Multilevel Models

Using plausible values when fitting multilevel models with large-scale assessment data using R

Article is open access. The mixPV function can now be accessed by installing the MLMusingR package.

Mar 1, 2024

Using robust standard errors for the analysis of binary outcomes with a small number of clusters

CR2 plug in for SPSS can be downloaded from: https://github.com/flh3/CR2

Jan 1, 2023

Practical multilevel modeling using R

Check out the latest info on the book here sample chapters additional code and an online appendix errata Some reviews: A major strength of this book is its accessibility. Huang effortlessly bridges the divide between the sometimes-abstruse literature on advanced statistics and the needs of applied researchers who lack extensive quantitative training. The result is an approachable text that covers all the basics, but also does not shy away from important advanced topics such as diagnostics, detecting and handling heteroscedasticity, and missing data handling methods. This book would make not only a useful guide to the application of multilevel modeling, but could also serve as an excellent companion text for a course on multilevel modeling. - Kristopher J. Preacher, Vanderbilt University

Jan 1, 2023

Accounting for heteroskedasticity resulting from between-group differences in multilevel models

Robust standard errors for multilevel models.

Jan 1, 2023

Using cluster-robust standard errors when analyzing group-randomized trials with few clusters

The SPSS version can be accessed here: https://github.com/flh3/CR2/tree/master/SPSS

Jan 1, 2022

Analyzing cross-sectionally clustered data using generalized estimating equations

As of 2024.10.03, the most read article on JEBS (for the last 6 months)! In the original paper draft, I had a section which showed how much more widely used mixed models (i.e., MLMs, HLMs) were compared to GEEs but was asked to remove that. I thought the usage was interesting so I am including it here:

Jan 1, 2022

Alternatives to logistic regression models when analyzing cluster randomized trials with binary outcomes

Linear probability models and modified Poisson regression models are good alternatives.

Jan 1, 2021

Multilevel modeling myths

Preprint available here.

Sep 1, 2018

Multilevel modeling and ordinary least squares regression: How comparable are they?

Jan 1, 2018

Alternatives to multilevel modeling for the analysis of clustered data

Researchers do not need an MLM necessarily to analyze clustered data.

Jan 1, 2016