ↗
1.5
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2014-06-13 · diff ↗
1.4-3
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2014-03-13 · diff ↗
1.4-2
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2014-02-01 · diff ↗
1.4-1
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2014-01-31 · diff ↗
1.4
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2014-01-28 · diff ↗
1.3-1
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2013-10-07 · diff ↗
1.3
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2013-09-21 · diff ↗
1.1-1
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2013-09-11 · diff ↗
1.1
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2013-06-17 · diff ↗
1.0
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2013-03-08
R
R 2.14.0 released · 2011-10-31

Package metadata

First published: 2012-03-08
Total releases: 47 / 14 yrs
License: GPL-2 OSI
Minimum R: ≥ 3.5.0
Download size: 4.0 MB

Appears in task views

Mixed, Multilevel, and Hierarchical Models in R Robust Statistical Methods

Cite

Cite this package

Run in R for the authors' entry:

citation("robustlmm")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.18637/jss.v075.i06.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for robustlmm version 3.5.0-2 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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