Learn R Programming

mlmhelpr

A package of helper functions for multilevel models fit using the lme4 package

Authors

Installation

To install the latest development version directly from Github, type:

install.packages(“remotes”)

remotes::install_github(“lrocconi/mlmhelpr”)

Functions

boot_se

Compute bootstrap standard errors and confidence intervals for fixed effects

center

Automatically grand- or group-mean center variables and re-estimates the model

design_effect

Calculate the design effect to determine if multilevel modeling is needed

hausman

Perform a Hausman test to test for differences between random- and fixed-effects models (experimental)

icc

Calculate the intraclass correlation

ncv_tests

Computes three different Non-constant variance tests (experimental)

plausible_values

Compute the plausible value range for random effects

r2_cor

Calculate the squared correlation between the observed and predicted values

r2_pve

Compute the proportion of variance explained for each random effect in the model

reliability

Calculate reliability coefficients for random effects

robust_se

Computes robust standard errors for lmer models

taucov

Calculate correlation between random intercepts and slopes

Copy Link

Version

Install

install.packages('mlmhelpr')

Monthly Downloads

331

Version

0.1.1

License

MIT + file LICENSE

Issues

Pull Requests

Stars

Forks

Maintainer

Louis Rocconi

Last Published

May 21st, 2024

Functions in mlmhelpr (0.1.1)

plausible_values

Plausible Values Range / Random Effect Confidence Intervals
taucov

Tau Covariance
design_effect

Design Effect
hausman

Hausman Test (experimental)
r2_cor

Pseudo R-squared: Squared correlation between predicted and observed values
hsb

HSB: High School and Beyond Data
center

Automatically grand-mean or group-mean center a fitted object
boot_se

Bootstrap Standard Errors (experimental)
ncv_tests

Non-constant Variance Tests at Level-1 (experimental)
r2_pve

Proportion of variance explained
icc

Intraclass Correlation (ICC)
reliability

Calculate reliability coefficients for random effects
robust_se

Robust Standard Errors