Confidence Intervals for Robust and Classical Linear Mixed Model Estimators
Overview
The main function calculates confidence intervals (CI) for Mixed Models, utilizing both classical estimators from the lmer() function in the 'lme4' package and robust estimators from the rlmer() function in the 'robustlmm' package, as well as the varComprob() function in the 'robustvarComp' package. Three methods are available: the classical Wald method, the wild bootstrap, and the parametric bootstrap. Bootstrap methods offer flexibility in obtaining lower and upper bounds through percentile or BCa methods. More details are given in Mason, F., Cantoni, E., & Ghisletta, P. (2021) doi:10.5964/meth.6607 and Mason, F., Cantoni, E., & Ghisletta, P. (2024) doi:10.1037/met0000643.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 2
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 100%
Downloads
Dependencies
Installing confintROB adds 31 packages (19 with compiled code, 31 MB of source tarballs). Heaviest: stringi 11 MB, lme4 4.3 MB, nloptr 2.1 MB.
Code & Tests
Datasets
People & History
Package metadata
- First published
- 2024-04-02
- Total releases
- 4 / 2 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 5.2 KB / 1 file
- Download size
- 26 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("confintROB")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1037/met0000643.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.