{
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"Title": "Penalized Linear Mixed Models for Correlated Data",
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"Description": "Fits penalized linear mixed models that correct for\nunobserved confounding factors. 'plmmr' infers and corrects for\nthe presence of unobserved confounding effects such as\npopulation stratification and environmental heterogeneity. It\nthen fits a linear model via penalized maximum likelihood.\nOriginally designed for the multivariate analysis of single\nnucleotide polymorphisms (SNPs) measured in a genome-wide\nassociation study (GWAS), 'plmmr' eliminates the need for\nsubpopulation-specific analyses and post-analysis p-value\nadjustments. Functions for the appropriate processing of\n'PLINK' files are also supplied. For examples, see the package\nhomepage .",
"License": "GPL-3",
"URL": "https://pbreheny.github.io/plmmr/,\nhttps://github.com/pbreheny/plmmr/",
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"User": "root"
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"Author": "Tabitha K. Peter [aut] (ORCID:\n), Anna C. Reisetter\n[aut] (ORCID: ), Yujing\nLu [aut], Oscar A. Rysavy [aut] (ORCID:\n), Patrick J. Breheny\n[aut, cre] (ORCID: )",
"Maintainer": "Patrick J. Breheny ",
"Repository": "https://cran.r-universe.dev",
"Date/Publication": "2026-06-11 11:52:15 UTC",
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"title": "A function to create a design for PLMM modeling",
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"title": "Cross-validation for plmm",
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"title": "A function to help with accessing example PLINK files.",
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]
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{
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"title": "Fit a linear mixed model via penalized maximum likelihood.",
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"title": "Plot method for 'plmm' class",
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