mlm4omics: Multilevel Model for Multivariate Responses with Missing Values

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.

Package details

AuthorIrene Zeng [aut, cre], Thomas Lumley [ctb]
Bioconductor views Bayesian Classification CopyNumberVariation ImmunoOncology MassSpectrometry Proteomics Regression Software
MaintainerIrene SL Zeng <>
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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mlm4omics documentation built on Oct. 31, 2019, 9:43 a.m.