eng
TQMP
Tutorials in Quantitative Methods for Psychology
1913-4126
2012-02-20
8
1
52
69
10.20982/tqmp.08.1.p052
article
An introduction to hierarchical linear modeling
Woltman, Heather
hwolt031@uottawa.ca
1
Feldstain, Andrea
hwolt031@uottawa.ca
1
MacKay, J. Christine
hwolt031@uottawa.ca
1
Rocchi, Meredith
hwolt031@uottawa.ca
1
University of Ottawa
This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is provided that describes when to use this statistical technique and identifies key factors to consider before conducting this analysis. The first section of the tutorial defines HLM, clarifies its purpose, and states its advantages. The second section explains the mathematical theory, equations, and conditions underlying HLM. HLM hypothesis testing is performed in the third section. Finally, the fourth section provides a practical example of running HLM, with which readers can follow along. Throughout this tutorial, emphasis is placed on providing a straightforward overview of the basic principles of HLM.
https://www.tqmp.org/RegularArticles/vol08-1/p052/p052.pdf
Hierarchical Linear Models
Nested Data
Hypothesis Testing
Parameter Estimation
HLM