30: Introducing mlmhelpr: A collection of R helper functions for lme4

Music City Center 

This poster session will introduce and discuss a new R package, mlmhelpr, which includes helper functions for lme4 to streamline the estimation of multilevel models for applied researchers. With mlmhelpr, users can easily conduct common tasks, such as calculating intraclass correlation coefficients and design effects, centering variables and refitting models, obtaining pseudo-R squared measures, and estimating random intercept and slope reliabilities. The package also includes functions to compute cluster-robust and bootstrap standard errors, non-constant variance tests for detecting heterocedasticity, and Hausman's statistic to test for differences between fixed-effect and random-effect models. Statics and tests reported in the package are from popular multilevel modeling textbooks including Raudenbush & Bryk (2002), Hox et al. (2018), Fox (2016), and Snijders & Bosker (2012).

linear mixed models

multilevel modeling

R programming

R package

statistical models 

Section on Statistical Computing