README.md

In jrising/hierlm: Hierarchical Linear Models

hierlm

Hierarchical Linear Model

The hierlm package allows researchers to perform a large range of hierarchical models, in which parameters are related to eachother or to 'hyper'-parameters. Coefficients are modeled as being drawn from Gaussian distributions, whose mean is estimated simultaneously with the value of those coefficients. The technique is very similar to Bayesian Hierarchical Modeling (See Bayesian Data Analysis, chapter 5, by Gelman et al.), but because it uses a linear model (OLS) can handle much larger datasets.

For more information, see the vingette and top-level hierlm() function documentation.

Terminology Note: Traditionally, "Hierarchical linear modeling" and "multilevel modeling" describe models where coefficients can be described with interactions with higher-level data. This package does not do multilevel modeling, since both the coefficients and the data in hierlm can describe more than one level.

Installation

Install this package from CRAN as normal, or get the code directly from the github repository. To install from github, first make sure you have the devtools package, and run the following:

library(devtools)
install_github("hierlm", username="jrising")
library(hierlm)

jrising/hierlm documentation built on May 31, 2019, 8:08 a.m.