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.
Original language | English (US) |
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Pages (from-to) | 271-277 |
Number of pages | 7 |
Journal | Journal of Nutrition Education and Behavior |
Volume | 44 |
Issue number | 3 |
DOIs | |
State | Published - May 2012 |
Keywords
- Hierarchical linear modeling
- Multilevel models
- Nutrition behavior
- Survey research
- WIC program
ASJC Scopus subject areas
- Medicine (miscellaneous)
- Nutrition and Dietetics