Related Experiment Video
Updated: May 25, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Managing clustered data using hierarchical linear modeling
Russell T Warne1, Yan Li, E Lisako J McKyer
1Department of Behavioral Science, Utah Valley University, Orem, UT 84058, USA. rwarne@uvu.edu
Abstract:
Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence assumption and lead to correct analysis of data, yet it is rarely used in nutrition research. The purpose of this viewpoint is to illustrate the benefits of hierarchical linear modeling within a nutrition research context.
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