mlmm: Multilevel Model for Multivariate Responses with Missing Values
Version 1.0

To conduct Bayesian inference regression for responses with multilevel explanatory variables and missing values(Zeng ISL (2017) ). Functions utilizing 'Stan', a software to implement posterior sampling using Hamiltonian MC and its variation Non-U-Turn algorithms are generated and provided to implement 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.

Getting started

Package details

AuthorIrene SL Zeng [aut, cre], Thomas Lumley [ctb], Trustees Columbia-University [cph]
Date of publication2017-11-02 11:45:44 UTC
MaintainerIrene SL Zeng <[email protected]>
LicenseGPL-2
Version1.0
URL https://doi.org/10.1101/153049
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("mlmm")

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mlmm documentation built on Nov. 17, 2017, 6:55 a.m.