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plmmr  

Penalized Linear Mixed Models for Correlated Data
View on CRAN: Click here


Download and install plmmr package within the R console
Install from CRAN:
install.packages("plmmr")

Install from Github:
library("remotes")
install_github("cran/plmmr")

Install by package version:
library("remotes")
install_version("plmmr", "4.3.0")



Attach the package and use:
library("plmmr")
Maintained by
Patrick J. Breheny
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-10-11
Latest Update: 2025-03-03
Description:
Fits penalized linear mixed models that correct for unobserved confounding factors. 'plmmr' infers and corrects for the presence of unobserved confounding effects such as population stratification and environmental heterogeneity. It then fits a linear model via penalized maximum likelihood. Originally designed for the multivariate analysis of single nucleotide polymorphisms (SNPs) measured in a genome-wide association study (GWAS), 'plmmr' eliminates the need for subpopulation-specific analyses and post-analysis p-value adjustments.Functions for the appropriate processing of 'PLINK' files are also supplied. For examples, see the package homepage. <https://pbreheny.github.io/plmmr/>.
How to cite:
Patrick J. Breheny (2024). plmmr: Penalized Linear Mixed Models for Correlated Data. R package version 4.3.0, https://cran.r-project.org/web/packages/plmmr. Accessed 04 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:41), 4.0.0 (2024-10-11 10:00), 4.1.0 (2024-10-24 00:20), 4.2.0 (2025-02-19 00:50), 4.2.1 (2025-03-03 19:10), 4.2.2 (2026-01-21 18:10), 4.2.3 (2026-01-26 18:10)
Other packages that cited plmmr R package
View plmmr citation profile
Other R packages that plmmr depends, imports, suggests or enhances
Complete documentation for plmmr
Functions, R codes and Examples using the plmmr R package
Full plmmr package functions and examples
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