DOI: 10.18129/B9.bioc.mlm4omics    

This is the development version of mlm4omics; to use it, please install the devel version of Bioconductor.

Multilevel Model for Multivariate Responses with Missing Values

Bioconductor version: Development (3.10)

To conduct Bayesian inference regression for responses with multilevel explanatory variables and missing values; It uses function from 'Stan', a software to implement posterior sampling using Hamiltonian MC and its variation Non-U-Turn algorithms. It implements the posterior sampling of regression coefficients from the multilevel regression models. The package has two main functions to handle not-missing-at-random missing responses and left-censored with not-missing-at random responses. The purpose is to provide a similar format as the other R regression functions but using 'Stan' models.

Author: Irene Zeng [aut, cre], Thomas Lumley [ctb]

Maintainer: Irene SL Zeng <i.zeng at>

Citation (from within R, enter citation("mlm4omics")):


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biocViews Bayesian, Classification, CopyNumberVariation, ImmunoOncology, MassSpectrometry, Proteomics, Regression, Software
Version 1.3.0
In Bioconductor since BioC 3.8 (R-3.5) (1 year)
License GPL-3
Depends R (>= 3.5.0), Rcpp (>= 0.12.17), methods, stats
Imports rstan (>= 2.17.3), rstantools (>= 1.5.0), MASS, Matrix, stats4, ggplot2
LinkingTo StanHeaders (>= 2.17.2), rstan (>= 2.17.3), BH (>= 1.66.0-1), Rcpp (>= 0.12.17), RcppEigen (>=
Suggests testthat, BiocStyle, knitr, rmarkdown, roxygen2 (>= 5.0.0)
SystemRequirements GNU make
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