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MLMusingR

MLMusingR is a companion package for the book Practical Multilevel Modeling using R.

Installation

You can install the released version of MLMusingR from CRAN with:

install.packages("MLMusingR")

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Version

Install

install.packages('MLMusingR')

Monthly Downloads

263

Version

0.4.0

License

GPL-2

Issues

0

Pull Requests

0

Stars

2

Forks

0

Maintainer

Francis Huang

Last Published

January 9th, 2025

Functions in MLMusingR (0.4.0)

wscale

Scale of Sampling Weights
summary.mixPV

Create summary output from the mixPV function
summary_all

Use the summary function on a saved list of mixPV results
wide

Wide dataset to be used for growth modeling
tidy.mixPV

Helper function to allow use with modelsummary
pisa2012

USA data from PISA 2012
tidy.CR2

Tidy a CR2 object
thai.sm

Thai data from PISA (reduced)
thai

Thai data from PISA
suspend

Suspension data from Virginia
ri_test1

Sample dataset 1 for testing the likelihood ratio test
MatSqrtInverse

Compute the inverse square root of a matrix
engage

Student engagement dataset (complete data).
lrtPV

Likelihood Ratio Test with Model Results Using Plausible Values
group_center

Group-mean center a variable
Htest

Test for homoskedasticity at level one
glance.CR2

Glance at goodness-of-fit statistics
group_mean

Computes the group mean of a variable
robust_mixed

Cluster robust standard errors with degrees of freedom adjustments for lmerMod/lme objects
pool_pv

Pool plausible values using Rubin's rules
satdf

Compute Satterthwaite degrees of freedom
mixPV

Fit Weighted Multilevel Models Using Plausible Values
nmiss

Amount of missing data per variable
%>%

Pipe operator
ri_test2

Sample dataset 2 for testing the likelihood ratio test (LRT)
cdata.ex

Clustered dataset for centering example
engage.miss

Student engagement dataset (with missing data).
hdp

Hospital, doctor, patient (hdp) dataset
sch29

Data from 29 schools (based on the NELS dataset) used for regression diagnostics